BACKGROUND:Smoking may negatively affect health-related quality of life (HRQOL) in prostate cancer survivors, even though it is not a smoking-related malignancy. The longitudinal association of smoking with HRQOL was evaluated by focusing on intensity and duration. METHODS:Patients from the population-based North Carolina Prostate Cancer Comparative Effectiveness and Survivorship Study, enrolled via the state cancer registry (2011-2013), were analyzed. HRQOL was measured with the Short Form 12 instrument at intervals of up to 5 years posttreatment. Smoking status was self-reported. Linear and mixed-effects models assessed associations with controlling for age, treatment, and time. RESULTS:Of 842 participants, 474 underwent prostatectomy, 258 had radiation therapy, and 110 had brachytherapy. Concurrent smoking was associated with worse general health, mental health, and physical functioning (all p < .05). Graded analysis revealed a significant dose response, with smoking ≥1 pack/day linked to the greatest declines in general health (β = -3.25; p < .001) and physical functioning (β = -2.35; p = .003) at 5 years. CONCLUSIONS:Smoking demonstrates significant concurrent and longitudinal associations with poorer HRQOL in prostate cancer survivors, with a clear dose-response pattern. These results underscore the critical need to integrate structured smoking assessment and cessation support as a core component of comprehensive prostate cancer survivorship care.

Despite high survival rates, testicular cancer survivors face unique, long-term survivorship challenges. Given the demographics of this population, online resources are well-positioned to provide support, yet substantial barriers persist. This study aims to understand how testicular cancer survivors currently use online support resources and to identify their preferences for a future online support platform. For this qualitative descriptive study, survivors of testicular cancer were recruited from a survivorship research registry, a survivorship clinic, and a community organization. Researchers conducted telephone interviews on care experiences, survivorship needs, online resource use, and online support preferences. Data were analyzed through thematic analysis with consensus coding and narrative summaries. Twenty-two testicular cancer survivors were interviewed (median age at diagnosis 30 years old; median survivorship 6 years). Participants used a range of online resources, including medical websites to meet their informational needs and social media to address their experiential and emotional needs. While online resources provided a repository of readily accessible information, multiple issues can limit trust and engagement and cause emotional distress. In envisioning a future survivorship support platform, participants sought a safe, trusted, and user-friendly environment. Desired features include up-to-date medical information personalized to disease type and stage; verified content with moderation and community standards to foster trust; linking information to instrumental support to promote survivorship; and testimonials, peer navigation, and interactive discussion spaces for connection, support, and community. Survivors of testicular cancer expressed strong preferences for a dedicated, online support platform that integrates reliable medical content with community. These results can guide the development and implementation of evidence-based online survivorship programs and digital health interventions to improve long-term well-being and quality of life among testicular cancer survivors.

Introduction Decision-making for T1 renal masses has become increasingly complex as more management options have become available. Most patients experience decisional conflict at some point in their decision-making process due to fear, uncertainty, and lack of understanding. Furthermore, decisional conflict may prompt patients to undergo a treatment that does not necessarily align with their priorities or values. For medical decisions, patients have a variety of unique support needs that impact their decision-making process, preferences, and treatment choice. To better support these patient needs, we sought to characterize support needs and coping mechanisms for patients presenting for small renal masses (SRM). Methods Forty patients previously enrolled onto the GRADE-SRM study, a prospective clinical trial examining cancer genomics and the impact of renal mass biopsy on decision-making, were recruited to participate in a follow-up qualitative study. Participants were purposely sampled based on high (21) vs. low (19) decisional conflict scores as well as diverse support needs and coping strategies. Trained qualitative researchers conducted semi-structured interviews asking participants questions related to decision-making support needs including factors that impacted their decision-making preferences and coping strategies. Qualitative researchers then conducted a coding-based thematic analysis to define pertinent themes regarding patient support needs that impact decision-making. Further post hoc analysis was conducted to synthesize and describe support needs and coping mechanisms across the cohort. Results Among the 40 interview participants, the mean age was 65.1, with 58% male and 72.5% White. A primary focus on either preparation/process or health outcomes tended to drive individual support needs. A focus on process entailed steps in management and the overall journey while a focus on outcomes encompassed impact on survival or other health effects. Patient support needs fell into three main categories that were identified in post hoc analysis: informational, emotional, and instrumental support. Within each category, patients desired support from both their healthcare team and personal support system. Informational supports included medical counseling from their urologist and advice externally. Patients required emotional support from both medical and social sources but mainly desired instrumental support from their social network. Patients described coping mechanisms employed from diagnosis through treatment. These fell into four categories: relying on faith, controlling outlook, depending on external support, and trusting in their urologist. Conclusions Patients display a diverse range of support needs and coping strategies during the process of diagnosis and decision-making for clinical T1 renal masses that we can overwhelmingly categorize into discrete subtypes. Further, patient support needs tend to be driven by either a focus on process or outcome. These findings provide further understanding and context for how support needs may be used to promote shared decision-making. Efforts to improve the decision-making process may consider support needs, drivers, and coping mechanisms during development.

