Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer.

PURPOSE: Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. PATIENTS AND METHODS: We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247) of patients undergoing PD-1/PD-L1 inhibitor-based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. RESULTS: Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor-based treatments, evidenced by high concordance between predicted and observed CB (R2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). CONCLUSION: Plasma proteome-based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor-based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy.

PURPOSE: Traditional methods of evaluating cardiotoxicity focus on radiation doses to the heart. Functional imaging has the potential to provide improved prediction for cardiotoxicity for patients with lung cancer. Fluorine-18 (18F) fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) imaging is routinely obtained in a standard cancer staging workup. This work aimed to develop a radiomics model predicting clinical cardiac assessment using 18F-FDG PET/CT scans before thoracic radiation therapy. METHODS: Pretreatment 18F-FDG PET/CT scans from three study populations (N = 100, N = 39, N = 70) were used, comprising two single-institutional protocols and one publicly available data set. A clinician (V.J.) classified the PET/CT scans per clinical cardiac guidelines as no uptake, diffuse uptake, or focal uptake. The heart was delineated, and 210 novel functional radiomics features were selected to classify cardiac FDG uptake patterns. Training data were divided into training (80%)/validation (20%) sets. Feature reduction was performed using the Wilcoxon test, hierarchical clustering, and recursive feature elimination. Ten-fold cross-validation was carried out for training, and the accuracy of the models to predict clinical cardiac assessment was reported. RESULTS: From 202 of 209 scans, cardiac FDG uptake was scored as no uptake (39.6%), diffuse uptake (25.3%), and focal uptake (35.1%), respectively. Sixty-two independent radiomics features were reduced to nine clinically pertinent features. The best model showed 93% predictive accuracy in the training data set and 80% and 92% predictive accuracy in two external validation data sets. CONCLUSION: This work used an extensive patient data set to develop a functional cardiac radiomic model from standard-of-care 18F-FDG PET/CT scans, showing good predictive accuracy. The radiomics model has the potential to provide an automated method to predict existing cardiac conditions and provide an early functional biomarker to identify patients at risk of developing cardiac complications after radiotherapy.

Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy.

Introduction: Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance. Methods: Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes. Results: The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage. Conclusions: Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.

The Inherited KRAS-variant as a Biomarker of Cetuximab Response in NSCLC.

PURPOSE: RTOG 0617 was a phase III randomized trial for patients with unresectable stage IIIA/IIIB non-small cell lung cancer comparing standard-dose (60 Gy) versus high-dose (74 Gy) radiotherapy and chemotherapy, plus or minus cetuximab. Although the study was negative, based on prior evidence that patients with the KRAS-variant, an inherited germline mutation, benefit from cetuximab, we evaluated KRAS-variant patients in RTOG 0617. EXPERIMENTAL DESIGN: From RTOG 0617, 328 of 496 (66%) of patients were included in this analysis. For time-to-event outcomes, stratified log-rank tests and multivariable Cox regression models were used. For binary outcomes, Cochran-Mantel-Haenzel tests and multivariable logistic regression models were used. All statistical tests were two sided, and a P value <0.05 was considered significant. RESULTS: A total of 17.1% (56/328) of patients had the KRAS-variant, and overall survival rates were similar between KRAS-variant and non-variant patients. However, there was a time-dependent effect of cetuximab seen only in KRAS-variant patients-while the hazard of death was higher in cetuximab-treated patients within year 1 [HR = 3.37, 95% confidence interval (CI): 1.13-10.10, P = 0.030], death was lower from year 1 to 4 (HR = 0.33, 95% CI: 0.11-0.97, P = 0.043). In contrast, in non-variant patients, the addition of cetuximab significantly increased local failure (HR = 1.59, 95% CI: 1.11-2.28, P = 0.012). CONCLUSIONS/DISCUSSION: Although an overall survival advantage was not achieved in KRAS-variant patients, there is potential impact of cetuximab for this genetic subset of patients. In contrast, cetuximab seems to harm non-variant patients. These findings further support the importance of genetic patient selection in trials studying the addition of systemic agents to radiotherapy. SIGNIFICANCE: The KRAS-variant is the first functional, inherited miRNA-disrupting variant identified in cancer. Our findings support that cetuximab has a potentially beneficial impact on KRAS-variant patients treated with radiation. The work confirms prior evidence that KRAS-variant patients are a subgroup who are especially sensitive to radiation. These findings further support the potential of this class of variants to enable true treatment personalization, considering the equally important endpoints of response and toxicity.

