Citations

Although recent studies have explored the potential of multidomain brain health programs, there is a dearth of literature on operationalizing this research to create a clinical treatment program specifically for subjective cognitive decline (SCD). Patients seen by geriatricians in primary care and by behavioral neurology services at our institution presenting with SCD were recruited via a patient-appropriate flyer. After all participants had a 1-h brain health consultation with a neuropsychologist and were provided with program materials, they were randomized to attend a 10-week intervention designed to support program implementation (N = 10) or the control group of implementing the program on their own (N = 11). The program included (1) a calendar-based executive and memory support system for compensatory training and (2) training in healthy lifestyle. There were no significant differences between groups for any outcomes. Participants across both groups showed significant improvements with moderate effect sizes in compensatory strategy use, anxiety symptoms, and daily functioning, which were sustained through 6-month follow-up. They also increased physical activity by the end of the intervention period but did not sustain this through 6-month follow-up. Our pilot study demonstrates preliminary feasibility of a cognitive compensatory and lifestyle-based brain health program. Additional research is recommended to further develop two potentially scalable implementation strategies—coaching and self-implementation after brief consultation.

Abstract Background: Prostate cancer is the most common cancer among men. Monitoring of patient-reported outcomes (PROs) can enhance provider-patient communication, promote better decision-making, and improve survival. Geospatial factors, namely rurality and neighborhood socioeconomic deprivation, could influence the experience across cancer treatment, thus impacting PROs and survival. This study examined associations of rurality, neighborhood socioeconomic deprivation (Area Deprivation Index [ADI]) with cancer treatment-related PROs and survival in men with prostate cancer. Methods: Data from men with prostate cancer in the trial NRG Oncology/RTOG 0415 were analyzed. In this trial, 1092 men were randomized to receive conventional radiotherapy (RT) or hypofractionated RT. Patients had Gleason scores of 2-6 and prostate-specific antigen of <10 ng/mL. Rurality was categorized as urban vs rural using Rural-Urban Continuum Codes via patient zip codes. Neighborhood socioeconomic deprivation was assessed by the ADI calculated via the American Community Survey by patient zip codes. The Expanded Prostate Cancer Index Composite (EPIC) measures cancer-specific quality of life (QOL); Hopkins Symptom Checklist measures anxiety and depression; EuroQoL-5 Dimension (EQ-5D) VAS and Index scores assess general health. All PROs were measured at baseline before and 6, 12, 24 and 60 months after RT. Overall survival (OS) and disease-free survival (DFS) were assessed using Cox proportional hazards models. Mixed effects models and generalized estimating equations were used to analyze PROs. Results: We analyzed 751 patients with complete data. Patients from the ADI 25% most deprived neighborhoods (vs. the other 75% of neighborhoods) were more likely to be non-white, unmarried and from rural areas. At baseline, patients from the most deprived areas had worse EPIC bowel score (P=0.011), worse sexual score (P=0.042) and worse hormonal score (P=0.015); patients from the most deprived areas had worse self-care (P=0.04) and more pain (P=0.047). Patients from rural areas had worse EPIC urinary score (P=0.03) and sexual score (P=0.003). Longitudinal analyses showed that ADI 25% most deprived areas (β=4.05, P=0.001) and rural areas (β=-5.70, P=0.003) were associated with worse EQ-5D VAS score. Compared to the 75% less deprived neighborhoods and urban, the ADI 25% most deprived neighborhoods and rural areas respectively had 47% (HR=1.466, P=0.033) and 93% (HR=1.925, P=0.026) relative increase in risk of recurrence or death (DFS). No differences were seen in OS. Conclusions: Patients with prostate cancer from the most deprived neighborhoods and rural areas had low QOL at baseline, poor general health and DFS. Interventions should target populations from socioeconomic deprived neighborhoods and rural areas to improve patient access to supportive care services and DFS. Citation Format: Jinbing Bai, Stephanie L. Pugh, Ronald Eldridge, Katherine Yeager, Qi Zhang, W Robert Lee, Amit B. Shah, Ian S. Dayes, David P. D'Souza, Jeff M. Michalski, Jason A. Efstathiou, John M. Longo, Thomas M. Pisansky, Jordan M. Maier, Sergio L. Faria, Anand B. Desai, Samantha A. Seaward, Howard M. Sandler, Mary E. Cooley, Deborah W. Bruner. Rurality and neighborhood socioeconomic deprivation associated with patient-reported outcomes andsurvivalin men with prostate cancer in NRG RTOG 0415 [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 2528.

60 Background: Mapping algorithms informing economic evaluations are often derived using baseline data from clinical trials. It is unclear if these algorithms can predict health utilities accurately in post-intervention data. Thus, this study examines the longitudinal predictive ability of mapping algorithms derived from baseline trial data and explores the factors associated with prediction errors. Methods: This methodological study utilized data from an international, multicenter, randomized controlled trial of patients with low-risk prostate cancer (PC), conducted by NRG Oncology (NCT00331773). In addition to patient demographic and clinical data, this study utilized PRO data collected at baseline and 6, 12 and 24 months post-intervention. The Expanded Prostate Cancer Index Composite (EPIC) questionnaire measures health-related quality-of-life (HRQoL) and has four domains (urinary, sexual, hormonal, and bowel) and two subdomains per domain (function and bother); EuroQOL-5D-3L (EQ5D) captures health utilities. Ordinary Least Squares (OLS) regression models were used to map EPIC scores to EQ5D utilities in the baseline data through 5-fold cross-validation. Predictive performance was tested in the post-intervention data; predicted and reported utilities were compared using t-tests, and the absolute prediction error was modeled using fixed effects, as a function of baseline demographic and clinical covariates, as well as observed and predicted EQ5D utilities. Results: A total of 267 (199) patients had complete EQ5D and EPIC domain (or subdomain) data at baseline and all subsequent assessments. In the EPIC domain sample, mean ± standard deviation observed EQ5D utility was 0.90±0.13 at baseline, 0.92±0.11 at 6 months, 0.90±0.13 at 12 months and 0.89±0.14 at 24 months. Mean absolute differences (MDs) between reported and predicted were lower for models using EPIC subdomain data compared to EPIC domain data, and generally decreased as the time of assessment increased. The mapping functions over-predicted utilities for patients in perfect health while the prediction errors were increasingly negative for lower reported EQ5D scores. According to the fixed effects model for EPIC domain data, lower observed and predicted baseline EQ5D scores, and time of assessment were significant predictors of the absolute prediction error; for EPIC subdomain data, lower observed and predicted baseline EQ5D scores, hormonal bother and function, and bowel function significantly predicted the absolute prediction error. Conclusions: This study is the first to demonstrate the longitudinal validity of EPIC questionnaire, and builds upon existing research on longitudinal validity of mapping functions. The low MDs in prediction errors in post-intervention data indicate that the mapping functions are sensitive to treatment effect, thereby increasing confidence in their use in economic evaluations in PC.

Anal cancer is rare in the general population but is steadily increasing in incidence over the past decade especially in women . Identification and screening of women with high risk facilitates detection of anal precancer and early-stage cancer, improves survival, and potentially uses less invasive therapies compared with the conventional chemoradiation treatments used for advanced cancers. No recently published guidelines currently describe details about screening women for anal squamous cell cancer (ASCC). The available evidence supports the existence of groups of women with higher prevalence of ASCC (e.g., women with human immunodeficiency virus, immune suppression, or previous lower-genital high-grade lesion or cancer) who would likely benefit from screening with some combination of anal cytology and human papillomavirus testing. Additional research is needed to establish the cost-effectiveness and the influence of screening on ASCC mortality rates.

