Development of a Web-Based Interactive Tool for Visualizing Breast Cancer Clinical Trial Tolerability Data.

PURPOSE: Longitudinal patient tolerability data collected as part of randomized controlled trials are often summarized in a way that loses information and does not capture the treatment experience. To address this, we developed an interactive web application to empower clinicians and researchers to explore and visualize patient tolerability data. METHODS: We used adverse event (AE) data (Common Terminology Criteria for Adverse Events) and patient-reported outcomes (PROs) from the NSABP-B35 phase III clinical trial, which compared anastrozole with tamoxifen for breast cancer-free survival, to demonstrate the tools. An interactive web application was developed using R and the Shiny web application framework that generates Sankey diagrams to visualize AEs and PROs using four tools: AE Explorer, PRO Explorer, Cohort Explorer, and Custom Explorer. RESULTS: To illustrate how users can use the interactive tool, examples for each of the four applications are presented using data from the NSABP-B35 phase III trial and the NSABP-B30 trial for the Custom Explorer. In the AE and PRO explorers, users can select AEs or PROs to visualize within specified time periods and compare across treatments. In the cohort explorer, users can select a subset of patients with a specific symptom, severity, and treatment received to visualize the trajectory over time within a specified time interval. With the custom explorer, users can upload and visualize structured longitudinal toxicity and tolerability data. CONCLUSION: We have created an interactive web application and tool for clinicians and researchers to explore and visualize clinical trial tolerability data. This adaptable tool can be extended for other clinical trial data visualization and incorporated into future patient-clinician interactions regarding treatment decisions.

High-resolution Diffusion-weighted Imaging to Detect Changes in Tumor Size and ADC, and Predict Adverse Biopsy Histology during Prostate Cancer Active Surveillance.

PURPOSE: Majority of men with low-risk prostate cancer can be managed with active surveillance (AS). This study evaluates a high-resolution diffusion-weighted imaging (HR-DWI) technique to predict adverse biopsy histology (AH), defined as Gleason score ≥7 on any biopsy or ≥3 increase in number of positive biopsy cores on systematic biopsies. We test the hypothesis that high-grade disease and progressing disease undergo subtle changes during even short intervals that can be detected by HR-DWI. EXPERIMENTAL DESIGN: In a prospective clinical trial, serial multiparametric MRIs, incorporating HR-DWI and standard DWI (S-DWI) were performed approximately 12 months apart prior to prostate biopsy (n = 59). HR-DWI, which uses reduced field-of-view and motion compensation techniques, was compared with S-DWI. RESULTS: HR-DWI had a 3-fold improvement in spacial resolution compared with S-DWI as confirmed using imaging phantoms. For detecting AH, multiparametric MRI using HR-DWI had a sensitivity of 75% and specificity of 83.9%, and MRI using S-DWI had a sensitivity of 71.4% and specificity of 54.8%. The AUC for HR-DWI was significantly higher (0.794 vs. 0.631, P = 0.014). Secondary analyses of univariable predictors of AH showed tumor size increase [OR 16.8; 95% confidence interval (CI): 4.06-69.48; P < 0.001] and apparent diffusion coefficient (ADC) decrease (OR 5.06; 95% CI: 1.39-18.38; P = 0.014) on HR-DWI were significant predictors of AH. CONCLUSION: HR-DWI outperforms S-DWI in predicting AH. Patient with AH have tumors that change in size and ADC that could be detected using HR-DWI. Future studies with longer follow-up should assess HR-DWI for predicting disease progression during AS. SIGNIFICANCE: We report on a prospective clinical trial using a MRI that has three times the resolution of standard MRI. During AS for prostate cancer, two high-resolution MRIs performed approximately a year apart can detect tumor changes that predict the presence of aggressive cancers that should be considered for curative therapy such as prostatectomy or radiation.

Supraphysiological glutamine as a means of depleting intracellular amino acids to enhance pancreatic cancer chemosensitivity.

