Work

Development and internal validation of a predictive model for thrombocytopenia in cervical cancer patients undergoing concurrent chemoradiotherapy

Year: 2026

Type: article

Abstract: Concurrent chemoradiotherapy (CCRT) enhances treatment efficacy in cervical cancer compared with radiotherapy alone but increases the risk of thrombocytopenia. This adverse effect has become a leading cause of dose reduction, treatment delays, and premature termination of CCRT, ultimately compromising patient survival. This study aimed to develop a simple and reliable model for pretherapeutic prediction of thrombocytopenia risk in patients undergoing CCRT. We retrospectively reviewed 146 cervical cancer patients treated with CCRT at the Cancer Hospital, Chinese Academy of Medical Sciences, Shenzhen Center, between April 2019 and September 2022. Patients were stratified into a thrombocytopenia group ( n = 64) and a non-thrombocytopenia group ( n = 82). Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable logistic regression analysis. Internal validation was performed via bootstrap resampling. Chemotherapy regimen, extended-field radiotherapy, body mass index (BMI), baseline platelet count (PLT), and the percentage of bone marrow volume receiving ≥ 25 Gy (BM_V25) were identified as independent predictors of thrombocytopenia. The predictive model demonstrated good discrimination (area under the curve [AUC] = 0.840; 95% confidence interval [CI], 0.773–0.904) and calibration (Brier score = 0.162; 95% CI, 0.128–0.195). Decision curve analysis confirmed its clinical utility. After internal validation, the model maintained good performance (AUC = 0.817; Brier score = 0.176). We developed and internally validated a predictive model based on clinical and dosimetric factors that enables early effectively identification of cervical cancer patients at high risk of thrombocytopenia during CCRT, facilitating individualized treatment planning.

Source: BMC Cancer

DOI: 10.1186/s12885-026-16725-5

Authors: Ling Lei, Renba Liang, Junfang Liao, Zhijian Chen, Jianghu Zhang

Institution: Chinese Academy of Medical Sciences & Peking Union Medical College

Language: English

Topic: Endometrial and Cervical Cancer Treatments

Subfield: Obstetrics and Gynecology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,390