ArticleJournal of the National Cancer Institute. Monographs2025
Practical design considerations for cluster randomized controlled trials: lessons learned in community oncology research.
Emily V Dressler, Stephanie L Pugh, Heather J Gunn, Joseph M Unger, David M Zahrieh, Anna C Snavely
Abstract read
In one paragraphArticle in Journal of the National Cancer Institute. Monographs, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from itWhat 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.
2 · The registryThe 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.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
6 authors.
Emily V DresslerDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC 27157, United States.ORCID 0000-0002-6054-7839 Stephanie L PughNRG Oncology Statistics and Data Management Center, American College of Radiology, Philadelphia, PA 19103, United States.
Heather J GunnDepartment of Quantitative Health Sciences and Alliance Statistics and Data Management Center, Mayo Clinic, Scottsdale, AZ 85259, United States.
Joseph M UngerSWOG Statistics and Data Management Center, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.
David M ZahriehDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, United States.
Anna C SnavelyDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC 27157, United States.
Funding
ECOG-ACRIN NCORP Research Base - TMISTUG1CA189828 · NCI · ECOG-ACRIN MEDICAL RESEARCH FOUNDATION · PI Peter J ODwyer, MITCHELL D. SCHNALL · 2014 to 2026
$199.7MStatistics CoreU10CA180822 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI James J. Dignam · 2014 to 2026
$146.4MNRG Oncology NCORP Research Base-BIQSFPUG1CA189867 · NCI · NRG ONCOLOGY FOUNDATION, INC. · PI Deborah Watkins Bruner, Lisa A. Kachnic · 2014 to 2026
$140.5MCollaborations and NCORP Collective ManagementUG1CA189823 · NCI · MAYO CLINIC ROCHESTER · PI Evanthia Galanis, Olwen Hahn · 2014 to 2026
$120.6MSWOG Statistics & Data Management Center complex - extension supplement for GY06U10CA180819 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Catherine M. Tangen · 2014 to 2026
$115.2MStatistics CoreU10CA180882 · NCI · MAYO CLINIC ROCHESTER · PI Sumithra Jay Mandrekar · 2014 to 2026
$115.0MSWOG NCORP Research BaseUG1CA189974 · NCI · THE HOPE FOUNDATION · PI CHARLES D. BLANKE, DAWN HERSHMAN · 2014 to 2026
$80.6MURCC NCORP Research BaseUG1CA189961 · NCI · UNIVERSITY OF ROCHESTER · PI Michelle C Janelsins, KAREN M. MUSTIAN · 2014 to 2026
$67.7MTowards a preventive cancer vaccine for children with constitutional mismatch repair deficiencyUG1CA189955 · NCI · PUBLIC HEALTH INSTITUTE · PI BRAD H POLLOCK, Michael E. Roth · 2014 to 2026
$62.5MWake Forest NCORP Research BaseUG1CA189824 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Emily Van Meter Dressler, GLENN J LESSER · 2014 to 2026
$57.9MImplementation of Smoking Cessation Services within NCI NCORP Community Sites with Organized Lung Cancer Screening ProgramsR01CA207158 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI CHILES, CAROLINE, FOLEY, KRISTIE L · 2016 to 2020
$2.2MACRIN UG1CA189828AHRQ HHS R01 HS025194AHRQ HHS R01HS025194Alliance for Clinical Trials in Oncology UG1CA189974Children's Oncology Group 5UG1CA189955-11ECOGNCI Community Oncology Research Program UG1CA189867NCI NIH HHS R01 CA207158NCI NIH HHS R01CA207158NCI NIH HHS U10 CA180819NCI NIH HHS U10 CA180822NCI NIH HHS U10 CA180882NCI NIH HHS UG1 CA189823NCI NIH HHS UG1 CA189824NCI NIH HHS UG1CA189824NCI NIH HHS UG1 CA189828NCI NIH HHS UG1 CA189867NCI NIH HHS UG1 CA189955NCI NIH HHS UG1 CA189961NCI NIH HHS UG1 CA189974NIH HHSNRG Oncology U10CA180882SWOG NCORP RBUniversity of Rochester UG1CA189961Wake Forest NCORP U10CA180822Wake Forest University UG1CA189824
6 · The paper itselfAbstract
Cancer care delivery research trials conducted within the National Cancer Institute (NCI) Community Oncology Research Program (NCORP) routinely implement interventions at the practice or provider level, necessitating the use of cluster randomized controlled trials (cRCTs). The intervention delivery requires cluster-level randomization instead of participant-level, affecting sample size calculation and statistical analyses to incorporate correlation between participants within a practice. Practical challenges exist in the conduct of these cRCTs due to unique trial network infrastructures, including the possibility of unequal participant accrual totals and rates and staggered study initiation by clusters, potentially with differences between randomized arms. Execution of cRCT designs can be complex, ie, if some clusters do not accrue participants, unintended cluster-level crossover occurs, how best to identify appropriate cluster-level stratification, timing of randomization, and multilevel eligibility criteria considerations. This article shares lessons learned with potential mitigation strategies from 3 NCORP cRCTs.
Indexed as
Medical OncologyNeoplasmsRandomized Controlled Trials as TopicResearch DesignCluster AnalysisHumansNational Cancer Institute (U.S.)United States
Identifiers
PMID39989035
PMCPMC11848037
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