Evidence map›Paper›PMID 35477176›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2022

Stage Shift as an Endpoint in Cancer Screening Trials: Implications for Evaluating Multicancer Early Detection Tests.

Lukas Owens, Roman Gulati, Ruth Etzioni

Open access · bronzeAbstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

  1. Late-Stage Outcomes as Surrogates for Mortality in Cancer Screening Trials: A Systematic Review and Meta-analysis.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Pooled it
  2. Article
  3. Article
  4. A Quantitative Framework to Assess the Potential of Earlier Cancer Detection to Improve Cancer Survival.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
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  12. Article
  13. Modeling the Impact of Multicancer Early Detection Tests: A Review of Natural History of Disease Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Review
  14. Article
  15. Article
  16. Article
  17. Multi-cancer early detection tests: Attributes for clinical implementation.Cancer biomarkers : section A of Disease markers · 2025
    Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Lukas OwensProgram in Biostatistics, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.ORCID 0000-0002-5149-5379
Roman GulatiProgram in Biostatistics, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.ORCID 0000-0002-7592-6567
Ruth EtzioniProgram in Biostatistics, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.ORCID 0000-0002-9164-6370
Fred Hutch Cancer Center · US

Funding

Statistical modeling to support population and translational cancer researchR50CA221836 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Roman Gulati · 2017 to 2026
$2.0M
NCI NIH HHS R50 CA221836
6 · The paper itself

Abstract

backgroundDisease-specific mortality is a consensus endpoint in cancer screening trials. New liquid biopsy-based screening tests, including multi-cancer early detection (MCED) tests, are creating a need to reduce the typically lengthy screening trial process. Endpoints based on the reduction in late-stage disease (stage shift) have been proposed but it is unclear how well they predict the impact of screening on disease-specific mortality across a variety of cancers potentially detectable by MCED tests.

methodsWe develop a mathematical formulation relating the reduction in late-stage cancer to the expected reduction in disease-specific mortality if cases diagnosed early via screening receive a corresponding shift in mortality. We investigate the similarity between the expected mortality reduction and the observed mortality reduction in published trials of screening for breast, lung, ovarian, and prostate cancer.

resultsThe expected mortality reduction for a given stage shift varies significantly depending on cancer- and stage-specific survival distributions, with some cancer types showing little possibility for mortality improvement even under substantial stage shift. The expected mortality reduction fails to consistently match the mortality outcomes of published trials.

conclusionsIn MCED, any mortality benefit is likely to vary substantially across target cancers. Stage shift does not appear to be a reliable basis for inference about mortality reduction across cancers potentially detectable by MCED tests. IMPACT: Stage shift may be an appealing endpoint for evaluation of cancer screening tests but it appears to be an unreliable predictor of mortality benefit; furthermore, the same stage shift can mean different things for different cancers.

Indexed as

Early Detection of CancerNeoplasmsHumansMass ScreeningModels, Theoretical

Identifiers

PMID35477176
PMCPMC9250620
OpenAlexW4225004030

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.