Faculty Bibliography

BACKGROUND:Prostate cancer (PCa) diagnosis and treatment can have a significant negative impact on sexual health, affecting patients and their partners; however, the impact on partners is insufficiently addressed in current practice. OBJECTIVE:We describe the development and validation of an instrument to measure sexual health in female partners of patients with PCa. DESIGN, SETTING, AND PARTICIPANTS/METHODS:Questions assessing sexual health were developed through a literature review, two qualitative studies, and an expert consensus process. Candidate survey items were tested through cognitive interviews and used to iteratively refine the questionnaire. INTERVENTION/METHODS:The final questionnaire was tested in a validation study among 200 female partners. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS/METHODS:We performed an exploratory factor analysis, followed by an analysis for internal validity, test-retest reliability, and convergent and discriminant validity. RESULTS AND LIMITATIONS/CONCLUSIONS:An initial set of 32 items was developed and refined through cognitive interviews. The resulting 27-item questionnaire was tested among 200 female partners of patients with PCa from across the USA. The exploratory factor analysis eliminated eight items and revealed seven key factors: (1) distress/satisfaction, (2) loss of connection as a couple, (3) active communication, (4) discomfort with communication, (5) frustration with sexual counseling, (6) expansion of sexual repertoire, and (7) nonpenetrative sexual activity. The overall scale demonstrated strong internal consistency (ordinal alpha 0.94) and test-retest reliability (0.89). Strengths of the study include development and evaluation of the first questionnaire to evaluate sexual quality of life among female partners of patients with PCa. However, additional work is needed to assess sexual health and quality of life among male and nonbinary partners. CONCLUSIONS:We developed a new instrument, the Sexual Concerns In Partners of Patients with Prostate cancer (SCIPPP-F), and found it to be valid in a diverse sample of female partners across the USA. PATIENT SUMMARY/RESULTS:Our new instrument can be used to characterize sexual health among female partners of patients with prostate cancer.

IMPORTANCE/UNASSIGNED:The US health care sector accounts for about 8.5% of national greenhouse gas (GHG) emissions. Reliable estimates of emissions associated with health care-related travel are essential for informing policy changes. OBJECTIVE/UNASSIGNED:To generate a comprehensive national estimate of carbon emissions due to patient health care-related travel in the US. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cross-sectional study used data from the 2022 National Household Travel Survey (NHTS), conducted from January 2022 to January 2023. Participants were selected using an address-based sample from the US Postal Service Delivery Sequence File. Participating households reported all trips taken within 24 hours by all household members aged 5 years or older. Approximate emissions per mile were obtained from typical vehicle emissions data provided by US government institutions. Data were analyzed between March 11 and May 29, 2024. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Estimated annual CO2 equivalent (CO2e) emissions from patient health care-related travel per year, per patient, per trip, and per mile. A survey-weighted λ regression analysis was used to identify factors associated with higher CO2e emissions per trip. An alternative scenario analysis estimated reductions if 30% or 50% of private vehicle users switched to electric vehicles. RESULTS/UNASSIGNED:The sample included 16 997 participants with a weighted total of 3 506 325 536 US health care trips. Of these trips, 52.0% were reported by female travelers, 80.1% were made in urban areas, and 19.9% were made in rural areas. These trips accounted for 84 057 963 340 miles, resulting in weighted annual estimated emissions of 35.7 megatons (Mt) (95% CI, 27.5-43.9 Mt) CO2e. Each mile traveled generated an estimated 424 g (95% CI, 418-428 g) CO2e. Emissions per trip were higher (exponentiated coefficient [exp(β)], 2.19; 95% CI, 1.51-2.86; P < .001) for rural patients compared with urban patients. However, 69.3% of emissions were attributable to urban patients and 30.7% to rural patients. Patients with annual median household incomes of $50 000 to $99 999 generated higher trip emissions (exp[β], 1.92; 95% CI, 1.09-2.76; P = .003) compared with those with incomes of $25 000 or less. A 30% shift to electric vehicles was estimated to reduce health care-related carbon emissions to 27.6 Mt (95% CI, 20.7-34.6 Mt) CO2e, and a 50% shift was estimated to lower emissions to 22.3 Mt (95% CI, 16.0-28.6 Mt) CO2e. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This cross-sectional study estimated that annual patient health care-related travel in the US generated 35.7 Mt CO2e, which accounts for a small but important proportion of total health care-related emissions in the US. These findings are essential for informing health care policy decisions and suggest that strategies such as telehealth and the adoption of electric vehicles may contribute to a small but significant reduction in health care-related GHG emissions.