Limited efficacy of systemic therapy for pancreatic ductal adenocarcinoma (PDAC) patients contributes to high mortality. Cancer cells develop strategies to secure nutrients in nutrient-deprived conditions and chemotherapy treatment. Despite the dependency of PDAC on glutamine (Gln) for growth and survival, strategies designed to suppress Gln metabolism have limited effects. Here, we demonstrated that supraphysiological concentrations of glutamine (SPG) could produce paradoxical responses leading to tumor growth inhibition alone and in combination with chemotherapy. Integrated metabolic and transcriptomic analysis revealed that the growth inhibitory effect of SPG was the result of a decrease in intracellular amino acid and nucleotide pools. Mechanistically, disruption of the sodium gradient, plasma membrane depolarization, and competitive inhibition of amino acid transport mediated amino acid deprivation. Among standard chemotherapies given to PDAC patients, gemcitabine treatment resulted in a significant enrichment of amino acid and nucleoside pools, exposing a metabolic vulnerability to SPG-induced metabolic alterations. Further analysis highlighted a superior anticancer effect of D-glutamine, a non-metabolizable enantiomer of the L-glutamine, by suppressing both amino acid uptake and glutaminolysis, in gemcitabine-treated preclinical models with no apparent toxicity. Our study suggests supraphysiological glutamine could be a means of inhibiting amino acid uptake and nucleotide biosynthesis, potentiating gemcitabine sensitivity in PDAC.

Dynamic Risk Prediction of Treatment Discontinuation Using Patient-Reported Outcomes Data in the Phase III NSABP B-35 Trial.

Predicting an individual's risk of treatment discontinuation is critical for the implementation of precision chemoprevention. We developed partly conditional survival models to predict discontinuation of tamoxifen or anastrozole using patient-reported outcome (PRO) data from postmenopausal women with ductal carcinoma in situ enrolled in the NSABP B-35 clinical trial. In a secondary analysis of the NSABP B-35 clinical trial PRO data, we proposed two models for treatment discontinuation within each treatment arm (anastrozole or tamoxifen treated patients) using partly conditional Cox-type models with time-dependent covariates. A 70/30 split of the sample was used for the training and validation datasets. The predictive performance of the models was evaluated using calibration and discrimination measures based on the Brier score and AUC from time-dependent ROC curves. The predictive models stratified high-risk versus low-risk early discontinuation at a 6-month horizon. For anastrozole-treated patients, predictive factors included baseline body mass index (BMI) and longitudinal patient-reported symptoms such as insomnia, joint pain, hot flashes, headaches, gynecologic symptoms, and vaginal discharge, all collected up to 12 months [Brier score, 0.039; AUC, 0.76; 95% confidence interval (CI), 0.57-0.95]. As for tamoxifen-treated patients, predictive factors included baseline BMI, and time-dependent covariates: cognitive problems, feelings of happiness, calmness, weight problems, and pain (Brier score, 0.032; AUC, 0.78; 95% CI, 0.65-0.91). A real-time calculator based on these models was developed in Shiny to create a web-based application with a future goal to aid healthcare professionals in decision-making. PREVENTION RELEVANCE: The dynamic prediction provided by partly conditional models offers valuable insights into the treatment discontinuation risks using PRO data collected over time from clinical trial participants. This tool may benefit healthcare professionals in identifying patients at high risk of premature treatment discontinuation and support interventions to prevent potential discontinuation.

Combination L-Glutamine with Gemcitabine and Nab-Paclitaxel in Treatment-Naïve Advanced Pancreatic Cancer: The Phase I GlutaPanc Study Protocol.

Advanced pancreatic cancer is underscored by progressive therapeutic resistance and a dismal 5-year survival rate of 3%. Preclinical data demonstrated glutamine supplementation, not deprivation, elicited antitumor effects against pancreatic ductal adenocarcinoma (PDAC) alone and in combination with gemcitabine in a dose-dependent manner. The GlutaPanc phase I trial is a single-arm, open-label clinical trial investigating the safety of combination L-glutamine, gemcitabine, and nab-paclitaxel in subjects (n = 16) with untreated, locally advanced unresectable or metastatic pancreatic cancer. Following a 7-day lead-in phase with L-glutamine, the dose-finding phase via Bayesian design begins with treatment cycles lasting 28 days until disease progression, intolerance, or withdrawal. The primary objective is to establish the recommended phase II dose (RP2D) of combination L-glutamine, gemcitabine, and nab-paclitaxel. Secondary objectives include safety of the combination across all dose levels and preliminary evidence of antitumor activity. Exploratory objectives include evaluating changes in plasma metabolites across multiple time points and changes in the stool microbiome pre and post L-glutamine supplementation. If this phase I clinical trial demonstrates the feasibility of L-glutamine in combination with nab-paclitaxel and gemcitabine, we would advance the development of this combination as a first-line systemic option in subjects with metastatic pancreatic cancer, a high-risk subgroup desperately in need of additional therapies.

