Application of a Non-Mixture Cure Rate Model for Analyzing Survival of Patients with Breast Cancer

Abstract

<b>Background:</b> As a result of significant progress made in treatment of many types of cancers during the lastfew decades, there have been an increased number of patients who do not experience mortality. We refer to theseobservations as cure or immune and models for survival data which include cure fraction are known as cure ratemodels or long-term survival models. Materials and <br/><b>Methods</b>: In this study we used the data collected from 438female patients with breast cancer registered in the Cancer Research Center in Shahid Beheshti University ofMedical Sciences, Tehran, Iran. The patients had been diagnosed from 1992 to 2012 and were followed up untilOctober 2014. We had to exclude some because of incomplete information. Phone calls were made to confirmwhether the patients were still alive or not. Deaths due to breast cancer were regarded as failure. To identifyclinical, pathological, and biological characteristics of patients that might have had an effect on survival of thepatients we used a non-mixture cure rate model; in addition, a Weibull distribution was proposed for the survivaltime. Analyses were performed using STATA version 14. The significance level was set at P ≤ 0.05. <br/><b>Results</b>: Atotal of 75 patients (17.1%) died due to breast cancer during the study, up to the last follow-up. Numbers ofmetastatic lymph nodes and histologic grade were significant factors. The cure fraction was estimated to be58%. <br/><b>Conclusions</b>: When a cure fraction is not available, the analysis will be changed to standard approachesof survival analysis; however when the data indicate that the cure fraction is available, we suggest analysis ofsurvival data via cure models.