Cancer Research and Treatment

Original Articles

Gastrointestinal cancer

Prognostic Evaluation and Survival Prediction for Combined Hepatocellular-Cholangiocarcinoma Following Hepatectomy: Seok-Joo Chun, Yu Jung Jung, YoungRok Choi, Nam-Joon Yi, Kwang-Woong Lee, Kyung-Suk Suh, Kyoung Bun Lee, Hyun-Cheol Kang, Eui Kyu Chie, Kyung Su Kim; Cancer Res Treat. 2025;57(1):229-239. Published online July 3, 2024; DOI: https://doi.org/10.4143/crt.2024.176

Abstract PDF Supplementary Material PubReader ePub: Purpose
This study aimed to assess prognostic factors associated with combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and to predict 5-year survival based on these factors.
Materials and Methods
Patients who underwent definitive hepatectomy from 2006 to 2022 at a single institution was retrospectively analyzed. Inclusion criteria involved a pathologically confirmed diagnosis of cHCC-CCA.
Results
A total of 80 patients with diagnosed cHCC-CCA were included in the analysis. The median progression-free survival was 15.6 months, while distant metastasis-free survival (DMFS), hepatic progression-free survival, and overall survival (OS) were 50.8, 21.5, and 85.1 months, respectively. In 52 cases of recurrence, intrahepatic recurrence was the most common initial recurrence (34/52), with distant metastasis in 17 cases. Factors associated with poor DMFS included tumor necrosis, lymphovascular invasion (LVI), perineural invasion, and histologic compact type. Postoperative carbohydrate antigen 19-9, tumor necrosis, LVI, and close/positive margin were associated with poor OS. LVI emerged as a key factor affecting both DMFS and OS, with a 5-year OS of 93.3% for patients without LVI compared to 35.8% with LVI. Based on these factors, a nomogram predicting 3-year and 5-year DMFS and OS was developed, demonstrating high concordance with actual survival in the cohort (Harrell C-index 0.809 for OS, 0.801 for DMFS, respectively).
Conclusion
The prognosis of cHCC-CCA is notably poor when combined with LVI. Given the significant impact of adverse features, accurate outcome prediction is crucial. Moreover, consideration of adjuvant therapy may be warranted for patients exhibiting poor survival and increased risk of local recurrence or distant metastasis.

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Genitourinary Cancer

A Predictive Model Based on Bi-parametric Magnetic Resonance Imaging and Clinical Parameters for Clinically Significant Prostate Cancer in the Korean Population: Tae Il Noh, Chang Wan Hyun, Ha Eun Kang, Hyun Jung Jin, Jong Hyun Tae, Ji Sung Shim, Sung Gu Kang, Deuk Jae Sung, Jun Cheon, Jeong Gu Lee, Seok Ho Kang; Cancer Res Treat. 2021;53(4):1148-1155. Published online December 31, 2020; DOI: https://doi.org/10.4143/crt.2020.1068

Abstract PDF Supplementary Material PubReader ePub

Purpose
This study aimed to develop and validate a predictive model for the assessment of clinically significant prostate cancer (csPCa) in men, prior to prostate biopsies, based on bi-parametric magnetic resonance imaging (bpMRI) and clinical parameters.
Materials and Methods
We retrospectively analyzed 300 men with clinical suspicion of prostate cancer (prostate-specific antigen [PSA] ≥ 4.0 ng/mL and/or abnormal findings in a digital rectal examination), who underwent bpMRI-ultrasound fusion transperineal targeted and systematic biopsies in the same session, at a Korean university hospital. Predictive models, based on Prostate Imaging Reporting and Data Systems scores of bpMRI and clinical parameters, were developed to detect csPCa (intermediate/high grade [Gleason score ≥ 3+4]) and compared by analyzing the areas under the curves and decision curves.
Results
A predictive model defined by the combination of bpMRI and clinical parameters (age, PSA density) showed high discriminatory power (area under the curve, 0.861) and resulted in a significant net benefit on decision curve analysis. Applying a probability threshold of 7.5%, 21.6% of men could avoid unnecessary prostate biopsy, while only 1.0% of significant prostate cancers were missed.
Conclusion
This predictive model provided a reliable and measurable means of risk stratification of csPCa, with high discriminatory power and great net benefit. It could be a useful tool for clinical decision-making prior to prostate biopsies.

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Abbreviated MRI Protocols in the Abdomen and Pelvis
Kristina I. Ringe, Jin Wang, Ying Deng, Shan Pi, Amine Geahchan, Bachir Taouli, Mustafa R. Bashir
Journal of Magnetic Resonance Imaging.2024; 59(1): 58. CrossRef
Magnetic Resonance Imaging, Clinical, and Biopsy Findings in Suspected Prostate Cancer
Arya Haj-Mirzaian, Kristine S. Burk, Ronilda Lacson, Daniel I. Glazer, Sanjay Saini, Adam S. Kibel, Ramin Khorasani
JAMA Network Open.2024; 7(3): e244258. CrossRef
The Barcelona Predictive Model of Clinically Significant Prostate Cancer
Juan Morote, Angel Borque-Fernando, Marina Triquell, Anna Celma, Lucas Regis, Manel Escobar, Richard Mast, Inés M. de Torres, María E. Semidey, José M. Abascal, Carles Sola, Pol Servian, Daniel Salvador, Anna Santamaría, Jacques Planas, Luis M. Esteban, E
Cancers.2022; 14(6): 1589. CrossRef
Efficacy of Tadalafil in Penile Rehabilitation Started Before Nerve-Sparing Robot-Assisted Radical Prostatectomy: A Double-Blind Pilot Study
Tae Il Noh, Ji Sung Shim, Sung Gu Kang, Jun Cheon, Jeong Gu Lee, Seok Ho Kang
Sexual Medicine.2022; 10(3): 1. CrossRef
Comparative Analysis of PSA Density and an MRI-Based Predictive Model to Improve the Selection of Candidates for Prostate Biopsy
Juan Morote, Angel Borque-Fernando, Marina Triquell, Anna Celma, Lucas Regis, Richard Mast, Inés M. de Torres, María E. Semidey, José M. Abascal, Pol Servian, Anna Santamaría, Jacques Planas, Luis M. Esteban, Enrique Trilla
Cancers.2022; 14(10): 2374. CrossRef
Magnetic Resonance Imaging-Based Predictive Models for Clinically Significant Prostate Cancer: A Systematic Review
Marina Triquell, Miriam Campistol, Ana Celma, Lucas Regis, Mercè Cuadras, Jacques Planas, Enrique Trilla, Juan Morote
Cancers.2022; 14(19): 4747. CrossRef

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Head and Neck Cancer

Development and Validation of Web-Based Nomograms to Precisely Predict Survival Outcomes of Non-metastatic Nasopharyngeal Carcinoma in an Endemic Area: Ji-Jin Yao, Li Lin, Tian-Sheng Gao, Wang-Jian Zhang, Wayne R. Lawrence, Jun Ma, Ying Sun; Cancer Res Treat. 2021;53(3):657-670. Published online December 7, 2020; DOI: https://doi.org/10.4143/crt.2020.899

Abstract PDF Supplementary Material PubReader ePub

Purpose
This study aimed to develop web-based nomograms to precisely predict survival outcomes in patients with non-metastatic nasopharyngeal carcinoma (NPC) in an endemic area.
Materials and Methods
A total of 10,126 patients who underwent radical intensity-modulated radiotherapy at Sun Yat-sen University Cancer Center (SYSUCC) from 2009 to 2015 were analyzed. We assigned patients into a training cohort (SYSUCC-A, n=6,751) and an internal validation cohort (SYSUCC-B, n=3,375) based on computer-generated random numbers. Patients collected from Wuzhou Red Cross Hospital (WZRCH) between 2012 and 2015 were used as the independent external validation cohort (WZRCH, n=450). Concordance index (C-index) was used to determine predictive accuracy and discriminative ability for the nomogram. The web-based clinicopathologic prediction models for predicting survival were based on Cox regression.
Results
The C-indexes for SYSUCC-A, SYSUCC-B, and WZRCH cohorts for the established nomograms to predict 3-year overall survival (OS) was 0.736, 0.715, and 0.691. Additionally, C-indexes to predict 3-year distant metastasis-free survival (DMFS) was 0.717, 0.706, and 0.686, disease-free survival (DFS) was 0.713, 0.697, and 0.656, local relapse-free survival was 0.695, 0.684, and 0.652, and regional relapse-free survival was 0.672, 0.650, and 0.616. The calibration plots showed great agreement between nomogram-predicted 3-year survival outcomes and actual 3-year survival outcomes. Moreover, C-indexes of the nomograms for OS, DMFS, and DFS were significantly superior than TNM stage (p< 0.001 for all).
Conclusion
These user-friendly nomograms can precisely predict survival endpoints in patients with non-metastatic NPC. They may serve as a useful tool for providing patient counseling and help physicians to make individual follow-up plans.

Citations

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Adverse prognosis of nasopharyngeal carcinoma following long-term exposure to multiple air pollutants
Xiao Lin, Yanan Jin, Jijin Yao, Xurui Sun, Tian Tian, Zhiqiang Li, Shimin Chen, Jie Jiang, Weihua Hu, Yuantao Hao, Liangping Xia, Wangjian Zhang
Environmental Chemistry Letters.2024; 22(1): 21. CrossRef
The development and external validation of a web-based nomogram for predicting overall survival with Ewing sarcoma in children
Yi Chen, Zirui Liu, Yaobin Wang, Hongwei Zhan, Jinmin Liu, Yongkang Niu, Ao Yang, Fei Teng, Jinfeng Li, Bin Geng, Yayi Xia
Journal of Children's Orthopaedics.2024; 18(2): 236. CrossRef
The efficacy and safety of adding PD-1 blockade to induction chemotherapy and concurrent chemoradiotherapy (IC-CCRT) for locoregionally advanced nasopharyngeal carcinoma: an observational, propensity score-matched analysis
Ya-Nan Jin, Meng-Yun Qiang, Ying Wang, Yu-Jing Lin, Ren-Wei Jiang, Wan-Wei Cao, Wang-Jian Zhang, Si-Yang Wang, Hong-Yu Zhang, Ji-Jin Yao
Cancer Immunology, Immunotherapy.2024;[Epub] CrossRef
Potential causal links of long‐term exposure to PM2.5 and its chemical components with the risk of nasopharyngeal carcinoma recurrence: A 10‐year cohort study in South China
Xurui Sun, Xiao Lin, Jijin Yao, Tian Tian, Zhiqiang Li, Shimin Chen, Weihua Hu, Jie Jiang, Hui Tang, Huanle Cai, Tong Guo, Xudan Chen, Zhibing Chen, Man Zhang, Yongqing Sun, Shao Lin, Yanji Qu, Xinlei Deng, Ziqiang Lin, Liangping Xia, Yanan Jin, Wangjian
International Journal of Cancer.2024; 155(9): 1558. CrossRef
ALYREF promotes the metastasis of nasopharyngeal carcinoma by increasing the stability of NOTCH1 mRNA
Yanan Jin, Jijin Yao, Jianchang Fu, Qitao Huang, Yilin Luo, Yafei You, Wangjian Zhang, Qian Zhong, Tianliang Xia, Liangping Xia
Cell Death & Disease.2024;[Epub] CrossRef
The continuous improvement of digital assistance in the radiation oncologist’s work: from web-based nomograms to the adoption of large-language models (LLMs). A systematic review by the young group of the Italian association of radiotherapy and clinical o
Antonio Piras, Ilaria Morelli, Riccardo Ray Colciago, Luca Boldrini, Andrea D’Aviero, Francesca De Felice, Roberta Grassi, Giuseppe Carlo Iorio, Silvia Longo, Federico Mastroleo, Isacco Desideri, Viola Salvestrini
La radiologia medica.2024; 129(11): 1720. CrossRef
Selection of induction chemotherapy cycles for stage N3 nasopharyngeal carcinoma based on pre-treatment plasma EBV DNA
Youliang Weng, Sunqin Cai, Chao Li, Yun Xu, Yuhui Pan, Zongwei Huang, Ying Li, Zijie Wu, Yu Chen, Sufang Qiu
Scientific Reports.2024;[Epub] CrossRef
A Nomogram for Predicting Recurrence in Stage I Non‐Small Cell Lung Cancer
Rongrong Bian, Feng Zhao, Bo Peng, Jin Zhang, Qixing Mao, Lin Wang, Qiang Chen
The Clinical Respiratory Journal.2024;[Epub] CrossRef
Individualized number of induction chemotherapy cycles for locoregionally advanced nasopharyngeal carcinoma patients based on early tumor response
Yu‐Ting Jiang, Kai‐Hua Chen, Zhong‐Guo Liang, Jie Yang, Song Qu, Ling Li, Xiao‐Dong Zhu
Cancer Medicine.2023; 12(4): 4010. CrossRef
The feasibility of reduced-dose radiotherapy in childhood nasopharyngeal carcinoma with favorable response to neoadjuvant chemotherapy
Ji-Jin Yao, Ya-Nan Jin, Yu-Jing Lin, Wang-Jian Zhang, Tia Marks, Ian Ryan, Hong-Yu Zhang, Liang-Ping Xia
Radiotherapy and Oncology.2023; 178: 109414. CrossRef
Conditional survival nomogram for monitoring real-time survival of young non-metastatic nasopharyngeal cancer survivors
Jianing Luo, Xiaonan Hu, Xiaofeng Ge
Journal of Cancer Research and Clinical Oncology.2023; 149(12): 10181. CrossRef
Construction of Prognostic Nomogram in Patients with N3-Stage Nasopharyngeal Carcinoma
Wenmiao Cao, Xiaoxin Li, Jianqi Yang, Enming Xing, Wenjuan Wu, Yizhi Ge, Buhai Wang
ORL.2023; 85(4): 195. CrossRef
Regional lymph node density-based nomogram predicts prognosis in nasopharyngeal carcinoma patients without distant metastases
Jie Ma, Rong Zhao, Yu-Lan Wu, Yang Liu, Guan-Qiao Jin, Dan-Ke Su
Cancer Imaging.2023;[Epub] CrossRef
Does three cycles of neoadjuvant chemotherapy prior to concurrent chemoradiotherapy provide benefits for all childhood patients with locoregionally advanced nasopharyngeal carcinoma?
Ya-Nan Jin, Hui-Jiao Cao, Xiao-Hua Gong, Wang-Jian Zhang, Tia Marks, Ji-Jin Yao, Liang-Ping Xia
Journal of Cancer Research and Clinical Oncology.2022; 148(10): 2569. CrossRef
Development of a web-based prognostic model to quantify the survival benefit of cumulative cisplatin dose during concurrent chemoradiotherapy in childhood nasopharyngeal carcinoma
Ya-Nan Jin, Qian-Qiong Yang, Zi-Qian Li, Xue-Qing Ou, Wang-Jian Zhang, Tia Marks, Ji-Jin Yao, Liang-Ping Xia
Radiotherapy and Oncology.2022; 166: 118. CrossRef
A predictive web-based nomogram for the early death of patients with lung adenocarcinoma and bone metastasis: a population-based study
Zhehong Li, Junqiang Wei, Haiying Cao, Mingze Song, Yafang Zhang, Yu Jin
Journal of International Medical Research.2021;[Epub] CrossRef
The Role of Pretreatment 18F-FDG PET/CT for Early Prediction of Neoadjuvant Chemotherapy Response in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma
Jijin Yao, Ying Wang, Yujing Lin, Yingying Yang, Jingjing Wan, Xiaohua Gong, Fanwei Zhang, Wangjian Zhang, Tia Marks, Siyang Wang, Hongjun Jin, Hong Shan
Drug Design, Development and Therapy.2021; Volume 15: 4157. CrossRef

