Development and validation of a risk-prediction model for adverse drug reactions in real-world cancer patients treated with anlotinib.

ABSTRACT:

Background

The risk factors related to the adverse drug reactions (ADRs) of anlotinib have been rarely investigated. In addition, a corresponding risk prediction model has not been established in China pertaining to anlotinib-related ADRs.

Objectives

To manage ADRs more efficiently and improve the prognosis of patients administered anlotinib.

Design

A retrospective analysis was conducted using the medical records of patients diagnosed with cancer who were administered anlotinib after hospitalization between January 1, 2020, and December 31, 2023.

Methods

We performed a combination of univariate analysis and multivariate binary logistic regression analysis to identify significant factors that can accurately predict ADRs. Model fitting was performed using forward

SUBMITTER: Qian J 

PROVIDER: S-EPMC11946284 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature