Evidence map›Paper›PMID 33579807›Full record

ReviewJournal of nuclear medicine : official publication, Society of Nuclear Medicine2021

Statistical Considerations in the Evaluation of Continuous Biomarkers.

Mei-Yin C Polley, James J Dignam

Abstract readReview
In one paragraph

Review in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

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

  1. Pooled it
  2. Trial
  3. Article
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  6. Review
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  9. Observational
  10. Innovations in biomarker stratification for precision oncology.Clinical and experimental medicine · 2026
    Review
  11. Article
  12. Review
  13. Article
  14. Biomarker-driven optimal designs for patient enrollment restriction.Statistical methods in medical research · 2025
    Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. 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

2 authors.

Mei-Yin C PolleyDepartment of Public Health Sciences, University of Chicago, Chicago, Illinois, and NRG Oncology Statistics and Data Management Center, Philadelphia, Pennsylvania mcpolley@uchicago.edu.
James J DignamDepartment of Public Health Sciences, University of Chicago, Chicago, Illinois, and NRG Oncology Statistics and Data Management Center, Philadelphia, Pennsylvania.

Funding

Statistics CoreU10CA180822 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Mei-Yin C Polley · 2014 to 2026
$146.4M
The Role of CHFR in Tumorigenesis and Paclitaxel-Sensitivity in Breast CancerP50CA116201 · NCI · MAYO CLINIC ROCHESTER · PI PETER C LUCAS · 2005 to 2026
$49.9M
NCI NIH HHS P50 CA116201NCI NIH HHS U10 CA180822
6 · The paper itself

Abstract

Discovery of biomarkers has been steadily increasing over the past decade. Although a plethora of biomarkers has been reported in the biomedical literature, few have been sufficiently validated for broader clinical applications. One particular challenge that may have hindered the adoption of biomarkers into practice is the lack of reproducible biomarker cut points. In this article, we attempt to identify some common statistical issues related to biomarker cut point identification and provide guidance on proper evaluation, interpretation, and validation of such cut points. First, we illustrate how discretization of a continuous biomarker using sample percentiles results in significant information loss and should be avoided. Second, we review the popular "minimal-

Indexed as

Statistics as TopicBiomarkersData Interpretation, StatisticalHumansBiomarkersarea under the ROC curvebiomarker cut pointbiomarker discretizationprognostic biomarkerresubstitution statisticsstatistics

Identifiers

PMID33579807
PMCPMC8844257

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.