Abstract
Rationale & ObjectiveAdaptive design methods are intended to improve the efficiency of clinical trials and are relevant to evaluating interventions in dialysis populations. We sought to determine the use of adaptive designs in dialysis clinical trials and quantify trends in their use over time.Study DesignWe completed a novel full-text systematic review that used a machine learning classifier (RobotSearch) for filtering randomized controlled trials and adhered to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines.Setting & Study PopulationsWe searched MEDLINE (PubMed) and ClinicalTrials.gov using sensitive dialysis search terms.Selection Criteria for StudiesWe included all randomized clinical trials with patients receiving dialysis or clinical trials with dialysis as a primary or secondary outcome. There was no restriction of disease type or intervention type.Data Extraction & Analytical ApproachWe performed a detailed data extraction of trial characteristics and a completed a narrative synthesis of the data.Results57 studies, available as 68 articles and 7 ClinicalTrials.gov summaries, were included after full-text review (initial search, 209,033 PubMed abstracts and 6,002 ClinicalTrials.gov summaries). 31 studies were conducted in a dialysis population and 26 studies included dialysis as a primary or secondary outcome. Although the absolute number of adaptive design methods is increasing over time, the relative use of adaptive design methods in dialysis trials is decreasing over time (6.12% in 2009 to 0.43% in 2019, with a mean of 1.82%). Group sequential designs were the most common type of adaptive design method used. Adaptive design methods affected the conduct of 50.9% of trials, most commonly resulting in stopping early for futility (41.2%) and early stopping for safety (23.5%). Acute kidney injury was studied in 32 trials (56.1%), kidney failure requiring dialysis was studied in 24 trials (42.1%), and chronic kidney disease was studied in 1 trial (1.75%). 27 studies (47.4%) were supported by public funding. 44 studies (77.2%) did not report their adaptive design method in the title or abstract and would not be detected by a standard systematic review.LimitationsWe limited our search to 2 databases (PubMed and ClinicalTrials.gov) due to the scale of studies sourced (209,033 and 6,002 results, respectively).ConclusionsAdaptive design methods are used in dialysis trials but there has been a decline in their relative use over time.
Highlights
Randomized clinical trials are the gold standard for evaluating efficacy, futility or harm of new therapies (2)
Adaptive design methods are employed in dialysis trials, but there has been a decline in their relative use over time
We reported overall outcomes and outcomes by (i) frequency and type of adaptive design; (ii) adaptive designs as a proportion of studies classified as dialysis RCTs by RobotSearch (iii) Population, Intervention and Outcome including dialysis modality; (iv) publication in high impact journals; (v) geographic location and funding; (vi) reporting of adaptive design methods in title and abstract; and (vii) a risk of bias assessment
Summary
We limited our search to two databases (Pubmed and Clinicaltrials.gov) due to the scale of studies sourced (209,033 and 6,002 results, respectively). Conclusions Adaptive design methods are employed in dialysis trials, but there has been a decline in their relative use over time. Key Words Dialysis, Adaptive design, Hemodialysis, Peritoneal Dialysis, End Stage Kidney Disease. We performed a systematic review by searching two large databases for dialysis trials with adaptive designs and found 57 examples. They are employed mostly in trials of acute kidney injury, they impacted (changed a trial) in half of the studies they were used in, and are usually not reported in Journal Pre-proof titles or abstracts of papers. Greater knowledge of adaptive design examples in dialysis will further improve uptake in dialysis randomized clinical trials
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