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.

PURPOSE: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas. METHODS: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS). RESULTS: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS. CONCLUSION: Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas.

Enhancing bladder cancer care through the multidisciplinary clinic approach.

INTRODUCTION: To report the impact of our 25-year multidisciplinary care delivery model experience on patients with muscle invasive bladder cancer treated at our National Cancer Institute (NCI)-designated Sidney Kimmel Cancer Center at Jefferson University. To our knowledge, our multidisciplinary genitourinary cancer clinic (MDC) is the longest continuously operating center of its kind at an NCI Cancer Center in the United States. MATERIALS AND METHODS: We selected a recent group of patients with cT2-4 N0-1 M0 bladder cancer seen in the Sidney Kimmel Cancer Center Genitourinary Oncology MDC from January 2016 to September 2019. These patients were identified retrospectively. SEER-18 (Surveillance, Epidemiology, and End Results) database, November 2019 submission was queried to obtain patients with similarly staged disease diagnosed between 2015 and 2017. Completion rates of radical cystectomy, use of neoadjuvant therapies, and survival outcomes were compared between the two cohorts. RESULTS: Ninety-one patients from the MDC form this time period were identified; 65.9% underwent radical cystectomy and 71.8% received neoadjuvant therapy in the form of chemotherapy, immune checkpoint inhibition or a combination of the two - higher than reported national trends for neoadjuvant therapies. Progression of disease was seen in 24.2% of patients. A total of 8675 patients met inclusion criteria in the SEER database. Rates of radical cystectomy were significantly higher in MCD patients when compared to SEER derived data (65.9% vs. 37.7%, p =< 0.001). MCD patients had significantly better cancer-specific survival (mean 20.4 vs. 18.3 months p = 0.028, median survival not reached). CONCLUSION: Our long term experience caring for patients with genitourinary malignancies such as bladder cancer in a uniform multidisciplinary team results in a high utilization of neoadjuvant therapies. When compared to a contemporary SEER-derived cohort, multidisciplinary patients were more likely to undergo radical cystectomy and had longer cancer-specific survival.

Practical Steps to Mitigate Cybersecurity Attacks on Radiation Oncology Practices.

Radiation oncology, as a technologically intensive discipline that requires communication between multiple and diverse computer systems, is vulnerable to cyberattack. Given the enormous amount of the loss of time, energy, and money that results from a cyberattack, it behooves radiation oncologists and their teams to minimize cybersecurity threats to their practices. In this article, we present practical steps that radiation oncologists can take to prevent, prepare for, and respond to a cyberattack.

Remote Activity Monitoring and Electronic Patient-Reported Outcomes Collection During Radiotherapy for Head and Neck Cancer: A Pilot Study.

PURPOSE: Modern wearable devices provide objective and continuous activity data that could be leveraged to enhance cancer care. We prospectively studied the feasibility of monitoring physical activity using a commercial wearable device and collecting electronic patient-reported outcomes (ePROs) during radiotherapy (RT) for head and neck cancer (HNC). METHODS: Patients planned for a course of external beam RT with curative intent for HNC were instructed to use a commercial fitness tracker throughout the RT course. During weekly clinic visits, physician-scored adverse events were recorded during using Common Terminology Criteria for Adverse Events version 4.0, and patients completed ePRO surveys using a clinic tablet or computer. Feasibility of activity monitoring was defined as collection of step data for at least 80% of the RT course for at least 80% of patients. Exploratory analyses described associations between step counts, ePROs, and clinical events. RESULTS: Twenty-nine patients with HNC were enrolled and had analyzable data. Overall, step data were recorded on 70% of the days during patients' RT courses, and there were only 11 patients (38%) for whom step data were collected on at least 80% of days during RT. Mixed effects linear regression models demonstrated declines in daily step counts and worsening of most PROs during RT. Cox proportional hazards models revealed a potential association between high daily step counts and both reduced risk of feeding tube placement (hazard ratio [HR], 0.87 per 1,000 steps, P < .001) and reduced risk of hospitalization (HR, 0.60 per 1,000 steps, P < .001). CONCLUSION: We did not achieve our feasibility end point, suggesting that rigorous workflows are required to achieve continuous activity monitoring during RT. Although limited by a modest sample size, our findings are consistent with previous reports indicating that wearable device data can help identify patients who are at risk for unplanned hospitalization.