BACKGROUND AND OBJECTIVE/OBJECTIVE:As most Prostate Imaging Reporting and Data System (PI-RADS) 5 lesions on MRI harbor Gleason grade (GG) group ≥2 disease on biopsy, optimal management of patients with imaging-biopsy discordance remains unclear. To estimate grade misclassification, we evaluated the incidence of Gleason upgrading among patients with GG1 disease in the setting of a PI-RADS 5 lesion. METHODS:We conducted a single-institution retrospective analysis to identify patients with GG1 prostate cancer on fusion biopsy with MRI demonstrating ≥1 PI-RADS 5 lesion. Primary study outcome was identification of ≥GG2 disease on subsequent active surveillance (AS) biopsy or radical prostatectomy (RP). We used multivariable models to examine factors associated with reclassification. RESULTS:We identified 110 patients with GG1 disease on initial biopsy and ≥1 PI-RADS 5 lesion. There were 104 patients (94.6%) initially managed with AS and 6 (5.5%) received treatment. Sixty-one patients (58.7%) on AS underwent additional biopsies. Of these, 43 (70.5%) patients had tumor upgrading, with 32 (74.4%) upgraded on first surveillance biopsy. Forty-four (40%) patients ultimately received treatment, including prostatectomy in 15 (13.6%) and radiation in 25 (22.7%). Two patients (1.8%) developed metastases. In multivariable models, genomic classifier score was associated with upgrading. Limitations include a lack of multi-institutional data and long-term outcomes data. CONCLUSIONS:Most patients diagnosed with GG1 prostate cancer on MRI-Ultrasound fusion biopsy in the setting of a PI-RADS 5 lesion were found to have ≥GG2 disease on subsequent tissue sampling, suggesting substantial initial misclassification and reinforcing the need for confirmatory testing.

BACKGROUND:Germline testing is important in prostate cancer and evaluation can be complex. METHODS:We instituted a monthly multi-disciplinary virtual genetics tumor board (7/2021-3/2022). Participants and panelists were surveyed on usefulness and acceptability. RESULTS:101 participants attended a session, and 77 follow-up surveys were completed. Over 90% participants and 100% panelists endorsed usefulness of the case discussions and usability of the technology. The majority felt it provided new information they will use. CONCLUSIONS:A multidisciplinary genetics board was successfully developed to address complexity in prostate cancer genetics. The virtual platform may enhance dissemination of expertise where there are regional gaps.

PURPOSE OF REVIEW/OBJECTIVE:Artificial intelligence (AI) chatbots are increasingly used as a source of information. Our objective was to review the literature on their use for patient education in urology. RECENT FINDINGS/RESULTS:There are many published studies examining the quality of AI chatbots, most commonly ChatGPT. In many studies, responses from chatbots had acceptable accuracy but were written at a difficult reading level without specific prompts to enhance readability. A few studies have examined AI chatbots for other types of patient education, such as creating lay summaries of research publications or generating handouts. SUMMARY/CONCLUSIONS:Artificial intelligence chatbots may provide an adjunctive source of patient education in the future, particularly if prompted to provide results with better readability. In addition, they may be used to rapidly generate lay research summaries, leaflets or other patient education materials for final review by experts.

Much of the disease nomenclature used for patients with advanced prostate cancer has negative connotations and can be confusing or intimidating. Experts in the field convened to recommend a clearer and more accurate approach to defining the nomenclature.

BACKGROUND AND OBJECTIVE/OBJECTIVE:Innovations have improved outcomes in advanced prostate cancer (PC). Nonetheless, we continue to lack high-level evidence on a variety of topics that greatly impact daily practice. The 2024 Advanced Prostate Cancer Consensus Conference (APCCC) surveyed experts on key questions in clinical management in order to supplement evidence-based guidelines. Here we present voting results for questions from APCCC 2024. METHODS:Before the conference, a panel of 120 international PC experts used a modified Delphi process to develop 183 multiple-choice consensus questions on eight different topics. Before the conference, these questions were administered via a web-based survey to the voting panel members ("panellists"). KEY FINDINGS AND LIMITATIONS/UNASSIGNED:Consensus was a priori defined as ≥75% agreement, with strong consensus defined as ≥90% agreement. The voting results show varying degrees of consensus, as discussed in this article and detailed in the Supplementary material. These findings do not include a formal literature review or meta-analysis. CONCLUSIONS AND CLINICAL IMPLICATIONS/CONCLUSIONS:The voting results can help physicians and patients navigate controversial areas of clinical management for which high-level evidence is scant or conflicting. The findings can also help funders and policymakers in prioritising areas for future research. Diagnostic and treatment decisions should always be individualised on the basis of patient and cancer characteristics, and should incorporate current and emerging clinical evidence, guidelines, and logistic and economic factors. Enrolment in clinical trials is always strongly encouraged. Importantly, APCCC 2024 once again identified important gaps (areas of nonconsensus) that merit evaluation in specifically designed trials.

Urological diseases and their varied forms of management warrant special attention in the setting of climate change. Regarding urological cancers, climate change will probably increase the incidence and severity of cancer diagnoses through exposures to certain environmental risk factors, while simultaneously disrupting cancer care delivery and downstream outcomes. Regarding benign urological diseases, a burgeoning body of work exists on climate-related heat waves, dehydration, urolithiasis, renal injury and infectious and vector-borne diseases. Adding to the potential effect on disease pathogenesis, many patients with urological diseases undergo high-tech, resource-intensive interventions, such as robotic surgery, and entail intensive longitudinal assessments over many years. These features incur a considerable carbon footprint, generate substantial waste, and can introduce vulnerabilities to climate-related weather events. Links exist between planetary health (the health of humans and the natural systems that support our health), climate change and urological disease and urological care providers face many challenges in the era of anthropogenic climate change. The next steps and priorities for research, management, and health care delivery include identification and prioritization of health care delivery strategies to minimize waste and carbon emissions, while supporting climate resilience. Examples include supporting telemedicine, limiting low-value care, and building resilience to minimize impacts of climate-related disasters to prepare for the challenges ahead.