Generating real-world evidence compatible with evidence from randomized controlled trials: a novel observational study design applicable to surgical transfusion research

Abstract

Abstract Background Numerous observational studies have revealed an increased risk of death and complications with transfusion, but this observation has not been confirmed in randomized controlled trials (RCTs). The “transfusion kills patients” paradox persists in real-world observational studies despite application of analytic methods such as propensity-score matching. We propose a new design to address this long-term existing issue, which if left unresolved, will be deleterious to the healthy generation of evidence that supports optimized transfusion practice. Methods In the new design, we stress three aspects for reconciling observational studies and RCTs on transfusion safety: (1) re-definition of the study population according to a stable hemoglobin range (gray zone of transfusion decision; 7.5–9.5 g/dL in this study); (2) selection of comparison groups according to a trigger value (last hemoglobin measurement before transfusion; nadir during hospital stay for control); (3) dealing with patient heterogeneity according to standardized mean difference (SMD) values. We applied the new design to hospitalized older patients (aged ≥60 years) undergoing general surgery at four academic/teaching hospitals. Four datasets were analyzed: a base population before (Base Match−) and after (Base Match+) propensity-score matching to simulate previous observational studies; a study population before (Study Match−) and after (Study Match+) propensity-score matching to demonstrate effects of our design. Results Of 6141 older patients, 662 (10.78%) were transfused and showed high heterogeneity compared with those not receiving transfusion, particularly regarding preoperative hemoglobin (mean: 11.0 vs. 13.5 g/dL) and intraoperative bleeding (≥500 mL: 37.9% vs. 2.1%). Patient heterogeneity was reduced with the new design; SMD of the two variables was reduced from approximately 100% (Base Match−) to 0% (Study Match+). Transfusion was related to a higher risk of death and complications in Base Match− (odds ratio [OR], 95% confidence interval [CI]: 2.68, 1.86–3.86) and Base Match+ (2.24, 1.43–3.49), but not in Study Match− (0.77, 0.32–1.86) or Study Match+ (0.66, 0.23–1.89). Conclusions We show how choice of study population and analysis could affect real-world study findings. Our results following the new design are in accordance with relevant RCTs, highlighting its value in accelerating the pace of transfusion evidence generation and generalization.