The Reverse Fragility Index for Mortality End Points in Randomized Trials Comparing Uncemented and Cemented Hemiarthroplasty for Intracapsular Hip Fractures

Abstract

BackgroundInterpreting clinical relevance of randomized clinical trials (RCTs) is challenging when P-values are marginally above or below the P = .05 threshold. This study examined the robustness of statistically insignificant mortality events from RCTs comparing hemiarthroplasty femoral fixation for displaced intracapsular hip fractures through the reverse fragility index (RFI). MethodsRCTs were identified using Pubmed, OVID/Medline, and Cochrane databases. Mortality endpoints were stratified into 3 categories: (1) within 30-days, (2) within 90-days, and (3) at latest follow-up. The RFI was derived by manipulating reported mortality events utilizing a contingency table while maintaining a constant number of participants. The reverse fragility quotient (RFQ) was quantified by dividing the RFI by the study sample. ResultsEight RCTs (2,494 participants) were included. The median RFI and RFQ within 30-days was 3.0 (interquartile range [IQR]: 3.0 to 6.0) and 0.016 (IQR: 0.015 to 0.021), suggesting nonsignificant findings were contingent on 1.6 mortality events/100 participants. The median RFI and RFQ within 90-days was 6.0 (IQR: 4.0 to 7.0) and 0.028 (IQR: 0.024 to 0.038), suggesting nonsignificant findings were contingent on 2.8 mortality events/100 participants. At latest follow-up, the median RFI and RFQ was 7.0 (IQR: 6.0 to 12.0) and 0.038 (IQR: 0.029 to 0.054), suggesting nonsignificant findings were contingent on only 3.8 mortality events/100 participants. Median loss to follow-up was 16.0 (IQR: 11.0 to 58.0; 228% greater than RFI), and exceeded the RFI in 6/7(85.7%) studies. ConclusionsA small number of events (median of 7) was required to convert a statistically nonsignificant finding to one that is significant for the endpoint of mortality. The median loss to follow-up exceeded the median RFI by greater than 200%, suggesting methodological limitations such as patient allocation could alter conclusions.