Although there are more than 3.5 million prostate cancer survivors in the United States, unmet needs in this population have not been fully characterized. In a population-based, prospective cohort of prostate cancer survivors, we assessed unmet needs in long-term survivors and whether racial disparities exist. The North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study is an observational cohort that enrolled patients with newly diagnosed prostate cancer throughout North Carolina from 2011 to 2013, in collaboration with the state's cancer registry, and followed these patients prospectively with patient-reported data, medical records, and cancer registry data. A total of 645 Black and White participants completed the validated Cancer Survivors' Unmet Needs (CaSUN) survey at 7 to 10 years after treatment. A total of 29.4% of prostate cancer survivors indicated at least 1 unmet need. Three most common unmet needs (related to sex life, financial support, and coordination of care) were each indicated by more than 11% of the cohort. Across all 35 CaSUN need items, a higher proportion of Black vs White prostate cancer survivors indicated an unmet need; in 24 (69%) items, this difference was statistically significant. Multivariable logistic regression showed that Black race (OR 1.73, P = .03) and younger age (OR .96/y, P = .02) were associated with increased odds of having an unmet need. A sizable portion of long-term prostate cancer survivors have at least 1 unmet need, and racial disparities exist. This study demonstrates that significant opportunities exist to identify, understand, and better address the needs of long-term cancer survivors.

Rural patients face unique barriers in obtaining high-quality cancer care. Research is lacking in determining whether these disparities translate to negative clinical outcomes. To determine if there are differences in the rate of biochemical recurrence in prostate cancer between rural and urban men. This cohort study used patient data that was abstracted from the North Carolina Prostate Cancer Comparative Effectiveness and Survivorship Study, a population-based cohort that prospectively followed patients with newly diagnosed prostate cancer from the Rapid Case Ascertainment system of the North Carolina Central Cancer Registry from January 1, 2011, to June 30, 2013. Patients were identified who had received either surgery or radiation within 1 year of diagnosis. Data were analyzed from January 2011 to December 2022. Patients were categorized as rural or urban using the Rural-Urban Continuum Code. Recurrence was determined by prostate-specific antigen testing. Demographic differences between rural and urban patients were assessed using 2-sample independent t test and χ2 test. Prostate cancer recurrence was analyzed using Cox proportional hazard models. A total of 778 patients were included with a median (IQR) follow-up of 4.6 (2.0 to 6.9) years and a mean (SD) age of 63 (7.4) years. Additionally, 213 were Black men (27.4%), 565 were White men (72.6%), 350 were Medicare insured (45.1%), 324 had an income ranging from $40 000 to $90 000 (43.1%), 370 were a National Comprehensive Cancer Network (NCCN) intermediate risk group (47.6%), 449 were treated with radical prostatectomy (57.7%), and 690 were in good to excellent health (88.7%) with 191 living in a rural setting (24.6%). On univariable analysis, rural residence (hazard ratio [HR], 2.19 [95% CI, 1.38 to 3.46]; P < .001), NCCN risk group (HR, 4.13 [95% CI, 2.25 to 7.57]; P < .001), and having had fewer than 12 biopsies (HR, 1.70 [95% CI, 1.08 to 2.67]; P = .02) were significantly associated with biochemical recurrence. On multivariable analysis adjusted for location of residence, marital status, overall health, number of cores biopsied, NCCN risk group, and treatment type, rural residence was significantly associated with recurrence (HR, 1.74 [95% CI, 1.07 to 2.82]; P = .03), while radiation therapy was inversely associated with recurrence (HR, 0.51 [95% CI, 0.31 to 0.85]; P = .01). In this cohort study of patients with newly diagnosed prostate cancer, rural patients with prostate cancer had higher rates of biochemical recurrence. The etiology of this disparity is unclear but is likely multifactorial. Factors that may play a role include socioeconomic status, delay and disruptions in care, and access to multidisciplinary cancer care.

