1Decoding Survival: Predictive Modeling of Progression-Free Outcomes in Platinum Based Chemotherapy

Abstract

The aim of the study is development and evaluation of predictive models for progression free survival in female reproductive tract cancers through clinical and demographic data. Large data of 1595 patients was analyzed having variables like age, patient staus, disease staus, ethnicity, comorbidities, overall survival, response rate, progression free survival, histology. Significant statistical correlation and exploratory data analysis was carried out to figure out corrlation between survival outcomes and patient’s characteristics. Various machine learning algorithms like linear regression, random forest model, support vector machine and XGBoost were used for the prediction of progression free survival. Different performance matrices were used to asses the safety and efficacy of the model. The outcomes show the practicalityand usefullness of predictive machine learning models for the prediction of disease progression, guidance of cutomized treatment strategies and development of clinical decision making in oncology.