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Gynecologic cancer

A Preoperative Nomogram for Predicting Chemoresistance to Neoadjuvant Chemotherapy in Patients with Locally Advanced Cervical Squamous Carcinoma Treated with Radical Hysterectomy: Zhengjie Ou, Dan Zhao, Bin Li, Yating Wang, Shuanghuan Liu, Yanan Zhang; Cancer Res Treat. 2021;53(1):233-242. Published online September 14, 2020; DOI: https://doi.org/10.4143/crt.2020.159

Abstract PDF PubReader ePub

Purpose
This study aimed to investigate the factors associated with chemoresistance to neoadjuvant chemotherapy (NACT) followed by radical hysterectomy (RH) and construct a nomogram to predict the chemoresistance in patients with locally advanced cervical squamous carcinoma (LACSC).
Materials and Methods
This retrospective study included 516 patients with International Federation of Gynecology and Obstetrics (2003) stage IB2 and IIA2 cervical cancer treated with NACT and RH between 2007 and 2017. Clinicopathologic data were collected, and patients were assigned to training (n=381) and validation (n=135) sets. Univariate and multivariate analyses were performed to analyze factors associated with chemoresistance to NACT. A nomogram was built using the multivariate logistic regression analysis results. We evaluated the discriminative ability and accuracy of the model using a concordance index and a calibration curve. The predictive probability of chemoresistance to NACT was defined as > 34%.
Results
Multivariate analysis confirmed menopausal status, clinical tumor diameter, serum squamous cell carcinoma antigen level, and parametrial invasion on magnetic resonance imaging before treatment as independent prognostic factors associated with chemoresistance to NACT. The concordance indices of the nomogram for training and validation sets were 0.861 (95% confidence interval [CI], 0.822 to 0.900) and 0.807 (95% CI, 0.807 to 0.888), respectively. Calibration plots revealed a good fit between the modelpredicted probabilities and actual probabilities (Hosmer-Lemeshow test, p=0.597). Furthermore, grouping based on the nomogram was associated with progression-free survival.
Conclusion
We developed a nomogram for predicting chemoresistance in LACSC patients treated with RH. This nomogram can help physicians make clinical decisions regarding primary management and postoperative follow-up of the patients.

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Neoadjuvant chemotherapy with carboplatin and paclitaxel in pregnant women with advanced stage cervical cancer: Maternal and perinatal outcomes
Bruna Elias Parreira Lopes Ferraz, Roney César Signorini Filho, Lucas Ribeiro Borges Carvalho, Michelle Samora Almeida, Tatiana Carvalho de Souza Bonetti, Edward Araujo Júnior, Antonio Braga, Sue Yazaki Sun
Journal of Gynecology Obstetrics and Human Reproduction.2025; 54(2): 102890. CrossRef
Are biomarkers expression and clinical-pathological factors predictive markers of the efficacy of neoadjuvant chemotherapy for locally advanced cervical cancer?
Antonino Ditto, Mariangela Longo, Giulia Chiarello, Luigi Mariani, Biagio Paolini, Umberto Leone Roberti Maggiore, Fabio Martinelli, Giorgio Bogani, Francesco Raspagliesi
European Journal of Surgical Oncology.2024; 50(6): 108311. CrossRef
A Deep Learning Radiomics Nomogram to Predict Response to Neoadjuvant Chemotherapy for Locally Advanced Cervical Cancer: A Two-Center Study
Yajiao Zhang, Chao Wu, Zhibo Xiao, Furong Lv, Yanbing Liu
Diagnostics.2023; 13(6): 1073. CrossRef
Machine Learning-Assisted Ensemble Analysis for the Prediction of Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer
Yibao Huang, Qingqing Zhu, Liru Xue, Xiaoran Zhu, Yingying Chen, Mingfu Wu
Frontiers in Oncology.2022;[Epub] CrossRef

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Gastrointestinal cancer

An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer: Jiahui Chen, Anqiang Wang, Jun Ji, Kai Zhou, Zhaode Bu, Guoqing Lyu, Jiafu Ji; Cancer Res Treat. 2021;53(1):148-161. Published online August 31, 2020; DOI: https://doi.org/10.4143/crt.2020.424

Abstract PDF Supplementary Material PubReader ePub

Purpose
Gastric cancer (GC) has substantial biological differences between Asian and non-Asian populations, which makes it difficult to have a unified predictive measure for all people. We aimed to identify novel prognostic biomarkers to help predict the prognosis of Asian GC patients.
Materials and Methods
We investigated the differential gene expression between GC and normal tissues of GSE66229. Univariate, multivariate and Lasso Cox regression analyses were conducted to establish a four-gene-related prognostic model based on the risk score. The risk score was based on a linear combination of the expression levels of individual genes multiplied by their multivariate Cox regression coefficients. Validation of the prognostic model was conducted using The Cancer Genome Atlas (TCGA) database. A nomogram containing clinical characteristics and the prognostic model was established to predict the prognosis of Asian GC patients.
Results
Four genes (RBPMS2, RGN, PLEKHS1, and CT83) were selected to establish the prognostic model, and it was validated in the TCGA Asian cohort. Receiver operating characteristic analysis confirmed the sensitivity and specificity of the prognostic model. Based on the prognostic model, a nomogram containing clinical characteristics and the prognostic model was established, and Harrell’s concordance index of the nomogram for evaluating the overall survival significantly higher than the model only focuses on the pathologic stage (0.74 vs. 0.64, p < 0.001).
Conclusion
The four-gene-related prognostic model and the nomogram based on it are reliable tools for predicting the overall survival of Asian GC patients.

Citations

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Nivolumab plus anlotinib hydrochloride in advanced gastric adenocarcinoma and esophageal squamous cell carcinoma: the phase II OASIS trial
Jing Wu, Shilong Zhang, Shan Yu, Guo An, Yi Wang, Yiyi Yu, Li Liang, Yan Wang, Xiaojing Xu, YanShi Xiong, Di Shao, Zhun Shi, Nannan Li, Jingyuan Wang, Dawei Jin, Tianshu Liu, Yuehong Cui
Nature Communications.2024;[Epub] CrossRef
An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma
Xiaoling Hong, Kai Zhuang, Na Xu, Jiang Wang, Yong Liu, Siqi Tang, Junzhang Zhao, Zunnan Huang
Frontiers in Molecular Biosciences.2023;[Epub] CrossRef
Analysis and application of RNA binding protein gene pairs to predict the prognosis of gastric cancer
Zhi-kun Ning, Hua-kai Tian, Jiang Liu, Ce-gui Hu, Zi-tao Liu, Hui Li, Zhen Zong
Heliyon.2023; 9(7): e18242. CrossRef
PLEKHS1 drives PI3Ks and remodels pathway homeostasis in PTEN-null prostate
Tamara A.M. Chessa, Piotr Jung, Arqum Anwar, Sabine Suire, Karen E. Anderson, David Barneda, Anna Kielkowska, Barzan A. Sadiq, Ieng Wai Lai, Sergio Felisbino, Daniel J. Turnham, Helen B. Pearson, Wayne A. Phillips, Junko Sasaki, Takehiko Sasaki, David Oxl
Molecular Cell.2023; 83(16): 2991. CrossRef
Evaluation of vital genes correlated with CD8 + T cell infiltration as prognostic biomarkers in stomach adenocarcinoma
Dun Pan, Hui Chen, Jiaxiang Xu, Xin Lin, Liangqing Li
BMC Gastroenterology.2023;[Epub] CrossRef
Bayesian hierarchical lasso Cox model: A 9-gene prognostic signature for overall survival in gastric cancer in an Asian population
Jiadong Chu, Na Sun, Wei Hu, Xuanli Chen, Nengjun Yi, Yueping Shen, Andy T. Y. Lau
PLOS ONE.2022; 17(4): e0266805. CrossRef
Three Prognostic Biomarkers Correlate with Immune Checkpoint Blockade Response in Bladder Urothelial Carcinoma
Ya Guo, Yin Bin Zhang, Yi Li, Wang Hui Su, Shan He, Shu Pei Pan, Kun Xu, Wei Hua Kou, Luca Falzone
International Journal of Genomics.2022; 2022: 1. CrossRef
KK-LC-1 may be an effective prognostic biomarker for gastric cancer
Jun Ji, Jiahui Chen, Anqiang Wang, Wei Zhang, Hongge Ju, Yang Liu, Leping Li
BMC Cancer.2021;[Epub] CrossRef
Multiomics analysis reveals CT83 is the most specific gene for triple negative breast cancer and its hypomethylation is oncogenic in breast cancer
Chen Chen, Dan Gao, Jinlong Huo, Rui Qu, Youming Guo, Xiaochi Hu, Libo Luo
Scientific Reports.2021;[Epub] CrossRef
Integrative analysis-based identification and validation of a prognostic immune cell infiltration-based model for patients with advanced gastric cancer
Siwei Pan, Qi Gao, Qingchuan Chen, Pengfei Liu, Yuen Tan, Funan Liu, Huimian Xu
International Immunopharmacology.2021; 101: 108258. CrossRef

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High Systemic Inflammation Response Index (SIRI) Indicates Poor Outcome in Gallbladder Cancer Patients with Surgical Resection: A Single Institution Experience in China: Lejia Sun, Wenmo Hu, Meixi Liu, Yang Chen, Bao Jin, Haifeng Xu, Shunda Du, Yiyao Xu, Haitao Zhao, Xin Lu, Xinting Sang, Shouxian Zhong, Huayu Yang, Yilei Mao; Cancer Res Treat. 2020;52(4):1199-1210. Published online July 21, 2020; DOI: https://doi.org/10.4143/crt.2020.303

Abstract PDF PubReader ePub

Purpose
The systemic inflammation response index (SIRI) has been reported to have prognostic ability in various solid tumors but has not been studied in gallbladder cancer (GBC). We aimed to determine its prognostic value in GBC.
Materials and Methods
From 2003 to 2017, patients with confirmed GBC were recruited. To determine the SIRI’s optimal cutoff value, a time-dependent receiver operating characteristic curve was applied. Univariate and multivariate Cox analyses were performed for the recognition of significant factors. Then the cohort was randomly divided into the training and the validation set. A nomogram was constructed using the SIRI and other selected indicators in the training set, and compared with the TNM staging system. C-index, calibration plots, and decision curve analysis were performed to assess the nomogram’s clinical utility.
Results
One hundred twenty-four patients were included. The SIRI’s optimal cutoff value divided patients into high (≥ 0.89) and low SIRI (< 0.89) groups. Kaplan-Meier curves according to SIRI levels were significantly different (p < 0.001). The high SIRI group tended to stay longer in hospital and lost more blood during surgery. SIRI, body mass index, weight loss, carbohydrate antigen 19-9, radical surgery, and TNM stage were combined to generate a nomogram (C-index, 0.821 in the training cohort, 0.828 in the validation cohort) that was significantly superior to the TNM staging system both in the training (C-index, 0.655) and validation cohort (C-index, 0.649).
Conclusion
The SIRI is an independent predictor of prognosis in GBC. A nomogram based on the SIRI may help physicians to precisely stratify patients and implement individualized treatment.

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Combining systemic inflammatory response index and albumin fibrinogen ratio to predict early serious complications and prognosis after resectable gastric cancer
Jing-Yao Ren, Da Wang, Li-Hui Zhu, Shuo Liu, Miao Yu, Hui Cai
World Journal of Gastrointestinal Oncology.2024; 16(3): 732. CrossRef
Association of Systemic Inflammation Response Index with Short-Term All-Cause Mortality in Decompensated Liver Cirrhosis Patients
Jin Cheng, Honglei Ju, Guixiang Wang, Chiyi He, Wei Wang
Journal of Inflammation Research.2024; Volume 17: 8985. CrossRef
Advances in the Study of the Relationship between Inflammation Markers and Post-Stroke Depression
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The systemic inflammation response index as a significant predictor of short-term adverse outcomes in acute decompensated heart failure patients: a cohort study from Southern China
Lin Xie, Qun Wang, Hengcheng Lu, Maobin Kuang, Shiming He, Guobo Xie, Guotai Sheng, Shuhua Zhang, Wei Wang, Yang Zou
Frontiers in Endocrinology.2024;[Epub] CrossRef
The role of systemic inflammatory response index (SIRI) and tumor-infiltrating lymphocytes (TILs) in the prognosis of patients with laryngeal squamous cell carcinoma
Tian Wang, Duo Zhang, Di Tang, Yu Heng, Li-ming Lu, Lei Tao
Journal of Cancer Research and Clinical Oncology.2023; 149(9): 5627. CrossRef
Preoperative Fibrinogen Albumin Ratio is an Effective Biomarker for Prognostic Evaluation of Gallbladder Carcinoma After Radical Resection: A 10-Year Retrospective Study at a Single Center
Qi Li, Jian Zhang, Qi Gao, Jialu Fu, Mengke Li, Hengchao Liu, Chen Chen, Dong Zhang, Zhimin Geng
Journal of Inflammation Research.2023; Volume 16: 677. CrossRef
Preoperative systemic inflammatory response index predicts the prognosis of patients with hepatocellular carcinoma after liver transplantation
Songping Cui, Shuang Cao, Qing Chen, Qiang He, Ren Lang
Frontiers in Immunology.2023;[Epub] CrossRef
Assessment of aggregate index of systemic inflammation and systemic inflammatory response index in dry age-related macular degeneration: a retrospective study
Naif S. Sannan
Frontiers in Medicine.2023;[Epub] CrossRef
Value of preoperative systemic inflammatory response index and prognostic nutritional index in predicting prognosis of patients with superficial esophageal squamous cell carcinoma
Jing Wang, Xue-Li Ding, Zi-Bin Tian
World Chinese Journal of Digestology.2023; 31(9): 369. CrossRef
The Prognostic Value and Potential Mechanism of Tumor-Nutrition-Inflammation Index and Genes in Patients with Advanced Lung Cancer
Huan Wang, Yuting Shi, Yueli Shi, Mengqing Cao, Long Zhang, Yuan Wu, Yun Xu, Kai Wang, Xianwu Weng, Bing Niu
International Journal of Clinical Practice.2023; 2023: 1. CrossRef
The Potential Value of Systemic Inflammation Response Index on Delirium After Hip Arthroplasty Surgery in Older Patients: A Retrospective Study
Wenbin Lu, Shengwei Lin, Cheng Wang, Peipei Jin, Jinjun Bian
International Journal of General Medicine.2023; Volume 16: 5355. CrossRef
Systemic Inflammation Response Index (SIRI) Independently Predicts Survival in Advanced Lung Adenocarcinoma Patients Treated with First-Generation EGFR-TKIs
Shun Jiang, Sisi Wang, Qianqian Wang, Chao Deng, Yuhua Feng, Fang Ma, Jin'an Ma, Xianling Liu, Chunhong Hu, Tao Hou
Cancer Management and Research.2021; Volume 13: 1315. CrossRef
The Prognostic Value of Preoperative Systemic Inflammatory Response Index (SIRI) in Patients With High-Grade Glioma and the Establishment of a Nomogram
Qian He, Longhao Li, Qinglan Ren
Frontiers in Oncology.2021;[Epub] CrossRef
Prognostic Value of Inflammatory Biomarkers in Patients With Stage I Lung Adenocarcinoma Treated With Surgical Dissection
Yu-Jia Shen, Li-Qiang Qian, Zheng-Ping Ding, Qing-Quan Luo, Heng Zhao, Wu-Yan Xia, Yuan-Yuan Fu, Wen Feng, Qin Zhang, Wen Yu, Xu-Wei Cai, Xiao-Long Fu
Frontiers in Oncology.2021;[Epub] CrossRef

