The reporting quality and methodological quality of dynamic prediction models for cancer prognosis
Abstract 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...
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2025-03-01
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| Online Access: | https://doi.org/10.1186/s12874-025-02516-2 |
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| author | Peijing Yan Zhengxing Xu Xu Hui Xiajing Chu Yizhuo Chen Chao Yang Shixi Xu Huijie Cui Li Zhang Wenqiang Zhang Liqun Wang Yanqiu Zou Yan Ren Jiaqiang Liao Qin Zhang Kehu Yang Ling Zhang Yunjie Liu Jiayuan Li Chunxia Yang Yuqin Yao Zhenmi Liu Xia Jiang Ben Zhang |
| author_facet | Peijing Yan Zhengxing Xu Xu Hui Xiajing Chu Yizhuo Chen Chao Yang Shixi Xu Huijie Cui Li Zhang Wenqiang Zhang Liqun Wang Yanqiu Zou Yan Ren Jiaqiang Liao Qin Zhang Kehu Yang Ling Zhang Yunjie Liu Jiayuan Li Chunxia Yang Yuqin Yao Zhenmi Liu Xia Jiang Ben Zhang |
| author_sort | Peijing Yan |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-d9b4d88d6ae04afdb28d5905c7ece053 |
| institution | OA Journals |
| issn | 1471-2288 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj-art-d9b4d88d6ae04afdb28d5905c7ece0532025-08-20T02:01:35ZengBMCBMC Medical Research Methodology1471-22882025-03-0125111210.1186/s12874-025-02516-2The reporting quality and methodological quality of dynamic prediction models for cancer prognosisPeijing Yan0Zhengxing Xu1Xu Hui2Xiajing Chu3Yizhuo Chen4Chao Yang5Shixi Xu6Huijie Cui7Li Zhang8Wenqiang Zhang9Liqun Wang10Yanqiu Zou11Yan Ren12Jiaqiang Liao13Qin Zhang14Kehu Yang15Ling Zhang16Yunjie Liu17Jiayuan Li18Chunxia Yang19Yuqin Yao20Zhenmi Liu21Xia Jiang22Ben Zhang23Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Health Statistics, School of Public Health, Southwest Medical UniversityEvidence Based Social Science Research Center, School of Public Health, Lanzhou UniversityDepartment of Health Research Methods, Evidence & Impact, McMaster UniversityThe Second Clinical Medical Hospital, Lanzhou UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Preventive Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Hygienic Toxicology, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityChinese Evidence-based Medicine Center, West China Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityEvidence Based Social Science Research Center, School of Public Health, Lanzhou UniversityDepartment of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Hygienic Toxicology, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityDepartment of Epidemiology and Biostatistics, Institute of Systems Epidemiology and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan UniversityAbstract 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.https://doi.org/10.1186/s12874-025-02516-2Cancer prognosisDynamic prediction modelsReporting qualityMethodological qualityMethodological characteristics |
| spellingShingle | Peijing Yan Zhengxing Xu Xu Hui Xiajing Chu Yizhuo Chen Chao Yang Shixi Xu Huijie Cui Li Zhang Wenqiang Zhang Liqun Wang Yanqiu Zou Yan Ren Jiaqiang Liao Qin Zhang Kehu Yang Ling Zhang Yunjie Liu Jiayuan Li Chunxia Yang Yuqin Yao Zhenmi Liu Xia Jiang Ben Zhang The reporting quality and methodological quality of dynamic prediction models for cancer prognosis BMC Medical Research Methodology Cancer prognosis Dynamic prediction models Reporting quality Methodological quality Methodological characteristics |
| title | The reporting quality and methodological quality of dynamic prediction models for cancer prognosis |
| title_full | The reporting quality and methodological quality of dynamic prediction models for cancer prognosis |
| title_fullStr | The reporting quality and methodological quality of dynamic prediction models for cancer prognosis |
| title_full_unstemmed | The reporting quality and methodological quality of dynamic prediction models for cancer prognosis |
| title_short | The reporting quality and methodological quality of dynamic prediction models for cancer prognosis |
| title_sort | reporting quality and methodological quality of dynamic prediction models for cancer prognosis |
| topic | Cancer prognosis Dynamic prediction models Reporting quality Methodological quality Methodological characteristics |
| url | https://doi.org/10.1186/s12874-025-02516-2 |
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