INTRODUCTION:The rising incidence of early-stage kidney cancer has driven comparative effectiveness research using cancer registry and administrative data. These sources may be biased for small renal masses (SRM), where histologic confirmation prior to treatment is not standard. To better understand these limitations, we compared characteristics of patient populations across three SRM data sources. PATIENTS AND METHODS:We identified patients diagnosed with clinical T1 renal masses from 2019 to 2020 at our institution. Data were obtained from the institutional cancer registry, a prospective clinical trial, and electronic health record (EHR) extraction. Demographic and clinical characteristics were compared across cohorts using chi-squared, Fisher's exact testing, and multivariable regression analysis. Radiologic reports were reviewed for terminology concordance with registry inclusion criteria. RESULTS:Among 555 cases, 169 (30.5%) were in the clinical trial, 273 (49.2%) in the cancer registry only, and 113 (20.4%) from EHR extraction only. Active surveillance was more common in the EHR extraction cohort (85%) than in the registry (48%) or trial (33%) (P < .001). The registry and trial cohorts had higher Charlson Comorbidity Index scores (P < .001), and the clinical trial cohort included fewer Hispanic/Latino patients (P = .04) and non-English speakers (P < .01). Registry capture was limited by terminology in radiologic reports, with qualifying terms present in only 15% of EHR cases and 49% of delayed registry entries. CONCLUSIONS:Cohort composition differed by data source, particularly for patients undergoing active surveillance. Clinicians must recognize potential bias when interpreting findings. Standardized radiologic reporting and revised registry criteria may ensure more complete data for early-stage kidney cancer.

You have accessJournal of UrologyHealth Services Research: Practice Patterns, Quality of Life and Shared Decision Making I (MP12)1 May 2024MP12-17 UNDERSTANDING PATIENT DECISION-MAKING FOR CLINICAL T1 RENAL MASSES Katherine E. Poulos, Allison Lazard, Lixin Song, Kathryn H. Gessner, Amir Feinberg, Deborah Usinger, Randall Teal, Debra Gottsleben, Marc Bjurlin, Eric Wallen, David Johnson, Mathew C. Raynor, and Hung-Jui Tan Katherine E. PoulosKatherine E. Poulos , Allison LazardAllison Lazard , Lixin SongLixin Song , Kathryn H. GessnerKathryn H. Gessner , Amir FeinbergAmir Feinberg , Deborah UsingerDeborah Usinger , Randall TealRandall Teal , Debra GottslebenDebra Gottsleben , Marc BjurlinMarc Bjurlin , Eric WallenEric Wallen , David JohnsonDavid Johnson , Mathew C. RaynorMathew C. Raynor , and Hung-Jui TanHung-Jui Tan View All Author Informationhttps://doi.org/10.1097/01.JU.0001009376.16371.fb.17AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Patients diagnosed with clinical T1 renal masses have multiple treatment options, especially those with a small renal mass (SRM). While numerous studies have examined clinical determinants of treatment choice, the patient perspective on treatment selection remains grossly understudied despite calls for shared decision-making. Accordingly, we sought to explore the decision-making process and experience in this patient population. METHODS: We purposefully recruited 40 participants from GRADE-SRM, a prospective clinical trial studying the impact of renal mass biopsy on decision-making, based on high (21) vs. low (19) levels of decisional conflict for interviews. Trained qualitative researchers asked participants about their decision-making experience including factors that affected their management choice. Using a coding-based approach, we identified themes related to the overlying process and facilitators and barriers of treatment selection. RESULTS: Of the 40 participants, mean age was 65.1, 27.5% were non-White, and 42% were female. Patients gave five primary reasons for selecting a treatment, with the majority describing the treatment was recommended by the urologist (N=14) or only one treatment was recommended (N=12) with other primary reasons being progressively less represented (Figure 1). Of the four primary options to consider, participants reported diverse facilitators and barriers behind their selection. Across all options, selection of treatment largely revolved around patients' perception of surgeon recommendation and communication. Barriers for choosing active surveillance (AS) and biopsy often involved fear and anxiety. Barriers for AS often revolved around anxiety and fear of living with a mass or desire to resolve treatment rather than prolong care. Uniquely, many patients who chose biopsy felt it was minimally invasive or could give confirmatory information, while other patients chose against biopsy because they felt uncomfortable due to negative past experiences. CONCLUSIONS: For patients, surgeon recommendation and the options provided largely shape treatment choice. In particular, patients may be more amendable to biopsy or active surveillance if their fears and concerns were alleviated. To improve decision-making, efforts may need to be directed toward these points. Download PPT Source of Funding: This work was supported by funding from the Department of Defense © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e207 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Katherine E. Poulos More articles by this author Allison Lazard More articles by this author Lixin Song More articles by this author Kathryn H. Gessner More articles by this author Amir Feinberg More articles by this author Deborah Usinger More articles by this author Randall Teal More articles by this author Debra Gottsleben More articles by this author Marc Bjurlin More articles by this author Eric Wallen More articles by this author David Johnson More articles by this author Mathew C. Raynor More articles by this author Hung-Jui Tan More articles by this author Expand All Advertisement PDF downloadLoading ...

