Expanding TNM for lung cancer through machine learning.

ABSTRACT:

Background

Expanding the tumor, lymph node, metastasis (TNM) staging system by accommodating new prognostic and predictive factors for cancer will improve patient stratification and survival prediction. Here, we introduce machine learning for incorporating additional prognostic factors into the conventional TNM for stratifying patients with lung cancer and evaluating survival.

Methods

Data were extracted from SEER. A total of 77 953 patients were analyzed using factors including primary tumor (T), regional lymph node (N), distant metastasis (M), age, and histology type. Ensemble algorithm for clustering cancer data (EACCD) and C-index were applied to generate prognostic groups and expand the current staging system.

Results

With T, N, and M, EACCD stratified patients i

SUBMITTER: Hueman M 

PROVIDER: S-EPMC8088955 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature