INTRODUCTION:Obesity in prostate cancer survivors may increase mortality. Better characterization of this effect may allow better counseling on obesity as a targetable lifestyle factor to reduce mortality in prostate cancer survivors. The purpose of this study was to determine whether pre- and post-diagnostic obesity and weight change affect all-cause mortality, cardiovascular disease specific mortality, and prostate cancer specific mortality in patients with nonmetastatic prostate cancer. PATIENTS AND METHODS:We performed a retrospective cohort analysis of 5,077 patients diagnosed with localized prostate cancer from 1997 to 2017 with median follow-up of 15.5 years. The Utah Population Database linked to the Utah Cancer Registry was used to identify patients at a variety of treatment centers. RESULTS:Pre-diagnosis obesity was associated with a 62% increased risk of cardiovascular disease specific mortality and a 34% increased risk of all-cause mortality (HR 1.62, 95% CI 1.05-2.50; HR 1.34, 95% CI 1.07-1.67, respectively). Post-diagnosis obesity increased the risk of cardiovascular disease specific mortality (HR 1.83, 95% CI 1.31-2.56) and all-cause mortality (HR 1.37, 95% CI 1.16-1.64) relative to non-obese men. We found no association between pre-diagnostic obesity or post-diagnostic weight gain and prostate cancer specific mortality. CONCLUSION:Our study strengthens the conclusion that pre-, post-diagnostic obesity and weight gain increase cardiovascular disease and all-cause mortality but not prostate cancer specific mortality compared to healthy weight men. An increased emphasis on weight management may improve mortality for prostate cancer survivors who are obese.

Introduction In 2021, 59.6% of low-risk prostate cancer patients were under active surveillance as their first course of treatment. However, active surveillance and watchful waiting are difficult to define in population-based cohorts. The primary aim of our study is to develop and validate a population-level machine learning model for distinguishing active surveillance (AS) and watchful waiting (WW) in the conservative treatment group. A secondary aim is to investigate initial cancer management trends from 2004 to 2017 and the risk of chronic diseases among prostate cancer patients with different treatment modalities. Methods A cohort of 18,134 cancer patients with prostate adenocarcinomas were diagnosed between 2004 and 2017 in Utah Cancer Registry. As a subset, 1,926 patients with available AS/WW information were diagnosed from 2010 to 2017 from the Surveillance, Epidemiology, and End Results Prostate with Watchful Waiting Database. Models were trained by four machine learning algorithms, and 10-fold cross-validation was performed. The area under the receiver operating curve, F-score, Brier score, and accuracy were used for model evaluation. Comorbidities diagnoses were identified from electronic medical records and statewide healthcare facilities data. Cox proportional hazard models were used to estimate hazard ratios (HRs) for the risk of chronic diseases. Results Logistic regression models performed better than other models in identifying AS from WW accurately. The developed model achieved a test area under the receiver operating curve of 0.73 (range 0.68-0.79), F-score of 0.79, accuracy of 0.71(range 0.66-0.76), and Brier score of 0.29 demonstrating good calibration, precision, and recall values. The top predictors were clinical factors, including Gleason Grade groups (p=0.0003), AJCC stage (p=0.017807), and T stage (p=0.0000109), and demographic characteristics, including race (p=0.007904) and birth year (p=0.046533). We noted a sharp increase in AS use between 2004 and 2016 among patients with low-risk prostate cancer and a moderate increase among intermediate-risk patients between 2008 and 2017. Compared to the AS group, radical treatment was associated with a lower risk of prostate cancer-specific mortality;but higher risks of Alzheimer's disease, anemia, glaucoma, hyperlipidemia, and hypertension. Conclusions A machine learning approach accurately distinguished AS and WW groups in conservative treatment in this decision analytical model study. Our results provide insight into the necessity to separate AS and WW in population-based studies.

Background: Few studies have evaluated mental health disorders comprehensively among patients with prostate cancer on long-term follow-up. The primary aim of our study was to assess the incidence of mental health disorders among patients with prostate cancer compared with a general population cohort. A secondary aim was to investigate potential risk factors for mental health disorders among patients with prostate cancer.Methods: Cohorts of 18 134 patients with prostate adenocarcinomas diagnosed between 2004 and 2017 and 73470 men without cancer matched on age, birth state, and follow-up time were identified. Mental health diagnoses were identified from electronic health records and statewide health-care facilities data. Cox proportional hazard models were used to estimate hazard ratios. All statistical tests were 2-sided.Results: The hazard ratios for mood disorders, including depression, among prostate cancer survivors increased for all follow-up periods compared with the general population. The hazard ratios for any mental illness increased with Hispanic, Black, or multiple races; people who were underweight or obese; those with advanced prostate cancer; and those undergoing their first course cancer treatment. We also observed statistically significantly increased hazard ratios for mental health disorders among patients with lower socioeconomic status (P < .0001) and increasing duration of androgen-deprivation therapy (P = .0348). Prostate cancer survivors had a 61% increased hazard ratio for death with a depression diagnosis.Conclusion: Prostate cancer diagnosis was associated with a higher risk of mental health disorders compared with the general population, which was observed as long as 10-16 years after cancer diagnosis. Providing long-term mental health support may be beneficial to increasing life expectancy for patients with prostate cancer.

OBJECTIVES:The incidence of oropharyngeal cancer continues to rise in the United States, yet studies on the quality of life (QoL) of oropharyngeal cancer patients are limited. The objective of this pilot study was to assess the impact of oral health on the QoL in oropharyngeal cancer survivors. MATERIALS AND METHODS:Oropharyngeal cancer survivors with a confirmed cancer diagnosis from 1996 to 2016 were sampled from the Utah Cancer Registry. The Oral Health Impact Profile-14 (OHIP-14) questionnaire was administrated between January and May of 2019. The impact of oral health on QoL was evaluated using simple linear regression (β-coefficient). RESULTS:Among the 260 oropharyngeal cancer survivors, the majority were male (84.6 %) and ≥ 60 years of age at the time of cancer diagnosis (74.0 %). The most frequently reported symptoms of OHIP-14 were discomfort while eating any foods (19.2 %) and worsening sense of taste (16.0 %). The overall OHIP-14 mean score was 13.3. Significantly worse OHIP-14 scores were observed for females (β = 12.85, p = 0.01), chemotherapy recipients (β = 6.60, p = 0.02), and past smokers (β = 5.25, p = 0.04). Better OHIP-14 scores (better oral QoL) were observed in patients with distant cancer stage (β = -7.66, p = 0.01), higher income (β = -2.50, p = 0.05), and older age at cancer diagnosis (β = -0.35, p = 0.03). CONCLUSION:The oral health-related quality of life scores observed in this pilot study suggest a need for improvement in patient symptom management over time.

306 Background: Prostate cancer treatment has been widely associated with developing and/or worsening metabolic syndrome. While numerous studies have explored the interplay between prostate cancer and metabolism, there have been very few studies investigating endocrine and metabolic disease diagnoses among prostate cancer survivors with long term follow up. The aim of this study is to examine the incidence of endocrine and metabolic disease among prostate cancer survivors compared to a general population cohort. A secondary aim is to investigate risk factors for endocrine and metabolic disease among prostate cancer survivors. Methods: Cohorts of 18,134 cancer patients with prostate adenocarcinomas diagnosed between 2004 and 2017 and 73,470 men without cancer matched by age, birth state and follow up time from the general population were identified. Incidental endocrine and metabolic diseases diagnoses were identified from electronic medical records and statewide healthcare facilities data. Cox proportional hazard models were used to estimate hazard ratios (HRs). Results: Prostate cancer patients had increased risks of endocrine and metabolic diseases for the overall 16-year follow-up after cancer diagnosis (1-5 years: HR=1.26, 99%CI=1.22-1.31; 5-10 years: HR=1.21, 99%CI=1.16-1.26; 10-16 years: HR=1.20, 99%CI=1.12-1.28) compared to the general population. Elevated risks of thyroid disorder among prostate cancer patients were observed across follow-up periods (1-5 years: HR=1.19, 99%CI=1.11-1.28; 5-10 years: HR=1.12, 99%CI=1.03-1.22; 10-16 years: HR=1.17, 99%CI=1.02-1.35). Similarly, disorders of lipid metabolism risks were higher for all follow-up periods (1-5 years: HR=1.53, 99%CI=1.41-1.66; 5-10 years: HR=1.21, 99%CI=1.15-1.26; 10-16 years: HR=1.20, 99%CI=1.11-1.29). The risks of obesity and diabetes mellitus were also increased within 1-10 years and 1-5 years, respectively. Risk factors for endocrine and metabolic diseases among prostate cancer survivors included non-Hispanic ethnicity, unhealthy BMI, CCI≥1, family history of cancer, older age at diagnosis, and higher cancer stage throughout the overall follow-up periods after prostate cancer diagnosis. Significant risk factors for endocrine and metabolic diseases within 1-10 years after prostate cancer diagnosis included family history of prostate cancer, single marital status, government health insurance, high socioeconomic level, and high household incomes. Moreover, prostate cancer survivors with a diagnosis of endocrine and metabolic diseases faced a 13% increased risk of death. Conclusions: This study highlights a heightened risk of endocrine and metabolic diseases among prostate cancer survivors throughout the entire follow-up period after cancer diagnosis. It underscores the importance of multidisciplinary care to monitor and manage endocrine and metabolic diseases in this population of survivors.

PURPOSE:In 2021, 59.6% of low-risk patients with prostate cancer were under active surveillance (AS) as their first course of treatment. However, few studies have investigated AS and watchful waiting (WW) separately. The objectives of this study were to develop and validate a population-level machine learning model for distinguishing AS and WW in the conservative treatment group, and to investigate initial cancer management trends from 2004 to 2017 and the risk of chronic diseases among patients with prostate cancer with different treatment modalities.METHODS:In a cohort of 18,134 patients with prostate adenocarcinoma diagnosed between 2004 and 2017, 1,926 patients with available AS/WW information were analyzed using machine learning algorithms with 10-fold cross-validation. Models were evaluated using performance metrics and Brier score. Cox proportional hazard models were used to estimate hazard ratios for chronic disease risk.RESULTS:Logistic regression models achieved a test area under the receiver operating curve of 0.73, F-score of 0.79, accuracy of 0.71, and Brier score of 0.29, demonstrating good calibration, precision, and recall values. We noted a sharp increase in AS use between 2004 and 2016 among patients with low-risk prostate cancer and a moderate increase among intermediate-risk patients between 2008 and 2017. Compared with the AS group, radical treatment was associated with a lower risk of prostate cancer-specific mortality but higher risks of Alzheimer disease, anemia, glaucoma, hyperlipidemia, and hypertension.CONCLUSION:A machine learning approach accurately distinguished AS and WW groups in conservative treatment in this decision analytical model study. Our results provide insight into the necessity to separate AS and WW in population-based studies.

267 Background: Prostate cancer is the most prevalent malignancy among men in the United States. However, only a limited number of studies have explored the impact of rural-urban disparities in survival among prostate cancer patients with long-term follow-up. In order to investigate disparities in prostate cancer survival, we assess prostate cancer mortality and prognostic factors based on rural-urban residence. Methods: A cohort of 18,134 cancer patients with prostate adenocarcinomas diagnosed between 2004 and 2017 was identified. Residential location information at the time of cancer diagnosis was used to stratify on rural-urban residence. All-cause death and prostate cancer-cause death risks were estimated using Cox proportional hazard regression models. Results: Among prostate cancer patients, 15.1% resided in rural counties in Utah. Patients living in rural counties were different in demographic and clinical characteristics compared to their urban counterparts. An association was observed between rural residence and elevated risks of all-cause mortality (HR=1.19, 99%CI=1.10-1.29) and prostate cancer-specific mortality (HR=1.21, 99%CI=1.03-1.43). Elevated risks of both all-cause and prostate cancer-specific mortality were associated to factors such as unhealthy BMI, comorbidity index ≥1, family history of cancer or prostate cancer, single marital status, low income, low socioeconomic status, government insurance, earlier year of diagnosis, advanced prostate cancer stage, and extensive cancer treatment. Furthermore, the observed disparities in demographic and clinical profiles appeared to contribute to the disparities in all-cause and prostate cancer-specific mortality risks between rural and urban prostate cancer patients. Conclusions: Rural residence exhibited a significant association with the risk of prostate cancer-related and all-cause mortality. Patients residing in rural areas demonstrated distinct factors influencing mortality risks, encompassing both demographic and clinical aspects. These findings underscore the imperative for targeted interventions aimed at mitigating the rural-urban disparities in prostate cancer outcomes.

You have accessJournal of UrologyCME1 Apr 2023PD21-05 CARDIOVASCULAR OUTCOMES IN A POPULATION-BASED COHORT OF PROSTATE CANCER PATIENTS Siqi Hu, Chun-Pin Chang, John Snyder, Vikrant Deshmukh, Michael Newman, Ankita Date, Carlos Carlos, Benjamin Haaland, Christy Porucznik, Lisa Gren, Alejandro Sanchez, Alejandro Sanchez, Shane Lloyd, Brock O’Neil, and Mia Hashibe Siqi HuSiqi Hu More articles by this author , Chun-Pin ChangChun-Pin Chang More articles by this author , John SnyderJohn Snyder More articles by this author , Vikrant DeshmukhVikrant Deshmukh More articles by this author , Michael NewmanMichael Newman More articles by this author , Ankita DateAnkita Date More articles by this author , Carlos CarlosCarlos Carlos More articles by this author , Benjamin HaalandBenjamin Haaland More articles by this author , Christy PorucznikChristy Porucznik More articles by this author , Lisa GrenLisa Gren More articles by this author , Alejandro SanchezAlejandro Sanchez More articles by this author , Alejandro SanchezAlejandro Sanchez More articles by this author , Shane LloydShane Lloyd More articles by this author , Brock O’NeilBrock O’Neil More articles by this author , and Mia HashibeMia Hashibe More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003287.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prostate cancer is the most common malignancy among men in the United States. Few studies have evaluated cardiovascular disease (CVD) risk comprehensively among prostate cancer patients with treatment dose-response relations. The primary aim of our study is to assess the incidence of cardiovascular diseases among prostate cancer patients compared to a general population cohort. A secondary aim is to investigate socioeconomic status (SES) and clinical risk factors for cardiovascular disorders among prostate cancer patients. METHODS: Cohorts of 18,134 cancer patients with prostate adenocarcinomas diagnosed between 2004 and 2017 and 73,470 men without cancer matched on age, birth state and follow-up time were identified. CVD diagnoses were identified from electronic medical records and statewide healthcare facilities data. Cox proportional hazard models were used to estimate hazard ratios (HRs), adjusted for race/ethnicity, education, baseline Body Mass Index (BMI), baseline Charlson Comorbidity Index (CCI), risk group, age at diagnosis, hyperlipidemia, smoking status, therapy type, and diagnosis year based on a comprehensive evaluation of confounding variables. RESULTS: The risks of CVDs, including hypertension, arterial diseases, and venous diseases, among prostate cancer survivors compared to general population were increased for all follow-up periods after cancer diagnosis (1-5 years: HR=1.17, 95% CI=1.13-1.20; 5-10 years: HR=1.11, 95% CI=1.07-1.16; 10-16 years: HR=1.13, 95% CI=1.06-1.21). The risk of CVD was increased with obesity, baseline comorbidities, lower SES, and advanced-stage cancer, and differed by first-course cancer treatment, with CVDs higher for androgen deprivation therapy (ADT) and conservative treatment. Compared to intermittent ADT, continuous ADT was associated with increased risks of all-cause mortality among prostate cancer patients (HR=1.78, 95% CI=1.04-3.05). We also observed that an increasing duration of ADT was associated with an increased risk of arterial diseases (dose-response p=0.022) and an increased risk of all-cause mortality (dose-response p value=0.0439). CONCLUSIONS: We found an increased risk of CVDs that lasted through 10-16 years post-prostate cancer diagnosis. Lifestyle interventions to decrease the risk of CVDs in prostate cancer survivors may be potentially beneficial to increasing life expectancy. Source of Funding: This work was supported by grants from the NIH (R01 CA244326, R21 CA185811, R03 CA159357, M.Hashibe, PI), the Huntsman Cancer Institute, and the Cancer Control and Population Sciences Program (HCI Cancer Center Support Grant P30CA042014). This research was supported by the Utah Cancer Registry, which is funded by the National Cancer Institute's SEER Program, Contract No. HHSN261201800016I, the US Center for Disease Control and Prevention's National Program of Cancer Registries, Cooperative Agreement No. NU58DP0063200-01, with additional support from the University of Utah and Huntsman Cancer Foundation. Partial support for all datasets within the Utah Population Database is provided by the University of Utah, Huntsman Cancer Institute and the Huntsman Cancer Institute Cancer Center Support grant, P30 CA42014 from the National Cancer Institute © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e591 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Siqi Hu More articles by this author Chun-Pin Chang More articles by this author John Snyder More articles by this author Vikrant Deshmukh More articles by this author Michael Newman More articles by this author Ankita Date More articles by this author Carlos Carlos More articles by this author Benjamin Haaland More articles by this author Christy Porucznik More articles by this author Lisa Gren More articles by this author Alejandro Sanchez More articles by this author Alejandro Sanchez More articles by this author Shane Lloyd More articles by this author Brock O’Neil More articles by this author Mia Hashibe More articles by this author Expand All Advertisement PDF downloadLoading ...

