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Time-varying SMART design and data analysis methods for evaluating adaptive intervention effects.

Tianjiao Dai1, Sanjay Shete2,3

  • 1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Dr, FCT4.6002, Houston, TX, 77030, USA.

BMC Medical Research Methodology
|September 1, 2016
PubMed
Summary
This summary is machine-generated.

A new time-varying SMART design offers a more cost-efficient adaptive intervention strategy. A joint modeling approach provides more accurate parameter estimates for analyzing time-varying SMART data.

Keywords:
Adaptive interventionsJoint modelLongitudinal modelSequential multiple assignment randomized trial (SMART)Time-varying mixed effects model (TVMEM)

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Adaptive Interventions

Background:

  • Standard two-stage SMART designs measure intermediate responses at a fixed time.
  • This can lead to increased side effects and costs.
  • A novel time-varying SMART design re-randomizes participants upon observed response, varying intervention duration.

Purpose of the Study:

  • To develop statistical models for analyzing time-varying SMART designs.
  • To compare the accuracy of a time-varying mixed effects model with a joint model.
  • To evaluate the cost-efficiency and effectiveness of the time-varying SMART design.

Main Methods:

  • Developed a time-varying mixed effects model and a joint model.
  • The joint model simultaneously analyzes intermediate/final outcomes and variable first-stage intervention durations.
  • A simulation study evaluated the statistical properties of the proposed models.

Main Results:

  • Both models accurately estimated final outcomes in SMART designs.
  • The joint modeling approach showed higher accuracy for estimating first-stage intervention coefficients and timing.
  • Simulation results supported the statistical properties of the developed models.

Conclusions:

  • The joint model is recommended for analyzing time-varying SMART designs due to superior parameter estimation and coverage probability.
  • The time-varying SMART design is cost-efficient and effective for selecting optimal adaptive interventions.
  • This approach reduces costs and side effects compared to standard SMART designs.