Effect of different statistical methods on union or time to union in a published study about clavicular fractures

Abstract

Background: Time to union is a suspect measure for comparing treatments given the absence of a consensus definition of union, the limited reliability of diagnostic tests, and inconsistency in evaluation times. The purpose of this study was to quantify the variations in union and time to union according to different statistical methods and different approaches to missing data.

Materials and methods: Data from a published multicenter, randomized trial comparing operative and nonoperative treatment of clavicular fractures were reanalyzed. Two main types of missing data were encountered: (1) lost to follow-up or died before union and (2) missed appointment. We studied the effect of four statistical methods-comparison of means, comparison of medians, χ(2), and Kaplan-Meier curves-for comparing union or time to union between cohorts for the following scenarios: strict intention-to-treat, intention-to-treat with exclusion of patients with less than 12 months of follow-up, as-treated analysis, and four different imputation methods for missing data.

Results: Mean and median time to union varied up to 17%, but comparative statistics consistently demonstrated shorter time to union among operatively treated patients. There were significant differences in the odds ratio, χ(2) values, and the number needed to treat (8%-62%) of union vs nonunion for the three principal analyses.

Conclusion: Different strategies for handling missed evaluations seem to influence categoric results (eg, union or nonunion) more than continuous measures such as time to union.