Evidence map›Paper›PMID 26786860›Full record

ArticleBreast cancer research and treatment2016

A two-stage approach to genetic risk assessment in primary care.

Swati Biswas, Philamer Atienza, Jonathan Chipman, Amanda L Blackford, Banu Arun, Kevin Hughes, Giovanni Parmigiani

Abstract read
In one paragraph

Article in Breast cancer research and treatment, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Genetic cancer risk assessment in general practice: systematic review of tools available, clinician attitudes, and patient outcomes.The British journal of general practice : the journal of the Royal College of General Practitioners · 2019
    Pooled it
  2. A validation of models for prediction of pathogenic variants in mismatch repair genes.Genetics in medicine : official journal of the American College of Medical Genetics · 2022
    Article
  3. Review
  4. The role of genomics in global cancer prevention.Nature reviews. Clinical oncology · 2021
    Review
  5. Article
  6. Article
  7. 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

7 authors.

Swati BiswasDepartment of Mathematical Sciences, University of Texas at Dallas, FO 35, 800 West Campbell Road, Richardson, TX, 75080-3021, USA. swati.biswas@utdallas.edu.
Philamer AtienzaDepartment of Biostatistics, School of Public Health, University of North Texas Health Science Center, Fort Worth, USA.
Jonathan ChipmanDepartment of Biostatistics, Vanderbilt School of Medicine, Nashville, USA.
Amanda L BlackfordDivision of Biostatistics and Bioinformatics, School of Medicine, Johns Hopkins University, Baltimore, USA.
Banu ArunDepartment of Breast Medical Oncology and Clinical Cancer Genetics, University of Texas M.D. Anderson Cancer Center, Houston, USA.
Kevin HughesMassachusetts General Hospital and Harvard School of Medicine, Boston, USA.
Giovanni ParmigianiDepartment of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, USA.

Funding

VectorP30CA006516 · NCI · DANA-FARBER CANCER INSTITUTE · PI A. Heather Eliassen · 1985 to 2026
$330.6M
Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Genetic Risk Prediction in Primary CareR03CA173834 · NCI · UNIVERSITY OF TEXAS DALLAS · PI ARUN, BANU K, BISWAS, SWATI · 2013 to 2014
$165k
NCI NIH HHS 1R03CA173834-02NCI NIH HHS 2P30CA006516-47NCI NIH HHS P30 CA006516NCI NIH HHS P30 CA016672NCI NIH HHS R03 CA173834
6 · The paper itself

Abstract

Genetic risk prediction models such as BRCAPRO are used routinely in genetic counseling for identification of potential BRCA1 and BRCA2 mutation carriers. They require extensive information on the counselee and her family history, and thus are not practical for primary care. To address this gap, we develop and test a two-stage approach to genetic risk assessment by balancing the tradeoff between the amount of information used and accuracy achieved. The first stage is intended for primary care wherein limited information is collected and analyzed using a simplified version of BRCAPRO. If the assessed risk is sufficiently high, more extensive information is collected and the full BRCAPRO is used (stage two: intended for genetic counseling). We consider three first-stage tools: BRCAPROLYTE, BRCAPROLYTE-Plus, and BRCAPROLYTE-Simple. We evaluate the two-stage approach on independent clinical data on probands with family history of breast and ovarian cancers, and BRCA genetic test results. These include population-based data on 1344 probands from Newton-Wellesley Hospital and mostly high-risk family data on 2713 probands from Cancer Genetics Network and MD Anderson Cancer Center. We use discrimination and calibration measures, appropriately modified to evaluate the overall performance of a two-stage approach. We find that the proposed two-stage approach has very limited loss of discrimination and comparable calibration as BRCAPRO. It identifies a similar number of carriers without requiring a full family history evaluation on all probands. We conclude that the two-stage approach allows for practical large-scale genetic risk assessment in primary care.

Indexed as

BRCA1 ProteinBRCA2 ProteinBreast NeoplasmsFemaleGenetic CounselingGenetic Predisposition to DiseaseHumansMaleMiddle AgedMutationOvarian NeoplasmsPedigreePrimary Health CareRetrospective StudiesRisk AssessmentRisk FactorsBRCA1 ProteinBRCA2 ProteinBayesMendelBRCA1BRCA2BRCAPROCancerGene

Identifiers

PMID26786860
PMCPMC4742331

What OpenQuestion holds

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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.