Abstract Purpose: Oropharyngeal cancer incidence continues to increase in the United States. Studies on the quality of life (QOL) experienced by oropharyngeal cancer patients usually assessed QOL one year after diagnosis instead of in the long term, and most were hospital-based. The aim of this study is to assess oral health and QOL in oropharyngeal cancer survivors in a population-based cohort over a long term follow-up. Methods: First primary oropharyngeal cancer patients, with confirmed cancer diagnosis from 1996 to 2016 were identified in the Utah Cancer Registry. Between January and May of 2019, the patients completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core-30 (EORTC QLQ-C30), Quality of Life Questionnaire Head and Neck Cancer Module (EORTC QLQ-H&N35) and Oral Health Impact Profile-14 (OHIP-14) questionnaire. Adjusted linear regression was used to assess associations between each dependent variables and QoL scores. The global health mean score ranges from 0 to 100; >70 is considered a high level of functioning and <70 is associated with lower level of symptomology based on previous studies. The OHIP-14 score ranges from 0 to 56; <9 is considered better functioning for oral health. Results: Among 262 oropharyngeal cancer survivors, 84.0% were male, 74.7% were sixty and older at cancer diagnosis, 21.8% were overweight (µ=26.5 (sd=4.9) kg/m2). More than half of participants had seen a dentist within the last 6 months (65.8%) and were former smokers (51.1%). The global QoL means scores for 1996-2000, 2001-2005, 2006-2010, and 2011-2016 were 77.5 (sd=16.3), 73.4 (sd=17.6), 67.3 (sd=24.1), and 73.4 (sd=20.4). Both the global QoL mean score (72.0 (sd=20.8)) and the OHIP-14 mean score (13.2 (sd=13.9)) were fairly high. Similarly, individual QoL physical, role, emotional, cognitive, and social mean scores from the QLQ-30 were also fairly high, ranging from 77.8 to 85.9. From the EORTC H&N35 symptomatology scale, the highest symptom related mean scores were observed for weight gain (85.8 (sd=35.0)), pain-killers use (64.4 (sd=48.0)), and dry mouth (61.7 (sd=35.6)). Higher global QoL mean scores were seen with higher education (postgraduate vs technical school, 81.9 (sd=19.3) vs 67.9 (sd=22.4)), higher income ($100,000+ vs less than $25,00, 76.4 (sd=17.3) vs 60.2 (sd=24.6)), younger age (<40 vs >70, 87.5 (sd=17.7) vs 71.9 (sd=2.6)), and BMI (<18.5 vs 18.5-24.9, 45.8 (sd=26.7) vs 74.8 (sd=20.2)). Conclusion: Global QoL improvement suggests adaptability to a new normal among this group of U.S. oropharyngeal cancer survivors when compared to previous studies which were largely based on a shorter follow-up time. Oral health-related quality of life was marginally poor in our study, suggesting needed improvement in patient management overtime, with worse improvement in physical discomfort and physical disability scores across all demographic patient characteristics except with distant stage and recurrence. Citation Format: Alzina Koric, Marcus Monroe, Seungmin Kim, Esther Chang, Qingqing Hu, Siqi Hu, Mia Hashibe. Quality of life among oropharyngeal cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 901.