[Development of criteria for the prospective assessment of the need for updating guideline recommendations: The AGIL criteria]. / Entwicklung von Kriterien für die prospektive Einschätzung des Aktualisierungsbedarfs von Leitlinienempfehlungen: AGIL-Kriterien.

BACKGROUND: Evidence-based guideline and vaccination recommendations should continuously be updated to appropriately support health care decisions. However, resources for updating guidelines are often limited. The aim of this project was to develop a list of criteria for the prospective assessment of the need for updating individual guideline or vaccination recommendations, which can be applied from the time a guideline or guideline update is finalised. METHODS: In this article we describe the development of the AGIL criteria (Assessment of Guidelines for Updating Recommendations). The AGIL criteria were developed by experienced scientists and experts in the field of guideline development in a multi-step process. The five steps included: 1) development of an initial list of criteria by the project team; 2) online survey of guideline experts on the initial version of the criteria list; 3) revision of the criteria list based on the results of the online survey; 4) workshop on the criteria list at the EbM Congress 2023; 5) creation of version 1.0 of the AGIL criteria based on the workshop results. RESULTS: The initial list included the following three criteria: 1) relevance of the question 2) availability of new relevant evidence, and 3) impact of potentially new evidence. The response rate of the online survey for fully completed questionnaires was 31.0% (N=195; 630 guideline experts were contacted by email). For 90.3% (n=176) of the respondents, the criteria list included all essential aspects for assessing the need for updating guideline recommendations. More than three quarters of respondents rated the importance of the three criteria as "very important" or "important" (criteria 1-3: 75.3%, 86.1%, 85.2%) and - with the exception of criterion 1 - comprehensibility as "very comprehensible" or "comprehensible" (criteria 1-3: 58.4%, 75.9%, 78.5%). The results of the online survey and the workshop generally confirmed the three criteria with their two sub-questions. The incorporation of all feedback resulted in the AGIL criteria (version 1.0), recapping: 1) relevance of the question regarding a) PICO components and b) other factors, e.g. epidemiological aspects; 2) availability of new evidence a) on health-related benefits and harms and b) on other decision factors, e.g. feasibility, acceptability; 3) impact of new evidence a) on the certainty of evidence on which the recommendation is based and b) on the present recommendation, e.g. DISCUSSION: The moderate response rate of the online survey may have limited its representativeness. Nevertheless, we consider the response rate to be satisfactory in this research context. The inclusion of many experts in the online survey and the EbM Congress workshop is a strength of the project and supports the quality of the results. CONCLUSIONS: The AGIL criteria provide a structured guidance for the prospective assessment of the need for updating individual guideline recommendations and other evidence-based recommendations. The implementation and evaluation of the AGIL criteria 1.0 in a field test is planned.

Clinical and methodological implications for research elements in systematic reviews on COVID-19 treatment were often unstructured and under-reported: a metaresearch study.

OBJECTIVES: Numerous systematic reviews (SRs) have been published in the first months of the COVID-19 pandemic and clinical trials were designed rapidly highlighting the importance of informative implications for research (IfRs) sections in SRs. IfR is one item of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 checklist and the Cochrane Handbook suggests considering population, intervention, control, outcome (PICO) and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) domains when developing IfR. We aimed (1) to assess whether SRs on COVID-19 treatments included any IfR statements and, for SRs with an IfR statement, (2) to examine which elements informed the IfR statement. STUDY DESIGN AND SETTING: We conducted a metaresearch study based on SRs on COVID-19 treatment identified in the Living OVerview of the Evidence COVID-19 database in May 2021 as part of another research project (CRD42021240423). We defined an IfR statement as at least one sentence that contained at least one bit of information that could be informative for planning future research. We extracted any IfR statements anywhere in the SRs on predefined IfR variables, in particular PICO elements, study design, and concepts underlying GRADE domains. Three authors extracted data independently after piloting the data extraction form. We resolved discrepancies in weekly discussions to ensure a high-quality data extraction. RESULTS: We included 326 SRs, of which 284 SRs (87.1%) stated IfR. Of these 284 SRs, 201 (70.8%) reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses and 66 (23.2%) using GRADE. IfR statements (n = 284) addressing PICO were unstructured and commonly reported 'population' (n = 195, 68.7%), 'intervention' (n = 242, 85.2%), and 'outcome' (n = 127, 44.7%) but not 'control' (n = 29, 10.2%). Concepts underlying GRADE domains were infrequently reported in IfR statements of SRs (n = 284): 'risk of bias' (n = 14, 4.9%), 'imprecision' (n = 8, 2.8%), 'inconsistency' (n = 7, 2.5%), 'publication bias' (n = 3, 1.1%), and 'indirectness' (n = 1, 0.4%). Additional IfR elements mentioned in IfR were 'better reporting' of future studies (n = 17, 6.0%) and 'standardization of procedures in clinical trials' (n = 12, 4.2%). CONCLUSION: Almost 90% of SRs on COVID-19 treatments reported IfR. IfR statements addressing PICO were unstructured across SRs and concepts underlying GRADE were rarely reported to inform IfR. Further work is needed to assess generalizability beyond COVID-19 and to define more precisely which IfR elements should be considered, and how they should be reported in SRs of interventions. Until then, considering PICO elements and concepts underlying GRADE to derive IfR seems to be a sensible starting point.