Developing a Patient-Reported Outcome Measure for Radionuclide Therapy for Prostate Cancer.

The field of radionuclide therapy (RNT) for prostate cancer (PC) is growing rapidly, with recent Food and Drug Administration approval of the first 177Lu-PSMA ligand. We aimed to develop the first patient-reported outcome (PRO) measure for PC patients receiving RNT. Methods: We identified relevant symptoms and toxicities by reviewing published trials and interviews with PC patients receiving RNT (n = 29), caregivers (n = 14), and clinicians (n = 11). Second, we selected items for measure inclusion. Third, we refined the item list with input from experts in RNTs and PROs. Fourth, we finalized the Functional Assessment of Cancer Therapy-Radionuclide Therapy (FACT-RNT) with patient input. Results: This multistep process yielded a brief 15-item measure deemed by key stakeholders to be relevant and useful in the context of RNT for PC. Conclusion: The FACT-RNT is a new standardized tool to monitor relevant symptoms and toxicities among PC patients in RNT trials and real-world settings.

Analysis of a Biopsy-Based Genomic Classifier in High-Risk Prostate Cancer: Meta-Analysis of the NRG Oncology/Radiation Therapy Oncology Group 9202, 9413, and 9902 Phase 3 Randomized Trials.

PURPOSE: Decipher is a genomic classifier (GC) prospectively validated postprostatectomy. We validated the performance of the GC in pretreatment biopsy samples within the context of 3 randomized phase 3 high-risk definitive radiation therapy trials. METHODS AND MATERIALS: A prespecified analysis plan (NRG-GU-TS006) was approved to obtain formalin-fixed paraffin-embedded tissue from biopsy specimens from the NRG biobank from patients enrolled in the NRG/Radiation Therapy Oncology Group (RTOG) 9202, 9413, and 9902 phase 3 randomized trials. After central review, the highest-grade tumors were profiled on clinical-grade whole-transcriptome arrays and GC scores were obtained. The primary objective was to validate the independent prognostic ability for the GC for distant metastases (DM), and secondary for prostate cancer-specific mortality (PCSM) and overall survival (OS) with Cox univariable and multivariable analyses. RESULTS: GC scores were obtained on 385 samples, of which 265 passed microarray quality control (69%) and had a median follow-up of 11 years (interquartile range, 9-13). In the pooled cohort, on univariable analysis, the GC was shown to be a prognostic factor for DM (per 0.1 unit; subdistribution hazard ratio [sHR], 1.29; 95% confidence interval [CI], 1.18-1.41; P < .001), PCSM (sHR, 1.28; 95% CI, 1.16-1.41; P < .001), and OS (hazard ratio [HR], 1.16; 95% CI, 1.08-1.22; P < .001). On multivariable analyses, the GC (per 0.1 unit) was independently associated with DM (sHR, 1.22; 95% CI, 1.09-1.36), PCSM (sHR, 1.23; 95% CI, 1.09-1.39), and OS (HR, 1.12; 95% CI, 1.05-1.20) after adjusting for age, Prostate Specific Antigen, Gleason score, cT stage, trial, and randomized treatment arm. GC had similar prognostic ability in patients receiving short-term or long-term androgen-deprivation therapy, but the absolute improvement in outcome varied by GC risk. CONCLUSIONS: This is the first validation of a gene expression biomarker on pretreatment prostate cancer biopsy samples from prospective randomized trials and demonstrates an independent association of GC score with DM, PCSM, and OS. High-risk prostate cancer is a heterogeneous disease state, and GC can improve risk stratification to help personalize shared decision making.

