Unveiling Recurrence Patterns: Analyzing Predictive Risk Factors for Breast Cancer Recurrence after Surgery.

ABSTRACT:

Objectives

Breast cancer (BC) stands as the second-leading cause of female-specific cancer-related fatalities globally, necessitating comprehensive research to address its critical aspects. This study aimed to explore the time intervals between surgery and disease recurrence in BC patients and their survival utilizing various parametric and semi-parametric models.

Methods

After the examination of data collected from 2010 to 2021 at a BC Center in Tehran, Iran, 171 cases met the criteria for analysis out of 2246 datasets. Model fitting, was assessed through the Akaike Information Criterion (AIC), and indicated the logistic distribution as the most fit one among concurrent and independent variable models.

Results

The Cox proportional hazard regression model consistently

SUBMITTER: Shahmoradi M 

PROVIDER: S-EPMC11549699 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature