Evidence map›Paper›PMID 17378937›Full record

ArticleBMC medical genetics2007

Incorporating medical interventions into carrier probability estimation for genetic counseling.

Hormuzd A Katki

Abstract read
In one paragraph

Article in BMC medical genetics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A two-stage approach to genetic risk assessment in primary care.Breast cancer research and treatment · 2016
    Article
  5. Recent BRCAPRO upgrades significantly improve calibration.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2014
    Article
  6. Article
  7. Article
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  10. Article
  11. Prediction of BRCA Mutations Using the BRCAPRO Model in Clinic-Based African American, Hispanic, and Other Minority Families in the United States.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2009
    Article
  12. 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.

Hormuzd A KatkiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, 6120 Executive Blvd, Room 8044 Rockville, MD 20852, USA. katkih@mail.nih.gov

Funding

Methods for Epidemiology StudiesZ01CP010181 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI CHATTERJEE, NILANJAN · 2003 to 2008
$4.8M
Statistical Methods for Cancer GenesR01CA105090 · NCI · JOHNS HOPKINS UNIVERSITY · PI PARMIGIANI, GIOVANNI · 2004 to 2007
$997k
Intramural NIH HHSNCI NIH HHS R01 CA105090NCI NIH HHS R01CA105090-01A1
6 · The paper itself

Abstract

backgroundMendelian models for predicting who may carry an inherited deleterious mutation of known disease genes based on family history are used in a variety of clinical and research activities. People presenting for genetic counseling are increasingly reporting risk-reducing medical interventions in their family histories because, recently, a slew of prophylactic interventions have become available for certain diseases. For example, oophorectomy reduces risk of breast and ovarian cancers, and is now increasingly being offered to women with family histories of breast and ovarian cancer. Mendelian models should account for medical interventions because interventions modify mutation penetrances and thus affect the carrier probability estimate.

methodsWe extend Mendelian models to account for medical interventions by accounting for post-intervention disease history through an extra factor that can be estimated from published studies of the effects of interventions. We apply our methods to incorporate oophorectomy into the BRCAPRO model, which predicts a woman's risk of carrying mutations in BRCA1 and BRCA2 based on her family history of breast and ovarian cancer. This new BRCAPRO is available for clinical use.

resultsWe show that accounting for interventions undergone by family members can seriously affect the mutation carrier probability estimate, especially if the family member has lived many years post-intervention. We show that interventions have more impact on the carrier probability as the benefits of intervention differ more between carriers and non-carriers.

conclusionThese findings imply that carrier probability estimates that do not account for medical interventions may be seriously misleading and could affect a clinician's recommendation about offering genetic testing. The BayesMendel software, which allows one to implement any Mendelian carrier probability model, has been extended to allow medical interventions, so future Mendelian models can easily account for interventions.

Indexed as

Genetic Carrier ScreeningHeterozygoteAdultAgedAged, 80 and overBayes TheoremBreast NeoplasmsFemaleGenes, BRCA1Genetic CounselingHumansMaleMiddle AgedModels, GeneticMutationOvariectomy

Identifiers

PMID17378937
PMCPMC1847675

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Registered trials

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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.