Clinical prediction models typically utilize a combination of multiple variables to predict individual health outcomes. However, multiple prediction models for the same outcome often exist, making it challenging to determine the suitable model for guiding clinical practice. In recent years, an increasing number of studies have evaluated and summarized prediction models using the systematic review/meta-analysis method. However, they often report poorly on critical information. To enhance the reporting quality of systematic reviews/meta-analyses of prediction models, foreign scholars published the TRIPOD-SRMA reporting guideline in BMJ in March 2023. As the number of such systematic reviews/meta-analyses is increasing rapidly domestically, this paper interprets the reporting guideline with a published example. This study aims to assist domestic scholars in better understanding and applying this reporting guideline, ultimately improving the overall quality of relevant research.
Clarifying the burden of disease is of great significance for determining the focus of healthcare and optimizing the allocation of medical resources. However, differences in research methods and assumptions often affect the comparability of different research results, thus leading to difficulties in healthcare decision-making. Disability-adjusted life year (DALY) is the most commonly used indicator to measure the burden of disease, but the reporting quality of disease burden studies using the DALY metric is uneven. To standardize the reporting of such studies, international scholars developed and recently published the STROBOD statement in Population Health Metrics. Its checklist includes seven parts: title, abstract, introduction, methods, results, discussion, and open science, involving a total of 28 items. To assist domestic scholars in better understanding and applying this reporting standard, this article interprets each item with published examples, aiming to improve the overall quality of disease burden research and provide high-quality evidence references for public health decision-making.