Moniz‐Garcia, Diogo

ImportanceImplementing multidisciplinary teams for treatment of complex brain tumors needing awake craniotomies is associated with significant costs. To date, there is a paucity of analysis on the cost utility of introducing advanced multidisciplinary standardized teams to enable awake craniotomies.ObjectiveTo assess the cost utility of introducing a standardized program of awake craniotomies.Design, Setting, and ParticipantsA retrospective economic evaluation was conducted at Mayo Clinic Florida. All patients with single, unilateral lesions who underwent elective awake craniotomies between January 2016 and December 2021 were considered eligible for inclusion. The economic perspective of the health care institution and a time horizon of 1 year were considered. Data were analyzed from October 2022 to May 2023.ExposureTreatment with an awake craniotomy before standardization (2016-2018) compared with treatment with awake craniotomy after standardization (2018-2021).Main Outcomes and MeasuresPatient demographics, perioperative, and postoperative outcomes, including length of stay, intensive care (ICU) admission, extent of resection, readmission rates, and 1-year mortality were compared between patients undergoing surgery before and after standardization. Direct medical costs were estimated from Medicare reimbursement rates for all billed procedures. A cost-utility analysis was performed considering differences in direct medical costs and in 1-year mortality within the periods before and after standardization of procedures. Uncertainty was explored in probability sensitivity analysis.ResultsA total of 164 patients (mean [SD] age, 49.9 [15.7] years; 98 [60%] male patients) were included in the study. Of those, 56 underwent surgery before and 108 after implementation of procedure standardization. Procedure standardization was associated with reductions in length of stay from a mean (SD) of 3.34 (1.79) to 2.46 (1.61) days (difference, 0.88 days; 95% CI, 0.33-1.42 days; P = .002), length of stay in ICU from a mean (SD) of 1.32 (0.69) to 0.99 (0.90) nights (difference, 0.33 nights; 95% CI, 0.06-0.60 nights; P = .02), 30-day readmission rate from 14% (8 patients) in the prestandardization cohort to 5% (5 patients) (difference, 9%; 95% CI, 19.6%-0.3%; P = .03), while extent of resection and intraoperative complication rates were similar between both cohorts. The standardized protocol was associated with mean (SD) savings of $7088.80 ($12 389.50) and decreases in 1-year mortality (dominant intervention). This protocol was found to be cost saving in 75.5% of all simulations in probability sensitivity analysis.Conclusions and RelevanceIn this economic evaluation of standardization of awake craniotomy, there was a generalized reduction in length of stay, ICU admission time, and direct medical costs with implementation of an optimized protocol. This was achieved without compromising patient outcomes and with similar extent of resection, complication rates, and reduced readmission rates.

BACKGROUND AND OBJECTIVES: Degenerative spine disease is a leading cause of disability, with increasing prevalence in the older patients. While age has been identified as an independent predictor of outcomes, its predictive value is limited for similar older patients. Here, we aimed to determine the most predictive frailty score of adverse events in patients aged 80 and older undergoing instrumented lumbar fusion. METHODS: We proceeded with a multisite (3 tertiary academic centers) retrospective review including patients undergoing instrumented fusion aged 80 and older from January 2010 to present. A composite end point encompassing 30-day return to operating room, readmission, and mortality was created. We estimated the area under the receiver operating characteristic curve for frailty scores (Modified Frailty Index-5 [MFI-5], Modified Frailty Index-11 [MFI-11], and Charlson Comorbidity Index [CCI]) in relation to that composite score. In addition, we estimated the association between each score and the composite end point by means of logistic regression. RESULTS: A total of 153 patients with an average age of 85 years at the time of surgery were included. We observed a 30-day readmission rate of 11.1%, reoperation of 3.9%, and mortality of 0.6%. The overall rate of the composite end point at 30 days was 25 (15.1%). The AUC for MFI-5 was 0.597 (0.501-0.693), for MFI-11 was 0.620 (0.518-0.723), and for CCI was 0.564 (0.453-0.675). The association between the scores and composite end point did not reach statistical significance for MFI-5 (odds ratio [OR] = 1.45 [0.98-2.15], P = .061) and CCI (OR = 1.13 [0.97-1.31], P = .113) but was statistically significant for MFI-11 (OR = 1.46 [1.07-2.00], P = .018). CONCLUSION: This is the largest study comparing frailty index scores in octogenarians undergoing instrumented lumbar fusion. Our findings suggest that while MFI-11 score correlated with adverse events, the predictive ability of existing scores remains limited, highlighting the need for better approaches to identify select patients at age extremes.

