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Background: Debate surrounds the issue of whether peripheral nerve blockade or periarticular infiltration (PAI) should be employed within a contemporary, comprehensive multimodal analgesia pathway for total hip arthroplasty. We hypothesized that patients treated with a continuous posterior lumbar plexus block (PNB) would report less pain and consume less opioid medication than those treated with PAI. Methods: This investigator-initiated, independently funded, 3-arm randomized clinical trial (RCT) performed at a single high-volume institution compared postoperative analgesia interventions for elective, unilateral primary total hip arthroplasty: (1) PNB; (2) PAI with ropivacaine, ketorolac, and epinephrine (PAI-R); and (3) PAI with liposomal bupivacaine, ketorolac, and epinephrine (PAI-L) using computerized randomization. The primary outcome was maximum pain during the morning (06:00 to 12:00) of the first postoperative day (POD) on an ascending numeric rating scale (NRS) from 0 to 10. Pairwise treatment comparisons were performed using the rank-sum test, with a p value of <0.017 indicating significance (Bonferroni adjusted). A sample size of 150 provided 80% power to detect a difference of 2.0 NRS units. Results: We included 159 patients (51, 54, and 54 patients in the PNB, PAI-R, and PAI-L groups, respectively). No significant differences were found with respect to the primary end point on the morning of the first POD (median, 3.0, 4.0, and 3.0, respectively; p > 0.033 for all). Opioid consumption was low and did not differ across groups at any intervals. Median maximum pain on POD 1 was 5.0, 5.5, and 4.0, respectively, and was lower for the PAI-L group than for the PAI-R group (p = 0.006). On POD 2, maximum pain (median, 3.5, 5.0, and 3.5, respectively) was lower for the PNB group (p = 0.014) and PAI-L group (p = 0.016) compared with the PAI-R group. The PAI-L group was not significantly different from the PNB group with respect to any outcomes: postoperative opioid use including rescue intravenous opioid medication, length of stay, and hospital adverse events, and 3-month follow-up data including any complication. Conclusions: In this RCT, we found a modest improvement with respect to analgesia in patients receiving PNB compared with those receiving PAI-R, but not compared with those who had PAI-L. Secondary analyses suggested that PNB or PAI-L provides superior postoperative analgesia compared with PAI-R. For primary total hip arthroplasty, a multimodal analgesic regimen including PNB or PAI-L provides opioid-limiting analgesia. Level of Evidence: Therapeutic Level I . See Instructions for Authors for a complete description of levels of evidence.

Introduction: The phase 3 international, randomized, double-blind ROBUST clinical trial (NCT02285062) compared progression-free survival between patients with previously untreated ABC-type DLBCL treated with placebo plus rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (placebo-R-CHOP) versus lenalidomide + R-CHOP (R2-CHOP) for 6 21-day cycles. HRQoL, as measured by the Functional Assessment of Cancer Therapy-Lymphoma (FACT-Lym) and the EuroQoL 5-dimension 3-level (EQ-5D-3L) patient-reported questionnaires, was evaluated as a secondary endpoint for the 2 treatment arms. Methods: For each treatment group, FACT-Lym and EQ-5D-3L scores were measured at baseline (BL), mid-, end-of-treatment (EOT), and post-treatment, in 12-week intervals from Week 34 onward. Patients were evaluated if they had completed BL and ≥ 1 post-BL calculable FACT-Lym subscale measurements. Non-inferiority (NI) of R2-CHOP versus placebo-R-CHOP was measured for 4 key FACT-Lym subscales: Physical Well-Being (PWB), Additional Concerns (AC), Functional Well-Being (FWB), and Trial Outcome Index (TOI). NI was assessed at EOT (typically 3-4 weeks after completing Cycle 6) and at post-treatment follow-up at Week 34 by analysis of covariance (ANCOVA). The NI margins were prespecified as 1 less than the higher published minimal important difference (MID) for each subscale. Since a range of MIDs have been published, a more conservative value was also used as a sensitivity analysis. Time to improvement (TTI), using published responder definitions, was also assessed for the FACT-Lym subscales. EQ-5D-3L scores were summarized descriptively. Results: Demographic and baseline disease characteristics were balanced across the 2 treatment arms (N = 285 per arm). The percentage of patients who completed the FACT-Lym out of the expected population remained &gt; 85% at all time points with &gt; 50 patients still on the study in each treatment arm up to Week 142. Completion rates and reasons