Evidence map›Paper›PMID 31296927›Full record

ArticleEuropean journal of human genetics : EJHG2019

Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees.

John Michael O Ranola, Ginger J Tsai, Brian H Shirts

Abstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Observational
  10. Modeling the impact of data sharing on variant classification.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  11. Review
  12. Nature and nurture: understanding phenotypic variation in inborn errors of immunity.Frontiers in cellular and infection microbiology · 2023
    Review
  13. Article
  14. Article
  15. Management of Secondary Genomic Findings.American journal of human genetics · 2020
    Review
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.

John Michael O RanolaDepartment of Laboratory Medicine, University of Washington, Seattle, WA, 98109, USA. ranolaj@uw.edu.
Ginger J TsaiDepartment of Laboratory Medicine, University of Washington, Seattle, WA, 98109, USA.ORCID http://orcid.org/0000-0002-8417-5697
Brian H ShirtsDepartment of Laboratory Medicine, University of Washington, Seattle, WA, 98109, USA.

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
NCI NIH HHS P30 CA015704
6 · The paper itself

Abstract

Recent studies have reported novel cancer risk associations with incidentally tested genes on cancer risk panels using clinically ascertained cohorts. Clinically ascertained pedigrees may have unknown ascertainment biases for both patients and relatives. We used a method to assess gene and variant risk and ascertainment bias based on comparing the number of observed disease instances in a pedigree given the sex and ages of individuals with those expected given established population incidence. We assessed the performance characteristics of the method by simulating families with varying genetic risk and proportion of individuals genotyped. We implemented this method using SEER cancer incidence data to assess clinical ascertainment bias in a set of 42 pedigrees with clinical testing ordered for either breast/ovarian cancer or colorectal/endometrial cancer at the University of Washington and negative sequencing results. In addition to expected biases consistent with the stated testing purpose, there were trends suggesting increased colorectal and endometrial cancer in pedigrees tested for breast cancer risk and trends suggesting increased breast cancer in families tested for colon cancer risk. There was no observed selection bias for prostate cancer in this set of families. This analysis illustrates that clinically ascertained data sets may have subtle biases. In the future, researchers seeking to explore risk associations with clinical data sets could assess potential ascertainment bias by comparing incidence of disease in families that test negative under given ordering criteria to expected population disease frequencies. Failure to assess for ascertainment bias increases the risk of false genetic associations.

Indexed as

PedigreeAdultBreast NeoplasmsColorectal NeoplasmsFemaleGenetic TestingHumansMaleMiddle AgedNeoplasmsOvarian NeoplasmsRisk AssessmentRisk FactorsSEER Program

Identifiers

PMID31296927
PMCPMC6871527

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.