Journal of Clinical Epidemiology最新文献

Objectives

To demonstrate how researchers can identify and translate reporting gaps from a systematic review into checklist items for reporting guidelines.

Study Design and Setting

Good quality research reporting ensures transparency, reproducibility, and utility, facilitated by reporting guidelines. Conducting a systematic review is an essential step in the development of these guidelines. The Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network's toolkit (2010) assists researchers in this process and is due for an update to address current gaps and evolving research methods. One significant gap is the translation of systematic review findings into checklist items. Reflecting on our experience developing the ACcurate Consensus Reporting Document, we illustrate this translation process aiming to empower researchers developing reporting guidelines to address potential biases and promote transparency. We highlight the challenges faced and how they were addressed.

Results

The systematic review search process was iterative, involving multiple adjustments to balance precision and sensitivity. Excessively stringent exclusion criteria may lead to missed valuable insights, especially when studies offer relevant content. An information specialist was invaluable in developing the search strategy. Key lessons learned include the necessity of maintaining flexibility and openness during data extraction, continuous adaptation based on panelist feedback, and promoting clear communication through understandable language. These principles can guide the development of future reporting guidelines and the updating of the EQUATOR toolkit, promoting transparency and robustness in research reporting.

Conclusion

Maintaining flexibility, capturing evolving insights, clear communication, and accommodating changes in research and technologies are key to translating systematic review findings into effective reporting checklists.

Meta-analysis is a statistical method for combining quantitative results across studies. A fundamental decision in undertaking a meta-analysis is choosing an appropriate model for analysis. This is the second of two companion articles which have the joint aim of describing the different meta-analysis models. In the first article, we focused on the common-effect (also known as fixed-effect [singular]) model, and in this article, we focus on the random-effects model. We describe the key assumptions underlying the random-effects model, how it is related to the common-effect and fixed-effects [plural] models, and present some of the arguments for selecting one model over another. We outline some of the methods for fitting a random-effects model. Finally, we present an illustrative example to demonstrate how the results can differ depending on the chosen model and method. Understanding the assumptions of the different meta-analysis models, and the questions they address, is critical for meta-analysis model selection and interpretation.

Background and Objective

Grading of Recommendations, Assessment, Development, and Evaluation (GRADE)-ADOLOPMENT is widely applied to efficiently use existing credible guidelines and contextualize them to a target setting. To highlight the experiences of a Latin American Guideline Development Group (GDG) applying GRADE-ADOLOPMENT to adapt the American Society of Hematology's clinical practice guideline on managing venous thromboembolisms (VTEs) in Latin America.

Study Design and Setting

We employed a mixed-method postevaluation using self-administered surveys and semistructured interviews. We assessed the Latin American GDG (1) general satisfaction and confidence using the approach, (2) their ratings on the usefulness, appropriateness, and importance of GRADE-ADOLOPMENT and its tools to inform their judgements, and (3) any additional facilitators and barriers to refine the process.

Results

Eleven of the 14 GDG members, including nine panelists and two methodologists, provided survey responses and eight participated in the interview. Respondents felt “mostly” or “completely” satisfied with the adapted guideline. Eight panelists who were surveyed agree that GRADE-ADOLOPMENT is useful in countries with limited resources. Although panelists expressed initial apprehensions in their understanding of the process, they demonstrated enhanced confidence in their capacity to apply GRADE after completing workshop training and by acquiring experience. Panelists reiterated the importance of considering evidence-to-decision (EtD) criteria (ie, resources, feasibility, and cost-effectiveness) when adapting recommendations. The GDG encountered challenges with collecting local and regional data, prioritizing recommendations while considering intraregional diversity, and the lengthy publication period, although the latter stemmed from procedures not related to GRADE-ADOLOPMENT.

Conclusions

GRADE-ADOLOPMENT is an important tool to facilitate the adaptation and uptake of clinical practice guidelines in novel settings. The GDG felt satisfied with their overall experience using the GRADE-ADOLOPMENT approach. However, their experience could have been optimized if they had access to robust regional evidence, more recommendations to adapt from, and worked with more efficient guideline production timelines.