for missing assessments were balanced across the 2 treatment arms. FACT-Lym subscale scores were generally higher after EOT, similar for both treatment groups, and mean changes from BL were close to or above MID (where defined), except for the Social/Family Well-Being subscale. Mean differences in FACT-Lym TOI between treatment arms are shown in Table 1. As positive treatment differences favor R2-CHOP and -10 was the predefined NI margin, NI was demonstrated for the FACT-Lym TOI subscale at both EOT and Week 34 assessments. Superiority of R2-CHOP was demonstrated at EOT as the confidence interval (CI) lies completely above 0 (P &lt; 0.04); however, this difference was not clinically meaningful. Furthermore, NI was also demonstrated when using the sensitivity analysis margin of -4.5. ANCOVA models were also fitted for the other key subscales of PWB, AC and FWB (Table 2). NI was demonstrated for all NI margins at both time points for the PWB and AC subscales. The FACT-Lym FWB subscale demonstrated NI for both margins at EOT and Week 34 for the primary NI margin of -2 based on the MID minus 1, but did not demonstrate NI when an NI margin of -1, based on an alternative published MID, was used. The TTI curves and associated summary statistics were similar for the 2 treatment arms, with a median TTI for the FACT-Lym TOI of 21 weeks (95% CI 15-22) for patients treated with R2-CHOP and 18 weeks (95% CI 15-22) for patients treated with placebo-R-CHOP. Mean EQ-5D-3L visual analogue scale (VAS) and Utility Index (UK weights) change from baseline scores were higher in both treatment arms and the mean changes were above, or close to, the published MID (7 for VAS, 0.1 for Utility Index) at EOT assessments. Prespecified sensitivity and subgroup analyses supported the conclusions from the primary HRQoL analyses. Conclusions: The predefined NI levels were met for the 4 key FACT-Lym subscales. Similar results were observed across the other HRQoL assessments, sensitivity, and subgroup analyses. Adding lenalidomide to the R-CHOP regimen did not adversely affect the HRQoL of patients with DLBCL as measured by FACT-Lym and EQ-5D-3L. These data serve as a benchmark for future clinical trials combining next-generation immunomodulatory drugs with standard R-CHOP to improve clinical efficacy while maintaining HRQoL in patients with DLBCL. HRQoL analyses should become an integral part of future clinical trials of novel combination regimens in DLBCL. Disclosures Chiappella: Roche: Speakers Bureau; Teva: Speakers Bureau; Servier: Other: advisory board, Speakers Bureau; Janssen: Other: advisory board, Speakers Bureau; Celgene: Other: advisory board, Speakers Bureau. Cocks:Adelphi Values: Employment; Amgen: Consultancy; BMS: Consultancy; Celgene Corporation: Consultancy; Endomag Ltd.: Consultancy. Greenwood:Adelphi Values: Employment. Williams:Adelphi Values: Employment. Scott:Celgene: Consultancy; Roche/Genentech: Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Janssen: Consultancy, Research Funding. Yamamoto:SymBio: Research Funding; Ono: Consultancy, Honoraria, Research Funding; Otsuka: Honoraria; Sanofi: Honoraria; Astra-Zeneca: Consultancy, Research Funding; Sumitomo Dainippon: Honoraria; Chugai: Consultancy, Honoraria, Research Funding; Eisai: Consultancy, Honoraria, Research Funding; Janssen: Honoraria; Gilead Sciences: Research Funding; Solasia Pharma: Research Funding; Bayer: Research Funding; Celgene Corporation: Consultancy, Honoraria, Research Funding; ARIAD: Research Funding; Pfizer: Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Kyowa Kirin: Honoraria; MSD: Consultancy, Honoraria; Mundipharma: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Research Funding; Meiji Seika Pharma: Consultancy, Honoraria; HUYA/IQVIA Services Japan: Consultancy, Honoraria; Novartis: Honoraria, Research Funding; Incyte: Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Jurczak:Bayer: Research Funding; Takeda: Research Funding; Gilead: Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees, Research Funding; Morphosys: Research Funding; Incyte: Research Funding; Celgene Corporation: Research Funding; Loxo: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celtrion: Research Funding; Novo Nordisk: Research Funding; Servier: Research Funding; TG Therapeutics: Research Funding. Özcan:Sanofi: Other: Travel support; Abdi Ibrahim: Other: Travel support; BMS: Other: Travel support; Takeda: Honoraria, Other: Travel support, Research Funding; Archigen: Research Funding; Roche: Other: Travel support, Research Funding; Bayer: Research Funding; Janssen: Other: Travel support, Research Funding; Celgene Corporation: Research Funding, Travel support; AbbVie: Other: Travel support, Research Funding; MSD: Research Funding; Novartis: Research Funding; Jazz: Other: Travel support; Amgen: Honoraria, Other: Travel support. Belada:Roche: Consultancy; Gilead Sciences: Consultancy; Takeda: Consultancy. Margunato-Debay:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Zhai:Celgene Corporation: Employment, Equity Ownership. Braverman:Celgene Corporation: Employment. Vitolo:Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; F. Hoffmann-La Roche: Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Nowakowski:Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding.

