Genitourinary Patients Research Articles

What are the perceived unmet needs for patient care, education, and research among genitourinary cancer nurses in Australia? A mixed method study

ObjectiveSpecialist genitourinary (GU) nurses provide care to a broad and diverse group of patients diagnosed with kidney, bladder, prostate, testicular, adrenal, and penile cancer. The purpose of this study was to identify GU cancer nurse perspectives of perceived unmet needs in service provision, specific educational and research priorities. MethodsA concurrent mixed methods study design incorporated quantitative and qualitative data collection from the GU Cancer nurses workforce in Australia. Quantitative data collected using an electronic survey instrument and were analysed using descriptive statistics. Qualitative data collected through semi-structured interviews and coded for thematic analysis. Ethical approval was gained. ResultsFifty responses were received from the electronic survey. 39/50 (78%) were female and 35 (70%) were metropolitan based. The highest domains of perceived unmet needs related to psychological/emotional needs – 17/23 (74%), intimacy needs – 15/23 (65%) and informational needs – 13/23 (57%). The themes from the qualitative interviews identified: (1) Patient needs – lack of tumour specific contact for cancer patients, fragmented delivery of cancer care, perception of better access to supportive care for public patients, lack of access to supportive care screening tools for needs assessment. (2) Educational needs – lack of GU specific cancer educational resources/learning opportunities and barriers to accessing educational opportunities. (3) Research priorities – impact on carers/partners, specific needs of different GU cancers, future focus on genetic testing/counselling, interventions for financial toxicity and development of models of care for geriatric GU patients. ConclusionsSpecialist GU cancer nurses support a broad group of patients. Given the prominence of addressing unmet cancer care needs among people with GU cancers in this study, cancer nursing as a discipline alongside the multidisciplinary team, requires innovative solutions to overcome fragmented care which is often highly complex, and develop individualised and integrated care across the cancer care continuum. We encourage clinicians, researchers, policy makers, people affected by cancer, and their care networks, to continue to drive innovation by (1) Embedding an integrated approach to cancer nursing, (2) Implementation of shared care, (3) Implementation of patient navigation, (4) Embracing emerging technologies, (5) Future focus on education, and (6) Future focus on nurse-led research.

Germline Pathogenic Variants Identified in Patients With Genitourinary Malignancies Undergoing Universal Testing: A Multisite Single-Institution Prospective Study.

This study aimed to investigate the prevalence of pathogenic germline variants (PGVs) in hereditary cancer genes utilizing a universal testing approach and to determine the rate of PGVs that would have been missed based on National Comprehensive Cancer Network (NCCN) guidelines in genitourinary (GU) malignancies. A multisite, single-institution prospective germline genetic test (GGT) was universally offered to patients with new or active diagnoses of GU malignancies (prostate, bladder, and renal) from April 2018 to March 2020 at Mayo Clinic sites. Participants were offered GGT using a next-generation sequencing panel of > 80 genes. Demographic, tumor characteristics, and genetic results were evaluated. NCCN GU cancer guidelines were used to identify whether patients had incremental findings, defined as PGV-positive patients who would not have received testing based on NCCN guidelines. Of 3095 individuals enrolled in the study, 601 patients had GU cancer (prostate = 358, bladder = 106, and renal = 137). The mean enrollment age was 67 years (SD 9.1), 89% were male, and 86% of patients were non-Hispanic White. PGVs were identified in 82 (14%) of all GU patients. PGV prevalence breakdown by cancer type was: 14% prostate, 14% bladder, and 13% renal cancer. Nearly one-third of identified PGVs were high penetrance, and the majority of these (67%) were clinically actionable. Incremental PGVs were identified in 28 (57%) prostate, 15 (100%) bladder, and 14 (78%) renal cancer patients. Of the 82 patients with PGV findings, 29 (35%) had at least 1 relative undergo cascade testing for the familial variant(s) identified. More than 1 in 8 patients with GU malignancies were found to carry a PGV, with 67% of patients with high-penetrance PGVs undergoing clinically actionable changes. The majority of these PGVs would not have been identified based on current testing criteria. These findings support universal GGT for GU malignancies and underscore its potential to enhance risk assessment and guide precision interventions in urologic oncology.

Telemonitoring program for genito-urinary cancer patients treated with oral anticancer agents.

e18731 Background: Oral anticancer agents (OAA) used has dramatically increased in treating genito-urinary (GU) cancer. Patients with metastatic prostate and kidney cancers, have advanced age, with comorbidities. The risks of OAA for this population with adverse effects, drug interactions and ambulatory administration must be detected, prevented and managed to decrease toxicity, improve compliance and efficacy. Here, we report the data of our comprehensive cancer center telemonitoring program named Outside the walls of the hospital (OWH), combining medical oncologist coordination, clinical pharmacist (CP) evaluations, and nurse follow-ups. Methods: Data from patients treated with OAA for advanced and metastatic prostate or kidney cancers in our center during year 2022 were retrospectively evaluated. At the start of OAA, the patients benefit from a consultation with the oncologist, clinical nurse (CN), and CP. For each drug, a standard telemonitoring program has been planned according to the patient's age and comorbidities. Results: The mean age of the patients was 68 years (44-90), 42% of the patients were over 70 years, 84% were men and 96% were in a metastatic setting. Out of 347 GU patients, 118 were included in the OWH telemonitoring program in 2022, representing 14% of the whole cancers patients enrolled in this program. Of these 118 new GU patients, 80% had a CP consultation, 76% for next generation hormonal therapy (NGHT) for advanced or metastatic prostate cancer and 24% for tyrosine kinase inhibitors (TKI) for kidney cancer. At least one drug interactions was detected for 54% of patients (61% of the NGHT and 35% of TKI). The associations was strongly discouraged for 18% because of an increase or decrease in drug concentration requiring a switch or an adaptation of dosage at the outset (statin (11 patients), oral anticoagulant (5 patients), analgesic (1 patient)). At least 1 complementary alternative medicine was used by 29% with 55% of them had an interaction with OAA. During follow-up, the frequency of consultations with CN or physician is reduced over time, in order to give priority to telemonitoring and visits to the oncologist for tumor assessment and if necessary at the request of the nurse or the patient. Conclusions: The OWH program makes it possible to limit medical visits by ensuring safe monitoring. It promotes patient empowerment and allows for medical visits when necessary, in the current context of declining medical demographic for an often elderly and fragile population.

Individualized treatment estimates to inform on personalized cancer care decisions for treatment selection and treatment management.

e13571 Background: Clinical trials report average effects of treatments at a population level. However, clinicians must balance treatment benefits against risks to personalize therapy. Here, we present a statistical framework which incorporates real-world data to estimate efficacy and symptom burden for an individual patient. We then assess the potential impact of continuing immunotherapy beyond progression in patients with metastatic solid malignancies on immune-related adverse events, progression, and survival. Methods: We corrected for sampling biases with inverse propensity score weighting (IPTW), and used the IPTW-transformed data to train predictive models of patient outcomes under each option. The models utilize a peer-based similarity based on 222 routinely-collected patient characteristics, such as cancer and treatment specific factors, laboratory tests, demographics, vitals, stage, comorbidities and symptoms, which are extracted from the electronic health record or natural language processing of clinician narratives, and Social Determinants of Health from Census data. We developed our methods on “Dataset A”: 5,919 breast and genitourinary (GU) cancer patients at a tertiary cancer center. We computed individualized treatment effect (ITE) estimates on “Dataset B”: 5,486 breast, GU, and thoracic cancer patients who received immunotherapy. Results: Our approach eliminated biases in Dataset A: the IPTW-transformation reduced the between-group standardized mean difference across identified confounders from an average of 0.225 to an average of 0.022. The similarity model exhibited strong discrimination (ROC-AUC > 0.75), and identified associations between patient characteristics and outcomes that matched clinicians’ expectations. Validations are ongoing to assess the ITE estimates on a held-out subset of Dataset B. These include subgroup analyses for metastatic triple-negative breast cancer and non-small cell lung cancer. Conclusions: We introduce a method to estimate the efficacy and toxicity of interventions, actions, or treatment decisions, which replicates the statistical robustness of a clinical trial while obtaining individualized insights. This framework provides causal estimates of symptom burden and risks of progression and survival to inform clinical decisions, including continuation of immunotherapy beyond progression. After IPTW, confounders in Dataset A were balanced between the treatment groups, with weighted standardized mean differences <0.1. [Table: see text]

Screening detects clinically significant hearing loss in patients with GU malignancies.

e18624 Background: Four in 10 people aged 60-69 have hearing loss in frequencies that mediate speech comprehension. Untreated losses undermine medication adherence, increase risk for accidental injury, and generate higher total healthcare expenditures. Genitourinary (GU) malignancies are most frequently diagnosed in people over 60, and these patients are commonly exposed to ototoxic treatments like platinum-based chemotherapy. We hypothesized that a significant number of GU patients would fail hearing screenings at levels reflecting clinically significant hearing loss. Methods: This is a prospective, two-cohort pilot study conducted at Tulane Medical Center. Consecutive patients with active GU malignancies who did not use hearing aids were enrolled in cohort A. The primary objective of cohort A (screening) was to determine the prevalence of hearing loss among GU patients. Cohort B (interventional) will investigate the efficacy of a non-custom amplifier in improving communication for patients with hearing loss. The hearing screening consisted of a 9-item Self-Assessment of Communication (SAC) and a 25 decibel (dB) pure tone hearing screening at 1 kHz, 2 kHz, 4 kHz via an Earscan3 portable audiometer with headphones in a quiet exam room. The primary endpoint was the proportion of patients who failed the hearing screening (missed ≥ 2/6 tones). The SAC generates a global handicap score (none, slight, mild-to-moderate, severe). Surveys identifying any amount of handicap were considered positive. Patients who failed screenings were offered referrals to audiology. Here, we present results from cohort A. Results: From 8/21 to 1/22, 66 patients were invited to participate. Nine patients screen-failed (n = 8 hearing aids; n = 1 uninterested). Cohort A enrolled 57 patients [median age 68 (33-86); 91% men; 60% prostate, 24% kidney and 14% bladder cancer]. Most patients (82%) had evidence of metastatic disease and 12%, 19%, 36%, 21% of patients were receiving chemotherapy, immunotherapy, hormonal therapy, and no active therapy, respectively. Twenty (35%) patients had prior exposure to neurotoxic chemotherapy. Forty patients (70%) met the primary endpoint. Compared to the pure tone screening, the SAC had a specificity of 94%, and a sensitivity of 40%. The SAC asks patients for a situation where they want to hear better; 61% of patients who volunteered a scenario (17/28) identified a complex listening environment like an outpatient encounter. A minority of patients (n = 3) accepted audiology referrals after failing screenings. Cohort B is actively enrolling. Conclusions: Clinically significant hearing loss was prevalent among patients with GU malignancies. Patients reported struggling in listening situations with auditory demands like outpatient encounters but were unable to self-identify losses and did not pursue audiology referrals after failed screenings. Interventional studies addressing this unmet need are warranted.

MP12-02 PROSPECTIVE EVALUATION OF CIRCULATING TUMOR DNA (ctDNA) IN DETECTING EARLY PROGRESSION ON IMMUNE CHECKPOINT INHIBITORS IN PATIENTS WITH ADVANCED GENITOURINARY CANCERS

MP12-02 PROSPECTIVE EVALUATION OF CIRCULATING TUMOR DNA (ctDNA) IN DETECTING EARLY PROGRESSION ON IMMUNE CHECKPOINT INHIBITORS IN PATIENTS WITH ADVANCED GENITOURINARY CANCERS

Evaluation of compliance of next-generation sequencing (NGS) testing in stage IV genitourinary (GU) cancer patients (pts) and the effect of an EHR prompt (EP) on increasing frequency.

48 Background: Previous reports have found that NGS testing on stage IV GU cancer patients is performed less commonly than expected based on the prevalence of GU tumors in comparison to other tumor types. In addition, most of the data on NGS testing frequency has been in the academic setting. This study will look at NGS testing in stage IV GU pts in the private practice setting. Methods: In the retrospective portion of the study, we used algorithms in Flatiron’s OncoEMR to identify baseline NGS testing frequency in all stage IV GU cancer patients. In the prospective portion, we used an EP to communicate with doctors about their stage IV GU cancer pts with upcoming appointments. Our primary endpoint was to determine the percentage of stage IV GU pts who had NGS testing; our secondary endpoint was to determine how often NGS testing would provide an alternative therapeutic option. Results: 91 stage IV GU cancer pts were identified retrospectively from 6/1/2020-12/31/2020. 20 (22%) of them had had NGS testing: 12 of 68 (18%) prostate cancer pts, 6 of 13 (46%) bladder cancer pts and 2 of 10 (20%) kidney cancer pts. Prospectively, 65 patients with Stage IV GU cancer and upcoming appointments were identified between 8/23/2021-9/13/2021. 17 (26%) had previously had NGS testing: 10 of 46 (22%) prostate pts, 4 of 9 (44%) bladder pts, and 3 of 10 (30%) kidney pts. The EP prompted additional testing of 10 pts. Of the total 27 pts, 8 (30%) were found to have actionable mutations: 7 of 17 (41%) prostate pts and 1 of 6 (17%) bladder pts. 6 of the 8 actionable mutations were either BRCA1/BRCA2 or PALB2. Conclusions: Our results supported those previously reported in academic settings which found that GU cancers were less likely than other metastatic cancers to have NGS testing performed. Prostate cancer was the least likely of the GU cancers to have NGS testing, however, the findings highlight the importance of germline testing in this population. A longer term study may have further borne out the benefits of EP. Improved communication (huddles, multidisciplinary rounds, etc.) would likely increase compliance with NGS testing as would automated order sets and “hard stops” in the EMR. As trials and standard options for GU cancers increase, physician ordering of NGS will follow. Universal NGS testing should be the goal of all stage IV GU patients to maximize therapeutic options.

Disparities among GU cancer patients referred to palliative care.

114 Background: The role of palliative care in genitourinary (GU) malignancies has been understudied. Despite representing nearly 25% of new cancer diagnoses, with over 350,000 new cases diagnosed each year, few GU patients have been included in palliative care trials under the theory that symptoms are less severe for GU patients than other solid tumors. Early involvement of palliative care services improves the patient care experience, decreases healthcare utilization, is associated with survival benefit, and results in improved quality of life and mood. To further elucidate the role of palliative care in oncology, we must study its utility in subsets of malignancy like GU cancers, as needs for patients may differ by malignancy type. Methods: A retrospective cross-sectional analysis of initial outpatient palliative care visits was performed using data from the Quality Data Collection Tool for Palliative Care (QDACT-PC) database from 2014-2020. QDACT-PC is a web-based, point-of-care registry used by physicians across the United States to track quality metrics associated with patient consultations. Data was collected and analyzed from patients' initial visits including pain scale, dyspnea scale, feeling of well-being (Quality of Life scale), fatigue scale, constipation scale, palliative performance status (PPS), and preference for resuscitation status. Scales for these variables were 0-10, with the exception of a scale of 0-100% for PPS. Patients less than 18 and greater than 90 years old were excluded. Chi-squared and Student’s t-tests were used to compare categorical and continuous variables, respectively. Results: 824 GU oncology patients (358 prostate cancer patients, 251 bladder cancer patients, 215 renal cancer patients) were compared against all patients with non-GU cancers (7807 patients). Notably, non-GU patients reported higher rates of fatigue (4.50 vs. 4.13, p = 0.0013) and dyspnea (1.63 vs. 1.11, p < 0.0001) than GU patients. GU malignancies had non-significant higher reported pain (3.73 vs. 3.60, p = 0.3109) and constipation (1.96 vs. 1.83, p = 0.2319) and lower PPS (4.95 vs. 4.96, p = 0.8555) and QOL (4.55 vs. 4.73, p = 0.0962). Preference for resuscitation at the time of referral was similar between the two groups (p = 0.6339). Only 16.5% of prostate cancer patients referred to palliative care in this database were black, while black patients are often estimated to represent 30% of new prostate cancer diagnoses each year. Conclusions: GU patients represent 9.54% of cancer patients seen by palliative care while the incidence is nearly 25%. Traditionally, GU patients were underrepresented in palliative care trials under the notion of less severe symptoms; however, this study demonstrates that GU patients have as severe symptoms as non-GU patients, highlighting a disparity in referral to palliative care. Furthermore, the lack of representation of black patients suggests potential inequity and warrants further investigation.

Abstract S09-03: Real world data analysis of patients with genitourinary cancers receiving systemic anticancer treatment during the COVID-19 pandemic at Guy's Cancer Centre: A single centre retrospective study in the UK

Abstract Background: To understand the impact of the COVID-19 pandemic on National Health Services (NHS) cancer service delivery, care and patients, we examined the impact of changes in cancer service delivery, treatment intensity and delay by evaluating oncological outcomes of genitourinary (GU) cancer patients receiving systemic anticancer treatment (SACT) during 1st March and 8th July 2020. Methods: We used data from patients with GU cancers (i.e. prostate, urothelial, kidney and testicular) treated with SACT at Guy’s Cancer Centre during the first wave of the COVID-19 pandemic in the UK: demographics (sex, age, ethnicity, ECOG performance status (PS), comorbidities, smoking history, socio-economic status (SES)) and disease characteristics (stage, treatment type and setting, lines of treatment), as well as results from SARS-CoV-2 PCR testing. Classification of COVID-19 severity was based on the World Health Organisation (WHO) guidelines. Results: A total of 457 GU cancer patients received SACT during the study period: 68% prostate cancer, 23% renal cancer, 7% urothelial cancer, 2% testicular cancer. Mean age was 69 years (SD: 11.2). 91% were males, 82% were classified as low SES and out of the 291 patients we had ethnicity data on 199 (68%) were White British. The majority of patients had a PS of 1 and 95% of all patients had stage IV disease and hence received palliative SACT, with 58% being in the second line setting. Half of the patients received hormone therapy, 17% received chemotherapy, 20% received targeted therapy, 13% received immunotherapy (IO) and 1% received combination IO and targeted treatment. Only 5 (1%) patients tested SARS-CoV-2 positive: 2 had prostate cancer, 2 renal and 1 bladder cancer. Mean age was 66 years (SD: 5.6). They were all male, 2 White British, 1 Black African and 2 of unknown ethnicity and were all classified as low SES. Average PS was 2. Of these 5 patients 3 had at least two comorbidities (i.ehypertension, diabetes mellitus, renal impairment, frailty) and were receiving multiple medications. All had stage IV disease and received palliative SACT. 3 were on hormone therapy alone and 2 on chemotherapy. 2 of the patients presented symptoms within less than 7 days from PCR diagnosis, 1 within 7 to 14 days and 1 after 14 days. All 5 COVID-19 positive patients required hospitalization, 4 suffered severe pneumonia, 1 died from COVID-19 and 2 died from cancer related causes. In comparison, the mortality rate for the COVID-19 negative patients was 3.3%. Conclusion: Despite the impact of COVID-19 in health provision, a large number of our GU patients at Guy’s Cancer Centre safely received SACT. Our results suggest that the continuation of SACT during the COVID-19 pandemic did not increase the risk of COVID-19 in our patient cohort (SARS-CoV-2 infection rate: 1%). Of note, the infection rate was lower than observed in a similar study in our centre for gastrointestinal cancer patients (SARS-CoV-2 infection rate: 3.4%). In light of the above, decisions against SACT or SACT intensity should carefully be evaluated. Citation Format: Christina Karampera, Beth Russell, Charlotte Moss, Rushan Sylva, Kieran Palmer, Elias Pintus, Sarah Rudman, Debra Josephs, Kamarul Zaki, Mieke Van Hemelrijck, Saoirse Dolly, Deborah Enting. Real world data analysis of patients with genitourinary cancers receiving systemic anticancer treatment during the COVID-19 pandemic at Guy's Cancer Centre: A single centre retrospective study in the UK [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2021 Feb 3-5. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(6_Suppl):Abstract nr S09-03.

Evaluation Of A Deep Learning-Based Auto-Segmentation Method For Quality Assurance Of Both Male And Female Pelvic Organ-At-Risk Contours In NCTN Clinical Trials

We previously reported a cascaded atrous convolution and spatial pyramid pooling module-based auto-segmentation method for organ-at-risk (OAR) segmentation and its quality assurance (QA) for radiotherapy clinical trial cases submitted from various disease sites. In this study, we enhanced the technique and evaluated the enhanced method for QA of OAR contouring using data submitted from both a genitourinary (GU) trial (NRG-RTOG 0938) and a gynecology (GYN) trial (NRG GY006). Three convolutional neural network (CNN)-based models were trained for rectum, bladder, left femur, and right femur: One GU model used data of 192 patients from RTOG 0938, one GYN model used data of 111 patients from GY006 and the third model used mixed data from both trials. Another 20 patient data sets from each trial, a total of 40 patient data sets, were used for model validation. Using these models, two sets of OAR contours were automatically generated on each test patient: One set used the GU and GYN models on 20 male and 20 female patients, respectively and another set used the mixed model for all 40 test patients. The performance of the models was evaluated using dice indices calculated using MiM software. For GU patients, contours generated using GU model vs. mixed model, the Dice Similarity Coefficient values were 0.94±0.03 vs. 0.94±0.03 for the bladder, 0.80±0.05 vs. 0.81±0.06 for the rectum, 0.87±0.04 vs. 0.86±0.05 for the left femur, and 0.88±0.03 vs. 0.87±0.05 for the right femur, respectively. For GYN patients’ contours generated using GYN model vs. mixed model, corresponding values were 0.80±0.15 vs. 0.85±0.18 for the bladder, 0.70±0.11 vs. 0.65±0.11 for the rectum, 0.45±0.21 vs. 0.45±0.18 for the left femur, and 0.46±0.20 vs. 0.44±0.19 for the right femur, respectively. The GYN data had fewer cases and relatively low image quality due to image artifacts caused by the inserted applicator. There was no guideline provided for GY006 femur contours in the protocol, which resulted in large variations in submitted contours. These factors have affected the auto-segmentation accuracy of the GYN models and test results using the GYN data. The CNN model-based method generates OAR segmentation with reasonable accuracy and has the potential to be used for contour QA for future patients enrolled on both GU and GYN trials. The models built using mixed male and female data also demonstrate acceptable accuracy for pelvic OARs for both male and female patients.

Abstract A133: Comparison of radiation therapy initiation timelines among varied referral streams to identify sources of delay

Abstract Purpose/Objective(s): Tertiary radiation oncology centers receive referrals from diverse care settings, including private facilities, Veteran’s Affair (VA) hospitals, and county hospitals. An exploratory study of county patients treated at our institution identified that each missed consult or simulation (sim) appointment was associated with a greater than three-week delay from referral to radiation (RT) start. We sought to validate this in a larger sample and compared RT referral-to-start timelines for a variety of referral streams. Materials and Methods: Up to 60 consecutively referred patients from each facility (internal health system, VA, county hospital, and external private facilities) between June to December 2018 were included. Primary disease site, interpreter requirements, and dates of referral, consultation, sim, and RT start were recorded. Linear regression and analysis of variance models were developed to identify variables associated with delays in RT. Results: Of 214 patients were included; 55 (26%) internal, 53 (25%) from the VA, 60 (29%) from the county hospital, and 46 (22%) from other facilities. Among the 33 patients requiring interpreters, 28 (85%) were county patients. The most common referrals were for genitourinary (GU) cancers (n = 63, 29%), followed by breast (n = 29, 14%), lung (n = 26, 12%), and head and neck (n = 21, 10%) cancers. The median days from referral to consult was 16 (IQR 7-28), with the shortest time to consult for bone (1.5 days, IQR 1-5) and central nervous system sites (5 days, IQR 3-9) and the longest for gynecologic cancers (21.5 days, IQR 8.5-44). Excluding GU patients, who often require two months of neoadjuvant hormone therapy prior to RT, the median days from consult to sim was 13 (IQR 6-20) with no significant differences in referral to consult or consult to sim by referring facility. In all patients, the median days from sim to RT start was 8 (IQR 6-14) with no significant differences by referral facility. In univariate analysis among non-GU patients, referring facility and requirement of an interpreter were not associated with referral-to-start delays; only missing one or more consult/sim appointments was significant (p < 0.001). Each missed appointment was associated with a 37-day delay (95% CI 26 – 48) in referral-to-start. Conclusion: In a patient cohort with heterogeneous cancer diagnoses, no facility-specific delays were identified despite county hospital patients having known socioeconomic vulnerability. Efforts to decrease RT delays may require department-wide, as opposed to interfacility, interventions. Future goals involve using site-specific referral-to-start benchmarks (e.g. one week for palliation and 10 weeks for GU) to further discriminate differences. Citation Format: Melody J Xu, Sumi Sinha, Sunny Wang, Terence Friedlander, Steve E Braunstein. Comparison of radiation therapy initiation timelines among varied referral streams to identify sources of delay [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A133.

Underrepresentation of genitourinary cancers in studies of venous thromboembolism (VTE) prophylaxis.

e17115 Background: Significant advances in the management of VTE in cancer have led to a recent ASCO clinical practice update for VTE prophylaxis and treatment in patients with cancer. Genitourinary (GU) cancers (including bladder, kidney, prostate, testicular) have a high incidence of VTE, but also frequent bleeding complications, and it is not clear if patients with GU cancers are adequately represented in studies of VTE prophylaxis. We sought to determine the frequency of inclusion of patients with GU cancers in prospective studies of VTE prophylaxis. Methods: A systematic review of the literature using MEDLINE (inception to January 2020) was conducted. We included randomized controlled trials that compared thromboprophylaxis to placebo or best supportive care in patients with an established diagnosis of cancer. Observational studies, case series, and case reports were excluded. The primary outcome was proportion of patients with GU malignancies included within the trials. Results: A total of 137 articles were identified under the original search and 7 underwent full text review. A total of 6066 patients were included in 7 thromboprophylaxis trials, of which only 119 (2.0%) had a defined GU malignancy (Table). Given the heterogeneity of the GU cancers represented in each study, and the small numbers of patients included with GU cancers, a patient-level meta-analysis among GU patients in this population was not performed. Conclusions: In spite of the high risk for VTE in GU cancers, in particular bladder and testicular cancer, GU cancers are underrepresented in prospective randomized trials investigating VTE prophylaxis. To ensure appropriate decision making for each individual patient, future prospective trials must ensure adequate representation of patients with GU cancers to better understand the potential role for VTE prophylaxis in this high-risk population.[Table: see text]

Does screening for frailty with the vulnerable elders survey (VES-13) identify older adults with GU malignancy who benefit most from a consultation in a geriatric oncology clinic?

209 Background: The VES-13 is a well-studied brief frailty screening tool for ≥ 65 older adults (OAs) in the oncology setting. Vulnerable patients (scoring ≥ 3) are at higher risk for adverse outcomes and will benefit from a Comprehensive Geriatric assessment (CGA) and cancer treatment decision optimization. Whether the VES-13 is effective specifically in patients with Genitourinary (GU) malignancies remains to be established. Primary objective: to determine if the VES-13 can predict which OAs with GU cancer (Bladder, Prostate, Kidney) had subsequent treatment modification after CGA. Secondary objective: to investigate if there is any association between VES-13 score with comorbidity and chemotherapy toxicity prediction tool (CARG). Methods: The VES-13 was administered to consecutive patients referred to the geriatric oncology (GO) clinic from GU site at the Princess Margaret Cancer Centre, Canada. All patients underwent CGA. CGA assess 8 domains including cognition, comorbidities, function, falls risk. Among patients referred for pre-treatment assessment, we examined whether the VES-13 predicted changes in the final treatment plan after CGA. Descriptive statistics were used to describe the VES-13 scores and final treatment impact. Results: From July 2015-October 2019, 77 were included in this analysis. The VES-13 ≥ 3 group were 52/77 (67.5%), and significantly associated with higher comorbidities (P = 0.003) and worse CARG scores (P = 0.005). The final treatment plan was modified in 36/77 (47%). In univariate analysis, the odds ratio (OR) for VES-13 ≥3 was 1.92 (95% CI 0.72-5.12) for change in final treatment, which was not statistically significant likely due to modest sample size. Interestingly in the same univariate analysis, there was a strong association between final treatment plan with falls risk (OR 2.63, 95% CI 1.03-6.72), physical performance (OR 2.51, 95% CI 0.98-6.45) and cognition (OR 3.95, 95% CI 1.19-13.19). Conclusions: The VES-13 identified vulnerable GU patients who will benefit from CGA and may predict treatment optimization by identifying patients at higher risk of chemotherapy toxicity and higher comorbidity.

Holistic, patient-centered symptom management for metastatic cancer: A comparison pilot study

ObjectivesTo determine the relative effectiveness of this holistic approach on metastatic cancer, breast (BC), genitourinary (GU), gynecologic (GYN), and lung (LC) cancer survival rates were compared to those from a similar oncology study investigating the impact of patient symptom reporting. As a secondary outcome, survival for BC, GU, GYN, LC, pancreatic (PC), and colon (CC) cancer patients from one through five years after metastatic cancer diagnosis was compared to normative data from the Surveillance, Epidemiology, and End Results Program (SEER) database. MethodsSurvival for breast, genitourinary, gynecologic, and lung cancers at one through five years was compared to (1) similar data from an electronic symptom self-reporting study; and (2) normative data from the Surveillance, Epidemiology, and End Results Program (SEER) using estimated survival curves and 95 % confidence intervals. ResultsCharts for 104 patients with metastatic breast, genitourinary (bladder and kidney), gynecologic (endometrial and ovarian), lung (non-small cell), pancreatic, and colon cancers were analyzed, and survival calculated. When analyzing only breast, genitourinary, gynecologic, and lung cancers to rates from the comparable study, the clinic’s one-year survival was significantly higher than with the comparable data (80.8 % vs. 75.1 % respectively) evidenced by 95 % confidence intervals. Comparison of the current population data (including all cancer types) and normative SEER data rendered statistically significant results for survival at 1, 2, 3, 4, and 5 years, evidenced by 95 % confidence intervals. ConclusionsThe clinic data showed survival that was higher than the computerized symptom monitoring arm of current reported research. Additionally, it was further increased when compared to normative SEER data. This suggested that results produced by electronic platforms used in large academic settings can be successfully reproduced by community oncology practices through non-electronic approaches to active symptom management and shared decision-making.

Impact of Genitourinary Injuries on Patients Requiring an Emergency Laparotomy for Trauma.

IntroductionIn patients having emergency abdominal surgery for trauma, the presence of urologic injury tends to increase mortality and morbidity.MethodsThis retrospective study evaluated patients requiring emergency surgery for abdominal trauma at a Level 1 Trauma Center over 30 years (1980-2010). Special attention was given to patients with concomitant genitourinary (GU) injuries.ResultsOf 1105 patients requiring an emergency laparotomy for trauma, 242 (22%) had urologic injuries including kidney 178 (16%), ureter 47 (4%), and bladder 46 (4%). Of the 242 patients, 50 (20%) died early (<48 hours) and 13 (5%) died later, primarily due to infection. A concept of “seven deadly signs” of hypoperfusion was developed. In patients with GU injuries, the presence of any deadly sign of hypoperfusion increased the mortality rate from 4% (6/152) to 63% (56/90), p<0.001. Of the 53 patients having a nephrectomy, 36 (68%) had one or more deadly signs and 27 (75%) died. Of 17 without deadly signs, only 2 (12%) died (p=0.001). Of 167 GU patients receiving blood, 59 (35%) developed infection vs 3/75(4%) in those receiving no blood (p<0.001).ConclusionsThe presence of deadly signs of severe injury and hypoperfusion on admission was the major factor determining mortality. With a severely injured kidney plus any deadly signs of hypoperfusion, special efforts should be made to avoid a nephrectomy.

Comparison of Radiation Initiation Timelines Among Varied Referral Streams to Identify Sources of Delay

Tertiary radiation oncology centers receive referrals from diverse care settings, including private facilities, Veteran’s Affair (VA) hospitals, and county hospitals. An exploratory study of county patients treated at our institution identified that each missed consult or simulation (sim) appointment was associated with a greater than three-week delay from referral to radiation (RT) start. We sought to validate this in a larger sample and compared RT referral-to-start timelines for a variety of referral streams. Up to 50 consecutive patients with VA insurance, the city health plan (CHP, Medicaid), and Medicare referred to our department from June to December 2018 were included. Patients with private insurance were excluded. Primary disease site, interpreter requirements, and dates of referral, consultation, sim, and RT start were recorded. Linear regression and analysis of variance models were developed to identify variables associated with delays in RT. Of 143 patients, the payor mix included VA (n = 50, 35%), CHP (n = 43, 30%), and Medicare (n = 50, 35%) insurances. These aligned closely with respective referral facilities: 51 (36%) from the VA, 48 (34%) from the county hospital, and 44 patients (31%) from other facilities. Among 23 patients requiring interpreters, 22 (96%) were county patients. The most common referrals were for genitourinary (GU) cancers (n = 47, 33%), followed by lung (n = 22, 15%) and breast (n = 20, 14%) cancers. The median days from referral to consult was 17 (IQR 7-29), with the shortest time to consult for bone (2 days, IQR 0-8.5) and central nervous system sites (2 days, IQR 0 – 5.5) and the longest for GU sites (28 days, IQR 16-56). Excluding GU patients, who often require neoadjuvant hormone therapy prior to RT, the median days from consult to sim was 13 (IQR 6-20) with no significant differences in referral to consult or consult to sim by referring facility or payor. In all patients, the median days from sim to RT start was 8 (IQR 7-14) with no significant differences by referral facility or payor. In univariate analysis, referring facility, payor, and number of missed consults/sims were statistically significantly associated with referral-to-start delays, but in multivariable analysis only number of missed appointments remained significant (p < 0.001). Each missed appointment was associated with a 40-day delay (95% CI 28 – 53) in referral-to-start. In a patient cohort with heterogeneous cancer diagnoses, no facility-specific delays were identified despite county hospital patients having known socioeconomic vulnerability. Efforts to decrease RT delays may require department-wide, as opposed to interfacility, interventions. Future goals involve expanding the sample size, including privately insured patients, and using site-specific referral-to-start benchmarks (e.g. one week for palliation and 10 weeks for GU) to further discriminate differences.

GUROPA survey: genito-urinary radiation oncology prescription attitudes.

To investigate the role of Radiation Oncology in the management of genito-urinary (GU) cancer excluding prostate and penile cancer. The questionnaire was focused on the evaluation of the degree of involvement of radiation oncologists in the work-up of bladder, renal cell carcinoma and testicular cancer (TC). Eighty-eight radiation oncologists completed the survey. The majority (85.4%) of participating radiation oncologists were senior consultants (> 5years of experience). Sixty-four (73.6%) carried out a multidisciplinary tumor board discussion of GU cases, while 23 (26.4%) did not. Seventy-five percent of responders reported that, every year, visited < 50 GU patients (pts), 18.1% visited 50-100 pts and 6.9% visited > 100 pts. Bladder cancer, curative radiotherapy (RT) as part of trimodality approach was claimed to be adopted in less than 10 cases per year. Regarding renal cell carcinoma (RCC) patients, primary tumor directed RT was adopted only in 8 cases (9.4%) in at least 10 pts per year. Palliative RT was more frequent in RCC (48.2%) in over than 10 pts per year. In case of TC, the prescription of RT was limited (< 10 patients per year) due to the low incidence of disease and recent shift to surveillance as a first option in stage I seminoma. Our survey showed that radiation oncologists are rarely involved in the decision making strategy of GU cancer, despite many clinical trials support RT use. These patients probably deserve a more uniform approach based on updated, detailed and evidence-based recommendations.

Impact of a geriatric oncology (GO) clinic on cancer treatment plans and supportive care for older adults with genitourinary (GU) cancer.

238 Background: Older adults with cancer are complex due to multiple comorbidities, polypharmacy, and functional/cognitive impairments, leading to over-treatment and undertreatment. Studies examining the impact of geriatric assessment (GA) in older adults with various cancers found a median of 39% of treatment plans were revised after the GA ( Ann Oncol 2014; 25:307). Although these findings support the need for a GO clinic, whether such a clinic leads to changes in treatment in patients with GU malignancies is not clear. We examined the impact on the treatment plan of a GO assessment in GU patients, along with other enhancements to patient care for consecutive patients referred to the GO clinic in a tertiary care hospital. Methods: All referred older adults (age 65+) with a GU malignancy seen in the GO clinic at the Princess Margaret Cancer Centre, Toronto, Canada between July 2015 and June 2017 were included. Patients were seen by a geriatric oncologist and GO nurse and treatment recommendations were provided to the referring oncologist. Pre- and post-GO clinic treatment plans and enhancements to supportive care were recorded prospectively. Analyses were descriptive. Results: 98 patients (mean age 80) were seen in the GO clinic, of whom 35 were seen pre-treatment (25 prostate, 5 kidney, 5 bladder). 31 of 35 were referred for input on the treatment plan. The initial treatment plan included surgery (n = 6), radiation (n = 14), systemic therapy (n = 8), and hormonal therapy (n = 11). The final treatment plan was intensified in 1 patient, reduced in 6 patients, changed to best supportive care in 8 patients, and unchanged in 15 patients. Overall, GO resulted in a treatment modification in 52% of patients. Enhancements to care included comorbidity management (87%), educational support (94%), disease-related symptoms (39%), and peri-operative management (19%). Conclusions: The GO clinic results in modifications to the proposed treatment plan in over half of referred patients (predominantly a reduction in treatment intensity), and enhancements to care in the vast majority of patients. GO clinics have the potential to avoid overtreatment and improve care for older adults with GU malignancies.

