Patient experiences with tissue-based genomic testing during active surveillance for prostate cancer.

Background: Tissue-based gene expression (genomic) tests provide estimates of prostate cancer aggressiveness and are increasingly used for patients considering or engaged in active surveillance. However, little is known about patient experiences with genomic testing and its role in their decision-making. Methods: We performed a qualitative study consisting of in-depth, semi-structured interviews of patients with low- or favourable-intermediate-risk prostate cancer managed with active surveillance. We purposively sampled to include patients who received biopsy-based genomic testing as part of clinical care. The interview guide focused on experiences with genomic testing during patients' decision-making for prostate cancer management and understanding of genomic test results. We continued interviews until thematic saturation was reached, iteratively created a code key and used conventional content analysis to analyse data. Results: Participants' (n = 20) mean age was 68 years (range 51-79). At initial biopsy, 17 (85%) had a Gleason grade group 1, and 3 (15%) had a grade group 2 prostate cancer. The decision to undergo genomic testing was driven by both participants and physicians' recommendations; however, some participants were unaware that testing had occurred. Overall, participants understood the role of genomic testing in estimating their prostate cancer risk, and the test results increased their confidence in the decision for active surveillance. Participants had some misconceptions about the difference between tissue-based gene expression tests and germline genetic tests and commonly believed that tissue-based tests measured hereditary cancer risk. While some participants expressed satisfaction with their physicians' explanations, others felt that communication was limited and lacked sufficient detail. Conclusion: Patients interact with and are influenced by the results of biopsy-based genomic testing during active surveillance for prostate cancer, despite gaps in understanding about test results. Our findings indicate areas for improvement in patient counselling in order to increase patient knowledge and comfort with genomic testing.

Association between sociodemographic factors and diagnosis of lethal prostate cancer in early life.

OBJECTIVE: A subset of patients are diagnosed with lethal prostate cancer (CaP) early in life before prostate-specific antigen (PSA) screening is typically initiated. To identify opportunities for improved detection, we evaluated patient sociodemographic factors associated with advanced vs. localized (CaP) diagnosis across the age spectrum. METHODS: We conducted a retrospective cohort study using the National Cancer Database, identifying patients diagnosed with CaP from 2004 to 2020. We compared characteristics of patients diagnosed at the advanced (cN1 or M1) versus localized (cT1-4N0M0) stage. Using multivariable logistic regression, we evaluated the associations among patient clinical and sociodemographic factors and advanced diagnosis, stratifying patients by age as ≤55 (before screening is recommended for most patients), 56 to 65, 66 to 75, and ≥76 years. RESULTS: We identified 977,722 patients who met the inclusion criteria. The mean age at diagnosis was 65.3 years and 50,663 (5.1%) had advanced disease. Overall, uninsured (OR = 3.20, 95% CI 3.03-3.78) and Medicaid-insured (OR 2.58, 95% CI 2.48-2.69) vs. privately insured status was associated with higher odds of diagnosis with advanced disease and this effect was more pronounced for younger patients. Among patients ≤55 years, uninsured (OR 4.14, 95% CI 3.69-4.65) and Medicaid-insured (OR 3.39, 95% CI 3.10-3.72) vs. privately insured patients were associated with higher odds of advanced cancer at diagnosis. Similarly, residence in the lowest vs. highest income quartile was associated with increased odds of advanced CaP in patients ≤55 years (OR 1.15, 95% CI 1.02-1.30). Black vs. White race was associated with increased odds of advanced CaP at diagnosis later in life (OR 1.17, 95% CI 1.09-1.25); however, race was not significantly associated with advanced stage CaP in those ≤55 years (P = 0.635). CONCLUSIONS: Sociodemographic disparities in diagnosis at advanced stages of CaP were more pronounced in younger patients, particularly with respect to insurance status. These findings may support greater attention to differential use of early CaP screening based on patient health insurance.

Implant Survival and Patient-Reported Outcomes After Total Hip Arthroplasty in Young Patients.

BACKGROUND: Younger patients are undergoing total hip arthroplasty (THA) for various conditions that affect the hip joint. This study evaluates the implant survival and long-term patient-reported outcomes of THA in patients aged 35 years or younger. METHODS: Data were collected through a retrospective chart review, and follow-up surveys were conducted to determine implant survival and patient-reported outcomes. Kaplan-Meier survival analysis was performed to evaluate implant survival, and the hip disability and osteoarthritis outcome score (HOOS) was used to describe patient-reported outcomes. Descriptive statistics were used to summarize baseline and follow-up data, and univariate and multivariate analyses were used to compare implant survival and patient-reported outcomes. RESULTS: This study included 400 patients (548 THAs). The average age at the time of surgery was 27 (range: 8-35) years, and the mean time to follow-up was 14 (range: 2-29.7) years. The 10- and 20-year implant survival was 87% and 61%, respectively. Implant survival differed based on primary diagnosis (P = .05), and it was significantly better in patients aged 25 years or older at the time of surgery, male patients, and patients with ceramic-on-ceramic or ceramic-on-plastic implants (P < .05). Mean HOOS scores at follow-up were 86 for pain, 84 for symptoms, 86 for ADLs, and 77 for sports. All HOOS scores were significantly worse after revision THA (P < .01). CONCLUSION: Young patients have good implant survival and favorable long-term outcomes after THA. There are several predictors of implant survival and patient-reported outcomes after THA in young patients.