Abstract Determining effective therapies for patients with recurrent glioblastoma remains difficult especially in small early phase clinical trials. Currently utilized estimators of treatment response rely on two-dimensional measurements of tumor progression (e.g. RANO, RECIST, MacDonald) that have often fallen short in reliably connecting patients who respond with positive survival outcomes. This has prompted consideration of advanced imaging and volumetric measurements by the RANO working group and others. Our proposed approach, Days Gained (DG), uses volumetric measurements to calculate a personalized response metric based on change in tumor growth characteristics pre/post-treatment. DG has shown promise for connecting imageable treatment response with clinically meaningful (statistically significant) survival benefit when applied in upfront and recurrent therapy settings, even in the context of coincident bevacizumab treatment. In this study, we seek to consider a new cohort of patients receiving bevacizumab in combination with other novel therapies to distinguish any subpopulation of patients with meaningful response. In this work, we identified a subset of 16 patients from bevacizumab clinical trials with data available for DG analysis requiring serial imaging (T1Gd and FLAIR) prior to and after the first cycle of therapy. Each trial evaluated bevacizumab alone versus bevacizumab plus either dasatinib or TRC105 in recurrent disease. Discrimination of time to progression (TTP) was evaluated at DG thresholds identified from our prior analysis of patients treated with bevacizumab. Using previously identified DG thresholds for clinically significant treatment benefit, in our cohort, DG measured by serial FLAIR imaging was significant in predicting longer TTP (120 DG, p=0.014), but T1Gd DG scores did not attain significance (p=0.630). Given the limited insights in connecting response metrics to accurately predicted outcomes, these data further support the use of DG as a burgeoning marker of treatment response (or lack of response) that may be useful for more routine integration into clinical trials.

Abstract PURPOSE Brain tumor related epilepsy (BTE) is a major co-morbidity in patients with glioma. It is difficult to determine whether the use of anti-epileptic drugs is necessary. We attempted to build a machine-learning model to predict the probability of seizure presentation (SP) with glioma. METHODS We trained a random forest classifier using the following variables: volumetric data of pre-treatment MR images (T1Gd and T2-FLAIR sequences), patient demographics (age; sex), and measurements of tumor proliferation (log(ρ)), invasiveness (log(D)) and their relative ratio (log(ρ/D)). Our cohort consisted of 221 patients total. Using an 80-20 ratio, we used 176 patients (76 SP, 100 nSP) for training and the remaining 45 patients (19 SP, 26 nSP) were used for testing. We also trained on male-only and female-only cohorts to evaluate any sex differences in prediction. For training, 108 males (53 SP, 55 nSP) were used and 28 for testing (14 SP, 14 nSP). We used 72 females (21 SP, 49 nSP) for training and 15 (7 SP, 8 nSP) for testing. We corrected for class imbalance in the female cohort before training. Using 10-fold cross-validation and a separate testing set, we measured performance by ROC curve (AUC), accuracy, sensitivity, and specificity of predictions (average of folds in cross validation). RESULTS The female model achieved the highest AUC (0.853) followed by the mixed model (0.726) and the male model (0.651). In the validation set, the accuracy/sensitivity/specificity of the three cohorts were as follows: mixed (0.726/0.696/0.750), female (0.853/0.830/0.875), and male (0.651/0.577/0.722). The performance of the testing set, in terms of accuracy/sensitivity/specificity were: mixed (0.733/0.74/0.73), female (0.8/0.57/1), and male (0.714/0.64/0.79). CONCLUSION We found a negative correlation between seizure probability and size and invasiveness of tumors. Our model shows promising performance on testing set data. Further cohort studies and training is warranted.