Patterns of Referral for Palliative Radiation Therapy

Palliative radiotherapy (PRT) is effective in alleviating the symptoms of many patients with advanced cancer, but there is evidence that it is underutilized, particularly in the elderly and in patients who live further from an RT center. Efforts to optimize access to PRT require an understanding of patterns of referral. The purpose of this study was to identify the sources of referral for PRT to a regional RT program. Our hypothesis is that the source of referral for PRT varies with the characteristics the patient. Medical and billing records were reviewed to identify the source of referral of patients who received PRT at a regional cancer center in Ontario between 2010 and 2015. Multivariate analysis was used to identify characteristics of the patient that are associated with the source of referral for PRT. Only the first course of PRT was considered. In total, 3,258 patients received PRT between 2010 and 2015. The patients’ median age was 70, 55% were male, and the median distance from patient residence to the radiotherapy center was 38.5 miles. The most common primary cancer sites were lung (37.2%), genitourinary (GU) (17.2%), gastrointestinal (GI) (12.8%), and breast (9.0%). PRT was given for locoregional disease in 36.0%, for distant metastases in 47.8%, and for indeterminate or multiple sites in 16.2%. Patients were referred by medical oncologists (MOs) (30.1%), other internists (26.4%), surgeons (24.2%), and family practitioners (FPs) (13.4%). In the remaining 5.9%, the need for PRT was identified by a radiation oncologist during follow-up after adjuvant or radical RT. The sources of PRT referrals varied significantly by primary cancer site (p<0.0001). Most lung cancer patients were referred by respirologists (34%), MOs (19%), or general internists (13%); most GU patients were referred by urologists (36%), FPs (20%), or MOs (19%); most GI patients were referred by MOs (47%), surgical oncologists (15%), or FPs (12%); and most breast patients were referred by MOs (61.2%), FPs (15%), or surgical oncologists (7%). The proportion of patents referred by their FP varied widely by disease site (range 7%-21%; p<0.0001). A multivariate analysis that controlled for primary site, showed that older patients were significantly more likely to be referred by their FP [>80 vs ≤60, OR 2.34 (1.67-3.27); 71-80 vs ≤60, OR 1.57 (1.15-2.14)], and that patients who lived further from the RT center were more likely be referred by their FP [>31 miles vs ≤31 miles, OR 1.37 (1.08-1.72)]. Diverse groups of doctors are involved in referring patients for PRT. Strategies for improving access to PRT should address the needs of specific patient groups by targeting the doctors who are most responsible for their care. FPs may be a key target for interventions aimed at enhancing access to PRT for older patients, and for those who reside further from an RT center.

A Call to Arms: moving forward from “Fostering the Partnership” Canadian GU Cancers Survivorship Conference 2011

Fostering the Partnership was a unique and innovative forum for genitourinary (GU) cancer survivors, advocacy groups and health care professionals (HCPs) to explore ways to collaboratively enhance GU cancer survivorship. The idea evolved from the growing recognition that new models of care are required to: (a) meet the diverse needs of an increasingly active and informed patient population; (b) respond to the desire of cancer survivors to give back; and (c) leverage their growing skill set as expert patients and potential research collaborators. The event, endorsed by the Canadian Urological Association, the Canadian Uro-Oncology Group and the Urology Nurses of Canada, and supported by industry partners, was held on January 19–20, 2011 in King City, Ontario. Forty-three individuals attended: 18 cancer survivors/caregivers, 22 HCPs and 3 researchers representing bladder, kidney, prostate and testicular cancers, clinical subspecialties and GU patient advocacy groups, including Bladder Cancer Canada, Kidney Cancer Canada, Prostate Cancer Canada and the Canadian Testicular Cancer Association. The event was an overwhelming success. Evaluations showed that 99% of attendees were extremely pleased with the event and would like to hold another. The following were identified as priorities. Meeting participants would like the Canadian GU community to recognize them as important future initiatives. Review current strategies and best practices that foster partnerships between cancer survivors and HCPs. Assess the knowledge of HCPs regarding the needs of GU cancer survivors, existing advocacy groups/community support organizations and their services, as well as barriers and facilitators for promoting active partnerships with cancer survivors. Establish priorities for GU cancer survivorship research with collaborative input from and participation by GU cancer survivors and HCPs. Facilitate direct communication, knowledge exchange and collaboration between GU cancer survivor advocacy groups and the HCPs. Facilitate networking, collaborative programming and fundraising among GU cancer survivor advocacy groups. Define the ideal patient journey for each GU cancer type, identify gaps in current services, and disseminate tools (e.g., Survivorship Care Plan/ Passport to Health) to facilitate improvement in these areas. Synthesize up-to-date information about GU cancer survivor advocacy groups/community support organizations and their services in an easy-to-access, web-based format for HCPs and cancer survivors. Facilitate ongoing opportunities for peer-to-peer support, community building and networking among GU cancer survivors throughout the cancer journey. Hold a follow-up conference led collaboratively by GU cancer survivors and HCPs based on the recommendations of this report. This is our “Call to Arms” to you, our colleagues. It is time to embrace survivorship in our practices and address these priorities. A complete description of the event, its recommendations and strategies to accomplish them is forthcoming.