Exaggeration of PFS by blinded, independent, central review (BICR). (23rd November 2018) - Stone, A; Gebski, V; Davidson, R; Bloomfield, R; Bartlett, J W; Sabin, A
Abstract: Background: Recent published studies have shown meaningful discrepancies between local investigator and blinded, independent, central review (BICR) assessed median progression-free survival (PFS). When the local review but not BICR shows progression, generally, no further assessments are carried out and patients are censored in the BICR analysis, leading to violation of the statistical assumptions of independence between censoring and outcome used in survival analysis methods. Methods: We carried out a simulation study to assess methodological reasons behind these discrepancies and corroborated our findings in a case study of three BRCA -mutated ovarian cancer trials. We briefly outline possible methodological solutions that may lead to improved estimation of the BICR medians. Results: The Kaplan–Meier (KM) curve for the BICR PFS can often be exaggerated. The degree of bias is largest when there is reasonably strong correlation between BICR and local PFS, especially when PFS is long compared with assessment frequency. This can result in an exaggeration of the medians and their difference; however, the hazard ratio (HR) is much less susceptible to bias. Our simulation shows that when the true BICR median PFS was 19 months, and patients assessed every 12 weeks, the estimated KM curves were materially biased whenever the correlation between BICR and local PFS was 0.4 or greater. This was corroborated by case studies where, in the active arm, the BICR median PFS was between 6 and 11 months greater than the local median PFS. Further research is required to find improved methods for estimating BICR survival curves. Conclusions: In general, when there is a difference between local and BICR medians, the true BICR KM curve is likely to be exaggerated and its true median will probably lie somewhere between the observed local and BICR medians. Presentation of data should always include both BICR and local results whenever a BICR is carried out.