You have accessJournal of UrologyHealth Services Research: Practice Patterns, Quality of Life and Shared Decision Making I (MP12)1 May 2024MP12-18 SUPPORTING DECISION-MAKING FOR PATIENTS WITH CLINICAL T1 RENAL MASSES: COMMUNICATION NEEDS AND PREFERENCES Katherine E. Poulos, Allison Lazard, Lixin Song, Kathryn H. Gessner, Amir Feinberg, Deborah Usinger, Randall Teal, Debra Gottsleben, Marc Bjurlin, Eric Wallen, David Johnson, Mathew C. Raynor, and Hung-Jui Tan Katherine E. PoulosKatherine E. Poulos , Allison LazardAllison Lazard , Lixin SongLixin Song , Kathryn H. GessnerKathryn H. Gessner , Amir FeinbergAmir Feinberg , Deborah UsingerDeborah Usinger , Randall TealRandall Teal , Debra GottslebenDebra Gottsleben , Marc BjurlinMarc Bjurlin , Eric WallenEric Wallen , David JohnsonDavid Johnson , Mathew C. RaynorMathew C. Raynor , and Hung-Jui TanHung-Jui Tan View All Author Informationhttps://doi.org/10.1097/01.JU.0001009376.16371.fb.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Decision-making for patients with clinical T1 renal masses has become increasingly nuanced and complex, with most patients experiencing decisional conflict at some point in their decision-making process. Given the emerging link between communication and decisional conflict, we sought to explore patient communication needs and preferences to better support patient decision-making for clinical T1 renal masses. METHODS: We recruited patients previously enrolled in GRADE-SRM, a prospective clinical trial investigating decision-making and cancer genomics, to participate in a follow-up study on decision-making and communication. Participants were sampled based on high (21) vs. low (19) decisional conflict. Trained qualitative researchers performed semi-structured interviews on the decision-making experience then conducted a coding-based analysis to define themes on communication needs and preferences that impact decision-making. RESULTS: Among 40 participants, mean age was 65.1, 58% were male and 27.5% were non-White. Patient communication needs and preferences fell into three thematic domains: content, delivery, and context (Figure 1). For content, participants desired mass-specific information, risks and benefits of treatment options (both recommended and not recommended), and clarifying treatment details, including approach, logistics, acute course, and recovery. Preferences for delivery varied greatly among patients, but overall, participants emphasized the importance of building trust with their surgeon, establishing rapport, and receiving tailored information. Overwhelmingly, patients desired to feel included in the process, which was facilitated by the surgeon encouraging patient questions, gauging patient values and priorities, and showing appreciation for their lived experiences. These two domains appeared influenced by the conditions surrounding communication (i.e., context), with participants valuing consistency of information across sources and time with their surgeon. CONCLUSIONS: Beyond content, the delivery and context in which information is communicated appear to weigh heavily on decision-making for clinical T1 masses. Efforts to improve decision-making may consider these aspects of communication in their developmental process. Download PPT Source of Funding: This work was supported by funding from the Department of Defense © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e208 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Katherine E. Poulos More articles by this author Allison Lazard More articles by this author Lixin Song More articles by this author Kathryn H. Gessner More articles by this author Amir Feinberg More articles by this author Deborah Usinger More articles by this author Randall Teal More articles by this author Debra Gottsleben More articles by this author Marc Bjurlin More articles by this author Eric Wallen More articles by this author David Johnson More articles by this author Mathew C. Raynor More articles by this author Hung-Jui Tan More articles by this author Expand All Advertisement PDF downloadLoading ...