Abstract INTRODUCTION Glioblastoma (GBM) is the most common malignant primary brain tumor in adults with a median overall survival (OS) of 15months. Despite advancements in treatments, prognosis is dismal and the prognostic significance of tumor location is not entirely understood. METHODOLOGY: In our study, we investigated sex-specific volumetric, tumor growth kinetics, and outcome differences among GBMs in various brain locations. Primary GBM patients with pretreatment magnetic resonance imaging (MRI) data (N=289, 173 males, 116 females) were selected from our brain tumor repository. Tumor abnormality was segmented on T1-weighted post-gadolinium contrast agent (T1Gd) MRIs. We utilized the Harvard-Oxford brain atlases to determine the location of GBMs. RESULTS Overall, our study found smaller tumors in the left hemisphere. This may be expected as left-hemispheric GBM symptoms could present earlier, leading to earlier diagnosis and treatment. However, when the cohort was split by sex, we found this observation significant for females only in the parietal lobe (p < 0.0001). Further, female GBMs demonstrated smaller necrotic volume in the left hemisphere (p = 0.030). Sex-specific differences in incidence were noted in the temporal and occipital lobes (2M:1F). Comparing tumor growth kinetics in different brain locations and hemispheres, females had significantly lower tumor proliferation rates in the left hemisphere (p = 0.009) and lower tumor proliferation rates in the left frontal lobe (p = 0.031). Controlling for treatment, patients with frontal lobe tumors had significantly longer OS compared to those with GBMs in the temporal lobe (p = 0.046, 312 days). Differences in growth velocities were noted between frontal and parietal lobe with frontal GBMs having lower velocities in comparison to parietal lobe GBMs. CONCLUSION Together, our results demonstrate that tumor growth and proliferation rates may vary based on location and sex. Additional research is needed to further explore the clinical significance of tumor location.

Abstract Sex differences in brain tumor related epilepsy (BTE) as an initial symptom of glioma are rarely investigated. Sex differences are being explored with increased interest more recently. Epidemiological studies have generally indicated overall incidence of epilepsy to be slightly higher in males than females, but a higher incidence of idiopathic generalized epilepsy has been seen in females in some studies. Clinicians regularly face the challenge of anti-epileptic drug prescription determination in patients with newly identified brain mass and would greatly benefit from knowing clinical characteristics in BTE. We analyzed clinical characteristics in patients with pathologically-determined glioma with known seizure status at clinical presentation using non-parametric and Fisher’s Exact tests with the entire cohort and male and female separately. From our clinical data repository, we identified 223 patients (females, n=86 (39%); males, n=137 (61%)) divided by those that presented with seizure (SP, n=96, 43%; F, n= 28; M, n= 68) and those that presented without seizure (nSP, n=127, 57%, F n=58, M n=69). In sex-specific analysis males had a significantly (x2=6.28, p=0.01) higher proportion of SP (49.6%) than females (32.6%). There was a dependence between seizure presentation status and tumor grade in males (x2=5.94, p=0.015). Tumor kinetics in the female cohort showed significantly (p< 0.0001) more diffuse tumors in SP compared to nSP. Right-sided tumors were predominantly nSP, while left-sided tumors were split more evenly between SP and nSP. The predominance of nSP among right-sided tumors seems to be driven by females (74%), male right-sided tumors were split more evenly between SP and nSP. Seizure status is dependent on tumor location for the combined cohort, however not for males (x2=5.23, p=0.16) or females (x2=4.34, p=0.23). Clearly there are sex differences and similarities in clinical characteristics at glioma presentation. Further characterization could lead to improved adherence of national standards for AED prescription.

