Fragility index of trials supporting approval of anti-cancer drugs in common solid tumors.

Abstract

2055 Background: The Fragility Index (FI) quantifies the reliability of positive trials by estimating the number of events which would change statistically significant results to non-significant results. Here, we calculate the FI of trials supporting approval of drugs for common solid tumors. Methods: We searched Drugs@FDA to identify randomized trials (RCT) supporting drug approvals by the US Food and Drug Administration between January 2009 and December 2019 in lung, breast, prostate, gastric and colon cancers. We adapted the FI framework (Walsh et al. J Clin Epidemiol 2014) to allow use of time to event data. First, we reconstructed survival tables from reported data using the Parmar Toolkit (Parmar et al. Stat Med 1998) and then calculated the number of events which would result in a non-significant effect for the primary endpoint of each trial. The FI was then compared quantitatively to the number of patients in each trial who withdrew consent or were lost to follow-up. Multivariable linear regression was used to explore association between RCT characteristics and the FI. Results: We identified 69 RCT with a median of 669 patients (range 123-4804) and 358 primary outcome events (range 56-884). The median FI was 26 (range 1-322). The FI was ≤10 in 21 trials (30%) and ≤20 in 31 trials (45%). Among the 69 RCT, the median number of patients who withdrew consent or were lost to follow up was 27 (range, 6-317). The number of patients who withdrew consent or were lost to follow-up was equal or greater than the FI in 42 trials (61%). There was statistically significant inverse association between FI and trial hazard ratio (p0,001) and a positive association with number of patients who were lost to follow-up or withdrew consent (p0,001). There was no association between trial sample size, year of approval or reported p-value and the FI. Conclusions: Statistical significance of trials supporting drug approval in common solid tumors relies often on a small number of events. In most trials the FI was lower than the number of patients lost to follow up or withdrawing consent. Post-approval randomized trials or real-world data analyses should be performed to ensure that effects observed in registration trials are robust.