Evidence map›Paper›PMID 31395442›Full record

ReviewLancet (London, England)2019

Family health history: underused for actionable risk assessment.

Geoffrey S Ginsburg, R Ryanne Wu, Lori A Orlando

Open access · greenAbstract readReview
In one paragraph

Review in Lancet (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 2 pooled it
5.2field-weighted citation impact, top 3% 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

58 citing papers in PubMed, 2 syntheses or guidelines pooled it, 108 citations in OpenAlex.

  1. Family history tools for primary care: A systematic review.The European journal of general practice · 2022
    Pooled it
  2. Pooled it
  3. Trial
  4. Review
  5. Review
  6. Article
  7. Article
  8. Knowledge, Perceptions, and Barriers to Collection of Family Health History Data.Journal of the American Board of Family Medicine : JABFM · 2026
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
  18. Article
  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

3 authors at 1 institution in 1 country.

Geoffrey S GinsburgDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA. Electronic address: geoffrey.ginsburg@duke.edu.
R Ryanne WuDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA; Durham Veteran Affairs Cooperative Studies Program Epidemiology Center, Durham, NC, USA.
Lori A OrlandoDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
Duke University · US

Funding

Implementation, Adoption, and Utility of Family History in Diverse Care SettingsU01HG007282 · NHGRI · DUKE UNIVERSITY · PI GINSBURG, GEOFFREY S, ORLANDO, LORI ANN · 2013 to 2018
$7.0M
NHGRI NIH HHS U01 HG007282
6 · The paper itself

Abstract

Family health history (FHH) is the most useful means of assessing risk for common chronic diseases. The odds ratio for risk of developing disease with a positive FHH is frequently greater than 2, and actions can be taken to mitigate risk by adhering to screening guidelines, genetic counselling, genetic risk testing, and other screening methods. Challenges to the routine acquisition of FHH include constraints on provider time to collect data and the difficulty in accessing risk calculators. Disease-specific and broader risk assessment software platforms have been developed, many with clinical decision support and informatics interoperability, but few access patient information directly. Software that allows integration of FHH with the electronic medical record and clinical decision support capabilities has provided solutions to many of these challenges. Patient facing, electronic medical record, and web-enabled FHH platforms have been developed, and can provide greater identification of risk compared with conventional FHH ascertainment in primary care. FHH, along with cascade screening, can be an important component of population health management approaches to overall reduction of risk.

Indexed as

Chronic DiseaseElectronic Health RecordsHumansMedical History TakingOdds RatioRisk AssessmentSoftware

Identifiers

PMID31395442
PMCPMC6822265
OpenAlexW2965787050

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.