Evidence map›Paper›PMID 34680343›Full record

ArticleCancers2021

Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models.

Sherly X Li, Roger L Milne, Tú Nguyen-Dumont, Dallas R English, Graham G Giles, Melissa C Southey, Antonis C Antoniou, Andrew Lee, Ingrid Winship, John L Hopper and 2 more

Abstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. 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

12 authors.

Sherly X LiCancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia.ORCID 0000-0002-7840-4051
Roger L MilneCancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia.
Tú Nguyen-DumontPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne 3800, Australia.ORCID 0000-0002-6217-0182
Dallas R EnglishCancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia.ORCID 0000-0001-7828-8188
Graham G GilesCancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia.
Melissa C SoutheyCancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia.
Antonis C AntoniouCentre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.ORCID 0000-0001-9223-3116
Andrew LeeCentre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.
Ingrid WinshipDepartment of Genomic Medicine, Royal Melbourne Hospital, Melbourne 3050, Australia.
John L HopperCentre for Epidemiology and Biostatistics, University of Melbourne, Melbourne 3010, Australia.
Mary Beth TerryDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Robert J MacInnisCancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia.ORCID 0000-0002-1627-5047

Funding

Cancer Research UK 20861
6 · The paper itself

Abstract

Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50-65 years and unaffected at commencement of follow-up two (conducted in 2003-2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50-54, 55-59, 60-65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56-0.62) and IBIS (0.57, 95% CI 0.54-0.61) than the other models (

Indexed as

breast cancercalibrationdiscriminationrisk model

Identifiers

PMID34680343
PMCPMC8534072

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.