Faculty Bibliography

PURPOSE/OBJECTIVE:Prostate cancer (PCA) germline testing (GT) informs precision therapy, cancer screening, and hereditary cancer risk for patients and families. To support patient-centered PCA GT, studying patient-reported outcomes (PROs) is essential. METHODS:PROGRESS was a national patient-driven registry (January 2021-April 2022) for English-speaking males older than 18 years with previous/current PCA GT and Internet access. Surveys collected demographics, PCA history, family cancer history, mode of genetics care delivery, satisfaction with genetic counseling, decisional conflict, cancer genetics knowledge, and attitudes toward GT. Multiple linear regression modeling was used to estimate and draw inferences (α = .05) on strength of relationships between participant characteristics and PROs. RESULTS:Analyses focused on 414 participants: White (88%), Black (3%), Asian (6%), and mixed/other (3%). Most participants were non-Hispanic (95.2%) and 46.9% had PCA. Genetic results were positive (pathogenic/likely pathogenic variants; mutations) in 27.9%. The three most common modes of genetics care were meeting with genetics professional (in-person or remotely; 30.9%), discussing with doctor (21.1%), and using website (20.8%). In covariate-adjusted models, satisfaction scores were highest with pretest counseling by phone (β = 1.31; 95% CI, 0.26 to 2.36) or discussion with doctor (β = 1.25; 95% CI, 0.38 to 2.12). Lower decisional conflict scores were reported for pretest counseling by phone (β = -3.76; 95% CI, -7.28 to -0.24). Males with mutations reported higher GT benefit scores (β = .30; 95% CI, 0.02 to 0.59) and importance of GT (β = .34; 95% CI, 0.08 to 0.61). Asian Americans reported lower GT satisfaction (β = -2.91; 95% CI, -4.34 to -1.48) and higher decisional conflict (β = 8.93; 95% CI, 4.36 to 13.51). CONCLUSION/CONCLUSIONS:PROGRESS Registry informs the first comprehensive report of PROs among males undergoing PCA GT, providing insights into opportunities to improve patient experience and leverage the benefit of GT.

BACKGROUND:Hispanic/Latinx males and those who are non-English proficient are significantly less likely to receive germline genetic evaluation for prostate cancer. Undertesting can impact downstream outcomes, including reduced access to approved targeted therapies, barriers to precision medicine trials, and hereditary cancer assessment for patients and family members. The goal of our study was to explore the knowledge and perceptions of genetic testing among U.S. Hispanic males, with the ultimate goal to identify potentially actionable targets to increase guideline-concordant genetic evaluation. METHODS:We conducted a nationwide online survey including U.S. Hispanic males aged ≥ 40 in English and Spanish using the 9-item Knowledge of Hereditary Prostate Cancer Scale and adapted questions about desire for more information from the Behavioral Beliefs about BRCA Genetic Counseling scale. RESULTS:Among 807 participants, the mean score for genetic knowledge was 5.8 out of 9, with gaps in understanding of incomplete penetrance of genes and maternal genetic inheritance. Medical mistrust and lower health literacy were associated with significantly lower knowledge of prostate cancer genetics. Overall, attitudes toward genetic counseling were favorable, with the majority of participants endorsing that it would help with decision-making, is concordant with cultural beliefs, and that they were interested in more information. Concerns about genetic evaluation included cost and impact for insurance. CONCLUSIONS:Despite generally favorable attitudes toward genetic evaluation among Hispanic males, there are important knowledge gaps, including the importance of both maternal and paternal family history, as well as logistical concerns. Addressing these gaps through culturally targeted outreach may help to promote equitable uptake of germline genetic evaluation.

IMPORTANCE/UNASSIGNED:The rise in chatbot health advice (CHA) studies is accompanied by heterogeneity in reporting standards, impacting their interpretability. OBJECTIVE/UNASSIGNED:To provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, 3 synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. RESULTS/UNASSIGNED:CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of CHA studies. These include title (subitem 1a), abstract or summary (subitem 1b), background (subitems 2ab), model identifiers (subitem 3ab), model details (subitems 4abc), prompt engineering (subitems 5ab), query strategy (subitems 6abcd), performance evaluation (subitems 7ab), sample size (subitem 8), data analysis (subitem 9a), results (subitems 10abc), discussion (subitems 11abc), disclosures (subitem 12a), funding (subitem 12b), ethics (subitem 12c), protocol (subitem 12d), and data availability (subitem 12e). CONCLUSIONS AND RELEVANCE/UNASSIGNED:The CHART checklist and corresponding methodological diagram were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of CHA studies.

