Evidence map›Paper›PMID 24891549›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2014

Recent BRCAPRO upgrades significantly improve calibration.

Emanuele Mazzola, Jonathan Chipman, Su-Chun Cheng, Giovanni Parmigiani

Open access · greenAbstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. A Pragmatic Testing-Eligibility Framework for Population Mutation Screening: The Example ofCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019
    Article
  6. Review
  7. Article
  8. Article
  9. Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2016
    Article
  10. Breast cancer risks and risk prediction models.Breast care (Basel, Switzerland) · 2015
    Review
  11. 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

4 authors at 1 institution in 1 country.

Emanuele MazzolaDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts mazzola@jimmy.harvard.edu.
Jonathan ChipmanDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Su-Chun ChengDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Giovanni ParmigianiDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Dana-Farber Cancer Institute · US

Funding

VectorP30CA006516 · NCI · DANA-FARBER CANCER INSTITUTE · PI A. Heather Eliassen · 1985 to 2026
$330.6M
Novel Tools for Familial Risk PredictionR21CA177233 · NCI · DANA-FARBER CANCER INST · PI PARMIGIANI, GIOVANNI LUIGI · 2013 to 2014
$406k
NCI NIH HHS 5P30CA006516-49NCI NIH HHS 5R21CA177233-02NCI NIH HHS P30 CA006516NCI NIH HHS R21 CA177233
6 · The paper itself

Abstract

The recent release of version 2.0-8 of the BayesMendel package contains an updated BRCAPRO risk prediction model, which includes revised modeling of contralateral breast cancer (CBC) penetrance, provisions for pedigrees of mixed ethnicity and an adjustment for mastectomies among family members. We estimated penetrance functions for CBC by a combination of parametric survival modeling of literature data and deconvolution of SEER9 data. We then validated the resulting updated model of CBC in BRCAPRO by comparing it with the previous release (BayesMendel 2.0-7), using pedigrees from the Cancer Genetics Network (CGN) Model Validation Study. Version 2.0-8 of BRCAPRO discriminates BRCA1/BRCA2 carriers from noncarriers with similar accuracy compared with the previous version (increase in AUC, 0.0043), is slightly more precise in terms of the root-mean-square error (decrease in RMSE, 0.0108), and it significantly improves calibration (ratio of observed to expected events of 0.9765 in version 2.0-8, compared with 0.8910 in version 2.0-7). We recommend that the new version be used in clinical counseling, particularly in settings where families with CBC are common.

Indexed as

Models, GeneticBreast NeoplasmsCalibrationFemaleGenes, BRCA1Genes, BRCA2Genetic Predisposition to DiseaseHeterozygoteHumansNeoplasms, Second PrimaryPedigreePenetrance

Identifiers

PMID24891549
PMCPMC4119541
OpenAlexW2128172940

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.