PURPOSE Patients living in rural communities have greater barriers to cancer care and poorer outcomes. We hypothesized that rural patients with prostate cancer have less access and receive different treatments compared with urban patients. METHODS We used a population-based prospective cohort, the North Carolina Prostate Cancer Comparative Effectiveness and Survivorship Study, to compare differences in prostate cancer diagnosis, access to care, and treatment in patients by geographic residence. The 2013 rural-urban continuum code (RUCC) was used to determine urban (RUCC 1-3) versus rural (RUCC 4-9) location of residence. RESULTS Patients with rural residence comprised 25% of the cohort (364 of 1,444); they were less likely to be White race and had lower income and educational attainment. Rural patients were more likely to have <12 cores on biopsy (47.1% v 35.7%; P < .001) and less likely (40.8% v 47.6%; P = .04) to receive multidisciplinary consultation. We observed significant differences in treatment between urban and rural patients, including rural patients receiving less active surveillance or observation (22.6% v 28.7%), especially in low-risk cancer (33.2% v 40.7%). On multivariable analysis that adjusted for patient and diagnostic factors, rural residence was associated with less use of active surveillance or observation over radical treatment (ie, surgery or radiation therapy; odds ratio, 0.49 v urban; P < .001) in patients with low-risk cancer. CONCLUSION Patients with prostate cancer who live in rural versus urban areas experience several differences in care that are likely clinically meaningful, including fewer cores in the diagnostic biopsy, less utilization of multidisciplinary consultation, less use of active surveillance, or observation for low-risk disease. Future studies are needed to assess the efficacy of interventions in mitigating these disparities.

You have accessJournal of UrologyProstate Cancer: Epidemiology & Natural History I (PD29)1 May 2024PD29-03 ASSOCIATION OF SMOKING WITH CONCURRENT AND LONG-TERM HEALTH-RELATED QUALITY OF LIFE (HRQOL) OUTCOMES IN PROSTATE CANCER SURVIVORS Hannah Kay, Ram Sankar Basak, Deborah Usinger, Ronald Chen, Richard Matulewicz, Adam Goldstein, Kimberly Shoenbill, and Marc Bjurlin Hannah KayHannah Kay , Ram Sankar BasakRam Sankar Basak , Deborah UsingerDeborah Usinger , Ronald ChenRonald Chen , Richard MatulewiczRichard Matulewicz , Adam GoldsteinAdam Goldstein , Kimberly ShoenbillKimberly Shoenbill , and Marc BjurlinMarc Bjurlin View All Author Informationhttps://doi.org/10.1097/01.JU.0001008736.23117.7f.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Despite no established causal relationship between smoking and the development of prostate cancer (CaP), smoking may have negative impacts on health-related quality of life (HRQoL) among CaP survivors. Our study aims to evaluate the impact of smoking on HRQoL outcomes among survivors of CaP, and to characterize HRQoL outcomes based on intensity and duration of tobacco use. METHODS: We analyzed patients from the North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC PROCESS). This population-based cohort study enrolled patients with newly-diagnosed localized CaP in collaboration with the NC Central Cancer Registry between January 1, 2011 & June 30, 2013 and longitudinally assessed HRQoL. The exposure variable, current smoking, was assessed at 3 months and every year following primary treatment. Linear and mixed-effects linear regression were used to analyze (standardized) HRQoL outcomes measured by the SF-12 instrument. RESULTS: A total of 842 patients responded to≥1 survey up to 60 months after diagnosis, and 499 completed the 60-month survey. 474 received prostatectomy (RALP) +/- radiation therapy (RT), 258 received RT without RALP, and 110 patients received brachytherapy (BT) without RALP or other RT. 544 patients smoked at some point during the survey collection period. Controlling for age, baseline outcome, treatment received, time since diagnosis, and subject-specific effects, concurrent smoking was associated with worse general health (GH) (mean difference (MD) = -1.12, p<0.05), mental health (MH) (MD = -1.28, p<0.05), physical function (PF) (MD = -1.58, p<0.01) but not with vitality (VT) (MD = -0.68, p=0.2) (Figure 1a-1d). CaP survivors who smoked for some or all of the survey period generally showed poorer outcomes at 5 years (Figure 1e-1h). For example, CaP survivors from each of the above smoking patterns and PF scores at 5 years, on average, about 7% points worse (p<0.01) compared to never smokers. CONCLUSIONS: There are baseline and long-term negative associations between smoking and worse HRQoL for survivors of CaP in the domains of GH, MH, and PF. These results underscore the need to treat smoking as an essential component of CaP care, with an emphasis on the longitudinal impacts of smoking on quality of life in CaP patients. Download PPT Source of Funding: Agency for Healthcare Research and Quality (AHRQ). Patient-Centered Outcomes Research Institute (PCORI) © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e619 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Hannah Kay More articles by this author Ram Sankar Basak More articles by this author Deborah Usinger More articles by this author Ronald Chen More articles by this author Richard Matulewicz More articles by this author Adam Goldstein More articles by this author Kimberly Shoenbill More articles by this author Marc Bjurlin More articles by this author Expand All Advertisement PDF downloadLoading ...