Extracellular vesicles in fatty liver promote a metastatic tumor microenvironment.

Liver metastasis is a major cause of death in patients with colorectal cancer (CRC). Fatty liver promotes liver metastasis, but the underlying mechanism remains unclear. We demonstrated that hepatocyte-derived extracellular vesicles (EVs) in fatty liver enhanced the progression of CRC liver metastasis by promoting oncogenic Yes-associated protein (YAP) signaling and an immunosuppressive microenvironment. Fatty liver upregulated Rab27a expression, which facilitated EV production from hepatocytes. In the liver, these EVs transferred YAP signaling-regulating microRNAs to cancer cells to augment YAP activity by suppressing LATS2. Increased YAP activity in CRC liver metastasis with fatty liver promoted cancer cell growth and an immunosuppressive microenvironment by M2 macrophage infiltration through CYR61 production. Patients with CRC liver metastasis and fatty liver had elevated nuclear YAP expression, CYR61 expression, and M2 macrophage infiltration. Our data indicate that fatty liver-induced EV-microRNAs, YAP signaling, and an immunosuppressive microenvironment promote the growth of CRC liver metastasis.

Antagonizing CD105 and androgen receptor to target stromal-epithelial interactions for clinical benefit.

Androgen receptor signaling inhibitors (ARSIs) are standard of care for advanced prostate cancer (PCa) patients. Eventual resistance to ARSIs can include the expression of androgen receptor (AR) splice variant, AR-V7, expression as a recognized means of ligand-independent androgen signaling. We demonstrated that interleukin (IL)-6-mediated AR-V7 expression requires bone morphogenic protein (BMP) and CD105 receptor activity in both PCa and associated fibroblasts. Chromatin immunoprecipitation supported CD105-dependent ID1- and E2F-mediated expression of RBM38. Further, RNA immune precipitation demonstrated RBM38 binds the AR-cryptic exon 3 to enable AR-V7 generation. The forced expression of AR-V7 by primary prostatic fibroblasts diminished PCa sensitivity to ARSI. Conversely, downregulation of AR-V7 expression in cancer epithelia and associated fibroblasts was achieved by a CD105-neutralizing antibody, carotuximab. These compelling pre-clinical findings initiated an interventional study in PCa patients developing ARSI resistance. The combination of carotuximab and ARSI (i.e., enzalutamide or abiraterone) provided disease stabilization in four of nine assessable ARSI-refractory patients. Circulating tumor cell evaluation showed AR-V7 downregulation in the responsive subjects on combination treatment and revealed a three-gene panel that was predictive of response. The systemic antagonism of BMP/CD105 signaling can support ARSI re-sensitization in pre-clinical models and subjects that have otherwise developed resistance due to AR-V7 expression.

Treatment of Cushing Disease With Pituitary-Targeting Seliciclib.

