ArticleEGEMS (Washington, DC)2015
Analytic Challenges Arising from the STOP CRC Trial: Pragmatic Solutions for Pragmatic Problems.
Article in EGEMS (Washington, DC), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
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
contextPragmatic trials lack the relatively tight quality control of traditional efficacy studies and hence may pose added analytic challenges owing to the practical realities faced in carrying them out. CASE DESCRIPTION: STOP CRC is a cluster randomized trial testing the effectiveness of automated, electronic medical record (EMR)-driven strategies to raise colorectal cancer (CRC) screening rates in safety net clinics. Screen-eligible participants were accrued during year 1 and followed for 12 months (measurement window) to assess completion of a fecal screening test. Control clinics implemented the intervention in year 2. IMPLEMENTATION CHALLENGES/ANALYTIC ISSUES: Due to limitations on how we could build the intervention tools, the overlap of the year 1 measurement windows with year 2 intervention rollout posed a potential for contamination of the primary outcome for control participants. In addition, a variety of factors led to a lack of synchronization of the measurement windows with actual intervention delivery. In both cases, the net impact of these factors would be to diminish the estimated impact of the intervention. PROPOSED SOLUTIONS: We dealt with the overlap issue by delaying the start of intervention rollout to control clinics in year 2 by 6 months and by truncating the measurement windows for intervention and control participants at this point. In addition we formulated three sensitivity analyses to help address the issue of asynchronization.
conclusionThis case study might help other investigators facing similar challenges think about such issues and the pros and cons of various strategies for dealing with them.
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What OpenQuestion holds
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.