PURPOSE:Cigarette smoking is the most common risk factor for the development of bladder cancer (BC), yet there is a paucity of data characterizing the relationship between smoking status and longitudinal health-related quality of life (HRQoL) outcomes in patients with BC. We examined the association between smoking status and HRQoL among patients with BC. MATERIALS AND METHODS:Data were sourced from a prospective, longitudinal study open between 2014 and 2017, which examined HRQoL in patients aged ≥ 18 years old diagnosed with BC across North Carolina. The QLQ-C30 (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core instrument) was administered at 3, 12, and 24 months after BC diagnosis. Our primary exposure of interest was current smoking status. Linear regression using generalized estimating equations was used to analyze the relationship between smoking status and various domains of the QLQ-C30. RESULTS:A total of 154 patients enrolled in the study. Eighteen percent were classified as smoking at 3 months from diagnosis, and packs per day ranged from < 0.5 to 2. When controlling for time from diagnosis, demographic covariates, cancer stage, and treatment type, mean differences for physical function (7.4), emotional function (5.6), and fatigue measures (-8.2) were significantly better for patients with BC who did not smoke. CONCLUSIONS:Patients with BC who do not smoke have significantly better HRQoL scores in the domains of physical function, emotional function, and fatigue. These results underscore the need to treat smoking as an essential component of BC care.

You have accessJournal of UrologyHealth Services Research: Practice Patterns, Quality of Life and Shared Decision Making III (PD40)1 May 2024PD40-05 GIST OVERRIDES NUMERIC RISK PERCEPTION IN SURGICAL DECISION-MAKING Elizabeth M. Nazzal, David Gotz, Hillary Heiling, Allison M. Deal, Kara Giannone, Deborah Usinger, Susan Blalock, Antonia V. Bennett, Matthew E. Nielsen, Daniel S. Reuland, Alex Sox-Harris, Allison Lazard, Greg Sacks, Ethan Basch, and Hung-Jui Tan Elizabeth M. NazzalElizabeth M. Nazzal , David GotzDavid Gotz , Hillary HeilingHillary Heiling , Allison M. DealAllison M. Deal , Kara GiannoneKara Giannone , Deborah UsingerDeborah Usinger , Susan BlalockSusan Blalock , Antonia V. BennettAntonia V. Bennett , Matthew E. NielsenMatthew E. Nielsen , Daniel S. ReulandDaniel S. Reuland , Alex Sox-HarrisAlex Sox-Harris , Allison LazardAllison Lazard , Greg SacksGreg Sacks , Ethan BaschEthan Basch , and Hung-Jui TanHung-Jui Tan View All Author Informationhttps://doi.org/10.1097/01.JU.0001009356.04608.d5.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Despite their wide availability, risk prediction tools have had limited impact on surgical care. In a previous randomized experiment, visual and numeric risk data reduced variation in surgeon-reported numeric risk but not their recommendation for surgery. Because surgical decision-making involves both rational and intuitive processes, we further examined the impact of visual and numeric risk data on gist-based risk perceptions of cancer surgery and treatment alternatives. METHODS: Society of Urologic Oncology and American Urological Association members completed 6 clinical vignettes on prostate, kidney, and bladder cancer from May-June 2022 and were randomized to one of three exposures: visual risk data, numeric risk data, or control. For each vignette, subjects provided a gist-based estimate of benefit with surgery, harm with surgery, benefit with best alternative, harm with best alternative on a 5-point Likert scale (1: Very Low, 5: Very High). Mean ratings by exposure were compared using one-way ANOVAs, with significance level set at 0.05. RESULTS: 333 urologists participated in the survey. Across the vignettes as a whole, there was no significant effect of exposure on gist-based ratings of benefit of surgery, harm of surgery, benefit of alternative, and harm of alternative or harm (Figure 1). However, there does appear to be some effect on gist-based estimates based on training and years in practice. When examining vignettes separately, a difference in ratings of benefit of surgery was observed for Vignette C (small renal mass; [F(2,330) = 5.30, p=0.005]). In this vignette, those receiving visual data (mean=3.12, 95% CI 2.92-3.31) or numeric data (mean=3.09, 95% CI 2.92-3.26) had a lower gist-based rating of benefit for surgery than those in the control (mean=3.44, 95% CI 3.29-3.59). There was no statistically significant difference between the visual and numeric exposure. CONCLUSIONS: In contrast to its effect on numeric risk perception, visual or numeric risk data did not affect gist-based risk perception. These findings may explain the lack of impact of risk prediction tools on surgery recommendations. Efforts to improve surgical care through risk prediction tools or decision aids need to focus on how to affect intuitive as opposed to numeric risk. Download PPT Source of Funding: American Cancer Society and UNC Junior Faculty Development Award © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e821 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Elizabeth M. Nazzal More articles by this author David Gotz More articles by this author Hillary Heiling More articles by this author Allison M. Deal More articles by this author Kara Giannone More articles by this author Deborah Usinger More articles by this author Susan Blalock More articles by this author Antonia V. Bennett More articles by this author Matthew E. Nielsen More articles by this author Daniel S. Reuland More articles by this author Alex Sox-Harris More articles by this author Allison Lazard More articles by this author Greg Sacks More articles by this author Ethan Basch More articles by this author Hung-Jui Tan More articles by this author Expand All Advertisement PDF downloadLoading ...

