ArticleJournal of the National Cancer Institute2024
Increasing power in screening trials by testing control-arm specimens: application to multicancer detection screening.
Article in Journal of the National Cancer Institute, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 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
4 citing papers in PubMed, 5 citations in OpenAlex.
- Increasing power and robustness in screening trials by testing stored specimens in the control arm.BMC medical research methodology · 2026Article
- Design of randomized controlled trials to estimate cancer-mortality reductions from multicancer detection screening.Journal of the National Cancer Institute · 2025Article
- Gauging the efficacy of multicancer screening: the road ahead may be long and bumpy.Journal of the National Cancer Institute · 2025Article
- Primary care physicians and laypersons' perceptions of multicancer detection clinical trial designs.JNCI cancer spectrum · 2024Article
Corrections and comments
- Retraction · 2024-09-12Error in Analyses · Error in Results and/or Conclusions · Retract and Replace · · see https://academic.oup.com/jnci/advance-article/doi/10.1093/jnci/djae218/7755746
- Republished as
- Retracted
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundCancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the "intended effect" (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests.
methodsWe simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial-colorectal component [PLCO-CRC]).
resultsCompared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 5-fold (NLST), 33-fold (MINN-FOBT-A), or 14 160-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 26% (NLST), 48% (MINN-FOBT-A), or 59% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives.
conclusionsTesting stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests.
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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.