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Background/Objectives: The American Urological Association (AUA) vasectomy guidelines’ current recommendation to obtain the first post-vasectomy semen analysis (PVSA) from 8 weeks to 16 weeks post-vasectomy is based predominantly on azoospermia rates. However, non-compliance with semen analysis after vasectomy is a known problem in this patient population. An approach that optimizes clearance and compliance is essential when adopting appropriate post-vasectomy care guidelines, specifically the scheduling of the first PVSA. We aimed to conduct a systematic review and meta-analysis of studies assessing compliance and clearance to determine the optimal time of first PVSA. Methods: Databases (MEDLINE, EMBASE, POPLINE) were searched for studies that contained the following: rate of azoospermia and rare nonmotile sperm (RNMS), compliance, recanalization, persistent RNMS, pregnancies, and incidence of repeat vasectomy. Results: A total of 28 studies were included in this review. The patient compliance was 47–100% and trended downward with increasing time to first PVSA. There was a positive trend in azoospermia rate as post-vasectomy time increased, but this plateaued at 8 weeks. Compliance and post-vasectomy semen analysis clearance (PVSAC) converged at 5.7 weeks, with rates of 74.5% and 74.6%, respectively. A proportion of 1.5% of patients exhibited persistent RNMS. Recanalization events had an incidence rate of 1.5%. Repeat vasectomies were performed in 1.6% of patients. Conclusions: Based on our study optimizing post-vasectomy semen clearance with follow-up compliance, we recommend initial PVSA between 6 to 18 weeks post-vasectomy, as this offers improved compliance over current AUA guidelines which recommend PVSA at 8 to 16 weeks and allows for the identification of instances of “subclinical recanalization” that may be missed at later time points.

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole, which inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. The increase in Letrozole resistance poses a unique problem for patients. To better understand the underlying molecular mechanism(s) of Letrozole resistance, we reanalyzed transcriptomic data by comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two significant differentially expressed genes (DEGs) between these patient cohorts, with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 gene products as being the top mechanistic transcriptional markers for ER+ treatment resistance. Many of the significant DEGs that we identified play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified are novel in the context of ER+ breast cancer. Many of the genes that we identified warrant further research to elucidate the more specific molecular mechanisms of Letrozole resistance in this patient population and could potentially be used as prognostic markers with further wet lab validation. We anticipate that these findings could contribute to improved detection and therapeutic outcomes in aromatase-resistant ER+ breast cancer patients.

Introduction: Currently, there is limited evidence for the relationship of Exosome-based Prostate Intelliscore (EPI) and multiparametric magnetic resonance imaging (mpMRI) in stratifying risk for clinically significant prostate cancer. Using a retrospective cohort study design, we sought to characterize the relationship between these two noninvasive metrics and prostate biopsy outcome. Methods: Data were collected via electronic medical record for all patients who underwent EPI testing from 1 January 2019 to 3 February 2022 and had available medical records at a single mid-western university medical center. Positive test result was defined as >15.6 for EPI, ≥3 PI-RADS score and ≥3 + 4 Gleason Score for biopsy findings. Utility of EPI, mpMRI and combined use was characterized through calculation of sensitivity, specificity, positive predictive value, negative predictive value, and ROC analysis. Results: A total of 226 patients were identified as receiving EPI testing for risk stratification of clinically significant prostate cancer. Sensitivity for EPI was 91%, mpMRI was 90%, and the highest was combined use at 96%. With ROC analysis, AUC for EPI alone was 0.57 (95% CI, 0.47–0.67) and 0.78 (95% CI, 0.70–0.87) for mpMRI alone. With prior positive EPI result, AUC for combined use with mpMRI was 0.80 (95% CI, 0.71–0.89). Further subgroup analysis resulted in increased AUC values of EPI 0.67 (95% CI, 0.48–0.87), mpMRI 0.90 (95% CI, 0.76–1.0), and combined 0.90 (95% CI, 0.75–1.0) in the African American population. Discussion: We observed that the combined use of EPI and mpMRI led to an avoided biopsy in 43% of patients. Using both parameters increased the overall sensitivity and diagnostic accuracy in detecting clinically significant prostate cancer. The best test performance was observed in the African American cohort. Identifying optimal noninvasive tools to assess risk for prostate cancer is crucial to providing accurate and cost-effective care. Future study should utilize a prospective study design to further support the combined use of these metrics.