Affiliation:
1. Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Abstract
Abstract
PurposeThe aim of this study is to develop and internal validate a novel and specific predictive model for severe neutropenia during adjuvant chemotherapy cycles among patients with gastric cancer.
Methods We included 391 gastric cancer patients underwent curative laparoscopic D2 gastrectomy and divided them into development cohort and validation cohorts. The study endpoint was grade 3/4 neutropenia. Multivariate logistic regression was performed to analyze the independent risk factor of severe neutropenia. Predictive nomogram was constructed based on the multivariate model using R. We applied area under ROC curve (AUC) and decision curve analysis (DCA) to evaluate the performance of the model.
Results 318 patients and 73 patients were divided into development and validation cohorts, treated with 1518 and 356 chemotherapy cycles respectively. The multivariable analysis revealed 4 predictive factors for severe neutropenia: Age, prealbumin level, prognostic nutritional index (PNI) and neutropenia in previous cycles. The constructed nomogram displayed a good predictive value, with AUCs as 0.825 (95%CI, 0.789-0.860) and 0.810 (95%CI, 0.783-0.835) in development and validation cohorts.
ConclusionsWe developed and internally validate a novel and specific risk prediction model for severe neutropenia among gastric cancer patients during adjuvant chemotherapy. This model is user-friendly and can guide clinical decision for personalized treatment plan. Further external validation should be necessary.
Publisher
Research Square Platform LLC