Objective:To investigate the influencing factors of falls in patients with chemotherapy-induced peripheral neuropathy for gynecological cancer, and establish a Nomogram model based on independent influencing factors.Methods:A total of 216 patients with peripheral neuropathy who received chemotherapy for gynecological cancer in The First Affiliated Hospital of Army Military Medical University of the People′s Liberation Army from February 2021 to April 2023 were retrospectively selected, and were divided into the modeling set and the validation set according to the ratio of 7∶3 using random number table method. According to the occurrence of falls in the modeling set, the patients were divided into the fall group and the non-fall group. Independent influencing factors were obtained through univariate analysis and multivariate Logistic regression analysis, and a prediction model was constructed based on the regression analysis. A Nomogram map was drawn using R language software. Receiver operating characteristic curve (ROC) and calibration curve were used to test the prediction efficiency, and the predictive benefits were evaluated by clinical decision curve.Results:Among the 216 patients, 151 were included in the modeling set and 65 in the validation set. Among the patients in the modeling set, 53 cases were in the fall group, aged (62.89 ± 8.58) years old, and 98 cases were in the non-fall group, aged (59.48 ± 8.12) years old. Chemotherapy cycle, Neuropathy Impairment Score-Lower Limbs, Barthel index, Home Falls and Accidents Screening Tool, regular exercise habits, diabetes and depression were all independent influencing factors for falls in patients with chemotherapy-induced peripheral neuropathy of gynecologic cancer ( OR values were 0.312-3.727, all P<0.05). The area under the curve (AUC) of the established Nomogram model was 0.873, with good discriminating ability. The mean absolute error (MAE) of calibration curve was 0.048, which fitted the ideal curve, indicating that the model has good calibration performance. The AUC of the validation set was 0.873 and the MAE of calibration curve was 0.073, indicating that the model has good external prediction efficiency. Conclusions:This Nomogram model can predict falls in patients with chemotherapy-induced peripheral neuropathy of gynecological cancer and provide evidence for clinical prevention of falls.