Construction of a Risk-Prediction Model for Severe Bone Marrow Suppression During Radiotherapy in Cervical Cancer Patients.

Background: This study aimed to examine severe bone marrow suppression risk factors during radiotherapy in patients with cervical cancer and to develop and validate a visual evaluation tool for predicting the risk of severe bone marrow suppression during radiotherapy in these patients. Methods: A total of 300 patients with cervical cancer who underwent radiotherapy were retrospectively included in this cohort study. Patients were randomly divided into a model group (n = 240) and a validation group (n = 60) at a ratio of 8:2. Univariate and multivariate logistic regression analyses were performed to explore and establish a nomogram prediction model. The feasibility of this nomogram model in predicting the risk of severe bone marrow suppression during radiotherapy in patients with cervical cancer was assessed in the validation cohort. The discrimination ability, accuracy, and clinical utility of the model were evaluated via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results: Menopausal status, Karnofsky performance score (KPS), clinical stage, concurrent chemotherapy status, and pre-radiotherapy creatinine level were identified as independent risk factors for severe bone marrow suppression during radiotherapy in patients (P < .05). DCA revealed that the nomogram model had a greater net benefit in predicting the risk of severe bone marrow suppression during radiotherapy in patients with cervical cancer when the patient's threshold probability was between 0.20 and 0.93. Conclusion: The nomogram model based on these independent risk factors exhibited good predictive performance, assisting in individualized risk assessment and facilitating early intervention to benefit patients during radiotherapy.