Abstract Sequencing efforts have identified key oncogenic drivers and transcriptomic subtypes of high-grade gliomas (HGGs), but this knowledge has not resulted in individualized therapy or improved patient outcomes. Here, we used a functional genomics approach combining integrated genomic/transcriptomic analyses with patient-derived 3D micro-cancers (mCancers) to rapidly identify individualized therapeutic vulnerabilities and determine predictive response biomarkers. 30 primary/recurrent HGGs, including 20 glioblastomas, 5 astrocytomas, and 5 oligodendrogliomas, were included for drug testing. mCancers recapitulated the structural and molecular alterations, cellularity, and heterogeneity, of parental patient tumors. A total of 119 single-agent drugs and 183 drug combinations were tested, while a pre-selected drug panel comprising 25 glioma-relevant treatment strategies was tested across all cases. In general, mCancer efficacy corresponded well to historical responses to previously tested agents (EGFR, HDAC inhibitors, etc.). Combined, strong efficacy (i.e. >70% growth inhibition at Cmax) of single treatments targeting deregulated receptor tyrosine kinase (RTK), p53/apoptosis, cell cycle, DNA damage repair, IDH, or telomere maintainance pathways, was observed in 14 out of 30 cases. Surprisingly, transcriptional signatures, but not specific genetic alterations, were found to stratify drug responses. For example, mCancers enriched for the most aggressive mesenchymal (MES) and glycolytic/plurimetabolic (GPM) transcriptional subtypes exhibited stronger response to the BET inhibitor JQ1 (and other clinical BET inhibitors) and the DNA-PKcs/mTOR dual inhibitor CC-115. This therapeutic vulnerability was associated with enrichment of YAP/TAZ signaling, and the glioblastoma stem cell G-STEM signature. Notably, individual combination strategies were effective across tumors, with strong responses ranging from 38% to 77% of all tumors tested. Overall, this study underscores the value of functional genomics in identifying novel vulnerabilities of HGGs and associated response biomarkers. It also highlights the need for further clinical validation of several novel therapies and especially drug combination strategies with strong efficacy in the ex vivo setting.

2071 Background: Despite advances in our understanding of brain cancer, the ability to discern between infiltrated and non-infiltrated tissue with current adjuncts, remains elusive. Isocitrate dehydrogenase (IDH) mutation is unique to IDH-mut glioma cells and can be used as a surrogate for tumor infiltration. Further, emerging evidence has shown unique signatures in brain cancer lipidomic profiling, with lipid metabolism playing a key role in brain cancer biology. Here, we aimed to evaluate the impact of desorption electrospray ionization-mass spectrometry (DESI-MS) as a near real-time method to determine infiltration status and the use of DESI-MS to perform intra-operative histological diagnosis. Methods: This is a prospective multi-institution cohort study using intra-operative DESI-MS on freshly obtained tumor samples to evaluate 2-hydroxyglutarate (2HG), with post-hoc validation by review by a board-certified neuropathologist. For tumor cell estimation and tissue diagnosis, high-throughput DESI-MS was used for rapid analysis of high-density arrays using lipidomic profiling. Analysis of the data was performed using a pre-written algorithm employing a combination of Python- and MATLAB-based custom software allowing results in less than a second per sample. Results: A total of 496 tumor biopsies from 72 patients have been analyzed. Earlier iterations focused on absolute quantitation of 2HG in 247 biopsies from 49 patients to determine IDH genotype yielding sensitivity, specificity, and accuracy values of 89, 100, and 94% for core biopsies (71). Improvement in accuracy was obtained with relative measurement of 2HG in comparison to glutamate allowing for detection of IDH-mut infiltration at the margin, resulting in 93% sensitivity, 100% specificity, and 98% accuracy with turnover times averaging 3 minutes in 183 biopsies from 23 patients. Margin assessment beyond the limits of neuro-navigation and surgeon assessment showed tumor infiltration in 88% of margin biopsies from IDH mutant tumors (30 of 34 biopsies) with 100% accuracy. Intra-operative tissue diagnosis was pursued in 66 unique tumor samples using DESI-MS lipidomic profiling, including samples of normal brain parenchyma, gliomas, meningiomas and pituitary adenomas, split into two microarray sets (36 and 40 samples). Using estimated principal components as input features, high accuracy ( > 90%; ROC AUCs ≥ 0.89) was obtained for supervised tissue classification using simple machine learning algorithms. Conclusions: We present a novel system for intra-operative evaluation of tumor infiltration at the margin in gliomas and for intra-operative tissue diagnosis of brain cancer. Our method identified tumor infiltration beyond the surgical margins and serves as a foundation for future uses employing DESI-MS to allow for molecularly guided surgery in IDH-mut gliomas.

Abstract Diffuse gliomas are aggressive brain tumors that lack effective therapies. Despite advances in the molecular characterization of gliomas, targeted treatments have failed to improve patient outcomes to date. Here, we employed a functional genomics approach to rapidly identify therapeutic vulnerabilities and provide a strategy to individualize patient treatment. Our process combined comprehensive genomic and transcriptomic tumor profiling, custom algorithms and visualization software for data integration, and preclinical 3-dimensional ex vivo models (mcancers) for drug screening to assess response to therapeutic agents targeting specific molecular alterations. A total of 32 cases, including 5 oligodendrogliomas (1 primary and 4 recurrent), 5 astrocytomas (1 primary and 4 recurrent), and 22 glioblastomas (5 primary and 17 recurrent), were included in the study. Immunohistochemistry and integrated genomics confirmed that mcancers maintain key molecular alterations, including mutations, chromosomal rearrangements and focal amplifications, cellularity, and heterogeneity, faithfully recapitulating the original tumor. A total of 119 single drugs and 183 combinations were tested, including a panel of 26-brain penetrant targeted agents (18 single drugs and 8 combinations) that was curated to target common glioma oncogenic pathways and was tested across all cases. A strong correlation was observed between therapeutic vulnerabilities of glioma mcancers to targeted agents (EGFR, MET, PDGFR, HDAC inhibitors, etc.) and clinical experience. Single agent activity of panel compounds in the ex vivo setting was generally poor, with only 35% mCancers exhibiting > 70% growth inhibition at Cmax. In contrast, combination strategies, especially ones including epigenetic drugs, were significantly more effective (affecting 22 out of 32 mCancers), underscoring the molecular complexity of gliomas and the need for clinical trials testing combination treatments. Our data identified a number of novel combination treatments with significant efficacy across glioma subtypes and molecular profiles, suggesting that our functional genomics pipeline can guide treatment selection and inform clinical trial enrollment for gliomas.