Cancer Research and Treatment

Original Articles

Trends in Incidence and Survival of Childhood and Adolescent Cancer in Korea, 2001–2020: Comparison with U.S. SEER Data: Jin Kyung Suh, Eun Hye Park, Meerim Park, Jun Ah Lee, Kyu-won Jung, Hyeon Jin Park; Received July 10, 2025 Accepted December 30, 2025 Published online January 2, 2026; DOI: https://doi.org/10.4143/crt.2025.722 [Epub ahead of print]

Abstract PDF PubReader ePub: Purpose
Childhood cancers are rare but clinically significant. Monitoring incidence and survival trends is essential for evaluating progress in cancer control and identifying areas for improvement.
Materials and Methods
We analyzed cancer incidence and survival trends among individuals aged 0-19 years in Korea using data from the Korea Central Cancer Registry from 2001 to 2020. Cancer types were classified according to the International Classification of Childhood Cancer, third edition (ICCC-3). Age-standardized incidence rates (ASRs) and annual percent changes (APCs) were calculated. Relative survival rates (RSRs) were estimated and compared with data from the United States.
Results
A total of 34,223 cancer cases were identified during the study period. The overall ASR was 151.3 per million person-years, with a significant increasing trend (APC 1.5%). Leukemias were the most common diagnostic group (ASR 43.7), followed by central nervous system tumors and lymphomas. Between 2001-2010 and 2011-2020, the 5-year and 10-year RSRs improved from 75.2% to 84.8% and from 72.7% to 82.7%, respectively. The largest survival gains were observed in leukemia (14.9 percentage points) and neuroblastoma (13.1 percentage points). Compared to Surveillance, Epidemiology, and End Results (SEER) data, Korea showed similar overall survival trends, although differences remained by cancer type and age group.
Conclusion
The incidence of childhood and adolescent cancers in Korea has increased, while survival has significantly improved over the past two decades. These findings highlight substantial progress in pediatric cancer care, while underscoring the need for targeted efforts for specific cancer subtypes and age groups.

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Kidney Failure–Related Mortality in Patients with Cancer: Insights from the Cancer Public Library Database in South Korea: Chang Seong Kim, Sang Heon Suh, Hong Sang Choi, Eun Hui Bae, Seong Kwon Ma, Jin Hyung Jung, Bongseong Kim, Kyung-Do Han, Soo Wan Kim; Received April 29, 2025 Accepted November 22, 2025 Published online November 24, 2025; DOI: https://doi.org/10.4143/crt.2025.466 [Epub ahead of print]

Abstract PDF Supplementary Material PubReader ePub

Purpose
Kidney failure is associated with an increased risk of death. However, since the impact of kidney failure on overall and cancer-related mortality among individuals with cancer remains unclear, we investigated kidney failure–related mortality in patients with cancer, stratified by various cancer types.
Materials and Methods
A total of 1,307,680 participants newly diagnosed with cancer were identified from the Cancer Public Library Database. We analyzed data from patients with preexisting kidney failure before cancer diagnosis and compared their mortality risk with patients without kidney failure using multivariable Cox proportional hazard models.
Results
All-cause and cancer-related mortality was significantly higher in the kidney failure group. Preexisting kidney failure was associated with an increased risk of mortality in all cancer types after adjusting for comorbidities and treatment modalities (adjusted hazard ratio [aHR] of all-cause death 1.75; 95% confidence interval [CI], 1.70 to 1.81; aHR of cancer-related death, 1.27; 95% CI, 1.22 to 1.32). Among specific cancer types, thyroid and breast cancers showed the highest mortality risks of kidney failure, with thyroid cancer presenting the greatest risk. However, the risk of death was attenuated in liver, gallbladder, and lung cancers. Furthermore, aHRs were lower for mortality in metastatic cancer compared to localized and regional stages.
Conclusion
Preexisting kidney failure significantly increases the risk of all-cause and cancer-related death among cancer patients, particularly in localized cancer and specific cancer types.

