Evidence map›Paper›PMID 42489042›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2026

Familial Risk Stratification Across Cancer Syndromes Using Fam3PRO.

Jane W Liang, Gregory E Idos, Christine Hong, Kristen M Shannon, Lauren M Bear, Joseph D Bonner, Sidney Lindsey, Jennifer Morales Pichardo, Zoe Guan, Anne Marie McCarthy and 3 more

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Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Jane W LiangDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA; Division of Research, Kaiser Permanente Northern California, Pleasanton, CA, USA. Electronic address: jane.w.liang@kp.org.
Gregory E IdosCenter of Precision Medicine, City of Hope, Duarte, CA, USA.
Christine HongCenter of Precision Medicine, City of Hope, Duarte, CA, USA.
Kristen M ShannonCancer Center Genetics Program, Massachusetts General Hospital, Boston, MA, USA.
Lauren M BearCancer Center Genetics Program, Massachusetts General Hospital, Boston, MA, USA.
Joseph D BonnerCenter of Precision Medicine, City of Hope, Duarte, CA, USA.
Sidney LindseyCenter of Precision Medicine, City of Hope, Duarte, CA, USA.
Jennifer Morales PichardoCollege of Medicine - Tucson, University of Arizona, Tucson, AZ, USA.
Zoe GuanBiostatistics, Massachusetts General Hospital, Boston, MA, USA.
Anne Marie McCarthyBiostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Stephen B GruberCenter of Precision Medicine, City of Hope, Duarte, CA, USA.
Danielle BraunDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.
Giovanni ParmigianiDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Funding

Precision approaches to refining TP53-associated cancer riskR01CA242218 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI AMOS, CHRISTOPHER I., GARBER, JUDY E. · 2019 to 2023
$8.5M
Integration of epidemiology, pathology, immunology and outcomes in colorectal cancerR01CA263318 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI STEPHEN B GRUBER · 2022 to 2026
$3.4M
Southern California Clinical and Translational Science InstituteKL2TR000131 · NCATS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BUCHANAN, THOMAS A · 2012 to 2015
$2.1M
NCATS NIH HHS KL2 TR000131NCI NIH HHS R01 CA242218NCI NIH HHS R01 CA263318
6 · The paper itself

Abstract

purposeQuantitative assessment of the risk of inherited cancer susceptibility should reflect the growing number of well-documented gene-cancer associations beyond single syndromes, to increase efficiency when identifying candidates for genetic testing and early detection.

methodsWe validate Fam3PRO, a computationally efficient Mendelian risk prediction methodology and platform that supports constructing models with an arbitrary number of genes and cancers, on three independent multi-ethnic panel cohorts. Fam3PRO was trained using population-level parameters from existing literature for 21 genes and 17 cancers.

resultsFam3PRO provides discrimination and calibration comparable to the widely-adopted syndrome-specific models BRCAPRO and MMRpro, for genes associated with Breast-Ovarian and Lynch syndromes. Furthermore, when assessing the probability of being heterozygous for at least one pathogenic variant in any of the 21 genes, Fam3PRO has a discrimination of 0.64 (95% C.I. 0.62-0.67) and a calibration (observed divided by expected) of 1.13 (95% C.I. 1.05-1.22) in the combined cohort. At probability thresholds of 2.5% and 5%, Fam3PRO identifies more individuals at high risk of being heterozygous for pathogenic variants in any of the 21 genes than BRCAPRO and MMRpro.

conclusionFam3PRO provides a validated approach for familial risk stratification across a broad spectrum of cancer types, including estimates of carrier probabilities and future cancer risk.

Indexed as

familial risk stratificationfamily historygenetic counselingMendelian modelsmulti-cancer early detectionMulti-gene panel testingrisk prediction

Identifiers

PMID42489042
PMCPMC13617544

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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.