Abstract INTRODUCTION Immunotherapy with engineered CAR T cells is a promising new therapy for glioblastoma, for which predictive and prognostic biomarkers are needed to inform effective intervention. Recently, our group analyzed standard-of-care (SOC) MRI images of long-term and short-term glioblastoma survivors and identified six intratumoral “habitats” of which “Habitat 6” was correlated with survival at diagnosis in high-grade glioma. Based on the MRI characteristics of “Habitat 6”, viz. high enhancement and high edema, we hypothesized that it could be a marker of tumor immune infiltrates. We are studying longitudinal changes in tumor “habitat” composition on MRIs of subjects with recurrent high-grade glioma treated with CAR T cells engineered to target IL13Ra2. METHODS MRI scans of the brain were acquired in 6 subjects at 3.0 T at baseline and various times before and after initiation of CAR T cell therapy. FLAIR, T1W and T1W-CE MRI images were registered to T2W images and six intratumoral “habitats” were computed as per our recently published methodology. The six habitats generated at the end of the tumor segmentation process were: “Habitat 1” (low FLAIR, low enhancement), “Habitat 2” (high FLAIR, low enhancement), “Habitat 3” (low FLAIR, medium enhancement), “Habitat 4” (high FLAIR, medium enhancement), “Habitat 5” (low FLAIR, high enhancement), and “Habitat 6” (high FLAIR, high enhancement). RESULTS Analysis of temporal changes in the six “habitats” shows an initial increase in both “Habitat 4” and “Habitat 6” following CAR T cell therapy initiation. Subjects with higher absolute volumes of “Habitat 6” at the baseline (pre-treatment) showed longer overall survival. Overall survival is a function of absolute “Habitat 6” volume at baseline, its direction of change immediately post-therapy, the duration of any increase in “Habitat 6” post-treatment, and the “Habitat 6” to “Habitat 4” ratio. Additional subjects are being evaluated to further understand these preliminary observations.

Abstract Background Immunosuppressive regimens associated with organ transplantation increase the risk of developing cancer. Transplant candidates and recipients with prostate cancer are often treated, even if low-risk features would ordinarily justify active surveillance. Methods Using SEER-Medicare, we identified 163 676 men aged 66 years and older diagnosed with nonmetastatic prostate cancer. History of solid organ transplant was identified using diagnosis or procedure codes. A propensity score-matched cohort was identified by matching transplanted men to nontransplanted controls by age, race, region, year, T-stage, grade, comorbidity, and cancer therapy. Fine-Gray competing risk models assessed associations between transplant status and prostate cancer-specific mortality (PCSM) and overall mortality (OM). Results We identified 620 men (0.4%) with transplant up to 10 years before (n = 320) or 5 years after (n = 300) prostate cancer diagnosis and matched them to 3100 men. At 10 years, OM was 55.7% and PCSM was 6.0% in the transplant cohort compared with 42.4% (P &lt; .001) and 7.6% (P = .70) in the nontransplant cohort, respectively. Adjusted models showed no difference in PCSM for transplanted men (hazard ratio = 0.88, 95% confidence interval = 0.61 to 1.27, P = .70) or differences by prostate cancer therapy. Among 334 transplanted men with T1-2N0, well or moderately differentiated “low-risk” prostate cancer, PCSM was similar for treated and untreated men (hazard ratio = 0.92, 95% confidence interval = 0.47 to 1.81). Conclusions Among men aged 66 years and older with prostate cancer, an organ transplant is associated with higher OM but no observable difference in PCSM. These findings suggest men with prostate cancer and previous or future organ transplantation should be managed per usual standards of care, including consideration of active surveillance for low-risk cancer characteristics.