Abstract

The Flexible Lifestyles Empowering Change (FLEX) trial, an 18-month randomized clinical trial testing an adaptive behavioral intervention in adolescents with type 1 diabetes, showed no overall treatment effect for its primary outcome, change in hemoglobin A1c (HbA1c) percentage of total hemoglobin, but demonstrated benefit for quality of life (QoL) as a prespecified secondary outcome. To apply a novel statistical method for post hoc analysis that derives an individualized treatment rule (ITR) to identify FLEX participants who may benefit from intervention based on changes in HbA1c percentage (primary outcome), QoL, and body mass index z score (BMIz) (secondary outcomes) during 18 months. This multisite clinical trial enrolled 258 adolescents aged 13 to 16 years with type 1 diabetes for 1 or more years, who had literacy in English, HbA1c percentage of total hemoglobin from 8.0% to 13.0%, a participating caregiver, and no other serious medical conditions. From January 5, 2014, to April 4, 2016, 258 adolescents were recruited. The post hoc analysis excluded adolescents missing outcome measures at 18 months (2 participants [0.8%]) or continuous glucose monitoring data at baseline (40 participants [15.5%]). Data were analyzed from April to December 2018. The FLEX intervention included a behavioral counseling strategy that integrated motivational interviewing and problem-solving skills training to increase adherence to diabetes self-management. The control condition entailed usual diabetes care. Subgroups of FLEX participants were derived from an ITR estimating which participants would benefit from intervention, which would benefit from control conditions, and which would be indifferent. Multiple imputation by chained equations and reinforcement learning trees were used to estimate the ITR. Subgroups based on ITR pertaining to changes during 18 months in 3 univariate outcomes (ie, HbA1c percentage, QoL, and BMIz) and a composite outcome were compared by baseline demographic, clinical, and psychosocial characteristics. Data from 216 adolescents in the FLEX trial were reanalyzed (166 [76.9%] non-Hispanic white; 108 teenaged girls [50.0%]; mean [SD] age, 14.9 [1.1] years; mean [SD] diabetes duration, 6.3 [3.7] years). For the univariate outcomes, a large proportion of FLEX participants had equivalent predicted outcomes under intervention vs usual care settings, regardless of randomization, and were assigned to the muted group (HbA1c: 105 participants [48.6%]; QoL: 63 participants [29.2%]; BMIz: 136 participants [63.0%]). Regarding the BMIz univariate outcome, mean baseline BMIz of participants assigned to the muted group was lower than that of those assigned to the intervention and control groups (muted vs intervention: mean difference, 0.48; 95% CI, 0.21 to 0.75; P = .002; muted vs control: mean difference, 0.86; 95% CI, 0.61 to 1.11; P < .001); this group also had a higher proportion of individuals with underweight or normal weight using weight status cutoffs (95 [69.9%] in muted group vs 24 [54.6%] in intervention group and 11 [30.6%] in control group; χ24 = 24.67; P < .001). The approach identified subgroups estimated to benefit based on HbA1c percentage (54 participants [25.0%]), QoL (89 participants [41.2%]), and BMIz (44 participants [20.4%]). Regarding the HbA1c percentage outcome, participants expected to benefit from the intervention did not have significantly higher baseline HbA1c percentages than those expected to benefit from usual care (9.4% vs 9.2%; difference, 0.2%; 95% CI, -0.16% to 0.56%; P = .44). However, participants in the muted group had higher mean HbA1c percentages at baseline than those assigned to the intervention or control groups (muted vs intervention: 9.9% vs 9.4%; difference, 0.5%; 95% CI, 0.13% to 0.89%; P = .02; muted vs control; 9.9% vs 9.2%; difference, 0.7%; 95% CI, 0.34% to 1.08%; P = .001). No significant differences were found between subgroups estimated to benefit in terms of the composite outcome from the FLEX intervention (91 participants [42.1%]) vs usual care (125 participants [57.9%]). The precision medicine approach represents a conceptually and analytically novel approach to post hoc subgroup identification. More work is needed to understand markers of positive response to the FLEX intervention. ClinicalTrial.gov identifier: NCT01286350.

Highlights

  • The Flexible Lifestyles Empowering Change (FLEX) trial, a National Institutes of Health–funded 18-month randomized clinical trial, tested the efficacy of an adaptive behavioral intervention to promote self-management and improve measures of blood glucose control in 258 adolescents aged 13 to 16 years with type 1 diabetes

  • We describe a method for the post hoc analysis of randomized clinical trials that leverages the full data set to identify subgroups defined by an estimated optimal individualized treatment rule (ITR)

  • Study Sample We analyzed data from the baseline visit of the FLEX trial. This randomized clinical trial tested an adaptive, 18-month intervention that included interventions to improve behavioral skills and problem solving for adolescents with type 1 diabetes, with respect to hemoglobin A1c (HbA1c) percentage of total hemoglobin, glycemic variability, cardiovascular disease risk factors, healthrelated quality of life (QOL), and cost-effectiveness.[1,9]

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Summary

Introduction

The Flexible Lifestyles Empowering Change (FLEX) trial, a National Institutes of Health–funded 18-month randomized clinical trial, tested the efficacy of an adaptive behavioral intervention to promote self-management and improve measures of blood glucose control in 258 adolescents aged 13 to 16 years with type 1 diabetes. The goal of the FLEX intervention was to increase adherence to type 1 diabetes self-management through a behavioral counseling strategy that integrated motivational interviewing and problem-solving skills training.[1] Despite high retention and fidelity, the FLEX study did not show efficacy with respect to the primary outcome of hemoglobin A1c (HbA1c) percentage 18 months after randomization.[1] the intervention was associated with improvements in several secondary psychosocial outcomes, including motivation, problem-solving skills, diabetes self-management, and health-related and general quality of life (QoL).[1]. In the setting of significant heterogeneity in response, aggregate reporting of average treatment can obfuscate whether some strategies helped some participants while harming others.[3,4] For this reason, statistical analyses that estimate aggregate effects over time for all participants are limited because they do not account for the fact that treatment responders and nonresponders can exhibit vastly divergent patterns of response.[5]

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