Evidence map›Paper›PMID 19574417›Full record

ArticleJournal of the National Cancer Institute2009

Improving the biomarker pipeline to develop and evaluate cancer screening tests.

Stuart G Baker

Abstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Cancer Screening Markers: A Simple Strategy to Substantially Reduce the Sample Size for Validation.Medical decision making : an international journal of the Society for Medical Decision Making · 2019
    Article
  10. Study Design Considerations for Cancer Biomarker Discoveries.The journal of applied laboratory medicine · 2018
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Improving the quality of biomarker discovery research: the right samples and enough of them.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2015
    Article
  17. A cancer theory kerfuffle can lead to new lines of research.Journal of the National Cancer Institute · 2015
    Article
  18. Article
  19. Urinary transforming growth factor α and serum α-fetoprotein as tumor markers of hepatocellular carcinoma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2014
    Article
  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

1 author.

Stuart G BakerBiometry Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA. sb16i@nih.gov

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biomarker pipeline to develop and evaluate cancer screening tests has three stages: identification of promising biomarkers for the early detection of cancer, initial evaluation of biomarkers for cancer screening, and definitive evaluation of biomarkers for cancer screening. Statistical and biological issues to improve this pipeline are discussed. Although various recommendations, such as identifying cases based on clinical symptoms, keeping biomarker tests simple, and adjusting for postscreening noise, have been made previously, they are not widely known. New recommendations include more frequent specimen collection to help identify promising biomarkers and the use of the paired availability design with interval cases (symptomatic cancers detected in the interval after screening) for initial evaluation of biomarkers for cancer screening.

Indexed as

BiasBiomarkers, TumorClinical Trials as TopicEarly Detection of CancerEquipment ContaminationHumansMass ScreeningNeoplasm ProteinsNeoplasmsPatient CompliancePredictive Value of TestsPrognosisROC CurveBiomarkers, TumorNeoplasm Proteins

Identifiers

PMID19574417
PMCPMC2728744

What OpenQuestion holds

Textmetadata
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.