NRG Oncology/RTOG1205: A Randomized Phase II Trial of Concurrent Bevacizumab and Reirradiation Versus Bevacizumab Alone as Treatment for Recurrent Glioblastoma.

PURPOSE: To assess whether reirradiation (re-RT) and concurrent bevacizumab (BEV) improve overall survival (OS) and/or progression-free survival (PFS), compared with BEV alone in recurrent glioblastoma (GBM). The primary objective was OS, and secondary objectives included PFS, response rate, and treatment adverse events (AEs) including delayed CNS toxicities. METHODS: NRG Oncology/RTOG1205 is a prospective, phase II, randomized trial of re-RT and BEV versus BEV alone. Stratification factors included age, resection, and Karnofsky performance status (KPS). Patients with recurrent GBM with imaging evidence of tumor progression ≥ 6 months from completion of prior chemo-RT were eligible. Patients were randomly assigned 1:1 to re-RT, 35 Gy in 10 fractions, with concurrent BEV IV 10 mg/kg once in every 2 weeks or BEV alone until progression. RESULTS: From December 2012 to April 2016, 182 patients were randomly assigned, of whom 170 were eligible. Patient characteristics were well balanced between arms. The median follow-up for censored patients was 12.8 months. There was no improvement in OS for BEV + RT, hazard ratio, 0.98; 80% CI, 0.79 to 1.23; P = .46; the median survival time was 10.1 versus 9.7 months for BEV + RT versus BEV alone. The median PFS for BEV + RT was 7.1 versus 3.8 months for BEV, hazard ratio, 0.73; 95% CI, 0.53 to 1.0; P = .05. The 6-month PFS rate improved from 29.1% (95% CI, 19.1 to 39.1) for BEV to 54.3% (95% CI, 43.5 to 65.1) for BEV + RT, P = .001. Treatment was well tolerated. There were a 5% rate of acute grade 3+ treatment-related AEs and no delayed high-grade AEs. Most patients died of recurrent GBM. CONCLUSION: To our knowledge, NRG Oncology/RTOG1205 is the first prospective, randomized multi-institutional study to evaluate the safety and efficacy of re-RT in recurrent GBM using modern RT techniques. Overall, re-RT was shown to be safe and well tolerated. BEV + RT demonstrated a clinically meaningful improvement in PFS, specifically the 6-month PFS rate but no difference in OS.

Genomic Testing in Localized Prostate Cancer Can Identify Subsets of African Americans With Aggressive Disease.

BACKGROUND: Personalized genomic classifiers have transformed the management of prostate cancer (PCa) by identifying the most aggressive subsets of PCa. Nevertheless, the performance of genomic classifiers to risk classify African American men is thus far lacking in a prospective setting. METHODS: This is a prospective study of the Decipher genomic classifier for National Comprehensive Cancer Network low- and intermediate-risk PCa. Study-eligible non-African American men were matched to African American men. Diagnostic biopsy specimens were processed to estimate Decipher scores. Samples accrued in NCT02723734, a prospective study, were interrogated to determine the genomic risk of reclassification (GrR) between conventional clinical risk classifiers and the Decipher score. RESULTS: The final analysis included a clinically balanced cohort of 226 patients with complete genomic information (113 African American men and 113 non-African American men). A higher proportion of African American men with National Comprehensive Cancer Network-classified low-risk (18.2%) and favorable intermediate-risk (37.8%) PCa had a higher Decipher score than non-African American men. Self-identified African American men were twice more likely than non-African American men to experience GrR (relative risk [RR] = 2.23, 95% confidence interval [CI] = 1.02 to 4.90; P = .04). In an ancestry-determined race model, we consistently validated a higher risk of reclassification in African American men (RR = 5.26, 95% CI = 1.66 to 16.63; P = .004). Race-stratified analysis of GrR vs non-GrR tumors also revealed molecular differences in these tumor subtypes. CONCLUSIONS: Integration of genomic classifiers with clinically based risk classification can help identify the subset of African American men with localized PCa who harbor high genomic risk of early metastatic disease. It is vital to identify and appropriately risk stratify the subset of African American men with aggressive disease who may benefit from more targeted interventions.

