The reporting quality and methodological quality of dynamic prediction models for cancer prognosis

The Landmark model and joint model show potential in DPM. The suboptimal reporting and methodological qualities of current DPM studies should be improved to facilitate clinical application.

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Publication Details

Journal
BMC Medical Research Methodology
Published
2025-03-01
DOI
https://doi.org/10.1186/s12874-025-02516-2
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00

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article

The reporting quality and methodological quality of dynamic prediction models for cancer prognosis

Kehu Yang, Chao Yang, Hui Xu, L Wang et al.
BMC Medical Research Methodology
Radiomics and Machine Learning in Medical Imaging
article

The reporting quality and methodological quality of dynamic prediction models for cancer prognosis

Kehu Yang, Chao Yang, Hui Xu, L Wang, Xiajing Chu, Xia Jiang, Peijing Yan, Zhengxing Xu, Yuqin Yao, Yan Ren, Yizhuo Chen, Chunxia Yang, Huijie Cui, Jiaqiang Liao, Qin Zhang, Yanqiu Zou, Li Zhang, Ling Zhang, Wenqiang Zhang, Ben Zhang, Yunjie Liu, Zhenmi Liu, Jiayuan Li, Shanpeng Xu
article en

Abstract

The Landmark model and joint model show potential in DPM. The suboptimal reporting and methodological qualities of current DPM studies should be improved to facilitate clinical application.

BMC Medical Research MethodologyVol. 25(1)
University of Electronic Science and Technology of China (CN), Sichuan University (CN), West China Medical Center of Sichuan University (CN), Southwest Medical University (CN), Lanzhou University Second Hospital (CN), Impact (CA), Lanzhou University (CN), McMaster University (CA)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 94%
Radiomics and Machine Learning in Medical Imaging
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