PURPOSE Precision medicine has revolutionized oncology; however, tumor biomarkers are not reflective of the heterogeneous cancer population. We evaluated NRG Oncology prostate cancer (PCa) clinical trials for demographic differences among patients with optional biospecimen collection (BC) consent and biospecimen submission (BSub). METHODS Data from 19 NRG PCa clinical trials closed before 2015 were analyzed. Patients who consented to BC and completed BSub were evaluated by race, ethnicity, median income, area deprivation index (ADI; categorized as highest v lowest three quartiles), age at enrollment, site, and year of enrollment. T/chi-square tests were used for continuous/categorical variables, respectively, followed by logistic regression. RESULTS Of the 15,648 randomized patients eligible for BC, 11,796 (75%) had specimens submitted. In all, 4,598 (82.2%) of 5,597 eligible patients consented for optional BC in nine clinical trials with a separate BC consent process (consent rates by race/ethnicity: 74.1% Black, 72.8% Hispanic/Latino, 83.8% White). A smaller proportion of Black and Hispanic/Latino patients consented to optional BC compared with those who did not (12.1% v 19.5% Black, P < .0001; 3.5% v 5.8% Hispanic, P = .0006). In univariable logistic regression models, high ADI (more socioeconomic disadvantage) was associated with a decreased likelihood for optional BC consent (odds ratio [OR], 0.67 [95% CI, 0.55 to 0.82]; P = .02), but not a decreased likelihood for BSub (OR, 0.74 [95% CI, 0.53 to 1.04]; P = .08). Multivariable models demonstrated that Black/Hispanic/Latino patients were less likely to consent to optional BC, and Black patients were less likely to have BSub ( P < .05 for all). CONCLUSION White/non-Hispanic patients and those with less socioeconomic disadvantage were more likely to consent to optional BC, whereas Black patients were less likely to have BSub. Targeted solutions are needed to improve biorepository representation so that precision medicine approaches better reflect the cancer population.
Long-Term Analysis of NRG Oncology RTOG 0415: A Randomized Phase III Noninferiority Study Comparing Two Fractionation Schedules in Patients With Low-Risk Prostate Cancer
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 ).
Integrative Medicine for Pain Management in Oncology: Society for Integrative Oncology–ASCO Guideline
PURPOSE The aim of this joint guideline is to provide evidence-based recommendations to practicing physicians and other health care providers on integrative approaches to managing pain in patients with cancer. METHODS The Society for Integrative Oncology and ASCO convened an expert panel of integrative oncology, medical oncology, radiation oncology, surgical oncology, palliative oncology, social sciences, mind-body medicine, nursing, and patient advocacy representatives. The literature search included systematic reviews, meta-analyses, and randomized controlled trials published from 1990 through 2021. Outcomes of interest included pain intensity, symptom relief, and adverse events. Expert panel members used this evidence and informal consensus to develop evidence-based guideline recommendations. RESULTS The literature search identified 227 relevant studies to inform the evidence base for this guideline. RECOMMENDATIONS Among adult patients, acupuncture should be recommended for aromatase inhibitor–related joint pain. Acupuncture or reflexology or acupressure may be recommended for general cancer pain or musculoskeletal pain. Hypnosis may be recommended to patients who experience procedural pain. Massage may be recommended to patients experiencing pain during palliative or hospice care. These recommendations are based on an intermediate level of evidence, benefit outweighing risk, and with moderate strength of recommendation. The quality of evidence for other mind-body interventions or natural products for pain is either low or inconclusive. There is insufficient or inconclusive evidence to make recommendations for pediatric patients. More research is needed to better characterize the role of integrative medicine interventions in the care of patients with cancer. Additional information is available at https://integrativeonc.org/practice-guidelines/guidelines and www.asco.org/survivorship-guidelines .
Methodological Comparison of Mapping the Expanded Prostate Cancer Index Composite to EuroQoL-5D-3L Using Cross-Sectional and Longitudinal Data: Secondary Analysis of NRG/RTOG 0415
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.
Effect of Electronic Symptom Monitoring on Patient-Reported Outcomes Among Patients With Metastatic Cancer
349527 Background: Symptoms are common during cancer care but often go undetected. Digital systems that elicit patient-reported outcomes (PRO) surveys may detect symptoms early and prompt clinicians to intervene, thereby alleviating suffering and averting complications. Methods: In a cluster-randomized trial, U.S.-based community oncology practices were randomized 1:1 to digital symptom monitoring with PRO surveys, or to usual care control. Patients receiving systemic treatment for metastatic cancer were eligible. At PRO practices, participants were invited to complete a weekly survey via web or automated telephone system for up to one year, including questions about nine common symptoms, performance status, and falls. Severe or worsening symptoms triggered electronic alerts to care team nurses, and reports showing longitudinal symptom data were available to oncologists at visits. Pre-specified secondary outcomes included impact on physical function, symptom control, and health-related quality of life (HRQL). The primary outcome of survival is not yet mature. Results: At 52 practices, 1,191 patients were eligible and enrolled (593 PRO; 598 control). Clinically meaningful benefits were experienced in physical function by 13.8% more patients with PRO versus control (P=0.009); symptom control by 16.1% (P=0.003); and HRQL by 13.4% (P=0.006). Mean changes from baseline were superior with PRO versus control for physical function (mean difference 2.47, 95% CI 0.41-4.53; P=0.02), symptom control (2.56, 0.95-4.17; P=0.002), and HRQL (2.43, 0.90-3.96; P=0.002). Patients completed 20,565/22,486 (91.5%) of expected weekly PRO surveys. Conclusions: Digital symptom monitoring during cancer treatment confers clinical benefits. Clinical trial information: NCT03249090.
Abstract 2528: Rurality and neighborhood socioeconomic deprivation associated with patient-reported outcomes andsurvivalin men with prostate cancer in NRG RTOG 0415
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.
Longitudinal predictive ability of mapping algorithms: Secondary analysis of NRG Oncology/RTOG 0415.
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.
Composite grading algorithm for the National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE)
Background: The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events is an item library designed for eliciting patient-reported adverse events in oncology. For each adverse event, up to three individual items are scored for frequency, severity, and interference with daily activities. To align the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events with other standardized tools for adverse event assessment including the Common Terminology Criteria for Adverse Events, an algorithm for mapping individual items for any given adverse event to a single composite numerical grade was developed and tested. Methods: A five-step process was used: (1) All 179 possible Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events score combinations were presented to 20 clinical investigators to subjectively map combinations to single numerical grades ranging from 0 to 3. (2) Combinations with <75% agreement were presented to investigator committees at a National Clinical Trials Network cooperative group meeting to gain majority consensus via anonymous voting. (3) The resulting algorithm was refined via graphical and tabular approaches to assure directional consistency. (4) Validity, reliability, and sensitivity were assessed in a national study dataset. (5) Accuracy for delineating adverse events between study arms was measured in two Phase III clinical trials (NCT02066181 and NCT01522443). Results: In Step 1, 12/179 score combinations had <75% initial agreement. In Step 2, majority consensus was reached for all combinations. In Step 3, five grades were adjusted to assure directional consistency. In Steps 4 and 5, composite grades performed well and comparably to individual item scores on validity, reliability, sensitivity, and between-arm delineation. Conclusion: A composite grading algorithm has been developed and yields single numerical grades for adverse events assessed via the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events, and can be useful in analyses and reporting.
Clinical Utility and User Perceptions of a Digital System for Electronic Patient-Reported Symptom Monitoring During Routine Cancer Care: Findings From the PRO-TECT Trial
PURPOSE There is increasing interest in implementing digital systems for remote monitoring of patients’ symptoms during routine oncology practice. Information is limited about the clinical utility and user perceptions of these systems. METHODS PRO-TECT is a multicenter trial evaluating implementation of electronic patient-reported outcomes (ePROs) among adults with advanced and metastatic cancers receiving treatment at US community oncology practices (ClinicalTrials.gov identifier: NCT03249090 ). Questions derived from the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) are administered weekly by web or automated telephone system, with alerts to nurses for severe or worsening symptoms. To elicit user feedback, surveys were administered to participating patients and clinicians. RESULTS Among 496 patients across 26 practices, the majority found the system and questions easy to understand (95%), easy to use (93%), and relevant to their care (91%). Most patients reported that PRO information was used by their clinicians for care (70%), improved discussions with clinicians (73%), made them feel more in control of their own care (77%), and would recommend the system to other patients (89%). Scores for most patient feedback questions were significantly positively correlated with weekly PRO completion rates in both univariate and multivariable analyses. Among 57 nurses, most reported that PRO information was helpful for clinical documentation (79%), increased efficiency of patient discussions (84%), and was useful for patient care (75%). Among 39 oncologists, most found PRO information useful (91%), with 65% using PROs to guide patient discussions sometimes or often and 65% using PROs to make treatment decisions sometimes or often. CONCLUSION These findings support the clinical utility and value of implementing digital systems for monitoring PROs, including the PRO-CTCAE, in routine cancer care.