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood. METHODS: We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group. RESULTS: We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins. CONCLUSIONS: Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

Variation in Molecularly Defined Prostate Tumor Subtypes by Self-identified Race.

Background: Socioeconomic and health care utilization factors are major drivers of prostate cancer (PC) mortality disparities in the USA; however, tumor molecular heterogeneity may also contribute to the higher mortality among Black men. Objective: To compare differences in PC subtype frequency and genomic aggressiveness by self-identified race. Design setting and participants: Five molecular subtype classifiers were applied for 426 Black and 762 White PC patients in the Decipher Genomics Resource Information Database (GRID). Outcome measurements and statistical analysis: Differences in subtype frequency and tumor genomic risk (Decipher score >0.6) by race were evaluated using χ2 tests and multivariable-adjusted logistic regression models. Results and limitations: Subtype frequencies differed by race for four classifiers. Subtypes characterized by the presence of SPOP mutations, SPINK1 overexpression, and neuroendocrine differentiation were more common among Black men. ERG and ETS fusion-positive subtypes were more frequent among White men, with no clear differences for subtypes reflecting luminal versus basal lineage. The hypothesized low-risk Kamoun S2 subtype was associated with a lower Decipher score among White men only (p = 0.01 for heterogeneity), while the aggressive You PCS1 subtype was associated with a higher Decipher score among White men only (p = 0.001 for heterogeneity). The Tomlins ERG+ subtype was associated with a higher Decipher score relative to all other subtypes among Black men, with no association among White men (p = 0.007 for heterogeneity). Conclusions: The frequency of PC molecular subtypes differed by self-identified race. Additional studies are required to evaluate whether our observations suggest differences in the tumor genomic risk of progression by self-identified race. Patient summary: We studied five classifiers that identify subtypes of prostate tumors and found that subtypes differed in frequency between Black and White patients. Further research is warranted to evaluate how differences in tumor subtypes may contribute to disparities in prostate cancer mortality.

A Pilot Feasibility Study of Digital Health Coaching for Men With Prostate Cancer.

PURPOSE: Prostate cancer is the most common cancer among men in the United States. The majority of prostate cancer treatment occurs in the ambulatory setting, and patients and their caregivers take on significant responsibility for monitoring and managing treatment and disease-related toxicity. Digital health coaching has shown promise as a tool to positively influence outcomes. We completed a single-arm pilot study to assess the feasibility of digital health coaching in men with prostate cancer. METHODS: Men with a history of prostate cancer requiring treatment in the past 2 years were eligible for inclusion. Participants engaged in a 12-week health coaching program, consisting of a combination of at least one telephone call and up to four digital nudges (defined as content delivered via text, e-mail, or app on the basis of the participant's preference) per week. Prostate cancer-specific content addressed one of the following topics each week: fatigue, pain management, healthy eating, exercise, managing incontinence, sexual health, managing stress and anxiety, financial toxicity, goal setting during treatment, managing side effects, communicating with the health care team, and medication adherence. Services were provided at no cost to the participant. RESULTS: A hundred patients were consented for the study, and 88 enrolled. The feasibility threshold of 60% was met with 63 of the 88 enrolled individuals completing the 3-month program (proportion = 71.6%; 90% CI, 62.6 to 79.4; P = .016). CONCLUSION: Digital health coaching for men with prostate cancer is feasible. These findings support further evaluation of digital health coaching for men with prostate cancer in larger randomized controlled trials.

Coeliac plexus radiosurgery for pain management in patients with advanced cancer : study protocol for a phase II clinical trial.