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Head/neck cancer

Nomogram for Predicting Central Lymph Node Metastasis in Papillary Thyroid Cancer: A Retrospective Cohort Study of Two Clinical Centers: Zheyu Yang, Yu Heng, Jianwei Lin, Chenghao Lu, Dingye Yu, Lei Tao, Wei Cai; Cancer Res Treat. 2020;52(4):1010-1018. Published online June 9, 2020; DOI: https://doi.org/10.4143/crt.2020.254

Abstract PDF PubReader ePub

Purpose
Central lymph node metastasis (CNM) are highly prevalent but hard to detect preoperatively in papillary thyroid carcinoma (PTC) patients, while the significance of prophylactic compartment central lymph node dissection (CLND) remains controversial as a treatment option. We aim to establish a nomogram assessing risks of CNM in PTC patients, and explore whether prophylactic CLND should be recommended.
Materials and Methods
One thousand four hundred thirty-eight patients from two clinical centers that underwent thyroidectomy with CLND for PTC within the period 2016–2019 were retrospectively analyzed. Univariate and multivariate analysis were performed to examine risk factors associated with CNM. A nomogram for predicting CNM was established, thereafter internally and externally validated.
Results
Seven variables were found to be significantly associated with CNM and were used to construct the model. These were as follows: thyroid capsular invasion, multifocality, creatinine > 70 μmol/L, age < 40, tumor size > 1 cm, body mass index < 22, and carcinoembryonic antigen > 1 ng/mL. The nomogram had good discrimination with a concordance index of 0.854 (95% confidence interval [CI], 0.843 to 0.867), supported by an external validation point estimate of 0.825 (95% CI, 0.793 to 0.857). A decision curve analysis was made to evaluate nomogram and ultrasonography for predicting CNM.
Conclusion
A validated nomogram utilizing readily available preoperative variables was developed to predict the probability of central lymph node metastases in patients presenting with PTC. This nomogram may help surgeons make appropriate surgical decisions in the management of PTC, especially in terms of whether prophylactic CLND is warranted.

Citations

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Ultrasonic Feature Prediction of Large-Number Central Lymph Node Metastasis in Clinically Node-Negative Solitary Papillary Thyroid Carcinoma
Weihan Xiao, Xiaomin Hu, Chaoxue Zhang, Xiachuan Qin
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Yubo Sun, Wei Sun, Jingzhe Xiang, Hao Zhang
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An integrated nomogram combining deep learning, clinical characteristics and ultrasound features for predicting central lymph node metastasis in papillary thyroid cancer: A multicenter study
Luchen Chang, Yanqiu Zhang, Jialin Zhu, Linfei Hu, Xiaoqing Wang, Haozhi Zhang, Qing Gu, Xiaoyu Chen, Sheng Zhang, Ming Gao, Xi Wei
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Central and lateral neck involvement in papillary thyroid carcinoma patients with or without thyroid capsular invasion: A multi-center analysis
Zheyu Yang, Yu Heng, Jian Zhou, Lei Tao, Wei Cai
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Development and validation of nomograms for predicting the risk of central lymph node metastasis of solitary papillary thyroid carcinoma of the isthmus
Yonghao Li, Xuefei Gao, Tiantian Guo, Jing Liu
Journal of Cancer Research and Clinical Oncology.2023; 149(16): 14853. CrossRef
Development and validation of an individualized nomogram for predicting the high-volume (> 5) central lymph node metastasis in papillary thyroid microcarcinoma
X. Wei, Y. Min, Y. Feng, D. He, X. Zeng, Y. Huang, S. Fan, H. Chen, J. Chen, K. Xiang, H. Luo, G. Yin, D. Hu
Journal of Endocrinological Investigation.2022; 45(3): 507. CrossRef
Preoperative Prediction of Central Cervical Lymph Node Metastasis in Fine-Needle Aspiration Reporting Suspicious Papillary Thyroid Cancer or Papillary Thyroid Cancer Without Lateral Neck Metastasis
Kai Zhang, Lang Qian, Jieying Chen, Qian Zhu, Cai Chang
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Relationship between subgroups of central and lateral lymph node metastasis in clinically node-negative papillary thyroid carcinoma
Jing Zhou, Da-Xue Li, Han Gao, Xin-Liang Su
World Journal of Clinical Cases.2022; 10(12): 3709. CrossRef
Hashimoto’s Thyroiditis Is Associated With Central Lymph Node Metastasis in Classical Papillary Thyroid Cancer: Analysis from a High-Volume Single-Center Experience
Bin Zeng, Yu Min, Yang Feng, Ke Xiang, Hang Chen, Zijing Lin
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Nomogram model based on preoperative serum thyroglobulin and clinical characteristics of papillary thyroid carcinoma to predict cervical lymph node metastasis
Qungang Chang, Jieming Zhang, Yaqian Wang, Hongqiang Li, Xin Du, Daohong Zuo, Detao Yin
Frontiers in Endocrinology.2022;[Epub] CrossRef
Ultrasound-based radiomics nomogram combined with clinical features for the prediction of central lymph node metastasis in papillary thyroid carcinoma patients with Hashimoto’s thyroiditis
Peile Jin, Jifan Chen, Yiping Dong, Chengyue Zhang, Yajun Chen, Cong Zhang, Fuqiang Qiu, Chao Zhang, Pintong Huang
Frontiers in Endocrinology.2022;[Epub] CrossRef
Lateral Involvement in Different Sized Papillary Thyroid Carcinomas Patients with Central Lymph Node Metastasis: A Multi-Center Analysis
Yu Heng, Zheyu Yang, Pengyu Cao, Xi Cheng, Lei Tao
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Risk factors and prediction models of lymph node metastasis in papillary thyroid carcinoma based on clinical and imaging characteristics
Yanyuan Deng, Jie Zhang, Jiao Wang, Jinying Wang, Junping Zhang, Lulu Guan, Shasha He, Xiudan Han, Wei Cai, Jixiong Xu
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Construction and validation of a nomogram for predicting cervical lymph node metastasis in classic papillary thyroid carcinoma
Y. Feng, Y. Min, H. Chen, K. Xiang, X. Wang, G. Yin
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Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma
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Reevaluation of Criteria and Establishment of Models for Total Thyroidectomy in Differentiated Thyroid Cancer
Zhenghao Wu, Yunxiao Xiao, Jie Ming, Yiquan Xiong, Shuntao Wang, Shengnan Ruan, Tao Huang
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Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study
Jingjing Li, Xinxin Wu, Ning Mao, Guibin Zheng, Haicheng Zhang, Yakui Mou, Chuanliang Jia, Jia Mi, Xicheng Song
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Nomogram Including Elastography for Prediction of Contralateral Central Lymph Node Metastasis in Solitary Papillary Thyroid Carcinoma Preoperatively

Ning Li, Ju-hua He, Chao Song, Li-chun Yang, Hong-jiang Zhang, Zhi-hai Li
Cancer Management and Research.2020; Volume 12: 10789. CrossRef

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Establishment and Validation of a Nomogram for Nasopharyngeal Carcinoma Patients Concerning the Prognostic Effect of Parotid Lymph Node Metastases: Chao Lin, Xue-Song Sun, Sai-Lan Liu, Xiao-Yun Li, Nian Lu, Xin-Ling Li, Lin-Quan Tang, Ling Guo; Cancer Res Treat. 2020;52(3):855-866. Published online March 10, 2020; DOI: https://doi.org/10.4143/crt.2019.772

Abstract PDF PubReader ePub

Purpose
The prognosis of nasopharyngeal carcinoma (NPC) patients with parotid lymph node (PLN) metastasis remains unclear. This study was performed to investigate the prognostic significance and optimal staging category of PLN metastasis and develop a nomogram for estimating individual risk.
Materials and Methods
Clinical data of 7,084 non-metastatic NPC patients were retrospectively reviewed. Overall survival (OS) was the primary endpoint. A nomogram was established based on the Cox proportional hazards regression model. The accuracy and calibration ability of this nomogram was evaluated by C-index and calibration curves with bootstrap validation.
Result
Totally, 164/7,084 NPC patients (2.3%) presented with PLNs. Multivariate analyses showed that PLN metastasis was a negative prognostic factor for OS, progression-free survival (PFS), distant metastasis-free survival (DMFS), and locoregional relapse-free survival (LRFS). Patients with PLN metastasis had a worse prognosis than N3 disease. Five independent prognostic factors were included in the nomogram, which showed a C-index of 0.743. The calibration curves for probability of 3- and 5-year OS indicated satisfactory agreement between nomogram-based prediction and actual observation. All results were confirmed in the validation cohort.
Conclusion
NPC patient with PLN metastasis had poorer survival outcome (OS, PFS, DMFS, and LRFS) than N3 disease. We developed a nomogram to provide individual prediction of OS for patients with PLN metastasis.

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Analysis of patients with parotid recurrence after parotid-sparing IMRT for nasopharyngeal carcinoma: case series and review of the literature
Sezin Yuce Sari, Melek Tugce Yilmaz, Gozde Yazici, Sepideh Mohammadipour, Gokhan Ozyigit, Ibrahim Gullu, Mustafa Cengiz
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Nomogram Based on Liver Function Test Indicators for Survival Prediction in Nasopharyngeal Carcinoma Patients Receiving PD-1 Inhibitor Therapy
Lixia Liang, Yan Li, Yansui Hong, Tianxing Ji, Hao Chen, Zhifang Lin
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A Randomized Controlled Trial on Evaluation of Plasma Epstein-Barr Virus Biomarker for Early Diagnosis in Patients With Nasopharyngeal Carcinoma
Wen Liu, Huilan Li, Hui Sheng, Xiaohua Liu, Peidong Chi, Xueping Wang, Minjie Mao
Advances in Therapy.2020; 37(10): 4280. CrossRef
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Qianqian Xia, Hua Jin, Xing Zhang, Wenjing Yan, Dan Meng, Bo Ding, Jian Cao, Dake Li, Shizhi Wang
International Immunopharmacology.2020; 88: 106935. CrossRef

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An Integrated Nomogram Combining Clinical Factors and Microtubule-Associated Protein 1 Light Chain 3B Expression to Predict Postoperative Prognosis in Patients with Intrahepatic Cholangiocarcinoma: Liang Chen, Hongyuan Fu, Tongyu Lu, Jianye Cai, Wei Liu, Jia Yao, Jinliang Liang, Hui Zhao, Jiebin Zhang, Jun Zheng, Yingcai Zhang, Yang Yang; Cancer Res Treat. 2020;52(2):469-480. Published online October 7, 2019; DOI: https://doi.org/10.4143/crt.2019.423

Abstract PDF Supplementary Material PubReader ePub

Purpose
Microtubule-associated protein 1 light chain 3B (LC3B) serves as a key component of autophagy, which is associated with the progression of carcinoma. Yet, it is still unclear whether LC3B is also an independent risk factor for intrahepatic cholangiocarcinoma (ICC). We aim to explore the predictive value of LC3B on prognosis of ICC, and to establish a novel and available nomogram to predict relapse-free survival (RFS) and overall survival (OS) for these patients after curative-intent hepatectomy.
Materials and Methods
From August 2004 to March 2017, 105 ICC patients were eligibly enrolled in the Third Affiliated Hospital of Sun Yat-sen University. Preoperative clinical information of enrolled patients was collected. Expression LC3B in the ICC specimen was detected by immunohistochemistry.
Results
The 5-year RFS and OS in this cohort were 15.7% and 29.6%, respectively. On multivariate Cox regression analysis, independent risk factors for 5-year OS were cancer antigen 125, microvascular invasion, LC3B expression and lymph node metastasis. Except for the above 4 factors, neutrophil/lymphocyte ratio and tumor differentiation were independent factors for 5-year RFS. The area under the curve of nomograms for OS and RFS were 0.820 and 0.747, respectively.
Conclusion
The nomograms based on LC3B can be considered as effective models to predict postoperative survival for ICC patients.

