Citation

Del Junco DJ, Fox EE, Camp EA, Rahbar MH, Holcomb JB. J. Trauma Acute Care Surg. 2013; 75(1 Suppl 1): S97-S103.

Affiliation

From the Biostatistics/Epidemiology/Research Design Core (D.J.d.J., E.E.F., M.H.R.); Center for Translational Injury Research (D.J.d.J., E.E.F., E.A.C., J.B.H.), Division of Acute Care Surgery, Department of Surgery, Medical School; and Division of Epidemiology, Human Genetics and Environmental Sciences (M.H.R.), School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas.

Copyright

(Copyright © 2013, Lippincott Williams and Wilkins)

DOI

10.1097/TA.0b013e318298b0a4

PMID

23778519

Abstract

BACKGROUND: Because randomized clinical trials in trauma outcomes research are expensive and complex, they have rarely been the basis for the clinical care of trauma patients. Most published findings are derived from retrospective and occasionally prospective observational studies that may be particularly susceptible to bias. The sources of bias include some common to other clinical domains, such as heterogeneous patient populations with competing and interdependent short- and long-term outcomes. Other sources of bias are unique to trauma, such as rapidly changing multisystem responses to injury that necessitate highly dynamic treatment regimens such as blood product transfusion. The standard research design and analysis strategies applied in published observational studies are often inadequate to address these biases. METHODS: Drawing on recent experience in the design, data collection, monitoring, and analysis of the 10-site observational PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study, 7 common and sometimes overlapping biases are described through examples and resolution strategies. RESULTS: Sources of bias in trauma research include ignoring (1) variation in patients' indications for treatment (indication bias), (2) the dependency of intervention delivery on patient survival (survival bias), (3) time-varying treatment, (4) time-dependent confounding, (5) nonuniform intervention effects over time, (6) nonrandom missing data mechanisms, and (7) imperfectly defined variables. This list is not exhaustive. CONCLUSION: The mitigation strategies to overcome these threats to validity require epidemiologic and statistical vigilance. Minimizing the highlighted types of bias in trauma research will facilitate clinical translation of more accurate and reproducible findings and improve the evidence-base that clinicians apply in their care of injured patients.

Language: en