ArticleStatistics in medicine2016
Design of sequentially randomized trials for testing adaptive treatment strategies.
Article in Statistics in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05814640 (Sequenced Treatment Alternatives to Relieve Adolescent Depression), which is not on this map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Sequenced Treatment Alternatives to Relieve Adolescent Depression (STAR-AD): a Pragmatic Clinical Trial
Who cites it
14 citing papers in PubMed.
- A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders.BMC psychiatry · 2021Trial
- Comparing adaptive treatment strategies in two-stage randomized trials with grouped survival data.Lifetime data analysis · 2026Article
- Within-trial data borrowing for sequential multiple assignment randomized trials.Biostatistics (Oxford, England) · 2025Article
- Sequenced treatment alternatives to relieve adolescent depression (STAR-AD): a multicentre open-label randomized controlled trial protocol.BMC psychiatry · 2023Article
- The Sequential Multiple Assignment Randomized Trial for Controlling Infectious Diseases: A Review of Recent Developments.American journal of public health · 2023Review
- Comparing Adaptive Interventions under a General Sequential Multiple Assignment Randomized Trial Design via Multiple Comparisons with the Best.Journal of statistical planning and inference · 2021Article
- SMARTAR: an R package for designing and analyzing Sequential Multiple Assignment Randomized Trials.PeerJ · 2021Article
- Sample size considerations for comparing dynamic treatment regimens in a sequential multiple-assignment randomized trial with a continuous longitudinal outcome.Statistical methods in medical research · 2020Review
- Power analysis in a SMART design: sample size estimation for determining the best embedded dynamic treatment regime.Biostatistics (Oxford, England) · 2020Article
- A gate-keeping test for selecting adaptive interventions under general designs of sequential multiple assignment randomized trials.Contemporary clinical trials · 2019Article
- Article
- Design and Analysis Considerations for Comparing Dynamic Treatment Regimens with Binary Outcomes from Sequential Multiple Assignment Randomized Trials.Journal of applied statistics · 2018Article
- Multilevel Interventions Targeting Obesity: Research Recommendations for Vulnerable Populations.American journal of preventive medicine · 2017Article
- Clinical Perspectives on Targeting Therapies for Personalized Medicine.Advances in protein chemistry and structural biology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
An adaptive treatment strategy (ATS) is an outcome-guided algorithm that allows personalized treatment of complex diseases based on patients' disease status and treatment history. Conditions such as AIDS, depression, and cancer usually require several stages of treatment because of the chronic, multifactorial nature of illness progression and management. Sequential multiple assignment randomized (SMAR) designs permit simultaneous inference about multiple ATSs, where patients are sequentially randomized to treatments at different stages depending upon response status. The purpose of the article is to develop a sample size formula to ensure adequate power for comparing two or more ATSs. Based on a Wald-type statistic for comparing multiple ATSs with a continuous endpoint, we develop a sample size formula and test it through simulation studies. We show via simulation that the proposed sample size formula maintains the nominal power. The proposed sample size formula is not applicable to designs with time-to-event endpoints but the formula will be useful for practitioners while designing SMAR trials to compare adaptive treatment strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.