Abstract Background Disparities in treatment selection based on socioeconomic status for prostate cancer exist. However, the association between patient-level income with treatment selection priorities and treatment received has not been studied. Methods A population-based cohort of 1382 individuals with newly diagnosed prostate cancer was enrolled throughout North Carolina prior to treatment. Patients self-reported household income and were asked about the importance of 12 factors contributing to their treatment decision-making process. Diagnosis details and primary treatment received were abstracted from medical records and cancer registry data. Results Patients with lower income were diagnosed with more advanced disease (P < .01). Cure was deemed to be “very important” by more than 90% of patients at all income levels. However, patients with lower vs higher household income were more likely to rate factors beyond cure as “very important” such as cost (P < .01), effect on daily activities (P = .01), duration of treatment (P < .01), recovery time (P < .01), and burden on family and friends (P < .01). On multivariable analysis, high vs low income was associated with increased utilization of radical prostatectomy (odds ratio = 2.01, 95% confidence interval = 1.33 to 3.04; P < .01) and decreased use of radiotherapy (odds ratio = 0.48, 95% confidence interval = 0.31 to 0.75; P < .01). Conclusions New insights from this study on the association between income and treatment decision-making priorities provide potential avenues for future interventions to reduce disparities in cancer care.

6578 Background: Men with localized prostate cancer must select from multiple treatment options, without one clear best choice. Consequently, personal factors, such as knowing other prostate cancer patients who have undergone treatment, may influence patient decision-making. However, associations between knowledge about others’ experiences and treatment decision-making among localized prostate cancer patients has not been well characterized. We used data from a population-based cohort of localized prostate cancer patients to examine whether patient-reported knowledge of others’ experiences is associated with treatment choice. Methods: The North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS) is a population-based cohort of localized prostate cancer patients enrolled from 2011-2013 throughout the state of North Carolina in collaboration with the North Carolina Central Cancer Registry. All patients were enrolled prior to treatment and followed prospectively. Patient decision-making factors including knowledge of others’ experiences with prostate cancer treatment options were collected through patient report. Patient treatment choice was determined through medical record abstraction and cancer registry data. Results: Among 1,202 patients, 17% reported knowing someone who pursued active surveillance (AS) while 28%, 46%, and 59% reported knowing someone who received brachytherapy, external beam radiation (EBRT), or radical prostatectomy (RP), respectively; 26% underwent AS, 9% brachytherapy, 21% EBRT, and 39% RP as their initial treatment. In unadjusted analyses, patients with knowledge of others’ experiences with brachytherapy, EBRT or RP had more than twice the odds of receiving that treatment compared to patients who did not. Knowledge of others’ experience with AS was not associated with choice to undergo AS. Multivariable analysis adjusting for age, race, risk group, and patient-reported goals of care showed knowledge of others’ experiences with brachytherapy (OR 4.60, 95% confidence interval [CI] 2.76 to 7.68), EBRT (OR 2.38, 95% CI 1.69 to 3.34), or RP (OR 4.02, 95% CI 2.84 to 5.70) was significantly associated with odds of receiving that treatment. The odds of receiving a particular treatment option were further increased among patients who reported knowing someone who had a “good” experience with the treatment in question. Conclusions: This is the first population-based study to directly demonstrate the impact of a patient’s knowledge of others’ experiences on treatment choice in prostate cancer. These data provide a new consideration to clinicians in their counseling of patients with newly diagnosed prostate cancer, and also impacts research into the informed decision-making process for this disease.