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Lymph node metastasis of intrahepatic cholangiocarcinoma: the present and prospect of detection and dissection
Ruoyu Zhang, Yunfei Tan, Mei Liu, Liming Wang
European Journal of Gastroenterology & Hepatology.2024; 36(12): 1359. CrossRef
Active Autophagy Is Associated with Favorable Outcome in Patients with Surgically Resected Cholangiocarcinoma
Katrin Bankov, Falko Schulze, Steffen Gretser, Henning Reis, Nada Abedin, Fabian Finkelmeier, Jörg Trojan, Stefan Zeuzem, Andreas A. Schnitzbauer, Dirk Walter, Peter J. Wild, Maximilian N. Kinzler
Cancers.2023; 15(17): 4322. CrossRef
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Hayat Khizar, Yufei Hu, Yanhua Wu, Jianfeng Yang
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Immunogenomics of cholangiocarcinoma
Virag Gehl, Colm J. O’Rourke, Jesper B. Andersen
Hepatology.2023;[Epub] CrossRef
Multiparametric MRI‐Based Radiomic Signature for Preoperative Evaluation of Overall Survival in Intrahepatic Cholangiocarcinoma After Partial Hepatectomy
Yang Yang, Xianlun Zou, Wei Zhou, Guanjie Yuan, Daoyu Hu, Dong Kuang, Yaqi Shen, Qingguo Xie, Qingpeng Zhang, Xuemei Hu, Zhen Li
Journal of Magnetic Resonance Imaging.2022; 56(3): 739. CrossRef
A Myeloid Signature-Based Nomogram Predicts the Postoperative Recurrence of Intrahepatic Cholangiocarcinoma
Jing Liang, Hui Zhou, Xiang-Qi Huang, Yan-Fei Liu, Lei Zhang, Dan He, Yongmei Cui, Jinrui Guo, Kunpeng Hu, Chong Wu
Frontiers in Molecular Biosciences.2021;[Epub] CrossRef
Therapeutic Potential of Autophagy Modulation in Cholangiocarcinoma
Hector Perez-Montoyo
Cells.2020; 9(3): 614. CrossRef

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8 Web of Science
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Novel Prognostic Nomograms Based on Inflammation-Related Markers for Patients with Hepatocellular Carcinoma Underwent Hepatectomy: Yifei Wang, Kaiyu Sun, Jingxian Shen, Bin Li, Ming Kuang, Qinghua Cao, Sui Peng; Cancer Res Treat. 2019;51(4):1464-1478. Published online March 11, 2019; DOI: https://doi.org/10.4143/crt.2018.657

Abstract PDF Supplementary Material PubReader ePub

Purpose
Hepatocellular carcinoma (HCC) is an aggressive disease with high recurrence rate. However, current staging systems were lack of predictive capacity for HCC recurrence. We aimed to develop prognostic nomograms based on inflammation-related markers for HCC patients underwent hepatectomy.
Materials and Methods
We recruited 889 surgically treated patients from two medical centers. Independent prognostic factors were identified by cox regression analyses. Nomograms for recurrence-free survival (RFS) and overall survival (OS) were established, and validated internally and externally. The performance, discrimination, and calibration of nomograms were assessed, and compared with existed staging systems.
Results
Neutrophil to lymphocyte ratio (NLR) and gamma-glutamyl transpeptidase to platelet ratio (GPR) were the two inflammation-related factor that independently correlated with survival. NLR, GPR, international normalized ratio (INR), microvascular invasion, satellite lesions, tumour number, tumour diameter, and macrovascular invasion were used to construct nomogram for RFS while GPR, total bilirubin, INR, α-fetoprotein, microvascular invasion, satellite lesions, tumour diameter, and macrovascular invasion were for OS. In the training cohort, the C-index of nomogram was 0.701 (95% confidence interval [CI], 0.669 to 0.732) for RFS and 0.761 (95% CI, 0.728 to 0.795) for OS. These results received both internal and external validation with C-index of 0.701 (95% CI, 0.647 to 0.755) and 0.707 (95% CI, 0.657 to 0.756) for RFS, and 0.706 (95% CI, 0.640 to 0.772) and 0.708 (95% CI, 0.646 to 0.771) for OS, respectively. The nomograms showed superior accuracy to conventional staging systems (p<0.001).
Conclusion
The nomograms based on inflammation-related markers are of high efficacy in predicting survival of HCC patients after hepatectomy, which will be valuable in guiding postoperative interventions and follow-ups.

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Lei Liu, Shangdong Qin, Kongying Lin, Qingguo Xu, Yuan Yang, Jinzhen Cai, Yongyi Zeng, Shengxian Yuan, Bangde Xiang, Wan Yee Lau, Weiping Zhou
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Carlos Constantin Otto, Guanwu Wang, Anna Mantas, Daniel Heise, Philipp Bruners, Sven Arke Lang, Tom Florian Ulmer, Ulf Peter Neumann, Lara Rosaline Heij, Jan Bednarsch
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Yang Zhang, Fangfang Jin, Yuan Wu, Bingyu Wang, Jingri Xie, Yu Li, Yujia Pan, Zhaolan Liu, Wenjuan Shen
European Journal of Gastroenterology & Hepatology.2023; 35(8): 803. CrossRef
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OncoTargets and Therapy.2020; Volume 13: 2093. CrossRef
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Dynamic Changes in the Neutrophil-to-Lymphocyte Ratio Predict the Prognosis of Patients with Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization

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Cancer Management and Research.2020; Volume 12: 3433. CrossRef
Combination of preoperative neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio: a superior prognostic factor of endometrial cancer
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Nomogram Development and External Validation for Predicting the Risk of Lymph Node Metastasis in T1 Colorectal Cancer: Jung Ryul Oh, Boram Park, Seongdae Lee, Kyung Su Han, Eui-Gon Youk, Doo-Han Lee, Do-Sun Kim, Doo-Seok Lee, Chang Won Hong, Byung Chang Kim, Bun Kim, Min Jung Kim, Sung Chan Park, Dae Kyung Sohn, Hee Jin Chang, Jae Hwan Oh; Cancer Res Treat. 2019;51(4):1275-1284. Published online January 17, 2019; DOI: https://doi.org/10.4143/crt.2018.569

Abstract PDF Supplementary Material PubReader ePub

Purpose
Predicting lymph node metastasis (LNM) risk is crucial in determining further treatment strategies following endoscopic resection of T1 colorectal cancer (CRC). This study aimed to establish a new prediction model for the risk of LNM in T1 CRC patients.
Materials and Methods
The development set included 833 patients with T1 CRC who had undergone endoscopic (n=154) or surgical (n=679) resection at the National Cancer Center. The validation set included 722 T1 CRC patients who had undergone endoscopic (n=249) or surgical (n=473) resection at Daehang Hospital. A logistic regression model was used to construct the prediction model. To assess the performance of prediction model, discrimination was evaluated using the receiver operating characteristic (ROC) curves with area under the ROC curve (AUC), and calibration was assessed using the Hosmer-Lemeshow (HL) goodness-of-fit test.
Results
Five independent risk factors were determined in the multivariable model, including vascular invasion, high-grade histology, submucosal invasion, budding, and background adenoma. In final prediction model, the performance of the model was good that the AUC was 0.812 (95% confidence interval [CI], 0.770 to 0.855) and the HL chi-squared test statistic was 1.266 (p=0.737). In external validation, the performance was still good that the AUC was 0.771 (95% CI, 0.708 to 0.834) and the p-value of the HL chi-squared test was 0.040. We constructed the nomogram with the final prediction model.
Conclusion
We presented an externally validated new prediction model for LNM risk in T1 CRC patients, guiding decision making in determining whether additional surgery is required after endoscopic resection of T1 CRC.

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Lupei Yan, Jingxing Tan, Hao Chen, Han Xiao, Yi Zhang, Qin Yao, Yuerong Li
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Zhenghua Piao, Rong Ge, Chunnian Wang
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Yoshiki Kajiwara, Shiro Oka, Shinji Tanaka, Takahiro Nakamura, Shoichi Saito, Yosuke Fukunaga, Manabu Takamatsu, Hiroshi Kawachi, Kinichi Hotta, Hiroaki Ikematsu, Motohiro Kojima, Yutaka Saito, Masayoshi Yamada, Yukihide Kanemitsu, Shigeki Sekine, Shinji
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Chao-Tao Tang, Jun Li, Peng Wang, You-Xiang Chen, Chun-Yan Zeng
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Karmele Saez de Gordoa, Maria Teresa Rodrigo-Calvo, Ivan Archilla, Sandra Lopez-Prades, Alba Diaz, Jordi Tarragona, Isidro Machado, Juan Ruiz Martín, Diana Zaffalon, Maria Daca-Alvarez, Maria Pellisé, Jordi Camps, Miriam Cuatrecasas
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Ilze Ose, Katarina Levic, Lau Caspar Thygesen, Orhan Bulut, Thue Bisgaard, Ismail Gögenur, Tine Plato Kuhlmann
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Hao Dang, Nik Dekkers, Saskia le Cessie, Jeanin E. van Hooft, Monique E. van Leerdam, Philip P. Oldenburg, Louis Flothuis, Jan W. Schoones, Alexandra M.J. Langers, James C.H. Hardwick, Jolein van der Kraan, Jurjen J. Boonstra
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Xinxin Cheng, Yaxin Lu, Sai Chen, Weilin Yang, Bo Xu, Jianyong Zou, Zhenguang Chen
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Katsuro Ichimasa, Shin‐ei Kudo, Hideyuki Miyachi, Yuta Kouyama, Kenichi Mochizuki, Yuki Takashina, Yasuharu Maeda, Yuichi Mori, Toyoki Kudo, Yuki Miyata, Yoshika Akimoto, Yuki Kataoka, Takafumi Kubota, Tetsuo Nemoto, Fumio Ishida, Masashi Misawa
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Jiawei Song, Huanhuan Yin, Yong Zhu, Shengqi Fei
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Zitao Liu, Chao Huang, Huakai Tian, Yu Liu, Yongshan Huang, Zhengming Zhu
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Jeong-ki Kim, Ye-Young Rhee, Jeong Mo Bae, Jung Ho Kim, Seong-Joon Koh, Hyun Jung Lee, Jong Pil Im, Min Jung Kim, Seung-Bum Ryoo, Seung-Yong Jeong, Kyu Joo Park, Ji Won Park, Gyeong Hoon Kang
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Yusuke Yamaoka, Akio Shiomi, Hiroyasu Kagawa, Hitoshi Hino, Shoichi Manabe, Kai Chen, Kenji Nanishi, Akifumi Notsu
International Journal of Colorectal Disease.2022; 37(11): 2387. CrossRef
Subpopulation analysis of survival in high-risk T1 colorectal cancer: surgery versus endoscopic resection only
Ryun Kyong Ha, Boram Park, Kyung Su Han, Dae Kyung Sohn, Chang Won Hong, Byung Chang Kim, Bun Kim, Sung Chan Park, Hee Jin Chang, Jae Hwan Oh
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Morten Hartwig, Karoline Bendix Bräuner, Rasmus Vogelsang, Ismail Gögenur
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Preoperative Predictors of Lymph Node Metastasis in Colon Cancer
Yansong Xu, Yi Chen, Chenyan Long, Huage Zhong, Fangfang Liang, Ling-xu Huang, Chuanyi Wei, Shaolong Lu, Weizhong Tang
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Risk Stratification of T1 Colorectal Cancer Metastasis to Lymph Nodes: Current Status and Perspective
Katsuro Ichimasa, Shin-ei Kudo, Hideyuki Miyachi, Yuta Kouyama, Masashi Misawa, Yuichi Mori
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Jinlian Jin, Haiyan Zhou, Shulin Sun, Zhe Tian, Haibing Ren, Jinwu Feng
Cancer Management and Research.2021; Volume 13: 8967. CrossRef
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Kaibo Guo, Yuqian Feng, Li Yuan, Harpreet S. Wasan, Leitao Sun, Minhe Shen, Shanming Ruan
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Shaobo Mo, Zheng Zhou, Weixing Dai, Wenqiang Xiang, Lingyu Han, Long Zhang, Renjie Wang, Sanjun Cai, Qingguo Li, Guoxiang Cai
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BMC Medicine.2020;[Epub] CrossRef

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Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer: Se Ik Kim, Minsun Song, Suhyun Hwangbo, Sungyoung Lee, Untack Cho, Ju-Hyun Kim, Maria Lee, Hee Seung Kim, Hyun Hoon Chung, Dae-Shik Suh, Taesung Park, Yong-Sang Song; Cancer Res Treat. 2019;51(3):1144-1155. Published online November 20, 2018; DOI: https://doi.org/10.4143/crt.2018.508

Abstract PDF Supplementary Material PubReader ePub

Purpose
Discovery of models predicting the exact prognosis of epithelial ovarian cancer (EOC) is necessary as the first step of implementation of individualized treatment. This study aimed to develop nomograms predicting treatment response and prognosis in EOC.
Materials and Methods
We comprehensively reviewed medical records of 866 patients diagnosed with and treated for EOC at two tertiary institutional hospitals between 2007 and 2016. Patients’ clinico-pathologic characteristics, details of primary treatment, intra-operative surgical findings, and survival outcomes were collected. To construct predictive nomograms for platinum sensitivity, 3-year progression-free survival (PFS), and 5-year overall survival (OS), we performed stepwise variable selection by measuring the area under the receiver operating characteristic curve (AUC) with leave-one-out cross-validation. For model validation, 10-fold cross-validation was applied.
Results
The median length of observation was 42.4 months (interquartile range, 25.7 to 69.9 months), during which 441 patients (50.9%) experienced disease recurrence. The median value of PFS was 32.6 months and 3-year PFS rate was 47.8% while 5-year OS rate was 68.4%. The AUCs of the newly developed nomograms predicting platinum sensitivity, 3-year PFS, and 5-year OS were 0.758, 0.841, and 0.805, respectively. We also developed predictive nomograms confined to the patients who underwent primary debulking surgery. The AUCs for platinum sensitivity, 3-year PFS, and 5-year OS were 0.713, 0.839, and 0.803, respectively.
Conclusion
We successfully developed nomograms predicting treatment response and prognosis of patients with EOC. These nomograms are expected to be useful in clinical practice and designing clinical trials.

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Comprehensive analyses of mitophagy-related genes and mitophagy-related lncRNAs for patients with ovarian cancer
Jianfeng Zheng, Shan Jiang, Xuefen Lin, Huihui Wang, Li Liu, Xintong Cai, Yang Sun
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Peripheral and tumor‐infiltrating immune cells are correlated with patient outcomes in ovarian cancer
Weiwei Zhang, Yawen Ling, Zhidong Li, Xingchen Peng, Yazhou Ren
Cancer Medicine.2023; 12(8): 10045. CrossRef
Nonalcoholic fatty liver disease and early prediction of gestational diabetes mellitus using machine learning methods
Seung Mi Lee, Suhyun Hwangbo, Errol R. Norwitz, Ja Nam Koo, Ig Hwan Oh, Eun Saem Choi, Young Mi Jung, Sun Min Kim, Byoung Jae Kim, Sang Youn Kim, Gyoung Min Kim, Won Kim, Sae Kyung Joo, Sue Shin, Chan-Wook Park, Taesung Park, Joong Shin Park
Clinical and Molecular Hepatology.2022; 28(1): 105. CrossRef
Toward More Comprehensive Homologous Recombination Deficiency Assays in Ovarian Cancer Part 2: Medical Perspectives
Stanislas Quesada, Michel Fabbro, Jérôme Solassol
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Construction and validation of a transcription factors-based prognostic signature for ovarian cancer
Qingyuan Cheng, Liman Li, Mingxia Yu
Journal of Ovarian Research.2022;[Epub] CrossRef
Predicting preterm birth through vaginal microbiota, cervical length, and WBC using a machine learning model
Sunwha Park, Jeongsup Moon, Nayeon Kang, Young-Han Kim, Young-Ah You, Eunjin Kwon, AbuZar Ansari, Young Min Hur, Taesung Park, Young Ju Kim
Frontiers in Microbiology.2022;[Epub] CrossRef
Prognostic nomogram that predicts progression-free survival and overall survival of patients with ovarian clear cell carcinoma
Jiayi Li, Dongyan Cao
Frontiers in Oncology.2022;[Epub] CrossRef
Recent Advances and Future Directions of Diagnostic and Prognostic Prediction Models in Ovarian Cancer
Judan Zeng, Wenjiao Cao, Lihua Wang
Journal of Shanghai Jiaotong University (Science).2021; 26(1): 10. CrossRef
Sphingolipids as multifaceted mediators in ovarian cancer
MelissaR Pitman, Martin K. Oehler, Stuart M. Pitson
Cellular Signalling.2021; 81: 109949. CrossRef
Development and validation for prognostic nomogram of epithelial ovarian cancer recurrence based on circulating tumor cells and epithelial–mesenchymal transition
Jiani Yang, Jun Ma, Yue Jin, Shanshan Cheng, Shan Huang, Nan Zhang, Yu Wang
Scientific Reports.2021;[Epub] CrossRef
Prediction Models for the Clinical Severity of Patients With COVID-19 in Korea: Retrospective Multicenter Cohort Study
Bumjo Oh, Suhyun Hwangbo, Taeyeong Jung, Kyungha Min, Chanhee Lee, Catherine Apio, Hyejin Lee, Seungyeoun Lee, Min Kyong Moon, Shin-Woo Kim, Taesung Park
Journal of Medical Internet Research.2021; 23(4): e25852. CrossRef
Development of Machine Learning Models to Predict Platinum Sensitivity of High-Grade Serous Ovarian Carcinoma
Suhyun Hwangbo, Se Ik Kim, Ju-Hyun Kim, Kyung Jin Eoh, Chanhee Lee, Young Tae Kim, Dae-Shik Suh, Taesung Park, Yong Sang Song
Cancers.2021; 13(8): 1875. CrossRef
M2 Macrophage-Based Prognostic Nomogram for Gastric Cancer After Surgical Resection
Jianwen Hu, Yongchen Ma, Ju Ma, Yanpeng Yang, Yingze Ning, Jing Zhu, Pengyuan Wang, Guowei Chen, Yucun Liu
Frontiers in Oncology.2021;[Epub] CrossRef
Prognosis for intrahepatic cholangiocarcinoma patients treated with postoperative adjuvant transcatheter hepatic artery chemoembolization
Ji-Bin Liu, Kai-Jian Chu, Chang-Chun Ling, Ting-Miao Wu, Hui-Min Wang, Yi Shi, Zhi-Zhen Li, Jing-Han Wang, Zhi-Jun Wu, Xiao-Qing Jiang, Gao-Ren Wang, Yu-Shui Ma, Da Fu
Current Problems in Cancer.2020; 44(6): 100612. CrossRef
Can we predict who lives long with ovarian cancer?
Michael A. Bookman
Cancer.2019; 125(S24): 4578. CrossRef

