Details

Autor(en) / Beteiligte

• Rehal, Sunita
• Morris, Tim P
• Fielding, Katherine
• Carpenter, James R
• Phillips, Patrick P J

Titel

Non-inferiority trials: are they inferior? A systematic review of reporting in major medical journals

Ist Teil von

• BMJ open, 2016-10, Vol.6 (10), p.e012594-e012594

Ort / Verlag

England: BMJ Publishing Group LTD

Erscheinungsjahr

2016

Link zum Volltext

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• To assess the adequacy of reporting of non-inferiority trials alongside the consistency and utility of current recommended analyses and guidelines. Review of randomised clinical trials that used a non-inferiority design published between January 2010 and May 2015 in medical journals that had an impact factor >10 (JAMA Internal Medicine, Archives Internal Medicine, PLOS Medicine, Annals of Internal Medicine, BMJ, JAMA, Lancet and New England Journal of Medicine). Ovid (MEDLINE). We searched for non-inferiority trials and assessed the following: choice of non-inferiority margin and justification of margin; power and significance level for sample size; patient population used and how this was defined; any missing data methods used and assumptions declared and any sensitivity analyses used. A total of 168 trial publications were included. Most trials concluded non-inferiority (132; 79%). The non-inferiority margin was reported for 98% (164), but less than half reported any justification for the margin (77; 46%). While most chose two different analyses (91; 54%) the most common being intention-to-treat (ITT) or modified ITT and per-protocol, a large number of articles only chose to conduct and report one analysis (65; 39%), most commonly the ITT analysis. There was lack of clarity or inconsistency between the type I error rate and corresponding CIs for 73 (43%) articles. Missing data were rarely considered with (99; 59%) not declaring whether imputation techniques were used. Reporting and conduct of non-inferiority trials is inconsistent and does not follow the recommendations in available statistical guidelines, which are not wholly consistent themselves. Authors should clearly describe the methods used and provide clear descriptions of and justifications for their design and primary analysis. Failure to do this risks misleading conclusions being drawn, with consequent effects on clinical practice.