Statistical grand rounds: Importance of appropriately modeling procedure and duration in logistic regression studies of perioperative morbidity and mortality.

Abstract

Multiple logistic regression studies frequently are performed with duration (e.g., operative time) included as an independent variable. We use narrative review of the statistical literature to highlight that when the association between duration and outcome is presumptively significant, the procedure itself (e.g., video-assisted thoracoscopic lobectomy or thoracotomy lobectomy) needs to be tested for inclusion in the logistic regression. If the procedure is a true covariate but excluded in lieu of category of procedure (e.g., lung resection), estimates of the odds ratios for other independent variables are biased. In addition, actual durations are sometimes used as the independent variable, rather than scheduled (forecasted) durations. Only the scheduled duration is known when a patient would be randomized in a trial of preoperative or intraoperative intervention and/or meets with the surgeon and anesthesiologist preoperatively. By reviewing the literature about logistic regression and about predicting case duration, we show that the use of actual instead of scheduled duration can result in biased logistic regression results.