55 Background: To compare the predictive ability of health utility mapping algorithms derived using cross-sectional and longitudinal data specific to the Expanded Prostate Cancer Index Composite (EPIC). Methods: This mapping study utilized data from an international, multicenter, randomized controlled trial of patients with low-risk prostate cancer conducted by NRG Oncology (NCT00331773). Health-related quality-of-life (HRQoL) data were collected using EPIC, and health utilities were obtained using EuroQOL-5D (EQ5D) at baseline and 6, 12 and 24 months post-intervention. Data were split into an estimation sample (70%) and a validation sample (30%). Ordinary Least Squares (OLS) regression models were estimated using baseline cross-sectional data as well as pooled data from all assessment periods. Random effects (RE) specifications that explicitly model the longitudinal nature of the data were also estimated. Candidate models were selected based on root mean square error (RMSE). Results: A total of 196 (147) patients in the estimation sample had complete EQ5D and EPIC domain (subdomain) data at all time points. OLS models using combined data outperformed the counter-part RE models as well as OLS models using baseline data in the five-fold cross-validation. Addition of covariates to the models resulted in improved predictive ability. In the external validation, when only EPIC domain/ subdomain data are available, the OLS model using combined data predicted EQ5D utilities better than the counterpart RE model and OLS model using baseline data (RMSE=0.121108 & 0.111345). OLS model using baseline data outperformed other model types for algorithms with EPIC domains and demographics (RMSE=0.121757), while RE models outperformed the other two model types for algorithms with EPIC subdomains and demographic data, (0.112782) and for algorithms with EPIC domains/ subdomains, demographics, and clinical covariates (RMSE=0.123589 & 0.163093). Conclusions: While algorithms using pooled data outperformed other model types in internal validation, RE models showed better predictive ability in external validation for algorithms with covariates. Clinical trial information: NCT00331773.

276 Background: Decipher is a genomic classifier (GC) that estimates risk of prostate cancer (PCa) distant metastases (DM) post-radical prostatectomy (RP). Herein, we validate the GC within the context of a randomized phase 3 trial. Methods: RP specimens from patients on the NRG/RTOG 9601 phase 3 placebo-controlled randomized trial of salvage radiotherapy (sRT) +/- 2 years of bicalutamide (NCT00002874) were centrally reviewed and the highest-grade tumor underwent RNA extraction. Samples passing quality control (QC) were run on a clinical-grade whole-transcriptome assay to assign the GC score (scale 0-1). Our NCTN-CCSC approved pre-specified statistical plan (NRG-GU-TS002 CSC0075) included the primary objective of validating the ability of the GC to independently prognosticate the cumulative incidence of DM, with secondary endpoints of prostate cancer-specific mortality (PCSM) and overall survival (OS). Results: Of patients with tissue available, 352 passed QC and were included for analysis. The final GC cohort was a representative sample of the overall cohort, with a median follow-up of 13 years. On multivariable analysis, the GC (continuous variable) was independently associated with DM (HR 1.19 [95%CI 1.06-1.35], p=0.003), PCSM (HR 1.37 [95%CI 1.18-1.61], p<0.001), and OS (HR 1.16 [95%CI 1.06-1.28], p=0.002) after adjusting for age, race, Gleason score, T-stage, margin status, entry PSA, and treatment arm. The estimated absolute impact of bicalutamide on 12-year OS was less in patients with lower vs higher GC scores (2.4% vs 8.9%), further demonstrated in men receiving early sRT at PSA <0.7 ng/mL (-2.0% vs 5.0%). Conclusions: This is the first validation of this GC in a prospective randomized trial cohort and demonstrates association of the GC with DM and PCSM independent of standard clinicopathologic variables. The GC may help personalize shared decision-making to weigh the absolute benefit from the addition of bicalutamide to sRT.

Aquifer Geriatrics, formerly web‐based Geriatrics Education Modules, was initially developed through Donald W. Reynolds Foundation funding, and is now the national curriculum of the American Geriatrics Society and the Association of Directors of Geriatric Academic Programs. Aquifer Geriatrics consists of 26 evidence‐based, peer‐reviewed, online case‐based modules based on the Association of American Medical Colleges/John A. Hartford Foundation Minimum Geriatrics Competencies for Medical Students and is available by subscription at www.aquifer.org/courses . This curriculum aims to help address the national shortage of geriatrics educators, complement current teaching, bridge content gaps in geriatrics education, and standardize geriatrics‐focused educational content. This report will describe the development of Aquifer Geriatrics, highlight best practices to incorporate cases in a variety of teaching settings, describe teaching methods that utilize the curriculum to create a robust experience for learners, and address the cost of obtaining the curriculum. J Am Geriatr Soc 67:811–817, 2019.