Dayes, Ian S.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. NRG Oncology RTOG 0415 is a randomized phase III noninferiority (NI) clinical trial comparing conventional fractionation (73.8 Gy in 41 fractions) radiotherapy (C-RT) with hypofractionation (H-RT; 70 Gy in 28) in patients with low-risk prostate cancer. The study included 1,092 protocol-eligible patients initially reported in 2016 with a median follow-up of 5.8 years. Updated results with median follow-up of 12.8 years are now presented. The estimated 12-year disease-free survival (DFS) is 56.1% (95% CI, 51.5 to 60.5) for C-RT and 61.8% (95% CI, 57.2 to 66.0) for H-RT. The DFS hazard ratio (H-RT/C-RT) is 0.85 (95% CI, 0.71 to 1.03), confirming NI ( P < .001). Twelve-year cumulative incidence of biochemical failure (BF) was 17.0% (95% CI, 13.8 to 20.5) for C-RT and 9.9% (95% CI, 7.5 to 12.6) for H-RT. The HR (H-RT/C-RT) comparing biochemical recurrence between the two arms was 0.55 (95% CI, 0.39 to 0.78). Late grade ≥3 GI adverse event (AE) incidence is 3.2% (C-RT) versus 4.4% (H-RT), with relative risk (RR) for H-RT versus C-RT 1.39 (95% CI, 0.75 to 2.55). Late grade ≥3 genitourinary (GU) AE incidence is 3.4% (C-RT) versus 4.2% (H-RT), RR 1.26 (95% CI, 0.69 to 2.30). Long-term DFS is noninferior with H-RT compared with C-RT. BF is less with H-RT. No significant differences in late grade ≥3 GI/GU AEs were observed between assignments (ClinicalTrials.gov identifier: NCT00331773 ).

320 Background: sRT is used in men with prostate cancer (PC) recurrence following radical prostatectomy (RP) signaled by a persistent or delayed elevation in PSA. It was previously reported that the use of AAT with RT improved cancer control and overall survival (OS). Long-term follow-up (FU) results are presented here. Methods: From 1998to 2003, 760 eligible post-RP patients with Stage pT3N0 or with pT2N0 and positive margins and PSA from 0.2 to 4.0 ng/mL were randomly assigned on a double-blinded, placebo-controlled trial of RT + placebo vs. RT + anti-androgen therapy (AAT) (24 months of bicalutamide, 150mg daily) during and after RT (64.8 Gy in 36 fractions prostate bed). The primary endpoint was OS estimated using Kaplan-Meier method. Time to PC death and metastatic PC (competing risk of death without an event) was estimated using cumulative incidence. The hazard ratio (HR) was obtained using Cox models (OS) and subdistribution HRs (sHRs) used the Fine-Gray model (time to PC death and metastatic PC). All tests are one-sided based on study design. Results: Median FU for surviving patients was 19 years. OS at 18 years was 53% [95% confidence interval (CI): 47-58%] for RT + AAT and 43% [95% CI: 38-48%] for RT + placebo (adjusted HR 0.82 [95% CI: 0.67-1.00], p = 0.025). The 18-year incidence of centrally reviewed PC deaths were 18% [95% CI: 14-22%] RT + AAT and 28% [95% CI: 23-32%] RT + placebo (adjusted sHR = 0.57 [95% CI: 0.42-0.78], p<0.001). The 18-year incidence of metastatic PC was 22% [95% CI: 18-26%] and 31% [95% CI: 26-35%] for AAT and placebo arms respectively with adjusted sHR = 0.59 [95% CI: 0.44-0.80, p<0.001]. Subgroup analyses is shown in the Table. Conclusions: Long term results of 24-month duration AAT during and after sRT are consistent with the primary report with significantly improved long-term OS, reduced incidence of metastatic PC and PC death for RT+AAT. Statistically significant metastatic PC was noted for Gleason score 8-10, study entry PSA>1.5 and margin positive patients and borderline significance was observed in patients with study entry PSA 0.7-1.5. Clinical trial information: NCT00002874 . [Table: see text]

