Two-Stage Training Framework Using Multicontrast MRI Radiomics for IDH Mutation Status Prediction in Glioma.

Purpose To develop a radiomics framework for preoperative MRI-based prediction of isocitrate dehydrogenase (IDH) mutation status, a crucial glioma prognostic indicator. Materials and Methods Radiomics features (shape, first-order statistics, and texture) were extracted from the whole tumor or the combination of nonenhancing, necrosis, and edema regions. Segmentation masks were obtained via the federated tumor segmentation tool or the original data source. Boruta, a wrapper-based feature selection algorithm, identified relevant features. Addressing the imbalance between mutated and wild-type cases, multiple prediction models were trained on balanced data subsets using random forest or XGBoost and assembled to build the final classifier. The framework was evaluated using retrospective MRI scans from three public datasets (The Cancer Imaging Archive [TCIA, 227 patients], the University of California San Francisco Preoperative Diffuse Glioma MRI dataset [UCSF, 495 patients], and the Erasmus Glioma Database [EGD, 456 patients]) and internal datasets collected from the University of Texas Southwestern Medical Center (UTSW, 356 patients), New York University (NYU, 136 patients), and University of Wisconsin-Madison (UWM, 174 patients). TCIA and UTSW served as separate training sets, while the remaining data constituted the test set (1617 or 1488 testing cases, respectively). Results The best performing models trained on the TCIA dataset achieved area under the receiver operating characteristic curve (AUC) values of 0.89 for UTSW, 0.86 for NYU, 0.93 for UWM, 0.94 for UCSF, and 0.88 for EGD test sets. The best performing models trained on the UTSW dataset achieved slightly higher AUCs: 0.92 for TCIA, 0.88 for NYU, 0.96 for UWM, 0.93 for UCSF, and 0.90 for EGD. Conclusion This MRI radiomics-based framework shows promise for accurate preoperative prediction of IDH mutation status in patients with glioma. Keywords: Glioma, Isocitrate Dehydrogenase Mutation, IDH Mutation, Radiomics, MRI Supplemental material is available for this article. Published under a CC BY 4.0 license. See also commentary by Moassefi and Erickson in this issue.

Synthesizing 3D Multi-Contrast Brain Tumor MRIs Using Tumor Mask Conditioning.

Data scarcity and data imbalance are two major challenges in training deep learning models on medical images, such as brain tumor MRI data. The recent advancements in generative artificial intelligence have opened new possibilities for synthetically generating MRI data, including brain tumor MRI scans. This approach can be a potential solution to mitigate the data scarcity problem and enhance training data availability. This work focused on adapting the 2D latent diffusion models to generate 3D multi-contrast brain tumor MRI data with a tumor mask as the condition. The framework comprises two components: a 3D autoencoder model for perceptual compression and a conditional 3D Diffusion Probabilistic Model (DPM) for generating high-quality and diverse multi-contrast brain tumor MRI samples, guided by a conditional tumor mask. Unlike existing works that focused on generating either 2D multi-contrast or 3D single-contrast MRI samples, our models generate multi-contrast 3D MRI samples. We also integrated a conditional module within the UNet backbone of the DPM to capture the semantic class-dependent data distribution driven by the provided tumor mask to generate MRI brain tumor samples based on a specific brain tumor mask. We trained our models using two brain tumor datasets: The Cancer Genome Atlas (TCGA) public dataset and an internal dataset from the University of Texas Southwestern Medical Center (UTSW). The models were able to generate high-quality 3D multi-contrast brain tumor MRI samples with the tumor location aligned by the input condition mask. The quality of the generated images was evaluated using the Fréchet Inception Distance (FID) score. This work has the potential to mitigate the scarcity of brain tumor data and improve the performance of deep learning models involving brain tumor MRI data.

Single-Fraction Versus Fractionated Preoperative Radiosurgery for Resected Brain Metastases: A PROPS-BM International Multicenter Cohort Study.

