Cancer Research and Treatment

Dan Zhao

1 Article

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

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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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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