Treatment Intensification Patterns and Utilization in Patients with Metastatic Castration-Sensitive Prostate Cancer.

INTRODUCTION: Patients with mCSPC experience a longer overall survival with treatment intensification by addition of novel hormonal therapy (NHT) or docetaxel to androgen deprivation vs androgen deprivation alone. Real-world data report, however, that nearly half of mCSPC patients do not receive treatment intensification. In this study, treatment patterns and utilization of treatment intensification in mCSPC patients were described using the IQVIA Anonymized Patient Longitudinal Data, a dataset of fully adjudicated pharmacy and medical claims. PATIENTS AND METHODS: Reports on first line (1L) treatment patterns were obtained for years 2015 to 2021. Medicaid, Medicare, Medicare part D, cash transactions, and commercial data were included for years 2012 to 2021. RESULTS: Nationwide, of 66,844 men with newly diagnosed mCSPC since 2015, on average 25% were prescribed NHT, and another 12% were prescribed chemotherapy. No differences were noted in treatment patterns based on U.S. regions and/or rural vs. urban communities. The disparity was observed in prescribing patterns between oncology and urology providers. Oncology providers prescribed 1L NHT on average 32% of the time, while urology providers did so 12% of the time. Furthermore, oncology providers prescribed chemotherapy on average 20% of the time, resulting in 52% of men with mCSPC receiving treatment intensification as 1L therapy. Patients' age group, community or health insurance did not account for the disparity between the 2 specialties. CONCLUSION: Both medical oncology and urology providers need to improve their treatment intensification efforts for men with mCSPC to increase their patients' overall survival.

Hypothesis driven single nucleotide polymorphism search (HyDn-SNP-S).

The advent of complete-genome genotyping across phenotype cohorts has provided a rich source of information for bioinformaticians. However the search for SNPs from this data is generally performed on a study-by-study case without any specific hypothesis of the location for SNPs that are predictive for the phenotype. We have designed a method whereby very large SNP lists (several gigabytes in size), combining several genotyping studies at once, can be sorted and traced back to their ultimate consequence in protein structure. Given a working hypothesis, researchers are able to easily search whole genome genotyping data for SNPs that link genetic locations to phenotypes. This allows a targeted search for correlations between phenotypes and potentially relevant systems, rather than utilizing statistical methods only. HyDn-SNP-S returns results that are less data dense, allowing more thorough analysis, including haplotype analysis. We have applied our method to correlate DNA polymerases to cancer phenotypes using four of the available cancer databases in dbGaP. Logistic regression and derived haplotype analysis indicates that ~80SNPs, previously overlooked, are statistically significant. Derived haplotypes from this work link POLL to breast cancer and POLG to prostate cancer with an increase in incidence of 3.01- and 9.6-fold, respectively. Molecular dynamics simulations on wild-type and one of the SNP mutants from the haplotype of POLL provide insights at the atomic level on the functional impact of this cancer related SNP. Furthermore, HyDn-SNP-S has been designed to allow application to any system. The program is available upon request from the authors.