CONTEXT: Preclinical studies show seliciclib (R-roscovitine) suppresses neoplastic corticotroph proliferation and pituitary adrenocorticotrophic hormone (ACTH) production. OBJECTIVE: To evaluate seliciclib as an effective pituitary-targeting treatment for patients with Cushing disease (CD). METHODS: Two prospective, open-label, phase 2 trials, conducted at a tertiary referral pituitary center, included adult patients with de novo, persistent, or recurrent CD who received oral seliciclib 400 mg twice daily for 4 consecutive days each week for 4 weeks. The primary endpoint in the proof-of-concept single-center study was normalization of 24-hour urinary free cortisol (UFC; ≤ 50 µg/24 hours) at study end; in the pilot multicenter study, primary endpoint was UFC normalization or ≥ 50% reduction in UFC from baseline to study end. RESULTS: Sixteen patients were consented and 9 were treated. Mean UFC decreased by 42%, from 226.4 ± 140.3 µg/24 hours at baseline to 131.3 ± 114.3 µg/24 hours by study end. Longitudinal model showed significant UFC reductions from baseline to each treatment week. Three patients achieved ≥ 50% UFC reduction (range, 55%-75%), and 2 patients exhibited 48% reduction; none achieved UFC normalization. Plasma ACTH decreased by 19% (P = 0.01) in patients who achieved ≥ 48% UFC reduction. Three patients developed grade ≤ 2 elevated liver enzymes, anemia, and/or elevated creatinine, which resolved with dose interruption/reduction. Two patients developed grade 4 liver-related serious adverse events that resolved within 4 weeks of seliciclib discontinuation. CONCLUSION: Seliciclib may directly target pituitary corticotrophs in CD and reverse hypercortisolism. Potential liver toxicity of seliciclib resolves with treatment withdrawal. The lowest effective dose requires further determination.

Simulation study comparing analytical methods for single-item longitudinal patient-reported outcomes data.

PURPOSE: Efficient analytical methods are necessary to make reproducible inferences on single-item longitudinal ordinal patient-reported outcome (PRO) data. A thorough simulation study was performed to compare the performance of the semiparametric probabilistic index models (PIM) with a longitudinal analysis using parametric cumulative logit mixed models (CLMM). METHODS: In the setting of a control and intervention arm, we compared the power of the PIM and CLMM to detect differences in PRO adverse event (AE) between these groups using several existing and novel summary scores of PROs. For each scenario, PRO data were simulated using copula multinomial models. Comparisons were also exemplified using clinical trial data. RESULTS: On average, CLMM provided substantially greater power than the PIM to detect differences in PRO-AEs between the groups when the baseline-adjusted method was used, and a small advantage in power when using the baseline symptom as a covariate. CONCLUSION: Although the CLMM showed the best performance among analytical methods, it relies on assumptions difficult to verify and that might not be fulfilled in the real world, therefore our recommendation is the use of PIM models with baseline symptom as a covariate.

Toxicity Index, patient-reported outcomes, and persistence of breast cancer chemotherapy-associated side effects in NRG Oncology/NSABP B-30.

Adjuvant chemotherapy improves breast cancer survival but is associated with bothersome short- and long-term toxicity. Factors associated with toxicity, especially subacute toxicity up to 2 years following chemotherapy, have not been fully elucidated. The NRG Oncology/NSABP B-30 clinical trial compared 3 different doxorubicin-, cyclophosphamide-, and docetaxel-based chemotherapy regimens given over 3-6 months. Patients with hormone receptor-positive breast cancer received subsequent adjuvant endocrine therapy. From baseline through 24 months, 2156 patients completed questionnaires serially. We used multivariable probabilistic index models to identify factors associated with acute (>0-12 months) and subacute (>12-24 months) difficulties with pain, cognition, vasomotor symptoms, and vaginal symptoms. For all symptom domains, presence of symptoms prior to chemotherapy initiation were associated with symptoms in the subacute period (all p < 0.001). In addition, different combinations of patient factors and breast cancer treatments were associated with increased likelihood of pain, vasomotor, and vaginal symptoms in the subacute period. Consideration of pre-treatment symptoms and patient factors, as well as treatments for breast cancer, can facilitate identification of groups of patients that may experience symptoms following completion of chemotherapy. This information may be important for treatment-decision-making when alternative regimens are equivalent in benefit.

Phase I trial of Bermekimab with nanoliposomal irinotecan and 5-fluorouracil/folinic acid in advanced pancreatic ductal adenocarcinoma.