203 Background: Rural residence is a source of disparity in cancer access and outcomes. It is not known to what extent rurality affects access to care in patients with prostate cancer. Methods: The North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS) is a population-based cohort of newly-diagnosed prostate cancer patients. Patients were enrolled from 2011-2013 through collaboration with the state cancer registry at diagnosis and followed prospectively. Urban/rural residence was defined by the rural urban continuum code (RUCC): 1-3 (urban) and 4-9 (rural). Medical records were collected and abstracted for prostate cancer care received. Individual-level sociodemographic information was collected by patient report. Results: Among 1,456 NC ProCESS participants with a median age of 65 years, 1089 were categorized as urban and 367 (25%) rural. This is a sociodemographically diverse cohort with 30.2% non-White (including 26.9% Black), 34.1% with high school education or less, and 37.3% with household income < = $40,000. The distance to travel for diagnostic scans was greater for rural patients (miles): CT (7.5 urban vs 17.1 rural, p = 0.07), MRI (8.1 vs 12.0, p = 0.04) and bone scan (6.8 vs 14.1, p = 0.009). However, there was no difference in the percent of patients who underwent CT (15.9% urban vs 12.8% rural, p = 0.15), MRI (7.8% vs 8.2%, p = 0.81) and bone scan (15.9% vs 19.4%, p = 0.13); or the percentage of patients with high risk or metastatic disease who had any staging scan (64.2% vs 66.6% p = 0.8). While all patients consulted with a urologist, rural patients were less likely to have had consultation with a radiation oncologist (42.4% vs 35.8%, p = 0.04). Rural patients were also more likely to report that treatment was more difficult due to travel, including robotic prostatectomy (6.8% vs 13.9% p = 0.001) and radiation therapy (8.01% vs 16.07%, p = 0.001). In patients with low risk cancer, rural patients were more likely to have reported treatment at 12 months (68.2% vs 58.7% p = 0.04) instead of surveillance or observation. For high risk patients, both rural and urban patients reported high rates of treatment by 3 months (96.3% vs 91.3%, p = 0.40). After adjustment for age, income, race, education and insurance, rural residence was associated with increased likelihood of receiving treatment at 1 year (OR 1.54, CI 0.99 – 2.39) in low risk patients, but not associated with receiving treatment at 3 months (OR 3.63, CI 0.24 -54.5) among high risk patients. Conclusions: In a population-based cohort, rural patients with prostate cancer have greater barriers such as travel distance, but similar proportions of rural and urban patients received staging scans and timely treatment for high-risk prostate cancer. Rural patients were less likely to receive multidisciplinary consultation prior to treatment, and were less likely to have surveillance for low risk disease.

6552 Background: Socioeconomic status affects goals of care and treatment choices. We investigated the impact of low household income on diagnosis, goals of care, and treatment choice in patients with localized prostate cancer. Methods: The North Carolina Prostate Cancer Comparative Effectiveness & Survivorship Study (NC ProCESS) is a population-based cohort of prostate cancer patients identified at the time of diagnosis, enrolled from 2011-2013, and followed prospectively. Sociodemographic information and decision making factors including goals of care were collected by patient report. Patients were asked to rate the importance of quality of life, cure, burden to friends and family, cost, and effect on daily activity as well as which of these goals was the most important in their treatment decision making. Annual household income was stratified in to 3 levels: < 40K (low), 40-90K (middle),>90K (high). Results: Of 1382 patients, 539 (39%), 553 (40%), and 290 (21%) reported low, medium, and high household income. Lower income patients were less college educated, more frequently unemployed, and had higher rates of either no insurance or government sponsored insurances. Low income patients had higher PSA and worse clinical stage at diagnosis. In goals of care, low income patients more frequently rated high importance on burden (78.8% vs 76.0% vs 65.2% p<0.01) and cost of cancer (61.2% vs 38.5% vs 14.5% p<0.01), and factors other than cure as the most important treatment decision factor. While overall treatment rate at 1 year was similar by income group, the type of treatment differed. On multivariate analyses, adjusting for age, race, clinical risk group, employment, insurance, and treatment goal, high income was associated with increased odds of having surgery (OR 1.81, CI 1.16 – 2.81), and reduced odds of having radiation (0.60, CI 0.36-0.99). Conclusions: Poor patients with low household income have worse prostate cancer at diagnosis. These patients have different goals of care which impact their choice of treatment. These findings provide novel insight into disparities in diagnosis and outcome in prostate cancer.[Table: see text]