INTRODUCTION: Pancreatic cancer is characterised by severe mid-back and epigastric pain caused by tumour invasion of the coeliac nerve plexus. This pain is often poorly managed with standard treatments. This clinical trial investigates a novel approach in which high-dose radiation (radiosurgery) is targeted to the retroperitoneal coeliac plexus nerve bundle. Preliminary results from a single institution pilot trial are promising: pain relief is substantial and side effects minimal. The goals of this study are to validate these findings in an international multisetting, and investigate the impact on quality of life and functional status among patients with terminal cancer. METHODS AND ANALYSIS: A single-arm prospective phase II clinical trial. Eligible patients are required to have severe coeliac pain of at least five on the 11-point BPI average pain scale and Eastern Cooperative Oncology Group performance status of two or better. Non-pancreatic cancers invading the coeliac plexus are also eligible. The intervention involves irradiating the coeliac plexus using a single fraction of 25 Gy. The primary endpoint is the complete or partial pain response at 3 weeks. Secondary endpoints include pain at 6 weeks, analgesic use, hope, qualitative of life, caregiver burden and functional outcomes, all measured using validated instruments. The protocol is expected to open at a number of cancer centres across the globe, and a quality assurance programme is included. The protocol requires that 90 evaluable patients" be accrued, based upon the assumption that a third of patients are non-evaluable (e.g. due to death prior to 3-weeks post-treatment assessment, or spontaneous improvement of pain pre-treatment), it is estimated that a total of 120 patients will need to be accrued. Supported by Gateway for Cancer Research and the Israel Cancer Association. ETHICS AND DISSEMINATION: Ethic approval for this study has been obtained at eight academic medical centres located across the Middle East, North America and Europe. Results will be disseminated through conference presentations and peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT03323489.

Meta-Analysis of Quality of Life in Cancer Patients Treated With Immune Checkpoint Inhibitors.

BACKGROUND: Trials of immune checkpoint inhibitors (ICIs) have published patient-reported quality of life (QOL), but the size and heterogeneity of this literature can make patient education difficult. This meta-analysis aimed to describe change in QOL and symptomatology in patients receiving ICIs for cancer. METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, databases were searched through November 2019 for articles or abstracts of prospective, original studies reporting longitudinal QOL in adult cancer patients treated with ICIs. The prespecified primary outcomes were change in global QOL among patients treated with ICIs and difference in change since baseline in global QOL between patients treated with ICI vs non-ICI active treatment. Secondary outcomes included physical functioning and symptomatology. All statistical tests were 2-sided. RESULTS: Of 20 323 publications, 26 met inclusion criteria. Global QOL did not change over time in patients treated with ICIs (k = 26, n = 6974; P = .19). Larger improvements in global QOL was observed in patients receiving ICI vs non-ICI regimens (k = 16, ICI: n = 3588; non-ICI: n = 2948; P < .001). Physical functioning did not change in patients treated with ICIs (k = 14, n = 3169; P = .47); there were no differences in mean change between ICI vs non-ICI regimens (k = 11, n = 4630; P = .94). Regarding symptoms, appetite loss, insomnia, and pain severity decreased, but dyspnea severity increased in patients treated with ICIs (k = 14, n = 3243-3499; P < .001). Insomnia severity was higher in patients treated with ICIs than non-ICI regimens (k = 11, n = 4791; P < .001). CONCLUSIONS: This study is among the first to quantitatively summarize QOL in patients treated with ICIs. Findings suggest ICI recipients report no change in global QOL and higher QOL than patients treated with non-ICI regimens.

Subpathologies and genomic classifier for treatment individualization of post-prostatectomy radiotherapy.