In this phase I dose-escalation trial, we assess the maximum tolerated dose (MTD) of Bermekimab in combination with Nanoliposomal Irinotecan (Nal-Iri) and 5-Fluorouracil/Folinic Acid (5-FU/FA). Secondarily, we investigate effects on weight, lean body mass, quality-of-life, the gut microbiome composition, inflammatory biomarkers, progression-free survival, and overall survival. This was a single-arm, open-label adaptive Bayesian dose-escalation study of Bermekimab combined with Nal-Iri and 5FU/FA in patients with advanced or locally advanced PDAC who failed gemcitabine-based chemotherapy. 22 patients enrolled between 2017 and 2019. 3 of 21 patients experienced dose-limiting toxicities attributable to the chemotherapy backbone. 58% (10/17) of patients exhibited weight stability. Physical performance status was preserved among all subjects. Patients reported improvements in quality-of-life metrics via QLQ-PAN26 questioner (-3.6, p = 0.18) and functional well-being (1.78, p = 0.02). Subjects exhibited a decrease in inflammatory cytokines, notably, vascular endothelial growth factor (-0.86, p = 0.017) with Bermekimab. Bermekimab treatment was associated with an increased abundance of gut health-promoting bacterial genera Akkermansia, with 3.82 Log2-fold change from baseline. In sum, Bermekimab is safe to be used in conjunction with Nal-Iri and 5-FU/FA chemotherapy. This benign toxicological profile warrants further Phase I/II investigation of Bermekimab in combinatorial strategies, and the impact of anti-IL-1α antibodies on the gut microbiome.Clinical trials registration: NCT03207724 05/07/2017.

A nonparametric Bayesian method for dose finding in drug combinations cancer trials.

We propose an adaptive design for early-phase drug-combination cancer trials with the goal of estimating the maximum tolerated dose (MTD). A nonparametric Bayesian model, using beta priors truncated to the set of partially ordered dose combinations, is used to describe the probability of dose limiting toxicity (DLT). Dose allocation between successive cohorts of patients is estimated using a modified continual reassessment scheme. The updated probabilities of DLT are calculated with a Gibbs sampler that employs a weighting mechanism to calibrate the influence of data vs the prior. At the end of the trial, we recommend one or more dose combinations as the MTD based on our proposed algorithm. We apply our method to a Phase I clinical trial of CB-839 and Gemcitabine that motivated this nonparametric design. The design operating characteristics indicate that our method is comparable with existing methods.

A Phase I Study of Autologous Dendritic Cell Vaccine Pulsed with Allogeneic Stem-like Cell Line Lysate in Patients with Newly Diagnosed or Recurrent Glioblastoma.

PURPOSE: Glioblastoma (GBM) is a heterogeneous malignancy with multiple subpopulations of cancer cells present within any tumor. We present the results of a phase I clinical trial using an autologous dendritic cell (DC) vaccine pulsed with lysate derived from a GBM stem-like cell line. PATIENTS AND METHODS: Patients with newly diagnosed and recurrent GBM were enrolled as separate cohorts. Eligibility criteria included a qualifying surgical resection or minimal tumor size, ≤ 4-mg dexamethasone daily dose, and Karnofsky score ≥70. Vaccine treatment consisted of two phases: an induction phase with vaccine given weekly for 4 weeks, and a maintenance phase with vaccines administered every 8 weeks until depletion of supply or disease progression. Patients with newly diagnosed GBM also received standard-of-care radiation and temozolomide. The primary objective for this open-label, single-institution trial was to assess the safety and tolerability of the autologous DC vaccine. RESULTS: For the 11 patients with newly diagnosed GBM, median progression-free survival (PFS) was 8.75 months, and median overall survival was 20.36 months. For the 25 patients with recurrent GBM, median PFS was 3.23 months, 6-month PFS was 24%, and median survival was 11.97 months. A subset of patients developed a cytotoxic T-cell response as determined by an IFNγ ELISpot assay. CONCLUSIONS: In this trial, treatment of newly diagnosed and recurrent GBM with autologous DC vaccine pulsed with lysate derived from an allogeneic stem-like cell line was safe and well tolerated. Clinical outcomes add to the body of evidence suggesting that immunotherapy plays a role in the treatment of GBM.

Combining cytotoxic agents with continuous dose levels in seamless phase I-II clinical trials.