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A Nomogram for Predicting the Oncotype DX Recurrence Score in Women with T1-3N0-1miM0 Hormone Receptor‒Positive, Human Epidermal Growth Factor 2 (HER2)‒Negative Breast Cancer: Sae Byul Lee, Junetae Kim, Guiyun Sohn, Jisun Kim, Il Yong Chung, Hee Jeong Kim, Beom Seok Ko, Byung Ho Son, Sei-Hyun Ahn, Jong Won Lee, Kyung Hae Jung; Cancer Res Treat. 2019;51(3):1073-1085. Published online November 1, 2018; DOI: https://doi.org/10.4143/crt.2018.357

Abstract PDF Supplementary Material PubReader ePub

Purpose
This preliminary study was conducted to evaluate the association between Oncotype DX (ODX) recurrence score and traditional prognostic factors. We also developed a nomogram to predict subgroups with low ODX recurrence scores (less than 25) and to avoid additional chemotherapy treatments for those patients.
Materials and Methods
Clinicopathological and immunohistochemical variables were retrospectively retrieved and analyzed from a series of 485 T1-3N0-1miM0 hormone receptor-positive, human epidermal growth factor 2‒negative breast cancer patients with available ODX test results at Asan Medical Center from 2010 to 2016. One hundred twenty-seven patients (26%) had positive axillary lymph node micrometastases, and 408 (84%) had ODX recurrence scores of ≤25. Logistic regression was performed to build a nomogram for predicting a low-risk subgroup of the ODX assay.
Results
Multivariate analysis revealed that estrogen receptor (ER) score, progesterone receptor (PR) score, histologic grade, lymphovascular invasion (LVI), and Ki-67 had a statistically significant association with the low-risk subgroup. With these variables, we developed a nomogram to predict the low-risk subgroup with ODX recurrence scores of ≤25. The area under the receiver operating characteristic curve was 0.90 (95% confidence interval [CI], 0.85 to 0.96). When applied to the validation group the nomogram was accurate with an area under the curve = 0.88 (95% CI, 0.83 to 0.95).
Conclusion
The low ODX recurrence score subgroup can be predicted by a nomogram incorporating five traditional prognostic factors: ER, PR, histologic grade, LVI, and Ki-67. Our nomogram, which predicts a low-risk ODX recurrence score, will be a useful tool to help select patients who may or may not need additional ODX testing.

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Efficacy, safety, and predictive model of Palbociclib in the treatment of HR-positive and HER2-negative metastatic breast cancer
Wei Wang, Wenqian Lei, Ziru Fang, Ruiyuan Jiang, Xiaojia Wang
BMC Cancer.2024;[Epub] CrossRef
Development and validation of a clinical breast cancer tool for accurate prediction of recurrence
Asim Dhungana, Augustin Vannier, Fangyuan Zhao, Jincong Q. Freeman, Poornima Saha, Megan Sullivan, Katharine Yao, Elbio M. Flores, Olufunmilayo I. Olopade, Alexander T. Pearson, Dezheng Huo, Frederick M. Howard
npj Breast Cancer.2024;[Epub] CrossRef
Prediction of Oncotype DX Recurrence Score Based on Systematic Evaluation of Ki-67 Scores in Hormone Receptor-Positive Early Breast Cancer
Ji Min Kim, Eun Yoon Cho
Journal of Breast Cancer.2024; 27(3): 201. CrossRef
Development of a nomogram to predict recurrence scores obtained using Oncotype DX in Japanese patients with breast cancer
Akio Shibata, Nobuko Tamura, Keiichi Kinowaki, Aya Nishikawa, Kiyo Tanaka, Yoko Kobayashi, Takuya Ogura, Yuko Tanabe, Hidetaka Kawabata
Breast Cancer.2024; 31(6): 1018. CrossRef
Shear-wave elastography-based nomograms predicting 21-gene recurrence score for adjuvant chemotherapy decisions in patients with breast cancer
Ji Hyun Youk, Eun Ju Son, Joon Jeong, Hye Mi Gweon, Na Lae Eun, Jeong-Ah Kim
European Journal of Radiology.2023; 158: 110638. CrossRef
Prediction of Oncotype DX Recurrence Score Using Clinicopathological Variables in Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer
Min Chong Kim, Sun Young Kwon, Jung Eun Choi, Su Hwan Kang, Young Kyung Bae
Journal of Breast Cancer.2023; 26(2): 105. CrossRef
Clinicopathological Factors Associated with Oncotype DX Risk Group in Patients with ER+/HER2- Breast Cancer
Ran Song, Dong-Eun Lee, Eun-Gyeong Lee, Seeyoun Lee, Han-Sung Kang, Jai Hong Han, Keun Seok Lee, Sung Hoon Sim, Heejung Chae, Youngmee Kwon, Jaeyeon Woo, So-Youn Jung
Cancers.2023; 15(18): 4451. CrossRef
A simplified risk scoring system for predicting high-risk groups in gene expression tests for patients with estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and node-positive breast cancer
Kwang Hyun Yoon, Suk Jun Lee, Yujin Kim, Jee Hyun Ahn, Jee Ye Kim, Hyung Seok Park, Seung Il Kim, Seho Park
Annals of Surgical Treatment and Research.2023; 105(6): 360. CrossRef
Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score
Hongxiao Li, Jigang Wang, Zaibo Li, Melad Dababneh, Fusheng Wang, Peng Zhao, Geoffrey H. Smith, George Teodoro, Meijie Li, Jun Kong, Xiaoxian Li
Frontiers in Medicine.2022;[Epub] CrossRef
A Novel Surrogate Nomogram Capable of Predicting OncotypeDX Recurrence Score©
Matthew G. Davey, Amirhossein Jalali, Éanna J. Ryan, Ray P. McLaughlin, Karl J. Sweeney, Michael K. Barry, Carmel M. Malone, Maccon M. Keane, Aoife J. Lowery, Nicola Miller, Michael J. Kerin
Journal of Personalized Medicine.2022; 12(7): 1117. CrossRef
Use of a supervised machine learning model to predict Oncotype DX risk category in node-positive patients older than 50 years of age
Austin D. Williams, Kate R. Pawloski, Hannah Y. Wen, Varadan Sevilimedu, Donna Thompson, Monica Morrow, Mahmoud El-Tamer
Breast Cancer Research and Treatment.2022; 196(3): 565. CrossRef
The Role of Oncotype DX® Recurrence Score in Predicting Axillary Response After Neoadjuvant Chemotherapy in Breast Cancer
Jaime A. Pardo, Betty Fan, Alessandra Mele, Stephanie Serres, Monica G. Valero, Isha Emhoff, Amulya Alapati, Ted A. James
Annals of Surgical Oncology.2021; 28(3): 1320. CrossRef
A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age
Jing Yu, Jiayi Wu, Ou Huang, Jianrong He, Li Zhu, Weiguo Chen, Yafen Li, Xiaosong Chen, Kunwei Shen
Journal of Translational Medicine.2021;[Epub] CrossRef
Clinicopathological correlates, oncological impact, and validation of Oncotype DX™ in a European Tertiary Referral Centre
Matthew G. Davey, Éanna J. Ryan, Sami Abd Elwahab, Jessie A. Elliott, Peter F. McAnena, Karl J. Sweeney, Carmel M. Malone, Ray McLaughlin, Michael K. Barry, Maccon M. Keane, Aoife J. Lowery, Michael J. Kerin
The Breast Journal.2021; 27(6): 521. CrossRef
Dynamic contrast enhanced-MRI and diffusion-weighted image as predictors of lymphovascular invasion in node-negative invasive breast cancer
Bo Bae Choi
World Journal of Surgical Oncology.2021;[Epub] CrossRef
Prognostic value of the 21-gene recurrence score for regional recurrence in patients with estrogen receptor-positive breast cancer
Minji Koh, Jinhong Jung, Su Ssan Kim, Seung Do Ahn, Eun Kyung Choi, Il Yong Chung, Jong Won Lee, Sung-Bae Kim, Jae Ho Jeong
Breast Cancer Research and Treatment.2021; 188(3): 583. CrossRef
A nomogram for predicting probability of low risk of MammaPrint results in women with clinically high-risk breast cancer
Young Joo Lee, Young Sol Hwang, Junetae Kim, Sei-Hyun Ahn, Byung Ho Son, Hee Jeong Kim, Beom Seok Ko, Jisun Kim, Il Yong Chung, Jong Won Lee, Sae Byul Lee
Scientific Reports.2021;[Epub] CrossRef
Development of a Nomogram to Predict the Recurrence Score of 21-Gene Prediction Assay in Hormone Receptor–Positive Early Breast Cancer
Shin Hye Yoo, Tae-Yong Kim, Miso Kim, Kyung-Hun Lee, Eunshin Lee, Han-Byoel Lee, Hyeong-Gon Moon, Wonshik Han, Dong-Young Noh, Sae-Won Han, Tae-You Kim, Seock-Ah Im
Clinical Breast Cancer.2020; 20(2): 98. CrossRef
Ki‐67 index, progesterone receptor expression, histologic grade and tumor size in predicting breast cancer recurrence risk: A consecutive cohort study
Yanna Zhang, Yidong Zhou, Feng Mao, Ru Yao, Qiang Sun
Cancer Communications.2020; 40(4): 181. CrossRef
Estrogen and Progesterone Receptor Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Guideline Update
Kimberly H. Allison, M. Elizabeth H. Hammond, Mitchell Dowsett, Shannon E. McKernin, Lisa A. Carey, Patrick L. Fitzgibbons, Daniel F. Hayes, Sunil R. Lakhani, Mariana Chavez-MacGregor, Jane Perlmutter, Charles M. Perou, Meredith M. Regan, David L. Rimm, W
Archives of Pathology & Laboratory Medicine.2020; 144(5): 545. CrossRef
Oncotype DX Predictive Nomogram for Recurrence Score Output: The Novel System ADAPTED01 Based on Quantitative Immunochemistry Analysis
Fabio Marazzi, Roberto Barone, Valeria Masiello, Valentina Magri, Antonino Mulè, Angela Santoro, Federica Cacciatori, Luca Boldrini, Gianluca Franceschini, Francesca Moschella, Giuseppe Naso, Silverio Tomao, Maria Antonietta Gambacorta, Giovanna Mantini,
Clinical Breast Cancer.2020; 20(5): e600. CrossRef

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333 Download
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21 Crossref

Score for the Survival Probability in Metastasis Breast Cancer: A Nomogram-Based Risk Assessment Model: Zhenchong Xiong, Guangzheng Deng, Xinjian Huang, Xing Li, Xinhua Xie, Jin Wang, Zeyu Shuang, Xi Wang; Cancer Res Treat. 2018;50(4):1260-1269. Published online January 2, 2018; DOI: https://doi.org/10.4143/crt.2017.443

Abstract PDF Supplementary Material PubReader ePub

Purpose
Survival of metastatic breast cancer (MBC) patient remains unknown and varies greatly from person to person. Thus, we aimed to construct a nomogram to quantify the survival probability of patients with MBC.
Materials and Methods
We had included 793 MBC patients and calculated trends of case fatality rate by Kaplan-Meier method and joinpoint regression. Six hundred thirty-four patients with MBC between January 2004 and July 2011 and 159 patients with MBC between August 2011 and July 2013 were assigned to training cohort and internal validation cohort, respectively. We constructed the nomogram based on the results of univariable and multivariable Cox regression analyses in the training cohort and validated the nomogram in the validation cohort. Concordance index and calibration curves were used to assess the effectiveness of nomogram.
Results

Case
fatality rate of MBC was increasing (annual percentage change [APC], 21.6; 95% confidence interval [CI], 1.0 to 46.3; p < 0.05) in the first 18 months and then decreased (APC, ‒4.5; 95% CI, ‒8.2 to ‒0.7; p < 0.05). Metastasis-free interval, age, metastasis location, and hormone receptor status were independent prognostic factors and were included in the nomogram, which had a concordance index of 0.69 in the training cohort and 0.67 in the validation cohort. Calibration curves indicated good consistency between the two cohorts at 1 and 3 years.
Conclusion
In conclusion, the fatality risk of MBC was increasing and reached the summit between 13th and 18th month afterthe detection of MBC. We have developed and validated a nomogram to predict the 1- and 3-year survival probability in MBC.