PURPOSE/OBJECTIVE: Risk-stratification for post-prostatectomy radiotherapy (PORT) using conventional clinicopathologic indexes leads to substantial over- and under-treatment. Better patient selection could spare unnecessary toxicities and improve outcomes. We investigated the prognostic utility of unfavorable subpathologies intraductal carcinoma and cribriform architecture (IDC/CA), and a 22-gene Decipher genomic classifier (GC) in prostate cancer (PCa) patients receiving PORT. MATERIAL/METHODS: A cohort of 302 men who received PORT at 2 academic institutions was pooled. PORT was predominately delivered as salvage (62% of cases); 20% received HT+PORT. Specimens were centrally reviewed for IDC/CA presence. In 104 cases, GC scores were determined. Endpoints were biochemical relapse-free (bRFR) and metastasis-free (mFR) rates. RESULTS: After a median follow-up of 6.49-years, 135 (45%) and 40 (13%) men experienced biochemical relapse and metastasis, respectively. IDC/CA were identified in 160 (53%) of cases. Men harboring IDC/CA experienced inferior bRFR (HR 2.6, 95%CI 1.8-3.2, P<0.001) and mFR (HR 3.1, 95%CI 1.5-6.4, P = 0.0014). Patients with GC scores, 22 (21%) were stratified low-, 30 (29%) intermediate-, and 52 (50%) high-risk. GC low-risk was associated with superior bRFR (HR 0.25, 95%CI 0.1-0.5, P<0.001) and mFR (HR 0.15, 95%CI 0.03-0.8, P = 0.025). On multivariable analyses, IDC/CA and GC independently predicted for bRFR, corresponding to improved discrimination (C-index = 0.737 (95%CI 0.662-0.813)). CONCLUSIONS: IDC/CA subpathologies and GC predict for biochemical relapse and metastasis beyond conventional clinicopathologic indexes in the PORT setting. Patients harboring IDC/CA are at higher risk of relapse after maximal local therapies, thus warranting consideration for treatment intensification strategies. Conversely, for men with absence of IDC/CA and low GC scores, de-intensification strategies could be explored.

Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I Meningiomas.

BACKGROUND: Although World Health Organization (WHO) grade I meningiomas are considered "benign" tumors, an elevated Ki-67 is one crucial factor that has been shown to influence tumor behavior and clinical outcomes. The ability to preoperatively discern Ki-67 would confer the ability to guide surgical strategy. OBJECTIVE: In this study, we develop a machine learning (ML) algorithm using radiomic feature analysis to predict Ki-67 in WHO grade I meningiomas. METHODS: A retrospective analysis was performed for a cohort of 306 patients who underwent surgical resection of WHO grade I meningiomas. Preoperative magnetic resonance imaging was used to perform radiomic feature extraction followed by ML modeling using least absolute shrinkage and selection operator wrapped with support vector machine through nested cross-validation on a discovery cohort (n = 230), to stratify tumors based on Ki-67 <5% and ≥5%. The final model was independently tested on a replication cohort (n = 76). RESULTS: An area under the receiver operating curve (AUC) of 0.84 (95% CI: 0.78-0.90) with a sensitivity of 84.1% and specificity of 73.3% was achieved in the discovery cohort. When this model was applied to the replication cohort, a similar high performance was achieved, with an AUC of 0.83 (95% CI: 0.73-0.94), sensitivity and specificity of 82.6% and 85.5%, respectively. The model demonstrated similar efficacy when applied to skull base and nonskull base tumors. CONCLUSION: Our proposed radiomic feature analysis can be used to stratify WHO grade I meningiomas based on Ki-67 with excellent accuracy and can be applied to skull base and nonskull base tumors with similar performance achieved.

Digital Literacy at an Urban Cancer Center: Implications for Technology Use and Vulnerable Patients.

PURPOSE: eHealth literacy, or the ability to seek, find, understand, and appraise health information from electronic sources, has become increasingly relevant in the era of COVID-19, when so many aspects of patient care became dependent on technology. We aimed to understand eHealth literacy among a diverse sample of patients with cancer and discuss ways for health systems and cancer centers to ensure that all patients have access to high-quality care. METHODS: A cross-sectional survey of patients with cancer and caregivers was conducted at an NCI-designated cancer center to assess access to the Internet, smartphone ownership, use of mobile apps, willingness to engage remotely with the health care team, and use of the patient portal. Descriptive statistics and bivariate analyses were used to assess frequencies and significant differences between variables. RESULTS: Of 363 participants, 55% (n = 201) were female, 71% (n = 241) identified as non-Hispanic White, and 29% (n = 85) reported that their highest level of education was a high school diploma. Most (90%, n = 323) reported having access to the Internet and most (82%, n = 283) reported owning a smartphone. Younger patients or those with a college degree were significantly more likely to own a smartphone, access health information online, know how to download an app on their own, have an interest in communicating with their health care team remotely, or have an account on the electronic patient portal. CONCLUSION: As cancer centers increasingly engage patients through electronic and mobile applications, patients with low or limited digital literacy may be excluded, exacerbating current cancer health disparities. Patient-, provider- and system-level technology barriers must be understood and mitigated.