Kevin J. Anstrom | Searcharxiv

arXiv2026

A Review of Methods and Practices for Missing Data in Sequential Multiple Assignment Randomized Trials (SMARTs): An Ancillary Study of a Scoping Review

Background: Missing data poses an acute threat to sequential multiple assignment randomized trial (SMART) analyses because of the sequential treatment structure and response-dependent re-randomization. Objectives: This study aimed to (1) review the current statistical methods for handling missing data in SMARTs, and (2) characterize how missing data is reported and handled in published SMARTs. Methods: We conducted a narrative review of statistical methods developed for missing data in SMARTs. Additionally, we conducted a pre-specified secondary extraction of a previously published scoping review of SMARTs focused on missing data. Extraction captured attrition rates, methods for handling missingness, and planned versus performed missing data analyses. Results: Seven methodological papers were identified; nearly all assume missing at random (MAR), and only one addresses the full set of SMART-specific missingness types. Across 30 published SMARTs, median overall attrition was 18.1% (range 0.6%-56.5%). Methods used to address missing data were described in 80% of the manuscripts; mixed-model methods were most common (30%). Among 14 studies with paired protocols, sensitivity analyses were pre-specified in 2 (14%). Conclusions: SMART-specific methodology for missing data is limited, and a substantial gap exists between available methodology and current SMART practice.

stat.ME↗

arXiv2025

Statistical Design and Rationale of the Biomarkers for Evaluating Spine Treatments (BEST) Trial

Chronic low back pain (cLBP) is a prevalent condition with profound impacts on functioning and quality of life. While multiple evidence-based treatments exist, they all have modest average treatment effects$\unicode{x2013}$potentially due to individual variation in treatment response and the diverse etiologies of cLBP. This multi-site sequential, multiple-assignment randomized trial (SMART) investigated four treatment modalities with two stages of randomization and aimed to enroll 630 protocol completers. The primary objective was to develop a precision medicine approach by estimating optimal treatment or treatment combinations based on patient characteristics and initial treatment response. The analysis strategy focuses on estimating interpretable dynamic treatment regimes and identifying subgroups most responsive to specific interventions. Broad eligibility criteria were implemented to enhance generalizability and recruitment, most notably that participants could be eligible to enroll even if they could not be assigned to one (but no more) of the study interventions. Enrolling participants with restrictions on the treatment they could be assigned necessitated modifications to standard minimization methods for balancing covariates. The BEST trial represents one of the largest SMARTs focused on clinical decision-making to date and the largest in cLBP. By collecting an extensive array of biomarker and phenotypic measures, this trial may identify potential treatment mechanisms and establish a more evidence-based approach to individualizing cLBP treatment in clinical practice.

stat.AP↗