PURPOSE To compare the predictive ability of mapping algorithms derived using cross-sectional and longitudinal data. METHODS This methodological assessment used data from a randomized controlled noninferiority trial of patients with low-risk prostate cancer, conducted by NRG Oncology (ClinicalTrials.gov identifier: NCT00331773 ), which examined the efficacy of conventional schedule versus hypofractionated radiation therapy (three-dimensional conformal external beam radiation therapy/IMRT). Health-related quality-of-life data were collected using the Expanded Prostate Cancer Index Composite (EPIC), and health utilities were obtained using EuroQOL-5D-3L (EQ-5D) at baseline and 6, 12, 24, and 60 months postintervention. Mapping algorithms were estimated using ordinary least squares regression models through five-fold cross-validation in baseline cross-sectional data and combined longitudinal data from all assessment periods; random effects specifications were also estimated in longitudinal data. Predictive performance was compared using root mean square error. Longitudinal predictive ability of models obtained using baseline data was examined using mean absolute differences in the reported and predicted utilities. RESULTS A total of 267 (and 199) patients in the estimation sample had complete EQ-5D and EPIC domain (and subdomain) data at baseline and at all subsequent assessments. Ordinary least squares models using combined data showed better predictive ability (lowest root mean square error) in the validation phase for algorithms with EPIC domain/subdomain data alone, whereas models using baseline data outperformed other specifications in the validation phase when patient covariates were also modeled. The mean absolute differences were lower for models using EPIC subdomain data compared with EPIC domain data and generally decreased as the time of assessment increased. CONCLUSION Overall, mapping algorithms obtained using baseline cross-sectional data showed the best predictive performance. Furthermore, these models demonstrated satisfactory longitudinal predictive ability.

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 &lt;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.

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.

1 Background: To determine whether the efficacy of a hypofractionated (H) schedule is no worse than a conventional (C) schedule in men with low-risk prostate cancer. Methods: From April 2006 to December 2009, one thousand one hundred fifteen men with low-risk prostate cancer (clinical stage T1-2a, Gleason ≤ 6, PSA < 10) were randomly assigned 1:1 to a conventional (C) schedule (73.8 Gy in 41 fractions over 8.2 weeks) or to a hypofractionated (H) schedule (70 Gy in 28 fractions over 5.6 weeks). The trial was designed to establish with 90% power and alpha = 0.05 that (H) results in 5-year disease-free survival (DFS) that is not lower than (C) by more than 7% (hazard ratio (HR) < 1.52). Secondary endpoints include freedom from biochemical recurrence (FFBR) and overall survival. At the third planned interim analysis (July 2015), the NRG Oncology Data Monitoring Committee recommended that the results of the trial be reported. Results: One thousand one hundred and one protocol eligible men were randomized: 547 to C and 554 to H. Median follow-up is 5.9 years. Baseline characteristics are not different according to treatment arm. At the time of analysis 185 DFS events have been observed; 99 in the C arm and 86 in the H arm. The estimated 7-year disease-free survival is 75.6% (95% CI 70.3, 80.1) in the C arm and 81.8% (77.5, 85.3) in the H arm. The DFS HR (C/H) is 0.85 (0.64, 1.14). Comparison of biochemical recurrence (HR = 0.77, (0.51, 1.17)) and overall survival (HR = 0.95, (0.65, 1.41)) also met protocol non-inferiority criteria. Grade ≥ 3 GI toxicity is 3.0% (C) vs. 4.6% (H), Relative risk (RR) for H vs. C 1.53, (95% CI 0.86, 2.83); grade ≥ 3 GU toxicity is 4.5% (C) vs. 6.4% (H), RR = 1.43 (0.86,2.37). Conclusions: In men with low-risk prostate cancer, 70 Gy in 28 fractions over 5.6 weeks is non-inferior to 73.8 Gy in 41 fractions over 8.2 weeks. Clinical trial information: NCT00331773.