Development and validation of the PREMMplus clinical prediction model for multigene hereditary cancer risk assessment.

Authors

Matthew Yurgelun

Matthew B. Yurgelun

Dana-Farber Cancer Institute, Boston, MA

Matthew B. Yurgelun , Hajime Uno , C. Sloane Furniss , Chinedu I. Ukaegbu , Miki Horiguchi , Anu B. Chittenden , Tara Fehlmann , Amal Yussuf , Holly LaDuca , Judy Ellen Garber , Sapna Syngal

Organizations

Dana-Farber Cancer Institute, Boston, MA, Dana–Farber Cancer Institute, Boston, MA, Ambry Genetics, Aliso Viejo, CA, Cancer Genetics and Prevention, Dana-Farber Cancer Institute, Boston, MA

Research Funding

U.S. National Institutes of Health
U.S. National Institutes of Health

Background: Current clinical prediction models provide syndrome-specific numeric estimates of an individual's likelihood of having a specific hereditary cancer syndrome (e.g., PREMM5 for Lynch syndrome; BRCAPRO for BRCA1/2). With the emergence of multigene panel testing (MGPT), there is a need to evaluate individuals' risk of carrying a pathogenic variant in a diverse array of cancer susceptibility genes in parallel. This study’s aim was to develop and validate the PREMMplus clinical prediction model for multigene cancer risk assessment. Methods: PREMMplus was developed in a cohort of 7296 individuals who had undergone germline MGPT at a single center. Logistic regression models were used to examine candidate predictive variables – including age, sex, ethnicity, and personal/family history of cancer – to provide a numeric estimate of an individual’s likelihood of carrying a pathogenic/likely pathogenic germline variant in one of 18 cancer susceptibility genes (11 high- [APC, BRCA1/2, CDH1, EPCAM, MLH1, MSH2, MSH6, biallelic MUTYH, PMS2, and TP53] and 7 moderate-penetrance [ATM, CDKN2A, CHEK2, PALB2, PTEN, RAD51C, and RAD51D]). Model performance was validated in an independent dataset of 14845 individuals who had undergone MGPT at a commercial laboratory. Results: Using clinical characteristics, including personal/family history of 18 cancers plus colorectal adenoma burden, PREMMplus demonstrated an excellent ability to predict pathogenic variants in high penetrance genes at 90% sensitivity. PREMMplus had acceptable performance with the addition of 7 moderate penetrance genes. PREMMplus was well-calibrated and demonstrated comparable performance in the external validation dataset. Conclusions: PREMMplus is the first validated risk assessment model to quantify an individual’s likelihood of carrying pathogenic variants in a wide diversity of cancer risk genes, and can be used to select individuals who should undergo MGPT. As expected, PREMMplus’s discriminatory capacity was reduced with the inclusion of moderate penetrance cancer risk genes.

CohortOutcomeSensitivitySpecificityPositive Predictive ValueNegative Predictive Value# Needed To Test to Detect 1 CarrierAUC (95% CI)
Development11 high penetrance genes90%34.8%7.4%98.4%13.50.74 (0.71-0.77)
Development18 high/moderate penetrance genes90%23.9%10.6%96.0%9.40.67 (0.65-0.69)
Validation11 high penetrance genes90%22.8%5.5%97.9%18.30.69 (0.66-0.71)
Validation18 high/moderate penetrance genes90%17.8%9.8%94.8%10.20.62 (0.60-0.64)

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Abstract Details

Meeting

2020 ASCO Virtual Scientific Program

Session Type

Poster Session

Session Title

Cancer Prevention, Risk Reduction, and Genetics

Track

Prevention, Risk Reduction, and Genetics

Sub Track

Germline Genetic Testing

Citation

J Clin Oncol 38: 2020 (suppl; abstr 1579)

DOI

10.1200/JCO.2020.38.15_suppl.1579

Abstract #

1579

Poster Bd #

71

Abstract Disclosures

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