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Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation
Erich P. Huang, Gene Pennello, Nandita M. deSouza, Xiaofeng Wang, Andrew J. Buckler, Paul E. Kinahan, Huiman X. Barnhart, Jana G. Delfino, Timothy J. Hall, David L. Raunig, Alexander R. Guimaraes, Nancy A. Obuchowski
Academic Radiology.2023; 30(2): 196. CrossRef
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Yixin Cheng, Pengkun Zhang, Yulin Huang, Zhihui Zhang, Ru Tang, Feng Chi, Jia-Yuan Sun, Zhenyu He
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Chong Hou, Fangxu Yin, Yipin Liu
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Niuniu Hou, Jun Yi, Zhe Wang, Lu Yang, Ying Wu, Meiling Huang, Guangdong Hou, Rui Ling
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A Nomogram for Predicting Survival in Patients With Breast Cancer Liver Metastasis: A Population-Based Study
Yu Xiong, Xia Shi, Qi Hu, Xingwei Wu, Enwu Long, Yuan Bian
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Prognostic Factors and a Nomogram Predicting Survival in Patients with Breast Ductal Carcinoma in situ with Microinvasion: A Population-Based Study
Yi-Zi Zheng, Hong-Bin Qin, Zi-Zheng Li, He-Sheng Jiang, Greg Zhang, Shi-Wei Yang, Xian-Ming Wang, Yang-Chun Xu, Zhen-Han Deng, Guo-Wen Liu
Clinical Epidemiology.2021; Volume 13: 1095. CrossRef
The E3 Ubiquitin Ligase Cbl-b Predicts Favorable Prognosis in Breast Cancer
Xiuming Liu, Yuee Teng, Xin Wu, Zhi Li, Bowen Bao, Yunpeng Liu, Xiujuan Qu, Lingyun Zhang
Frontiers in Oncology.2020;[Epub] CrossRef
Prognostic Factors for Premenopausal Women with Distant Metastatic Breast Cancer
Jeungho Seung, Jai Min Ryu, Seok Jin Nam, Jeong Eon Lee, Jonghan Yu, Se Kyung Lee, Byung Joo Chae, Seok Won Kim
Journal of Breast Disease.2020; 8(1): 1. CrossRef
Primary 21-Gene Recurrence Score and Disease Outcome in Loco-Regional and Distant Recurrent Breast Cancer Patients
Yujie Lu, Yiwei Tong, Jiahui Huang, Lin Lin, Jiayi Wu, Xiaochun Fei, Ou Huang, Jianrong He, Li Zhu, Weiguo Chen, Yafen Li, Xiaosong Chen, Kunwei Shen
Frontiers in Oncology.2020;[Epub] CrossRef
Independent risk factors evaluation for overall survival and cancer-specific survival in thyroid cancer patients with bone metastasis
Yuexin Tong, Zhangheng Huang, Chuan Hu, Changxing Chi, Meng Lv, Pengfei Li, Chengliang Zhao, Youxin Song
Medicine.2020; 99(36): e21802. CrossRef
A nomogram for predicting survival in patients with de novo metastatic breast cancer: a population-based study
Wen Zhao, Lei Wu, Andi Zhao, Mi Zhang, Qi Tian, Yanwei Shen, Fan Wang, Biyuan Wang, Le Wang, Ling Chen, Xiaoai Zhao, Danfeng Dong, Lingxiao Zhang, Jin Yang
BMC Cancer.2020;[Epub] CrossRef
Establishing a predicted model to evaluate prognosis for initially diagnosed metastatic Her2-positive breast cancer patients and exploring the benefit from local surgery
Hong Lin, Yanxuan Wu, Guoxi Liang, Liming Chen, Anna Sapino
PLOS ONE.2020; 15(11): e0242155. CrossRef
Predictors of time to death after distant recurrence in breast cancer patients
Victoria Sopik, Ping Sun, Steven A. Narod
Breast Cancer Research and Treatment.2019; 173(2): 465. CrossRef
Prognostic nomogram for patients with non-metastatic HER2 positive breast cancer in a prospective cohort
Chuanxu Luo, Xiaorong Zhong, Zhu Wang, Yu Wang, Yanping Wang, Ping He, Qian Peng, Hong Zheng
The International Journal of Biological Markers.2019; 34(1): 41. CrossRef
B2 Prognostic Score: External Validation of a Clinical Decision-making Tool for Metastatic Breast Cancer
Tanja Nadine Stueber, Manfred Wischnewsky, Elena Leinert, Joachim Diessner, Catharina Bartmann, Roland Gregor Stein, Achim Woeckel
Clinical Breast Cancer.2019; 19(5): 333. CrossRef
Development and Validation of a Nomogram for Predicting Survival in Male Patients With Breast Cancer
Siying Chen, Yang Liu, Jin Yang, Qingqing Liu, Haisheng You, Yalin Dong, Jun Lyu
Frontiers in Oncology.2019;[Epub] CrossRef
Could local surgery improve survival in de novo stage IV breast cancer?
Zhenchong Xiong, Guangzheng Deng, Jin Wang, Xing Li, Xinhua Xie, Zeyu Shuang, Xi Wang
BMC Cancer.2018;[Epub] CrossRef

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A Novel Prognostic Nomogram for Predicting Risks of Distant Failure in Patients with Invasive Breast Cancer Following Postoperative Adjuvant Radiotherapy: Yu Jin Lim, Sea-Won Lee, Noorie Choi, Jeanny Kwon, Keun-Yong Eom, Eunyoung Kang, Eun-Kyu Kim, Jee Hyun Kim, Yu Jung Kim, Se Hyun Kim, So Yeon Park, In Ah Kim; Cancer Res Treat. 2018;50(4):1140-1148. Published online December 7, 2017; DOI: https://doi.org/10.4143/crt.2017.508

Abstract PDF Supplementary Material PubReader ePub

Purpose
This study aimed to identify predictors for distant metastatic behavior and build a related prognostic nomogram in breast cancer.
Materials and Methods
A total of 1,181 patients with non-metastatic breast cancer between 2003 and 2011 were analyzed. To predict the probability of distant metastasis, a nomogram was constructed based on prognostic factors identified using a Cox proportional hazards model.
Results
The 7-year overall survival and 5-year post-progression survival of locoregional versus distant recurrence groups were 67.6% versus 39.1% (p=0.027) and 54.2% versus 33.5% (p=0.043), respectively. Patients who developed distant metastasis showed early and late mortality risk peaks within 3 and after 5 years of follow-up, respectively, but a broad and low risk increment was observed in other patients with locoregional relapse. In multivariate analysis of distant metastasis-free interval, age (≥ 45 years vs. < 45 years), molecular subtypes (luminal A vs. luminal B, human epidermal growth receptor 2, and triple negative), T category (T1 vs. T2-3 and T4), and N category (N0 vs. N1 and N2-3) were independently associated (p < 0.05 for all). Regarding the significant factors, a well-validated nomogram was established (concordance index, 0.812). The risk score level of patients with initial brain failure was higher than those of non-brain sites (p=0.029).
Conclusion
The nomogram could be useful for predicting the individual probability of distant recurrence in breast cancer. In high-risk patients based on the risk scores, more aggressive systemic therapy and closer surveillance for metastatic failure should be considered.

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Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning
Audrey Shiner, Alex Kiss, Khadijeh Saednia, Katarzyna J. Jerzak, Sonal Gandhi, Fang-I Lu, Urban Emmenegger, Lauren Fleshner, Andrew Lagree, Marie Angeli Alera, Mateusz Bielecki, Ethan Law, Brianna Law, Dylan Kam, Jonathan Klein, Christopher J. Pinard, Ale
Genes.2023; 14(9): 1768. CrossRef
Nomograms for Predicting Specific Distant Metastatic Sites and Overall Survival of Breast Invasive Ductal Carcinoma Patients After Surgery: A Large Population-Based Study
Yuqian Feng, Yiting Zhang, Yuying Xiang, Kaibo Guo, Huimin Jin, Shanming Ruan, Zhuoya Guan
Frontiers in Surgery.2022;[Epub] CrossRef
Cost-effectiveness of postmastectomy hypofractionated radiation therapy vs conventional fractionated radiation therapy for high-risk breast cancer
Jing Yang, Shu-Nan Qi, Hui Fang, Yong-Wen Song, Jing Jin, Yue-Ping Liu, Wei-Hu Wang, Yong Yang, Yu Tang, Hua Ren, Bo Chen, Ning-Ning Lu, Yuan Tang, Ning Li, Hao Jing, Shu-Lian Wang, Ye-Xiong Li
The Breast.2021; 58: 72. CrossRef
Prediction of distant metastatic recurrence by tumor-infiltrating lymphocytes in hormone receptor-positive breast cancer
Koji Takada, Shinichiro Kashiwagi, Yuka Asano, Wataru Goto, Rika Kouhashi, Akimichi Yabumoto, Sae Ishihara, Tamami Morisaki, Masatsune Shibutani, Hiroaki Tanaka, Kosei Hirakawa, Masaichi Ohira
BMC Women's Health.2021;[Epub] CrossRef
Nomogram for the personalisation of radiotherapy treatments in breast cancer patients
Inmaculada Beato Tortajada, Carlos Ferrer Albiach, Virginia Morillo Macias
The Breast.2021; 60: 255. CrossRef
Prognostic Factors and Nomograms to Predict Overall and Cancer-Specific Survival for Children with Wilms’ Tumor
Fucai Tang, Hanbin Zhang, Zechao Lu, Jiamin Wang, Chengwu He, Zhaohui He
Disease Markers.2019; 2019: 1. CrossRef
Score for the Survival Probability in Metastasis Breast Cancer: A Nomogram-Based Risk Assessment Model
Zhenchong Xiong, Guangzheng Deng, Xinjian Huang, Xing Li, Xinhua Xie, Jin Wang, Zeyu Shuang, Xi Wang
Cancer Research and Treatment.2018; 50(4): 1260. CrossRef

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Proposal of a Pretreatment Nomogram for Predicting Local Recurrence after Intensity-Modulated Radiation Therapy in T4 Nasopharyngeal Carcinoma: A Retrospective Review of 415 Chinese Patients: Lu-Lu Zhang, Yi-Yang Li, Jiang Hu, Guan-Qun Zhou, Lei Chen, Wen-Fei Li, Ai-Hua Lin, Jun Ma, Zhen-Yu Qi, Ying Sun; Cancer Res Treat. 2018;50(4):1084-1095. Published online November 15, 2017; DOI: https://doi.org/10.4143/crt.2017.359

Abstract PDF PubReader ePub

Purpose
Local relapse-free survival (LRFS) differs widely among patients with T4 category nasopharyngeal carcinoma (NPC). We aimed to build a nomogram incorporating clinicopathological information to predict LRFS in T4 NPC after definitive intensity-modulated radiation therapy (IMRT).
Materials and Methods
Retrospective study of 415 Chinese patients with non-metastatic T4 NPC treated with definitive IMRT with or without chemotherapy at our cancer center between October 2009 and September 2013. The nomogram for LRFS at 3 and 5 years was generated based on multivariate Cox proportional hazards regression, and validated using bootstrap resampling, assessing discriminative performance using the concordance index (C-index) and determining calibration ability via calibration curves.
Results
Five-year LRFS was 88.8%. We identified and incorporated four independent prognostic factors for LRFS: ethmoid sinus invasion, primary gross tumor volume, age, and pretreatment body mass index. The C-index of the nomogram for local recurrence was 0.732 (95% confidence interval, 0.726 to 0.738), indicating excellent predictive accuracy. The calibration curve revealed excellent agreement between nomogram-predicted and observed LRFS probabilities. Risk subgroups based on total point score cutoff values enabled effective discrimination of LRFS.
Conclusion
This pretreatment nomogram enables clinicians to accurately predict LRFS in T4 NPC after definitive IMRT, and could help to facilitate personalized patient counselling and treatment strategies.

Citations

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Radiomics and Deep Learning in Nasopharyngeal Carcinoma: A Review
Zipei Wang, Mengjie Fang, Jie Zhang, Linquan Tang, Lianzhen Zhong, Hailin Li, Runnan Cao, Xun Zhao, Shengyuan Liu, Ruofan Zhang, Xuebin Xie, Haiqiang Mai, Sufang Qiu, Jie Tian, Di Dong
IEEE Reviews in Biomedical Engineering.2024; 17: 118. CrossRef
Novel prediction model combining PET/CT metabolic parameters, inflammation markers, and TNM stage: prospects for personalizing prognosis in nasopharyngeal carcinoma
Huan Liang, Weilin Tan, Jie Wang, Mengdan Li, Hua Pang, Xiaohui Wang, Lu Yang, Xingguo Jing
Annals of Nuclear Medicine.2024; 38(10): 802. CrossRef
Can Epstein–Barr virus‐deoxyribonucleic acid load after induction chemotherapy combined with American Joint Committee on Cancer stage determine the chemotherapy intensity of locally advanced nasopharyngeal carcinoma?
Qun Zhang, Zhen‐Wei Peng, Zhuo‐Sheng Gu, Yan Wang, Fang He, Wen‐Bin Zhao, Wei Luo, Yong‐Yu Mei
Cancer Medicine.2023; 12(1): 223. CrossRef
Prioritizing sufficient dose to gross tumor volume over normal tissue sparing in intensity‐modulated radiotherapy treatment of T4 nasopharyngeal carcinoma
Yanyan Chen, Quxia Zhang, Tianzhu Lu, Cairong Hu, Jingfeng Zong, Yun Xu, Wei Zheng, Lisha Chen, Senan Lin, Sufang Qiu, Luying Xu, Jianji Pan, Qiaojuan Guo, Shaojun Lin
Head & Neck.2023; 45(5): 1130. CrossRef
Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma
Bingxin Gu, Mingyuan Meng, Mingzhen Xu, David Dagan Feng, Lei Bi, Jinman Kim, Shaoli Song
European Journal of Nuclear Medicine and Molecular Imaging.2023; 50(13): 3996. CrossRef
Prognostic significance of AKR1C4 and the advantage of combining EBV DNA to stratify patients at high risk of locoregional recurrence of nasopharyngeal carcinoma
Shan-Shan Guo, Yan-Zhou Chen, Li-Ting Liu, Rong-Ping Liu, Yu-Jing Liang, Dong-Xiang Wen, Jing Jin, Lin-Quan Tang, Hai-Qiang Mai, Qiu-Yan Chen
BMC Cancer.2022;[Epub] CrossRef
DeepMTS: Deep Multi-Task Learning for Survival Prediction in Patients With Advanced Nasopharyngeal Carcinoma Using Pretreatment PET/CT
Mingyuan Meng, Bingxin Gu, Lei Bi, Shaoli Song, David Dagan Feng, Jinman Kim
IEEE Journal of Biomedical and Health Informatics.2022; 26(9): 4497. CrossRef
Development and Validation of Prognostic Nomograms Based on Gross Tumor Volume and Cervical Nodal Volume for Nasopharyngeal Carcinoma Patients With Concurrent Chemoradiotherapy
Cui-Dai Zhang, Mei Li, Ying-Ji Hong, Ze-Man Cai, Kai-Chun Huang, Zhi-Xiong Lin, Zhi-Ning Yang
Frontiers in Oncology.2021;[Epub] CrossRef
Development and Validation of Web-Based Nomograms to Precisely Predict Survival Outcomes of Non-metastatic Nasopharyngeal Carcinoma in an Endemic Area
Ji-Jin Yao, Li Lin, Tian-Sheng Gao, Wang-Jian Zhang, Wayne R. Lawrence, Jun Ma, Ying Sun
Cancer Research and Treatment.2021; 53(3): 657. CrossRef
Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery
Yang-Yu Huang, Lei-Lei Wu, Xuan Liu, Shen-Hua Liang, Guo-Wei Ma
BMC Cancer.2021;[Epub] CrossRef
Establishment and validation of a nomogram with intratumoral heterogeneity derived from 18F-FDG PET/CT for predicting individual conditional risk of 5-year recurrence before initial treatment of nasopharyngeal carcinoma
Bingxin Gu, Jianping Zhang, Guang Ma, Shaoli Song, Liqun Shi, Yingjian Zhang, Zhongyi Yang
BMC Cancer.2020;[Epub] CrossRef
Prognostic Nomogram for Patients with Radical Surgery for Non-Metastatic Colorectal Cancer Incorporating Hematological Biomarkers and Clinical Characteristics

Peiyun Long, Youya Zang, Huan Wang, Xiumei Liang, Xuekun Xie, Zhiwei Han, Dongyi Lin, Zongyu Wang, Shan Huang, Chuang Chen
OncoTargets and Therapy.2020; Volume 13: 2093. CrossRef
Impact of Paranasal Sinus Invasion on Oncologic and Dosimetric Outcomes in Nasopharyngeal Carcinoma Following Intensity-Modulated Radiation Therapy—Implications for Risk Stratification and Planning Optimization
Xin Zhou, Xiayun He, Fen Xue, Xiaomin Ou, Chaosu Hu
Frontiers in Oncology.2020;[Epub] CrossRef
Role of IMRT/VMAT-Based Dose and Volume Parameters in Predicting 5-Year Local Control and Survival in Nasopharyngeal Cancer Patients
Nicola Alessandro Iacovelli, Alessandro Cicchetti, Anna Cavallo, Salvatore Alfieri, Laura Locati, Eliana Ivaldi, Rossana Ingargiola, Domenico A. Romanello, Paolo Bossi, Stefano Cavalieri, Chiara Tenconi, Silvia Meroni, Giuseppina Calareso, Marco Guzzo, Ce
Frontiers in Oncology.2020;[Epub] CrossRef
Development of a Nomogram Model for Treatment of Nonmetastatic Nasopharyngeal Carcinoma
Lu-Lu Zhang, Fei Xu, Di Song, Meng-Yao Huang, Yong-Shi Huang, Qi-Ling Deng, Yi-Yang Li, Jian-Yong Shao
JAMA Network Open.2020; 3(12): e2029882. CrossRef
Radiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroups
En-Hong Zhuo, Wei-Jing Zhang, Hao-Jiang Li, Guo-Yi Zhang, Bing-Zhong Jing, Jian Zhou, Chun-Yan Cui, Ming-Yuan Chen, Ying Sun, Li-Zhi Liu, Hong-Min Cai
European Radiology.2019; 29(10): 5590. CrossRef
Impact of paranasal sinus invasion on advanced nasopharyngeal carcinoma treated with intensity‐modulated radiation therapy: the validity of advanced T stage of AJCC/UICC eighth edition staging system
Ying Wang, Jie Zhao, Yajie Zhao, Zhen Yang, Mingjun Lei, Zhanzhan Li, Rui Wei, Dengming Chen, Yuxiang He, Liangfang Shen
Cancer Medicine.2018; 7(7): 2826. CrossRef

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Survival Nomograms after Curative Neoadjuvant Chemotherapy and Radical Surgery for Stage IB2-IIIB Cervical Cancer: Claudia Marchetti, Francesca De Felice, Anna Di Pinto, Alessia Romito, Angela Musella, Innocenza Palaia, Marco Monti, Vincenzo Tombolin, Ludovico Muzii, PierLuigi Benedetti Panici; Cancer Res Treat. 2018;50(3):768-776. Published online July 19, 2017; DOI: https://doi.org/10.4143/crt.2017.141

Abstract PDF PubReader ePub

Purpose
The purpose of this study was to develop nomograms for predicting the probability of overall survival (OS) and progression-free survival (PFS) in locally advanced cervical cancer treated with neoadjuvant chemotherapy and radical surgery.
Materials and Methods
Nomograms to predict the 5-year OS rates and the 2-year PFS rates were constructed. Calibration plots were constructed, and concordance indices were calculated. Evaluated variableswere body mass index, age, tumor size, tumor histology, grading, lymphovascular space invasion, positive parametria, and positive lymph nodes.
Results
In total 245 patients with locally advanced cervical cancer who underwent neoadjuvant chemotherapy and radical surgery were included for the construction of the nomogram. The 5-year OS and PFS were 72.6% and 66%, respectively. Tumor size, grading, and parametria status affected the rate of OS, whereas tumor size and positive parametria were the main independent PFS prognostic factors.
Conclusion
We constructed a nomogram based on clinicopathological features in order to predict 2-year PFS and 5-year OS in locally advanced cervical cancer primarily treated with neoadjuvant chemotherapy followed by radical surgery. This tool might be particularly helpful for assisting in the follow-up of cervical cancer patients who have not undergone concurrent chemoradiotherapy.

Citations

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Plasma-based proteomic and metabolomic characterization of lung and lymph node metastases in cervical cancer patients
Yue Feng, Zijian Sun, Huan Zhang, Zhao Wang, Lichao Wang, Hui Ye, Xiaojing Zhang, Zhuomin Yin, Juan Ni, Jingkui Tian, Hanmei Lou, Xiaojuan Lv, Wei Zhu
Journal of Pharmaceutical and Biomedical Analysis.2025; 253: 116521. CrossRef
Dose prediction for cervical cancer in radiotherapy based on the beam channel generative adversarial network
Hui Xie, Tao Tan, Hua Zhang, Qing Li
Heliyon.2024; 10(18): e37472. CrossRef
Systematic review and meta-analysis of prediction models used in cervical cancer
Ashish Kumar Jha, Sneha Mithun, Umeshkumar B. Sherkhane, Vinay Jaiswar, Biche Osong, Nilendu Purandare, Sadhana Kannan, Kumar Prabhash, Sudeep Gupta, Ben Vanneste, Venkatesh Rangarajan, Andre Dekker, Leonard Wee
Artificial Intelligence in Medicine.2023; 139: 102549. CrossRef
Development and validation of radiomic signature for predicting overall survival in advanced-stage cervical cancer
Ashish Kumar Jha, Sneha Mithun, Umeshkumar B. Sherkhane, Vinay Jaiswar, Sneha Shah, Nilendu Purandare, Kumar Prabhash, Amita Maheshwari, Sudeep Gupta, Leonard Wee, V. Rangarajan, Andre Dekker
Frontiers in Nuclear Medicine.2023;[Epub] CrossRef
Advanced cervical stump cancer after laparoscopic subtotal hysterectomy: a case report of imaging, laparoscopic staging and treatment approach
Dimitrios Andrikos, Argyrios Andrikos, Antoine Naem, Olga Ebertz, Rajesh Devassy, Rudy Leon De Wilde, Michael Khamou, Harald Krentel
BMC Women's Health.2023;[Epub] CrossRef
Successful neoadjuvant chemotherapy plus sintilimab for locally advanced cervical cancer: case series and review of the literature
Linlin Liu, Xianbo Deng, Shuang Guo, Shouhua Yang
Diagnostic Pathology.2023;[Epub] CrossRef
Influence of the Clinical Nursing Pathway on Nursing Outcomes and Complications of Cervical Carcinoma Patients Undergoing Chemotherapy via PICC
Hongxia Tang, Li Gao, Yahui Li, Zhiqian Zhang
Evidence-Based Complementary and Alternative Medicine.2022; 2022: 1. CrossRef
Current and future direction in treatment of HPV-related cervical disease
Niloofar Khairkhah, Azam Bolhassani, Reza Najafipour
Journal of Molecular Medicine.2022; 100(6): 829. CrossRef
Machine Learning of Dose-Volume Histogram Parameters Predicting Overall Survival in Patients with Cervical Cancer Treated with Definitive Radiotherapy
Zhiyuan Xu, Li Yang, Qin Liu, Hao Yu, Longhua Chen, Claudia Marchetti
Journal of Oncology.2022; 2022: 1. CrossRef
Efficacy and safety of pembrolizumab on cervical cancer: A systematic review and single-arm meta-analysis
Lin Qi, Ning Li, Aimin Lin, Xiuli Wang, Jianglin Cong
Frontiers in Oncology.2022;[Epub] CrossRef
Outcomes and prognostic factors in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy
Jing Liu, Guyu Tang, Qin Zhou, Weilu Kuang
Radiation Oncology.2022;[Epub] CrossRef
The comparative study for survival outcome of locally advanced cervical cancer treated by neoadjuvant arterial interventional chemotherapy or intravenous chemotherapy followed by surgery or concurrent chemoradiation
Yi Sun, Gailing Li, Panpan Hai, Yuan Cao, Pin Han, Yuchen Liu, Jing Wen, Yuanpei Wang, Xiaoran Cheng, Fang Ren
World Journal of Surgical Oncology.2022;[Epub] CrossRef
Pembrolizumab for advanced cervical cancer: safety and efficacy
Francesca De Felice, Elena Giudice, Giulia Bolomini, Maria Grazia Distefano, Giovanni Scambia, Anna Fagotti, Claudia Marchetti
Expert Review of Anticancer Therapy.2021; 21(2): 221. CrossRef
Nomograms predicting the overall survival and cancer-specific survival of patients with stage IIIC1 cervical cancer
Yifan Feng, Ye Wang, Yangqin Xie, Shuwei Wu, Yuyang Li, Min Li
BMC Cancer.2021;[Epub] CrossRef
Comparison of therapeutic effects of chemo-radiotherapy with neoadjuvant chemotherapy before radical surgery in patients with bulky cervical carcinoma (stage IB3 & IIA2)
Setareh Akhavan, Abbas Alibakhshi, Mahdieh Parsapoor, Abbas Alipour, Elahe Rezayof
BMC Cancer.2021;[Epub] CrossRef
Macleayins A From Macleaya Promotes Cell Apoptosis Through Wnt/β-Catenin Signaling Pathway and Inhibits Proliferation, Migration, and Invasion in Cervical Cancer HeLa Cells
Chunmei Sai, Wei Qin, Junyu Meng, Li-Na Gao, Lufen Huang, Zhen Zhang, Huannan Wang, Haixia Chen, Chaohua Yan
Frontiers in Pharmacology.2021;[Epub] CrossRef
Nomogram Predicting Overall Survival in Patients with FIGO II to III Squamous Cell Cervical Carcinoma Under Radical Radiotherapy: A Retrospective Analysis Based on 2018 FIGO Staging
Lele Zang, Qin Chen, Xiaozhen Zhang, Xiaohong Zhong, Jian Chen, Yi Fang, An Lin, Min Wang
Cancer Management and Research.2021; Volume 13: 9391. CrossRef
Prediction of early response to concurrent chemoradiotherapy in cervical cancer: Value of multi-parameter MRI combined with clinical prognostic factors
Xiaomin Zheng, Weiqian Guo, Jiangning Dong, Liting Qian
Magnetic Resonance Imaging.2020; 72: 159. CrossRef
Calculating the overall survival probability in patients with cervical cancer: a nomogram and decision curve analysis-based study
Guilan Xie, Ruiqi Wang, Li Shang, Cuifang Qi, Liren Yang, Liyan Huang, Wenfang Yang, Mei Chun Chung
BMC Cancer.2020;[Epub] CrossRef
SPP1 inhibition improves the cisplatin chemo-sensitivity of cervical cancer cell lines
Xing Chen, Dongsheng Xiong, Liya Ye, Huichun Yang, Shuangshuang Mei, Jinhong Wu, Shanshan Chen, Ruoran Mi
Cancer Chemotherapy and Pharmacology.2019; 83(4): 603. CrossRef
Systemic therapy in cervical cancer: 30 years in review
Michalis Liontos, Anastasios Kyriazoglou, Ioannis Dimitriadis, Meletios-Athanasios Dimopoulos, Aristotelis Bamias
Critical Reviews in Oncology/Hematology.2019; 137: 9. CrossRef
Adjuvant chemoradiotherapy versus radiotherapy in cervical cancer patients with intermediate-risk factors: A systematic review and meta-analysis
Meng Li, Mengyang Hu, Yuanjian Wang, Xingsheng Yang
European Journal of Obstetrics & Gynecology and Reproductive Biology.2019; 238: 1. CrossRef
Neoadjuvant chemotherapy followed by radical hysterectomy for stage IB2-to-IIB cervical cancer: a retrospective cohort study
Lei Li, Ming Wu, Shuiqing Ma, Xianjie Tan, Sen Zhong
International Journal of Clinical Oncology.2019; 24(11): 1440. CrossRef
Immune check-point in cervical cancer
F. De Felice, C. Marchetti, I. Palaia, R. Ostuni, L. Muzii, V. Tombolini, P. Benedetti Panici
Critical Reviews in Oncology/Hematology.2018; 129: 40. CrossRef

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Can We Skip Intraoperative Evaluation of Sentinel Lymph Nodes? Nomogram Predicting Involvement of Three or More Axillary Lymph Nodes before Breast Cancer Surgery: Soo Kyung Ahn, Min Kyoon Kim, Jongjin Kim, Eunshin Lee, Tae-Kyung Yoo, Han-Byoel Lee, Young Joon Kang, Jisun Kim, Hyeong-Gon Moon, Jung Min Chang, Nariya Cho, Woo Kyung Moon, In Ae Park, Dong-Young Noh, Wonshik Han; Cancer Res Treat. 2017;49(4):1088-1096. Published online January 25, 2017; DOI: https://doi.org/10.4143/crt.2016.473

Abstract PDF Supplementary Material PubReader ePub

Purpose
The American College of Surgeons Oncology Group Z0011 trial reported that complete dissection of axillary lymph nodes (ALNs) may not be warranted in women with clinical T1-T2 tumors and one or two involved ALNs who were undergoing lumpectomy plus radiation followed by systemic therapy. The present study was conducted to identify preoperative imaging predictors of ≥ 3 ALNs.
Materials and Methods
The training set consisted of 1,917 patients with clinical T1-T2 and node negative invasive breast cancer. Factors associated with ≥ 3 involved ALNs were evaluated by logistic regression analysis. The validation set consisted of 378 independent patients. The nomogram was applied prospectively to 512 patients who met the Z0011 criteria.
Results
Of the 1,917 patients, 204 (10.6%) had ≥ 3 positive nodes. Multivariate analysis showed that involvement of ≥ 3 nodes was significantly associated with ultrasonographic and chest computed tomography findings of suspicious ALNs (p < 0.001 each). These two imaging criteria, plus patient age, were used to develop a nomogram calculating the probability of involvement of ≥ 3 ALNs. The areas under the receiver operating characteristic curve of the nomogram were 0.852 (95% confidence interval [CI], 0.820 to 0.883) for the training set and 0.896 (95% CI, 0.836 to 0.957) for the validation set. Prospective application of the nomogram showed that 60 of 512 patients (11.7%) had scores above the cut-off. Application of the nomogram reduced operation time and cost, with a very low re-operation rate (1.6%).
Conclusion
Patients likely to have ≥ 3 positive ALNs could be identified by preoperative imaging. The nomogram was helpful in selective intraoperative examination of sentinel lymph nodes.

