Recombinant human activated protein C for the treatment of severe sepsis and septic shock: A study protocol for incorporating observational evidence using a Bayesian approach

Abstract

Introduction: Activated protein C (aPC) plays a pivotal role in modulating a severe inflammatory response and is thought to be beneficial for patients with sepsis. However, several meta-analyses of randomised controlled trials (RCTs) show that aPC is not significantly associated with improved survival in critically ill patients with sepsis. One suggestion is that these analyses simply ignored observational evidence. The present study aims to quantitatively demonstrate how observational data can alter the findings derived from synthesised evidence from RCTs by using a Bayesian approach. Methods and analysis: RCTs and observational studies investigating the effect of aPC on mortality outcome in critically ill patients with sepsis will be included. The quality of included RCTs will be assessed by using the Delphi list. Publication bias will be quantitatively analysed by using the traditional Egger regression test and the Begg rank correlation test. Observational data will be used as the informative prior for the distribution of OR. A power transformation of the observational data likelihood will be considered. Observational evidence will be down-weighted by a power of α which takes values from 0 to 1. Trial sequential analysis will be performed to quantify the reliability of data in meta-analysis adjusting significance levels for sparse data and multiple testing on accumulating trials. Trial registration number: PROSPERO (CRD42014009562).