Novel nutritional indicator as predictors among subtypes of lung cancer in diagnosis.

ABSTRACT:

Introduction

Lung cancer is a serious global health concern, and its subtypes are closely linked to lifestyle and dietary habits. Recent research has suggested that malnutrition, over-nutrition, electrolytes, and granulocytes have an effect on the development of cancer. This study investigated the impact of combining patient nutritional indicators, electrolytes, and granulocytes as comprehensive predictors for lung cancer treatment outcomes, and applied a machine learning algorithm to predict lung cancer.

Methods

6,336 blood samples were collected from lung cancer patients classified as lung squamous cell carcinoma (LUSC), lung adenocarcinoma (LUAD), and small cell lung cancer (SCLC). 2,191 healthy individuals were used as controls to compare the differences in nutritional i

SUBMITTER: Li H 

PROVIDER: S-EPMC9909296 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature