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

We developed and validated a simple model to use the ADR risk score in patients who were administered anlotinib. This risk prediction model was well-calibrated and discriminative. It can be used as a reference for clinical decision-making. It has clinical significance for preventing ADRs, improving the prognosis of patients, and providing support for the rational use of drugs.

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Publication Details

Journal
Therapeutic Advances in Drug Safety
Published
2025-03-22
DOI
https://doi.org/10.1177/20420986251328687
Citations
1
Primary Topic
Lung Cancer Research Studies
Type
article
Field-Weighted Citation Impact
1.05
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article

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

Jiyong Liu, Jiajia Qian, Yunyun Cai, Wenjun Yi et al.
1 citations
Therapeutic Advances in Drug Safety
Lung Cancer Research Studies
1.05
article

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

Jiyong Liu, Jiajia Qian, Yunyun Cai, Wenjun Yi, Cong Ruan, Rui Xu
article en
1 citations

Abstract

We developed and validated a simple model to use the ADR risk score in patients who were administered anlotinib. This risk prediction model was well-calibrated and discriminative. It can be used as a reference for clinical decision-making. It has clinical significance for preventing ADRs, improving the prognosis of patients, and providing support for the rational use of drugs.

Therapeutic Advances in Drug SafetyVol. 16
Shanghai Medical College of Fudan University (CN), Fudan University Shanghai Cancer Center (CN)
Reduced inequalities
Openalex Percentile: Top 24%
Lung Cancer Research Studies
1.05
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