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Adverse Renal Outcomes in Patients With Mesothelioma—A Territory‐Wide Real‐World Data
Wang Chun Kwok, James Chung Man Ho, Isaac Sze Him Leung, Desmond Yat Hin Yap
Cancer Medicine.2026;[Epub] CrossRef

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Breast cancer

Response to Neoadjuvant Systemic Therapy May Serve as an Indicator for Omitting Post–Breast-Conserving Surgery Radiation Therapy in Women with Early-Stage Breast Cancer: Chaofan Li, Yusheng Wang, Mengjie Liu, Shiyu Sun, Yiwei Jia, Jingkun Qu, Shuqun Zhang, Chong Du; Cancer Res Treat. 2026;58(4):1174-1193. Published online September 10, 2025; DOI: https://doi.org/10.4143/crt.2025.584

Abstract PDF Supplementary Material PubReader ePub: Purpose
To avoid unnecessary toxicities and optimize the allocation of healthcare resources, it is crucial to adequately select patients with extremely low recurrence risk to downgrade or eliminate radiation therapy (RT).
Materials and Methods
From the Surveillance, Epidemiology, and End Results database, clinical data of 7,291 female patients with early-stage breast cancer who underwent neoadjuvant systemic therapy (NST) and breast-conserving surgery (BCS) were collected for this study. The patients were stratified by their response to NST, and the long-term survival and risk of recurrence were assessed using Cox regression analysis and Fine-Gray competing risk models for those with and without post-BCS RT, respectively.
Results
Our results showed that female patients with early-stage breast cancer who achieved complete response (CR) to NST, omitting post-BCS RT achieved the same overall survival and disease-free survival as those who received the post-BCS RT, and the omission did not increase the risk of recurrence or breast cancer–specific death. For patients who did not achieve CR to NST, five clinical indicators (including age, N category, grade, response to NST, and molecular subtype) were employed to construct a nomogram for clinical prediction of overall survival, thereby identifying of patients at relatively low recurrence risk. The validated results affirmed our model’s ability to accurately discriminate high- and low-risk patients and its promising clinical application value.
Conclusion
Post-BCS RT can be omitted for women with early-stage breast cancer who achieved CR to NST. For those who failed to achieve CR to NST, a nomogram was constructed for clinicians to decide whether to omit post-BCS RT or not based on individualized assessment.

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Gastrointestinal cancer

Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer: Mohamed Hosny Osman, Reham Hosny Mohamed, Hossam Mohamed Sarhan, Eun Jung Park, Seung Hyuk Baik, Kang Young Lee, Jeonghyun Kang; Cancer Res Treat. 2022;54(2):517-524. Published online June 15, 2021; DOI: https://doi.org/10.4143/crt.2021.206

Abstract PDF Supplementary Material PubReader ePub

Purpose
Machine learning (ML) is a strong candidate for making accurate predictions, as we can use large amount of data with powerful computational algorithms. We developed a ML based model to predict survival of patients with colorectal cancer (CRC) using data from two independent datasets.
Materials and Methods
A total of 364,316 and 1,572 CRC patients were included from the Surveillance, Epidemiology, and End Results (SEER) and a Korean dataset, respectively. As SEER combines data from 18 cancer registries, internal validation was done using 18-Fold-Cross-Validation then external validation was performed by testing the trained model on the Korean dataset. Performance was evaluated using area under the receiver operating characteristic curve (AUROC), sensitivity and positive predictive values.
Results
Clinicopathological characteristics were significantly different between the two datasets and the SEER showed a significant lower 5-year survival rate compared to the Korean dataset (60.1% vs. 75.3%, p < 0.001). The ML-based model using the Light gradient boosting algorithm achieved a better performance in predicting 5-year-survival compared to American Joint Committee on Cancer stage (AUROC, 0.804 vs. 0.736; p < 0.001). The most important features which influenced model performance were age, number of examined lymph nodes, and tumor size. Sensitivity and positive predictive values of predicting 5-year-survival for classes including dead or alive were reported as 68.14%, 77.51% and 49.88%, 88.1% respectively in the validation set. Survival probability can be checked using the web-based survival predictor (http://colorectalcancer.pythonanywhere.com).
Conclusion
ML-based model achieved a much better performance compared to staging in individualized estimation of survival of patients with CRC.

Citations

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Explainable AI for colorectal cancer mortality and risk factor prediction in Korea: A nationwide cancer cohort study
Sang Won Park, Na Young Yeo, Tae-Hoon Kim, Myoung Nam Lim, Inhyeok Yim, Oh Beom Kwon, Seung-Joo Nam, Hui-Young Lee, Woo Jin Kim
International Journal of Medical Informatics.2026; 205: 106125. CrossRef
A clinical visualization model for predicting distant metastasis and prognostic outcomes in mucinous adenocarcinoma of the appendix: a SEER database study
Xiaoming Xu, Hualei Chen, Jingzhi Wang
Expert Review of Anticancer Therapy.2026; 26(1): 131. CrossRef
Predicting Postresection Colorectal Liver Metastases Recurrence Using Advanced Graph Neural Networks with Explainability and Causal Inference
Jubair Ahmed, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Sami Azam
Advanced Intelligent Systems.2026;[Epub] CrossRef
Artificial Intelligence Remote Patient Monitoring for Predicting Overall Survival for Patients Undergoing Radical Cystectomy for Bladder Cancer: Exploratory Analysis of the Prospective Trial
Yansong Liu, Pramit Khetrapal, Ronnie Strafford, Adamos Hadjivasilou, Nikhil Vasdev, Philip Charlesworth, Muhamaad Shamim Khan, Ahmed Abdulaal, Zhaoyan Dong, James W F Catto, Yukun Zhou, John D Kelly, Ivana Drobnjak
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Husne Farah, Fahmida Islam, Shuvo Biswas, Mohammad Shorif Uddin
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Bhagvat J Maheta, Rachel L Ross, Isabella Raspi, Christina Keny, Marti N Okech, Selen Bozkurt, Karleen F Giannitrapani
JMIR Perioperative Medicine.2026; 9: e89936. CrossRef
Development and validation of a biomarker-based prediction model for metastasis in patients with colorectal cancer: Application of machine learning algorithms
Erfan Ayubi, Sajjad Farashi, Leili Tapak, Saeid Afshar
Heliyon.2025; 11(1): e41443. CrossRef
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Alireza Jafarkhani, Behzad Imani, Soheila Saeedi, Amir Shams
Health Science Reports.2025;[Epub] CrossRef
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Personalized surveillance in colorectal cancer: Integrating circulating tumor DNA and artificial intelligence into post-treatment follow-up
Ionut Negoi
World Journal of Gastroenterology.2025;[Epub] CrossRef
Association of sarcopenia with all-cause and cause-specific mortality in cancer patients: development and validation of a 3-year and 5-year survival prediction model
Feng Cui, Xiangji Dang, Daiyun Peng, Yuanhua She, Yubin Wang, Ruifeng Yang, Zhiyao Han, Yan Liu, Hanteng Yang
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Interpretable machine learning models based on body composition and inflammatory nutritional index (BCINI) to predict early postoperative recurrence of colorectal cancer: Multi-center study
Yongjie Zhou, Jinhong Zhao, Fei Zou, Yongming Tan, Wei Zeng, Jiahui Jiang, Jiale Hu, Qiao Zeng, Lianggeng Gong, Lan Liu, Linhua Zhong
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Jakob Woerner, Yonghyun Nam, Sang-Hyuk Jung, Manu Shivakumar, Matthew Lee, Eun Kyung Choe, Min Jung Kim, Rumi Shin, Seung-Bum Ryoo, Seung-Yong Jeong, Kyu Joo Park, Sung Chan Park, Dae Kyung Sohn, Jae Hwan Oh, Dokyoon Kim, Ji Won Park
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Semra Demirli Atici, Aras Emre Canda, Mustafa Cem Terzi
World Journal of Gastroenterology.2025;[Epub] CrossRef
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R. Sh. Abdulaeva, V. I. Pavlova, T. G. Gevorkyan, Y. V. Belenkaya, M. Sh. Manukyan, S. S. Gordeev
Koloproktologia.2025; 24(4): 125. CrossRef
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Frontiers in Medicine.2024;[Epub] CrossRef
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Erkan Kayikcioglu, Arif Hakan Onder, Burcu Bacak, Tekin Ahmet Serel
Surgical Oncology.2024; 54: 102079. CrossRef
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Yonghong Wang, Ke Liu, Wanbin He, Jie Dan, Mingjie Zhu, Lei Chen, Wenjie Zhou, Ming Li, Jiangpeng Li
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Light gradient boost tree classifier predictions on appendicitis with periodontal disease from biochemical and clinical parameters
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Lanni Zhou, Lizhu Ouyang, Baoliang Guo, Xiyi Huang, Shaomin Yang, Jialing Pan, Liwen Wang, Ming Chen, Fan Xie, Yunjing Li, Yongxing Du, Xinjie Chen, Qiugen Hu, Fusheng Ouyang
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Healthcare Analytics.2023; 3: 100132. CrossRef
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Tadashi Miyagawa, Marina Saga, Minami Sasaki, Miyuki Shimizu, Akira Yamaura, Alvan Ukachukwu
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Tianzhi Huang, Dejin Le, Lili Yuan, Shoujia Xu, Xiulan Peng, Samuele Ceruti
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洪铭崔
Advances in Clinical Medicine.2023; 13(03): 3942. CrossRef
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Fan Zhang, Boqi Xu, Yao Peng, Zhongqi Mao
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Omitting Adjuvant Radiotherapy for Hormone Receptor‒Positive Early-Stage Breast Cancer in Old Age: A Propensity Score Matched SEER Analysis: Yi-Jun Kim, Kyung Hwan Shin, Kyubo Kim; Cancer Res Treat. 2019;51(1):326-336. Published online May 10, 2018; DOI: https://doi.org/10.4143/crt.2018.163

Abstract PDF PubReader ePub

Purpose
The purpose of this study was to investigate the non-inferiority of omitting radiotherapy (RT) after breast-conserving surgery (BCS) for hormone receptor (HR)‒positive T1N0 breast cancer in elderly women.
Materials and Methods
From 2004 to 2014, HR-positive T1N0 breast cancer patients aged 50 years or older and receiving BCS were retrieved from the Surveillance, Epidemiology, and End Results 18 database. After propensity score matching between the no-RT and RT groups, univariate and multivariate analyses were performed. Identified prognostic factors were used to stratify the risk groups. In each risk group, 10-year cancer-specific survival (CSS) rates were compared between the no-RT and RT groups.
Results
After propensity score matching, the numbers of patients in the no-RT and RT groups were both 18,586. For patients who satisfied both a tumor size of 1-10 mm and a tumor grade of 1-2, omitting RT did not decrease the CSS rate at any age group, ranging from ≥ 50 to ≥ 85 years; for patients aged ≥ 50 years, the 10-year CSS rates in the no-RT and RT groups were 97.2% and 96.8%, respectively (adjusted hazard ratio, 0.862; p=0.312). However, for patients with a tumor size of 11-20 mm or tumor grade of 3-4, RT significantly increased the CSS rate irrespective of age.
Conclusion
RT after BCS for HR-positive T1N0 breast cancer in elderly women might be omitted without causing a decrease in the CSS rate, but only in patients who satisfy both a small tumor size (≤ 10 mm) and low tumor grade (1-2).

Citations

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Meta-Analysis of Different Surgical Methods for Breast Cancer Patients
Xiaoshu Zhao, Xunan Wei, Qing Shen, Xuanhong Zhou
International Journal of Pharmacology.2024; 20(5): 892. CrossRef
Radiotherapy is recommended for hormone receptor-negative older breast cancer patients after breast conserving surgery
Yaxiong Liu, Jinsong Li, Honghui Li, Gongyin Zhang, Changwang Li, Changlong Wei, Jinsheng Zeng
Scientific Reports.2024;[Epub] CrossRef
Comparison of breast‐conserving surgery without radiotherapy and mastectomy in the treatment of elderly patients with early breast cancer: A PSM and SEER database study
Baiyang Fu, Xi Chen, Wenlong Liang, Yao Wang, Yuan Yao, Jianguo Zhang
Cancer Medicine.2023; 12(14): 15229. CrossRef
Ways to improve breast cancer patients' management and clinical outcome: The 2020 Assisi Think Tank Meeting
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Critical Reviews in Oncology/Hematology.2022; 177: 103774. CrossRef
Research on the cutoff tumor size of omitting radiotherapy for BCSS after breast conserving surgery in women aged 65 years or oder with low-risk invasive breast carcinoma: Results based on the SEER database
Zejian Yang, Kunlong Li, Pei Qiu, Yifei Ma, Bin Wang, Yu Yan, Du Meng, Chen Feng, Yu Ren, Yijun Li, Pingping Li, Can Zhou
The Breast.2021; 60: 287. CrossRef
Effectiveness of radiotherapy after breast-conserving surgery in older patients with T1-2N0 breast cancer
Anna Z. de Boer, Esther Bastiaannet, Nienke A. de Glas, Perla J. Marang-van de Mheen, Olaf M. Dekkers, Sabine Siesling, Linda de Munck, Kelly M. de Ligt, Johanneke E. A. Portielje, Gerrit Jan Liefers
Breast Cancer Research and Treatment.2019; 178(3): 637. CrossRef

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Evaluation of the Benefit of Radiotherapy in Patients with Occult Breast Cancer: A Population-Based Analysis of the SEER Database: Byoung Hyuck Kim, Jeanny Kwon, Kyubo Kim; Cancer Res Treat. 2018;50(2):551-561. Published online June 1, 2017; DOI: https://doi.org/10.4143/crt.2017.189

Abstract PDF Supplementary Material PubReader ePub

Purpose
Few studies for occult breast cancer (OBC) have evaluated the effect of radiotherapy (RT) after mastectomy or axillary lymph node dissection (ALND) with/without breast surgery. Therefore, we investigated clinicopathologic factors of OBC with the impact of postoperative RT to determine its prognostic significance using large population-based data.
Materials and Methods
We performed a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER) database from 1983 to 2013. A total of 1,045 eligible patients with OBC were identified. We compared overall survival (OS) using Cox proportional hazards regression with propensity score matching after verifying an imbalance of prognosticators between RT group (n=518) and non-RT group (n=479).
Results
Patients with age < 70 (p=0.033), married marital status (p < 0.001), undergoing ALND (p < 0.001), more examined lymph nodes (LNs) (p < 0.001), and more metastatic LNs (p < 0.001) were more likely to receive RT. Multivariate analysis after propensity score matching (n=798) showed that patients treated with RT survived significantly longer than those without RT (5-year OS, 81.5% vs. 78.3%; p=0.014). A significantly prolonged OS was observed when RT was given to patients treated with mastectomy (p=0.033), those treated with ALND (p=0.036), or those with more than seven metastatic LNs (p=0.016).
Conclusion
RT may offer survival benefit in OBC even after mastectomy or ALND, especially in patients with more than seven metastatic LNs. Further prospective studies are needed to validate these findings.

Citations

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Interactions of clinicopathological features and surgical interventions in occult breast cancer: A population-based study
Yang Man, Sun Jiale, Lin Dongcai, Cui Qiuxia, Chen Xiaoqi, Jiang Hongnan, Liu Liqiong, Gao Jidong
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Acquired resistance to molecularly targeted therapies for cancer
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Occult breast cancer in an older woman: A case report
Cong Liu, Hua Xing
Experimental and Therapeutic Medicine.2024;[Epub] CrossRef
Reconceptualizing the clinicopathological features, locoregional therapy and prognostic factors of occult breast cancer in the era of molecular subtyping
Xin Ye, Li Yang, Qi He, Xiaoyan Lin, Jie Wang, Rongrong Cui, Cheng Xu
Women & Health.2023; 63(2): 105. CrossRef
Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Occult Breast Cancer Patients
Jingkun Qu, Chaofan Li, Mengjie Liu, Yusheng Wang, Zeyao Feng, Jia Li, Weiwei Wang, Fei Wu, Shuqun Zhang, Xixi Zhao
Journal of Clinical Medicine.2023; 12(9): 3097. CrossRef
Best treatment options for occult breast cancer: A meta-analysis
Rong Wang, Hong-xin Yang, Jie Chen, Jian-jun Huang, Qing Lv
Frontiers in Oncology.2023;[Epub] CrossRef
Occult Breast Cancer Patients with Mastectomy have Better Prognosis than those with Breast-Conserving Therapy
Jiayi Li, Gang Liu, Ziqi Jia, Fei Ren, Dawei Dong, Menglu Zhang, Xiang Wang, Yipeng Wang
Future Oncology.2023; 19(36): 2405. CrossRef
Surgical treatment trends and identification of primary breast tumors after surgery in occult breast cancer: a study based on the Japanese National Clinical Database—Breast Cancer Registry
Mitsuo Terada, Minoru Miyashita, Hiraku Kumamaru, Hiroaki Miyata, Kenji Tamura, Masayuki Yoshida, Etsuyo Ogo, Masayuki Nagahashi, Sota Asaga, Yasuyuki Kojima, Takayuki Kadoya, Kenjiro Aogi, Naoki Niikura, Kotaro Iijima, Naoki Hayashi, Makoto Kubo, Yutaka
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D. Mantas, Z. Garoufalia, C. Kontzoglou
Indian Journal of Surgery.2021; 83(S2): 364. CrossRef
Treatment for occult breast cancer: A propensity score analysis of the National Cancer Database
Catherine Tsai, Beiqun Zhao, Theresa Chan, Sarah L. Blair
The American Journal of Surgery.2020; 220(1): 153. CrossRef
Outcome of breast-conserving treatment for axillary lymph node metastasis from occult breast cancer with negative breast MRI
Haeyoung Kim, Won Park, Su Ssan Kim, Sung Ja Ahn, Yong Bae Kim, Tae Hyun Kim, Jin Hee Kim, Jin-Hwa Choi, Hae Jin Park, Jee Suk Chang, Doo Ho Choi
The Breast.2020; 49: 63. CrossRef
Breast-Conserving Surgery in Patients With Mammary Paget's Disease
Yufeng Yao, Li Sun, Yan Meng, Yan Zhuang, Lin Zhao, Qiao Yu, Chengshuai Si
Journal of Surgical Research.2019; 241: 178. CrossRef
Evaluation of the benefit of post‑mastectomy radiotherapy in patients with early‑stage breast cancer: A propensity score matching study
Wenjie Shi, Youhong Luo, Dongkang Zhao, Hao Huang, Weiyi Pang
Oncology Letters.2019;[Epub] CrossRef

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A National Study of Survival Trends and Conditional Survival in Nasopharyngeal Carcinoma: Analysis of the National Population-Based Surveillance Epidemiology and End Results Registry: Jia-Wei Lv, Xiao-Dan Huang, Yu-Pei Chen, Guan-Qun Zhou, Ling-Long Tang, Yan-Ping Mao, Wen-Fei Li, Ai-Hua Lin, Jun Ma, Ying Sun; Cancer Res Treat. 2018;50(2):324-334. Published online April 19, 2017; DOI: https://doi.org/10.4143/crt.2016.544

Abstract PDF PubReader ePub

Purpose
Conditional survival (CS) provides important information on survival for a period of time after diagnosis. Currently, information on CS patterns of patients with nasopharyngeal carcinoma (NPC) is lacking. We aimed to analyze survival rate over time and estimate CS for NPC patients using a national population-based registry.
Materials and Methods
Patients diagnosed with NPC between 1973 and 2007 with at least 5-year follow-up were identified from the Surveillance Epidemiology End Results registry. Traditional survival rates and crude CS estimateswere calculated using Kaplan-Meier analysis. Risk-adjusted survival curves were plotted from the proportional hazards model using the correct group prognosis method.
Results
For 7,713 patients analyzed, adjusted baseline 5-year overall survival improved significantly from 36.0% in patients diagnosed in 1973-1979, 41.7% in 1980-1989, 46.6% in 1990- 1999, to 54.7% in 2000-2007 (p < 0.01). CS analysis demonstrated that for every additional year survived, adjusted probability of surviving the next 5 years increased from 66.7% (localized), 54.0% (regional), and 35.3% (distant) at the time of diagnosis, to 83.7% (localized), 75.0% (regional), and 62.2% (distant) for patients who had survived 5 years. Adjusted 5-year CS differed among age, sex, tumor histology, ethnicity, and stage subgroups initially, but converged with time.
Conclusion
Treatment outcomes of NPC patients have greatly improved over the decades. Increases in CS become more prominent in patients with distant disease than in those with localized or regional disease as patients survive longer. CS provides more dynamic prognostic information for patients who have survived a period of time after diagnosis.

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