Phase I-II cancer clinical trial designs are intended to accelerate drug development. In cases where efficacy cannot be ascertained in a short period of time, it is common to divide the study in two stages: i) a first stage in which dose is escalated based only on toxicity data and we look for the maximum tolerated dose (MTD) set and ii) a second stage in which we search for the most efficacious dose within the MTD set. Current available approaches in the area of continuous dose levels involve fixing the MTD after stage I and discarding all collected stage I efficacy data. However, this methodology is clearly inefficient when there is a unique patient population present across stages. In this article, we propose a two-stage design for the combination of two cytotoxic agents assuming a single patient population across the entire study. In stage I, conditional escalation with overdose control (EWOC) is used to allocate successive cohorts of patients. In stage II, we employ an adaptive randomization approach to allocate patients to drug combinations along the estimated MTD curve, which is constantly updated. The proposed methodology is assessed with extensive simulations in the context of a real case study.

Modeling synergism in early phase cancer trials with drug combination with continuous dose levels: is there an added value?

In parametric Bayesian designs of early phase cancer clinical trials with drug combinations exploring a discrete set of partially ordered doses, several authors claimed that there is no added value in including an interaction term to model synergism between the two drugs. In this paper, we investigate these claims in the setting of continuous dose levels of the two agents. Parametric models will be used to describe the relationship between the doses of the two agents and the probability of dose limiting toxicity and efficacy. Trial design proceeds by treating cohorts of two patients simultaneously receiving different dose combinations and response adaptive randomization. We compare trial safety and efficiency of the estimated maximum tolerated dose (MTD) curve between models that include an interaction term with models without the synergism parameter with extensive simulations. Under a selected class of dose-toxicity models and dose escalation algorithm, we found that not including an interaction term in the model can compromise the safety of the trial and reduce the pointwise reliability of the estimated MTD curve.

Visualizing adverse events in clinical trials using correspondence analysis with R-package visae.

BACKGROUND: Graphical displays and data visualization are essential components of statistical analysis that can lead to improved understanding of clinical trial adverse event (AE) data. Correspondence analysis (CA) has been introduced decades ago as a multivariate technique that can communicate AE contingency tables using two-dimensional plots, while quantifying the loss of information as other dimension reduction techniques such as principal components and factor analysis. METHODS: We propose the application of stacked CA using contribution biplots as a tool to explore differences in AE data among treatments in clinical trials. We defined five levels of refinement for the analysis based on data derived from the Common Terminology Criteria for Adverse Events (CTCAE) grades, domains, terms and their combinations. In addition, we developed a Shiny app built in an R-package, visae, publicly available on Comprehensive R Archive Network (CRAN), to interactively investigate CA configurations based on the contribution to the explained variance and relative frequency of AEs. Data from two randomized controlled trials (RCT) were used to illustrate the proposed methods: NSABP R-04, a neoadjuvant rectal 2 × 2 factorial trial comparing radiation therapy with either capecitabine (Cape) or 5-fluorouracil (5-FU) alone with or without oxaliplatin (Oxa), and NSABP B-35, a double-blind RCT comparing tamoxifen to anastrozole in postmenopausal women with hormone-positive ductal carcinoma in situ. RESULTS: In the R04 trial (n = 1308), CA biplots displayed the discrepancies between single agent treatments and their combinations with Oxa at all levels of AE classes, such that these discrepancies were responsible for the largest portion of the explained variability among treatments. In addition, an interaction effect when adding Oxa to Cape/5-FU was identified when the distance between Cape+Oxa and 5-FU + Oxa was observed to be larger than the distance between 5-FU and Cape, with Cape+Oxa and 5-FU + Oxa in different quadrants of the CA biplots. In the B35 trial (n = 3009), CA biplots showed different patterns for non-adherent Anastrozole and Tamoxifen compared with their adherent counterparts. CONCLUSION: CA with contribution biplot is an effective tool that can be used to summarize AE data in a two-dimensional display while minimizing the loss of information and interpretation.

Home-based virtual reality for chronic pain: protocol for an NIH-supported randomised-controlled trial.

