| Title: |
From a genomic risk model to clinical trial implementation in a learning health system: the ProGRESS Study |
| Authors: |
Vassy, Jason L; Dornisch, Anna M; Karunamuni, Roshan; Gatzen, Michael; Kachulis, Christopher J; Lennon, Niall J; Brunette, Charles A; Danowski, Morgan E; Hauger, Richard L; Garraway, Isla P; Kibel, Adam S; Lee, Kyung Min; Lynch, Julie A; Maxwell, Kara N; Rose, Brent S; Teerlink, Craig C; Xu, George J; Hofherr, Sean E; Lafferty, Katherine A; Larkin, Katie; Malolepsza, Edyta; Patterson, Candace J; Toledo, Diana M; Donovan, Jenny L; Hamdy, Freddie; Martin, Richard M; Neal, David E; Turner, Emma L; Andreassen, Ole A; Dale, Anders M; Mills, Ian G; Batra, Jyotsna; Clements, Judith; Cussenot, Olivier; Cybulski, Cezary; Eeles, Rosalind A; Fowke, Jay H; Grindedal, Eli Marie; Hamilton, Robert J; Lim, Jasmine; Lu, Yong-Jie; MacInnis, Robert J; Maier, Christiane; Mucci, Lorelei A; Multigner, Luc; Neuhausen, Susan L; Nielsen, Sune F; Parent, Marie-Élise; Park, Jong Y; Petrovics, Gyorgy; Plym, Anna; Razack, Azad; Rosenstein, Barry S; Schleutker, Johanna; Sørensen, Karina Dalsgaard; Travis, Ruth C; Vega, Ana; West, Catharine ML; Wiklund, Fredrik; Zheng, Wei; Committee, Profile Steering; Committee and Collaborators, IMPACT Study Steering; Consortium, PRACTICAL; Program, Million Veteran; Seibert, Tyler M |
| Publisher Information: |
eScholarship, University of California |
| Publication Year: |
2024 |
| Collection: |
University of California: eScholarship |
| Subject Terms: |
Biological Sciences; Biomedical and Clinical Sciences; Genetics; Health Services and Systems; Health Sciences; Clinical Sciences; Oncology and Carcinogenesis; Clinical Research; Human Genome; Urologic Diseases; Prevention; Prostate Cancer; Health Services; Cancer; 4.2 Evaluation of markers and technologies; Good Health and Well Being |
| Description: |
Background: As healthcare moves from a one-size-fits-all approach towards precision care, individual risk prediction is an important step in disease prevention and early detection. Biobank-linked healthcare systems can generate knowledge about genomic risk and test the impact of implementing that knowledge in care. Risk-stratified prostate cancer screening is one clinical application that might benefit from such an approach. Methods: We developed a clinical translation pipeline for genomics-informed prostate cancer screening in a national healthcare system. We used data from 585,418 male participants of the Veterans Affairs (VA) Million Veteran Program (MVP), among whom 101,920 self-identify as Black/African-American, to develop and validate the Prostate CAncer integrated Risk Evaluation (P-CARE) model, a prostate cancer risk prediction model based on a polygenic score, family history, and genetic principal components. The model was externally validated in data from 18,457 PRACTICAL Consortium participants. A novel blended genome-exome (BGE) platform was used to develop a clinical laboratory assay for both the P-CARE model and rare variants in prostate cancer-associated genes, including additional validation in 74,331 samples from the All of Us Research Program. Results: In overall and ancestry-stratified analyses, the polygenic score of 601 variants was associated with any, metastatic, and fatal prostate cancer in MVP and PRACTICAL. Values of the P-CARE model at ≥80th percentile in the multiancestry cohort overall were associated with hazard ratios (HR) of 2.75 (95% CI 2.66-2.84), 2.78 (95% CI 2.54-2.99), and 2.59 (95% CI 2.22-2.97) for any, metastatic, and fatal prostate cancer in MVP, respectively, compared to the median. When high– and low-risk groups were defined as P-CARE HR>1.5 and HR |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
qt64w7z5m1; https://escholarship.org/uc/item/64w7z5m1; https://escholarship.org/content/qt64w7z5m1/qt64w7z5m1.pdf |
| DOI: |
10.1101/2024.11.03.24316516 |
| Availability: |
https://escholarship.org/uc/item/64w7z5m1; https://escholarship.org/content/qt64w7z5m1/qt64w7z5m1.pdf; https://doi.org/10.1101/2024.11.03.24316516 |
| Rights: |
public |
| Accession Number: |
edsbas.9FF196E4 |
| Database: |
BASE |