Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study.

ABSTRACT:

Objective

To develop a clinically useful model that estimates the 10 year risk of breast cancer related mortality in women (self-reported female sex) with breast cancer of any stage, comparing results from regression and machine learning approaches.

Design

Population based cohort study.

Setting

QResearch primary care database in England, with individual level linkage to the national cancer registry, Hospital Episodes Statistics, and national mortality registers.

Participants

141 765 women aged 20 years and older with a diagnosis of invasive breast cancer between 1 January 2000 and 31 December 2020.

Main outcome measures

Four model building strategies comprising two regression (Cox proportional hazards and competing risks regression) and two machine learn

SUBMITTER: Clift AK 

PROVIDER: S-EPMC10170264 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature