{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T06:35:26Z","timestamp":1774593326161,"version":"3.50.1"},"reference-count":69,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T00:00:00Z","timestamp":1772841600000},"content-version":"vor","delay-in-days":6,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Reviews in Medical Virology"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Small randomized controlled trials (RCTs) in COVID\u201019 meta\u2010analyses have been associated with more favourable treatment effects and reduced result stability. This study assessed how trial size impacts effect estimates, statistical stability, and risk of bias. Following PRISMA guidelines, we identified meta\u2010analyses of COVID\u201019 treatments included in WHO, NIH, and the LIVING Project. Trials were classified by log\u2010scale sample size, and separate pooled meta\u2010analyses were conducted for large\u2010only, small\u2010only, and combined trials. Comparative metrics included the Ratio of Odds Ratios (ROR), Kappa statistics, Fragility Index (FI), Reverse Fragility Index (RFI), and Cochrane Risk of Bias assessments. Sensitivity analyses applied alternative size thresholds (\u2265 1000 participants and median\u2010based cutoffs) and stratified results by treatment and outcome type. Across 25 meta\u2010analyses including 221 RCTs (46 large, 175 small), small trials produced more extreme estimates in 19 analyses and wider confidence intervals in 23. The pooled ROR was 0.85 (95% CI: 0.76\u20130.95;\n                    <jats:italic>P<\/jats:italic>\n                    \u00a0=\u00a00.004), decreasing to 0.81 (95% CI: 0.68\u20130.95;\n                    <jats:italic>P<\/jats:italic>\n                    \u00a0=\u00a00.011) when limited to small trials published before the first large trial. RORs remained below 1 across treatment and outcome types. Agreement between small and large trials was minimal, while large trials showed substantial agreement with overall estimates. Stability and bias profiles favoured large trials (FI: 14.0 vs. 4.0; RFI: 10.0 vs. 5.0). In conclusion, small RCTs tend to overestimate treatment effects and yield less precise, less stable results. Meta\u2010analyses should prioritise large, high\u2010quality trials and interpret small\u2010study findings with caution, particularly in rapidly evolving research contexts.\n                  <\/jats:p>","DOI":"10.1002\/rmv.70125","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T14:27:09Z","timestamp":1772980029000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Impact of Study Size on COVID\u201019 Treatment Outcomes: A Meta\u2010Epidemiological Study Comparing Large and Small Randomized Controlled Trials"],"prefix":"10.1002","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5618-1472","authenticated-orcid":false,"given":"Dong Hyun","family":"Kim","sequence":"first","affiliation":[{"name":"Yonsei University College of Medicine  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soojin","family":"Lim","sequence":"additional","affiliation":[{"name":"Yonsei University College of Medicine  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8505-1186","authenticated-orcid":false,"given":"Michael","family":"Eisenhut","sequence":"additional","affiliation":[{"name":"Luton &amp; Dunstable University Hospital Bedfordshire Hospitals NHS Foundation Trust  Luton UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Kronbichler","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine IV Nephrology and Hypertension Medical University Innsbruck  Innsbruck Austria"},{"name":"Department of Health Medicine and Caring Sciences Link\u00f6ping University  Link\u00f6ping Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3525-8805","authenticated-orcid":false,"given":"Eunyoung","family":"Kim","sequence":"additional","affiliation":[{"name":"Data Science Evidence\u2010Based and Clinical Research Laboratory Department of Health Social and Clinical Pharmacy College of Pharmacy Chung\u2010Ang University  Seoul Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min Seo","family":"Kim","sequence":"additional","affiliation":[{"name":"Cardiovascular Disease Initiative Broad Institute of MIT and Harvard  Cambridge Massachusetts USA"},{"name":"Cardiovascular Research Center Massachusetts General Hospital  Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefania I.","family":"Papatheodorou","sequence":"additional","affiliation":[{"name":"Department of Epidemiology Harvard T.H. Chan School of Public Health  Boston Massachusetts USA"},{"name":"Department of Biostatistics and Epidemiology Rutgers University  Newark New Jersey USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1117-6947","authenticated-orcid":false,"given":"Justin","family":"Stebbing","sequence":"additional","affiliation":[{"name":"School of Life Sciences Anglia Ruskin University  Cambridge UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5508-1819","authenticated-orcid":false,"given":"Yonghong","family":"Peng","sequence":"additional","affiliation":[{"name":"Faculty of Science and Engineering Anglia Ruskin University  Cambridge UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah Soyeon","family":"Oh","sequence":"additional","affiliation":[{"name":"Institute for Global Engagement &amp; Empowerment Yonsei University  Seoul 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