INTRODUCTION: Chronic pain is highly prevalent and associated with a large burden of illness; there is a pressing need for safe, home-based, non-pharmacological, interventions. Virtual reality (VR) is a digital therapeutic known to be effective for acute pain, but its role in chronic pain is not yet fully elucidated. Here we present a protocol for the National Institute of Health (NIH) Back Pain Consortium (BACPAC) VR trial that evaluates the effectiveness of three forms of VR for patients with chronic lower back pain (cLBP), a highly prevalent form of chronic pain. METHODS AND ANALYSIS: The NIH BACPAC VR trial will randomise 360 patients with cLBP into one of three arms, each administered through a head-mounted display: 1) skills-based VR, a program incorporating principles of cognitive behavioural therapy, mindful meditation and physiological biofeedback therapy using embedded biometric sensors; 2) distraction-based VR, a program using 360-degree immersive videos designed to distract users from pain; and 3) sham VR, a non-immersive program using two-dimensional videos within a VR headset. Research participants will be monitored for 12 weeks using a combination of patient-reported outcomes administered via REDCap (Research Electronic Data Capture), wearable sensor data collected via Fitbit Charge 4 and electronic health record data. The primary outcome will be the NIH Patient-Reported Outcomes Measurement Information System (PROMIS) Pain Interference scale. Secondary outcomes will include PROMIS Anxiety, PROMIS Sleep Disturbance, opioid prescription data and Pain Catastrophizing Scale Short Form. A subgroup analysis will explore patient level predictors for VR efficacy. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Institutional Review Board of Cedars-Sinai Health System in April 2020. The results will be disseminated in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT04409353.

Nodal staging convergence for HPV- and HPV+ oropharyngeal carcinoma.

BACKGROUND: Modern disease staging systems have restructured human papillomavirus (HPV)-negative (HPV-) and HPV-positive (HPV+) oropharyngeal carcinoma (OPC) into distinct pathologic nodal systems. Given that quantitative lymph node (LN) burden is the dominant prognostic factor in most head and neck cancers, we investigated whether HPV- and HPV+ OPC warrant divergent pathologic nodal classification. METHODS: Multivariable Cox regression models of OPC surgical patients identified via U.S. cancer registry data were constructed to determine associations between survival and nodal characteristics. Nonlinear associations between metastatic LN number and survival were modeled with restricted cubic splines. Recursive partitioning analysis (RPA) was used to derive unbiased nodal schema. RESULTS: Mortality risk escalated continuously with each successive positive LN in both OPC subtypes, with analogous slope. Survival hazard increased by 18.5% (hazard ratio [HR], 1.19 [95% CI, 1.16-1.21]; P < .001) and 19.1% (HR, 1.19 [95% CI, 1.17-1.21]; P < .001), with each added positive LN for HPV- and HPV+ OPC, respectively, up to identical change points of 5 positive LNs. Extranodal extension (ENE) was an independent predictor of HPV- OPC (HR, 1.55 [95% CI, 1.20-1.99]; P < .001) and HPV+ OPC (HR 1.73 [95% CI, 1.36-2.20]; P < .001) mortality. In RPA for both diseases, metastatic LN was the principal nodal covariate driving survival, with ENE as a secondary determinant. Given the similarities across analyses, we propose a concise, unifying HPV-/HPV+ OPC pathologic nodal classification schema: N1, 1-5 LN+/ENE-; N2, 1-5 LN+/ENE+; N3, >5 LN+. CONCLUSION: HPV- and HPV+ OPC exhibit parallel relationships between nodal characteristics and relative mortality. In both diseases, metastatic LN number represents the principal nodal covariate governing survival, with ENE being an influential secondary element. A consolidated OPC pathologic nodal staging system that is based on these covariates may best convey prognosis. LAY SUMMARY: The current nodal staging system for oropharyngeal carcinoma (OPC) has divided human papillomavirus (HPV)-negative (HPV-) and HPV-positive (HPV+) OPC into distinct systems that rely upon criteria that establish them as separate entities, a complexity that may undermine the core objective of staging schema to clearly communicate prognosis. Our large-scale analysis revealed that HPV- and HPV+ pathologic nodal staging systems in fact mirror each other. Multiple analyses produced conspicuously similar nodal staging systems, with metastatic lymph node number and extranodal extension delineating the highest risk groups that shape prognosis. We propose unifying HPV- and HPV+ nodal systems to best streamline prognostication and maximize staging accuracy.