The reporting quality and methodological quality of dynamic prediction models for cancer prognosis
Peijing Yan, Zhengxing Xu, Hui Xu, Xiajing Chu, Yizhuo Chen, Chao Yang, Shanpeng Xu, Huijie Cui, Li Zhang, Wenqiang Zhang, L Wang, Yanqiu Zou, Yan Ren, Jiaqiang Liao, Qin Zhang, Kehu Yang, Ling Zhang, Yunjie Liu, Jiayuan Li, Chunxia Yang · BMC Medical Research Methodology · 2025
BACKGROUND: To evaluate the reporting quality and methodological quality of dynamic prediction model (DPM) studies on cancer prognosis. METHODS: Extensive search for DPM studies on cancer prognosis was conducted in MEDLINE, EMBASE, and the Cochrane Library databases. The Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) and the Prediction model Risk of Bias Assessment Tool (PROBAST) were used to assess reporting quality and methodological quality, respectively. RESULTS: A total of 34 DPM studies were identified since the first publication in 2005, the main modeling methods for DPMs included the landmark model and the joint model. Regarding the reporting quality, the median overall TRIPOD adherence score was 75%. The TRIPOD items were poorly reported, especially the title (23.53%), model specification, including presentation (55.88%) and interpretation (50%) of the DPM usage, and implications for clinical use and future research (29.41%). Concerning methodological quality, most studies were of low quality (n = 30) or unclear (n = 3), mainly due to statistical analysis issues. CONCLUSIONS: 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.