A "placement of death" approach for studies of treatment effects on ICU length of stay

作者：Lin Winston^*; Halpern Scott D; Kerlin Meeta Prasad; Small Dylan S

来源：Statistical Methods in Medical Research, 2017, 26(1): 292-311.

DOI：10.1177/0962280214545121

• length of stay
• intensive care unit
• censoring by death
• quantile treatment effects
• bootstrap confidence intervals
• rank tests
• Wilcoxon rank sum test
• Mann-Whitney U-test
• Brunner-Munzel test
• nonparametric Behrens-Fisher problem

Length of stay in the intensive care unit (ICU) is a common outcome measure in randomized trials of ICU interventions. Because many patients die in the ICU, it is difficult to disentangle treatment effects on length of stay from effects on mortality; conventional analyses depend on assumptions that are often unstated and hard to interpret or check. We adapt a proposal from Rosenbaum that addresses concerns about selection bias and makes its assumptions explicit. A composite outcome is constructed that equals ICU length of stay if the patient was discharged alive and indicates death otherwise. Given any preference ordering that compares death with possible lengths of stay, we can estimate the intervention's effects on the composite outcome distribution. Sensitivity analyses can show results for different preference orderings. We discuss methods for constructing approximate confidence intervals for treatment effects on quantiles of the outcome distribution or on proportions of patients with outcomes preferable to various cutoffs. Strengths and weaknesses of possible primary significance tests (including the Wilcoxon-Mann-Whitney rank sum test and a heteroskedasticity-robust variant due to Brunner and Munzel) are reviewed. An illustrative example reanalyzes a randomized trial of an ICU staffing intervention.

• 出版日期2017-2