Development of an effective predictive screening tool for prostate cancer using the ClarityDX machine learning platform

. 2024 Jun 20 ; 7 (1) : 163. [epub] 20240620

Status PubMed-not-MEDLINE Jazyk angličtina Země Anglie, Velká Británie Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid38902526

Grantová podpora
G2017000328 Alberta Innovates
ACF 26001 Alberta Cancer Foundation
PCC MTA TAG2014-03 Prostate Cancer Canada (Cancer de la Prostate Canada)

Odkazy

PubMed 38902526
PubMed Central PMC11190196
DOI 10.1038/s41746-024-01167-9
PII: 10.1038/s41746-024-01167-9
Knihovny.cz E-zdroje

The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients' risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.

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