BACKGROUND:The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice, referred to as Chatbot Health Advice (CHA) studies. METHODS:CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, three synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. RESULTS:CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of CHA studies. These include Title (subitem 1a), Abstract/Summary (subitem 1b), Background (subitems 2ab), Model Identifiers (subitems 3ab), Model Details (subitems 4abc), Prompt Engineering (subitems 5ab), Query Strategy (subitems 6abcd), Performance Evaluation (subitems 7ab), Sample Size (subitem 8), Data Analysis (subitem 9a), Results (subitems 10abc), Discussion (subitems 11abc), Disclosures (subitem 12a), Funding (subitem 12b), Ethics (subitem 12c), Protocol (subitem 12d), and Data Availability (subitem 12e). CONCLUSION/CONCLUSIONS:The CHART checklist and corresponding methodological diagram were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of CHA studies.

The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice, referred to as Chatbot Health Advice (CHA) studies. CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, three synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of CHA studies. These include Title (subitem 1a), Abstract/Summary (subitem 1b), Background (subitems 2ab), Model Identifiers (subitem 3ab), Model Details (subitems 4abc), Prompt Engineering (subitems 5ab), Query Strategy (subitems 6abcd), Performance Evaluation (subitems 7ab), Sample Size (subitem 8), Data Analysis (subitem 9a), Results (subitems 10abc), Discussion (subitems 11abc), Disclosures (subitem 12a), Funding (subitem 12b), Ethics (subitem 12c), Protocol (subitem 12d), and Data Availability (subitem 12e). The CHART checklist and corresponding methodological diagram were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of CHA studies.

BACKGROUND:Potential rural-urban differences in prostate cancer care are understudied, particularly regarding the utilization of advanced diagnostic tests. Herein we examined variations in Positron Emission Tomography (PET) utilization for prostate cancer care, including diagnosis, staging and treatment planning, across residential regions in the United States. METHODS:Patients newly diagnosed with prostate cancer between 2019 and 2021 and post-diagnostic PETs were identified using full Medicare claims data. PET use was assessed in all newly diagnosed patients, though indications vary by risk. Patients' counties were categorized as metro, urban, or rural, from most to least urbanized. Regional PET utilization was further examined at the level of hospital referral regions. A multivariable logistic regression model was performed to assess the impact of rurality on PET imaging. A secondary analysis included an interaction term for race to explore the effect of residence on PET imaging by racial group. RESULTS:Overall, 495 865 patients were included in the analysis: 393 861 (79.4%) lived in metro, 56 698 (11.4%) in urban and 39 707 (8.0%) in rural counties. Patients in metro counties underwent PET imaging more often (8.4%) than patients in urban (7.3%) or rural counties (7.2%), p < 0.0001. At a level of hospital referral region, PET utilization rates ranged from 2.2 to 20.8%. PET imaging was more commonly performed in White compared to Black or Hispanic patients. Rural patients were less likely to undergo PET imaging compared to metro patients (odds ratio [OR] 0.87, 95% Confidence interval [CI]: 0.82-0.92 p < 0.0001). Rural Black (OR 0.69, 95%CI 0.57-0.83, p < 0.0001) and rural White patients (OR 0.89, 95%CI 0.83-0.94 p < 0.0001) were less likely to obtain PET imaging compared to their metro counterparts, p-interaction < 0.0001. CONCLUSION/CONCLUSIONS:Rural patients were less likely to undergo PET imaging than metro patients. The effect of rurality was most pronounced among Black patients. Our findings underscore the need for strategies to support equitable use of PET imaging.

BACKGROUND:Personalized therapeutic approaches for localized prostate cancer have evolved significantly, with tissue-based biomarker tests supplementing traditional risk stratification tools. However, national testing patterns and geographic variability remain limited a decade after coverage implementation. We aimed to assess current nationwide utilization and urban-rural differences in tissue-based biomarker testing. METHODS:Using full Medicare claims data, we retrospectively identified patients with newly diagnosed prostate cancer and tissue-based biomarker testing claims from 2019 to 2023. Patients' county of residence was categorized as metro, urban, or rural. Regional testing rates were further assessed across hospital referral regions. A multivariable logistic regression model was performed to assess the effect of residence on test receipt. RESULTS:Our final cohort included 749,202 patients, of whom 79.5% lived in metro, 11.4% in urban and 8.00% in rural counties. Overall, 86,908 (11.6%) patients underwent tissue-based biomarker tests. Hospital referral region-level testing rates ranged from 2.4% to 42.7%. Rural patients were 18% less likely to undergo testing compared to metro patients (Odds Ratio [OR] 0.82 95% Confidence Interval [CI] 0.73-0.91). Independently, the odds of undergoing testing were lower among Black (OR 0.82, 95% CI 0.77-0.88) and Hispanic patients (OR 0.80, 95% CI 0.73-0.88) compared to White patients. CONCLUSION/CONCLUSIONS:This study reveals high geographic variability in tissue-based biomarker testing for prostate cancer. Further, Black and Hispanic patients were less likely to receive testing. Our findings highlight regional practice variation in the use of advanced, not routinely recommended tests and underscore the need to minimize disparities in diagnostic access.