What Are the Tradeoffs in Outcomes after Casting Versus Surgery for Closed Extraarticular Distal Radius Fractures in Older Patients? A Statistical Learning Model

Distal radius fractures (DRFs) are one of the most common major fractures. Despite their frequency, the tradeoffs in different outcomes after casting or surgery for closed extraarticular DRFs in older adults are unknown. (1) For adults older than 60 years with closed extraarticular DRFs, what are the tradeoffs in outcomes for choosing casting versus surgery? (2) In what settings would surgery be preferred over casting? This is a secondary analysis of data from the Wrist and Radius Injury Surgical Trial (WRIST), a randomized, multicenter clinical trial that enrolled patients from April 10, 2012 to December 31, 2016. For WRIST, researchers recruited patients older than 60 years who sustained closed extraarticular distal radius fractures from 24 sites in the United States, Canada, and Singapore. We conducted a secondary analysis using data from WRIST, which had longitudinal data from a robust collection of covariates for patients who underwent surgery and casting. Among the 296 patients recruited in the WRIST study, 59% (174) of patients (mean age 71 ± 9 years) with complete sociodemographic data and 12-month follow-up for each primary outcome were included in the main analysis. More patients underwent surgery than casting (72% [126 of 174] versus 28% [48 of 174]). Most sociodemographic variables were similar between the surgery and casting groups, except for age and volar tilt. The surgical cohort was composed of patients randomized to external fixation, closed reduction percutaneous pinning, or volar locking plate internal fixation. The casting cohort consisted of patients who elected to be treated with closed reduction and casting. A tree-based reinforcement statistical learning method was used to determine the best treatment, either surgery or casting, to maximize functional and esthetic outcomes while minimizing pain. Tree-based reinforcement learning is a statistical learning method to build an unsupervised decision tree within a causal inference framework that will identify useful variables and their cutoff values to tailor treatment assignment accordingly to achieve the best health outcome desired. The primary outcome was minimization of pain (12-month Michigan Hand Outcomes Questionnaire pain subdomain score), maximization of grip strength, total ROM (supination and wrist arc of motion), and esthetics (12-month Michigan Hand Outcomes Questionnaire esthetics subdomain score). Casting was the best treatment to reduce pain and maximize esthetics, wherea