Quantitative Proteomics-Based Prostate Cancer Prediction Models for African American and Caucasian American Military Patients
Abstract
In 2023, an estimated 288,300 men will be newly diagnosed with prostate cancer and 34,700 men will die from this disease in the United States (1). The burden of disease is particularly heavy on Black/African American men, who have a 1.5-fold incidence rate and 2-fold mortality rate, as compared to White/Caucasian American men (1). However, data on determinants of prostate disease aggressiveness at time of initial cancer detection are sorely lacking. Predictive models that simultaneously incorporate demographic, clinical, social determinants of health (SDOH), and biological data are urgently needed to identify men at earlier time points, who are fated for aggressive disease, especially for Black men, to inform treatment stratification and informed treatment decision-making. Such models could help avoid overtreatment of clinically indolent disease, as well as spare men unnecessary repeat biopsies, which are costly in terms of dollars but also in terms of reductions in patient quality of life, and to ensure proper treatment intensity for men whose disease maybe fated to metastasize. By addressing biological underpinnings in the form of protein expression of indolent versus aggressive PCa at diagnosis, as well as comparing protein expression in men who remain under suspicion for PCa but do not develop cancer, this study could have immediate relevance for informing timing, type, and intensity of treatment for men undergoing biopsy due to suspicion for PCa. Data on early markers of detection for PCa specific to African American men are very limited, potentially leading to sub-optimal care.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2023
- Accession Number
- AD1218530
Entities
People
- Jennifer Cullen
Organizations
- Case Western Reserve University
- Pacific Northwest National Laboratory