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Asia-Pacific Journal of Clinical Oncology.2023;[Epub] CrossRef
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Ling Li, Jing Zhao, Yu Zhang, Zhanyu Pan, Jin Zhang
Thoracic Cancer.2023; 14(35): 3465. CrossRef
Stratification of Axillary Lymph Node Metastasis Risk with Breast MRI in Breast Cancer
Jieying Chen, Xiaolian Su, Tingting Xu, Qifeng Luo, Lin Zhang, Guangyu Tang
Future Oncology.2022; 18(15): 1849. CrossRef
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Journal of the American College of Radiology.2022; 19(5): S87. CrossRef
Avoiding unnecessary intraoperative sentinel lymph node frozen section biopsy of patients with early breast cancer
Jongwon Kang, Tae-Kyung Yoo, Ahwon Lee, Jun Kang, Chang Ik Yoon, Bong Joo Kang, Sung Hun Kim, Woo Chan Park
Annals of Surgical Treatment and Research.2022; 102(5): 241. CrossRef
A nomogram for predicting three or more axillary lymph node involvement before breast cancer surgery
Young-Joon Kang, Jung Hyun Park, Young Wook Ju, Kyoung-Eun Kim, Yumi Kim, Eunshin Lee, Han-Byoel Lee, Dong-Young Noh, Wonshik Han
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Angela Lombardi, Nicola Amoroso, Loredana Bellantuono, Samantha Bove, Maria Colomba Comes, Annarita Fanizzi, Daniele La Forgia, Vito Lorusso, Alfonso Monaco, Sabina Tangaro, Francesco Alfredo Zito, Roberto Bellotti, Raffaella Massafra
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Antonio Piñero-Madrona, Francisco Ripoll-Orts, José Ignacio Sánchez-Méndez, Asunción Chaves-Benito, Maximiliano Rodrigo Gómez-de la Bárcena, Ana Calatrava-Fons, Salomón Menjón-Beltrán, Vicente Peg-Cámara
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Nomograms Predicting Platinum Sensitivity, Progression-Free Survival, and Overall Survival Using Pretreatment Complete Blood Cell Counts in Epithelial Ovarian Cancer: E Sun Paik, Insuk Sohn, Sun-Young Baek, Minhee Shim, Hyun Jin Choi, Tae-Joong Kim, Chel Hun Choi, Jeong-Won Lee, Byoung-Gie Kim, Yoo-Young Lee, Duk-Soo Bae; Cancer Res Treat. 2017;49(3):635-642. Published online September 27, 2016; DOI: https://doi.org/10.4143/crt.2016.282

Abstract PDF Supplementary Material PubReader ePub

Purpose
This study was conducted to evaluate the prognostic significance of pre-treatment complete blood cell count (CBC), including white blood cell (WBC) differential, in epithelial ovarian cancer (EOC) patients with primary debulking surgery (PDS) and to develop nomograms for platinum sensitivity, progression-free survival (PFS), and overall survival (OS).
Materials and Methods
We retrospectively reviewed the records of 757 patients with EOC whose primary treatment consisted of surgical debulking and chemotherapy at Samsung Medical Center from 2002 to 2012. We subsequently created nomograms for platinum sensitivity, 3-year PFS, and 5-year OS as prediction models for prognostic variables including age, stage, grade, cancer antigen 125 level, residual disease after PDS, and pre-treatment WBC differential counts. The models were then validated by 10-fold cross-validation (CV).
Results
In addition to stage and residual disease after PDS, which are known predictors, lymphocyte and monocyte count were found to be significant prognostic factors for platinum-sensitivity, platelet count for PFS, and neutrophil count for OS on multivariate analysis. The area under the curves of platinum sensitivity, 3-year PFS, and 5-year OS calculated by the 10-fold CV procedure were 0.7405, 0.8159, and 0.815, respectively.
Conclusion
Prognostic factors including pre-treatment CBC were used to develop nomograms for platinum sensitivity, 3-year PFS, and 5-year OS of patients with EOC. These nomograms can be used to better estimate individual outcomes.

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The Gustave Roussy immune score as a novel scoring system for predicting platinum resistance in advanced high-grade serous ovarian cancer
Xianglin Nie, Ting Xu, Lin Zhang, Wenjun Cheng
European Journal of Obstetrics & Gynecology and Reproductive Biology.2024; 294: 97. CrossRef
Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis
Qingyi Wang, Zhuo Chang, Xiaofang Liu, Yunrui Wang, Chuwen Feng, Yunlu Ping, Xiaoling Feng
Journal of Medical Internet Research.2024; 26: e48527. CrossRef
Candidate prognostic biomarkers and prediction models for high-grade serous ovarian cancer from urinary proteomics
Maowei Ni, Danying Wan, Junzhou Wu, Wangang Gong, Junjian Wang, Zhiguo Zheng
Journal of Proteomics.2024; 304: 105234. CrossRef
Preoperative Immune Cell Dysregulation Accompanies Ovarian Cancer Patients into the Postoperative Period
Jonas Ulevicius, Aldona Jasukaitiene, Arenida Bartkeviciene, Zilvinas Dambrauskas, Antanas Gulbinas, Daiva Urboniene, Saulius Paskauskas
International Journal of Molecular Sciences.2024; 25(13): 7087. CrossRef
A nomogram with Ki-67 in the prediction of postoperative recurrence and death for glioma
Fengfeng Li, Dongyuan Wang, Nana Wang, Linlin Wu, Bo Yu
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Machine learning for epithelial ovarian cancer platinum resistance recurrence identification using routine clinical data
Li-Rong Yang, Mei Yang, Liu-Lin Chen, Yong-Lin Shen, Yuan He, Zong-Ting Meng, Wan-Qi Wang, Feng Li, Zhi-Jin Liu, Lin-Hui Li, Yu-Feng Wang, Xin-Lei Luo
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Comparison of older and younger patients with ovarian cancer: A post hoc study (JGOG3016‐A3) of the treatment strength and prognostic outcomes of conventional or dose‐dense chemotherapy
Yoshio Itani, Hitomi Sakai, Tetsutaro Hamano, Mikiko Asai‐Sato, Masayuki Futagami, Masaki Fujimura, Yoichi Aoki, Nao Suzuki, Yoshio Yoshida, Takayuki Enomoto
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Stanislas Quesada, Michel Fabbro, Jérôme Solassol
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Development of Machine Learning Models to Predict Platinum Sensitivity of High-Grade Serous Ovarian Carcinoma
Suhyun Hwangbo, Se Ik Kim, Ju-Hyun Kim, Kyung Jin Eoh, Chanhee Lee, Young Tae Kim, Dae-Shik Suh, Taesung Park, Yong Sang Song
Cancers.2021; 13(8): 1875. CrossRef
Beyond BRCA Status: Clinical Biomarkers May Predict Therapeutic Effects of Olaparib in Platinum-Sensitive Ovarian Cancer Recurrence
Kazuho Nakanishi, Takashi Yamada, Gen Ishikawa, Shunji Suzuki
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Inflammatory indexes as predictive factors for platinum sensitivity and as prognostic factors in recurrent epithelial ovarian cancer patients: a MITO24 retrospective study
Alberto Farolfi, Emanuela Scarpi, Filippo Greco, Alice Bergamini, Lucia Longo, Sandro Pignata, Claudia Casanova, Gennaro Cormio, Alessandra Bologna, Michele Orditura, Laura Zavallone, Laura Attademo, Valentina Gallà, Elisena Franzese, Eva Pigozzi, Vera Lo
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Pertinence des marqueurs tumoraux, scores (cliniques et biologiques) et algorithmes à visée diagnostique et pronostique devant une masse ovarienne suspecte d’un cancer épithélial. Article rédigé sur la base de la recommandation nationale de bonnes pratiqu
S. Bendifallah, G. Body, E. Daraï, L. Ouldamer
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Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer
Se Ik Kim, Minsun Song, Suhyun Hwangbo, Sungyoung Lee, Untack Cho, Ju-Hyun Kim, Maria Lee, Hee Seung Kim, Hyun Hoon Chung, Dae-Shik Suh, Taesung Park, Yong-Sang Song
Cancer Research and Treatment.2019; 51(3): 1144. CrossRef

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Nomogram for Predicting Breast Conservation after Neoadjuvant Chemotherapy: Min Kyoon Kim, Wonshik Han, Hyeong-Gon Moon, Soo Kyung Ahn, Jisun Kim, Jun Woo Lee, Ju-Yeon Kim, Taeryung Kim, Kyung-Hun Lee, Tae-Yong Kim, Sae-Won Han, Seock-Ah Im, Tae-You Kim, In Ae Park, Dong-Young Noh; Cancer Res Treat. 2015;47(2):197-207. Published online September 4, 2014; DOI: https://doi.org/10.4143/crt.2013.247

Abstract PDF PubReader ePub

Purpose
The ability to accurately predict the likelihood of achieving breast conservation surgery (BCS) after neoadjuvant chemotherapy (NCT) is important in deciding whether NCT or surgery should be the first-line treatment in patients with operable breast cancers. Materials and Methods We reviewed the data of 513 women, who had stage II or III breast cancer and received NCT and surgery from a single institution. The ability of various clinicopathologic factors to predict the achievement of BCS and tumor size reduction to ≤ 3 cm was assessed. Nomograms were built and validated in an independent cohort. Results BCS was performed in 50.1% of patients, with 42.2% of tumors reduced to ≤ 3 cm after NCT. A multivariate logistic regression analysis showed that smaller initial tumor size, longer distance between the lesion and the nipple, absence of suspicious calcifications on mammography, and a single tumor were associated with BCS rather than mastectomy (p < 0.05). Negative estrogen receptor, smaller initial tumor size, higher Ki-67 level, and absence of in situ component were associated with residual tumor size ≤ 3 cm (p < 0.05). Two nomograms were developed using these factors. The areas under the receiver operating characteristic curves for nomograms predicting BCS and residual tumor ≤ 3 cm were 0.800 and 0.777, respectively. The calibration plots showed good agreement between the predicted and actual probabilities. Conclusion We have established a model with novel factors that predicts BCS and residual tumor size after NCT. This model can help in making treatment decisions for patients who are candidates for NCT.

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Risk scoring system for predicting breast conservation after neoadjuvant chemotherapy
Lobna Ouldamer, Sofiane Bendifallah, Joseph Pilloy, Flavie Arbion, Gilles Body, Caroline Brisson, Vincent Lavoué, Jean Lévêque, Emile Daraï
The Breast Journal.2019; 25(4): 696. CrossRef
Score for the Survival Probability in Metastasis Breast Cancer: A Nomogram-Based Risk Assessment Model
Zhenchong Xiong, Guangzheng Deng, Xinjian Huang, Xing Li, Xinhua Xie, Jin Wang, Zeyu Shuang, Xi Wang
Cancer Research and Treatment.2018; 50(4): 1260. CrossRef
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Predicting Successful Conservative Surgery after Neoadjuvant Chemotherapy in Hormone Receptor-Positive, HER2-Negative Breast Cancer
Chang Seok Ko, Kyu Min Kim, Jong Won Lee, Han Shin Lee, Sae Byul Lee, Guiyun Sohn, Jisun Kim, Hee Jeong Kim, Il Yong Chung, Beom Seok Ko, Byung Ho Son, Seung Do Ahn, Sung-Bae Kim, Hak Hee Kim, Sei Hyun Ahn
Journal of Breast Disease.2018; 6(2): 52. CrossRef
External validation of a published nomogram for prediction of brain metastasis in patients with extra-cerebral metastatic breast cancer and risk regression analysis
Ludivine Genre, Henri Roché, Léonel Varela, Dorra Kanoun, Monia Ouali, Thomas Filleron, Florence Dalenc
European Journal of Cancer.2017; 72: 200. CrossRef
Facteurs prédictifs de traitement conservateur après chimiothérapie néo-adjuvante dans le cancer du sein
J. Pilloy, C. Fleurier, M. Chas, L. Bédouet, M.L. Jourdan, F. Arbion, G. Body, L. Ouldamer
Gynécologie Obstétrique Fertilité & Sénologie .2017; 45(9): 466. CrossRef
Actual Conversion Rate from Total Mastectomy to Breast Conservation after Neoadjuvant Chemotherapy for Stages II–III Breast Cancer Patients
Hyejin Mo, Yumi Kim, Jiyoung Rhu, Kyung-Hun Lee, Tae-Yong Kim, Seock-Ah Im, Eun-Shin Lee, Han-Byoel Lee, Hyeong-Gon Moon, Dong-Young Noh, Wonshik Han
Journal of Breast Disease.2017; 5(2): 51. CrossRef

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Nomogram to Predict Treatment Outcome of Fluoropyrimidine/Platinum-Based Chemotherapy in Metastatic Esophageal Squamous Cell Carcinoma: Hyun Ae Jung, Antoine Adenis, Jeeyun Lee, Se Hoon Park, Chi Hoon Maeng, Silvia Park, Hee Kyung Ahn, Young Mog Shim, Nicolas Penel, Young-Hyuck Im; Cancer Res Treat. 2013;45(4):285-294. Published online December 31, 2013; DOI: https://doi.org/10.4143/crt.2013.45.4.285

Abstract PDF PubReader ePub

PURPOSE
The degree of benefit from palliative chemotherapy differs widely among patients with metastatic esophageal squamous cell carcinoma (MESCC). The purpose of this study was to develop and validate a prognostic nomogram to predict survival and aid physicians and patients in the decision-making process regarding treatment options.
MATERIALS AND METHODS
Clinicopathologic variables and treatment outcomes of 239 patients who were diagnosed with MESCC and received either fluorouracil/cisplatin (FP) or capecitabine/cisplatin (XP) as first-line chemotherapy were reviewed. A nomogram was developed as a prognostic scoring system incorporating significant clinical and laboratory variables based on a multivariate Cox proportional hazards regression model. An independent series of 61 MESCC patients treated with FP served as an independent data set for nomogram validation.
RESULTS
No difference in response rate was observed between the FP group (44.8%) and the XP group (54.2%). Similarly, no significant differences in median progression-free survival and median overall survival were observed between regimen groups. Multivariate analysis showed that poor performance status (Eastern Cooperative Oncology Group [ECOG] status> or =2), weight loss (10% of the weight loss for 3 months), low albumin level (< or =3.5 g/dL), and absence of previous esophagectomy at the time of chemotherapy were significantly associated with low OS in both groups (p<0.05). Based on these findings, patients were classified into favorable (score, 0 to 90), intermediate (91-134), and poor (>135) prognostic groups. The median survival for those with a favorable ECOG was 13.8 months (95% confidence interval [CI], 10.8 to 18.6 months), for intermediate 11.2 months (95% CI, 8.7 to 11.9 months), and for poor, 7.0 months (95% CI, 3.6 to 10.0 months). External validation of the nomogram in a different patient cohort yielded significantly similar findings.
CONCLUSION
The nomogram described here predicts survival in MESCC patients and could serve as a guide for the use of FP/XP chemotherapy in MESCC patients.

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Annals of Surgical Oncology.2019; 26(2): 321. CrossRef
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Vaibhav Gupta, Natalie Coburn, Biniam Kidane, Kenneth R. Hess, Carolyn Compton, Jolie Ringash, Gail Darling, Alyson L. Mahar
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