PURPOSE: Preoperative stereotactic radiosurgery (SRS) is a feasible alternative to postoperative SRS for resected brain metastases (BM). Most reported studies of preoperative SRS used single-fraction SRS (SF-SRS). The goal of this study was to compare outcomes and toxicity of preoperative SF-SRS with multifraction (3-5 fractions) SRS (MF-SRS) in a large international multicenter cohort (Preoperative Radiosurgery for Brain Metastases-PROPS-BM). METHODS AND MATERIALS: Patients with BM from solid cancers, of which at least 1 lesion was treated with preoperative SRS followed by planned resection, were included from 8 institutions. SRS to synchronous intact BM was allowed. Exclusion criteria included prior or planned whole brain radiation therapy. Intracranial outcomes were estimated using cumulative incidence with competing risk of death. Propensity score matched (PSM) analyses were performed. RESULTS: The study cohort included 404 patients with 416 resected index lesions, of which SF-SRS and MF-SRS were used for 317 (78.5%) and 87 patients (21.5%), respectively. Median dose was 15 Gy in 1 fraction for SF-SRS and 24 Gy in 3 fractions for MF-SRS. Univariable analysis demonstrated that SF-SRS was associated with higher cavity local recurrence (LR) compared with MF-SRS (2-year: 16.3% vs 2.9%; P = .004), which was also demonstrated in multivariable analysis. PSM yielded 81 matched pairs (n = 162). PSM analysis also demonstrated significantly higher rate of cavity LR with SF-SRS (2-year: 19.8% vs 3.3%; P = .003). There was no difference in adverse radiation effect, meningeal disease, or overall survival between cohorts in either analysis. CONCLUSIONS: Preoperative MF-SRS was associated with significantly reduced risk of cavity LR in both the unmatched and PSM analyses. There was no difference in adverse radiation effect, meningeal disease, or overall survival based on fractionation. MF-SRS may be a preferred option for neoadjuvant radiation therapy of resected BMs. Additional confirmatory studies are needed. A phase 3 randomized trial of single-fraction preoperative versus postoperative SRS (NRG-BN012) is ongoing (NCT05438212).

The clinical and financial impact of remote clinical oncology pharmacist engagement in community-based practices within The US Oncology Network.

INTRODUCTION: The integration of clinical oncology pharmacists into multidisciplinary healthcare teams is not well-described in the community practice setting. This study aims to analyze the clinical and financial impact of a remote-based clinical oncology pharmacist in four community oncology practices within The US Oncology Network. METHODS: Oncology-trained clinical pharmacists electronically reviewed chemotherapy orders for clinical optimization and financial stewardship within four community oncology practices. Each pharmacist was appointed at 0.5 full-time equivalents per practice. Financial, clinical, and workload metrics were tracked to monitor the impact of pharmacist engagement. RESULTS: Over 12 months, 5716 order reviews were completed with an intervention rate of 57%. The most common interventions identified by the pharmacists were interventions with clinical impact on the patient (36%), followed by dose rounding (35%) and therapeutic interchange (30%). Overall, interventions improved the cumulative practice margins by $1,455,033 and reduced total medication costs by $5,962,551. The average program return on investment was 415% (range 100-915%). CONCLUSION: Community oncology practices seek to provide high-value care in a lean, resource-constrained model. An oncology clinical pharmacist is a cost-effective and clinically invaluable care team member in community oncology practice. Pharmacists in this setting identified opportunities to improve medication safety and regimen optimization and demonstrated a significant tremendous financial impact on small-scale budgets in community oncology.

Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study.

BACKGROUND: In the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume and low attenuation plaque volume. The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes. DESIGN: CONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3-4 years. SUMMARY: CONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.

MRI-Based Deep Learning Method for Classification of IDH Mutation Status.

Isocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas. This study sought to develop deep learning networks for non-invasive IDH classification using T2w MR images while comparing their performance to a multi-contrast network. Methods: Multi-contrast brain tumor MRI and genomic data were obtained from The Cancer Imaging Archive (TCIA) and The Erasmus Glioma Database (EGD). Two separate 2D networks were developed using nnU-Net, a T2w-image-only network (T2-net) and a multi-contrast network (MC-net). Each network was separately trained using TCIA (227 subjects) or TCIA + EGD data (683 subjects combined). The networks were trained to classify IDH mutation status and implement single-label tumor segmentation simultaneously. The trained networks were tested on over 1100 held-out datasets including 360 cases from UT Southwestern Medical Center, 136 cases from New York University, 175 cases from the University of Wisconsin-Madison, 456 cases from EGD (for the TCIA-trained network), and 495 cases from the University of California, San Francisco public database. A receiver operating characteristic curve (ROC) was drawn to calculate the AUC value to determine classifier performance. Results: T2-net trained on TCIA and TCIA + EGD datasets achieved an overall accuracy of 85.4% and 87.6% with AUCs of 0.86 and 0.89, respectively. MC-net trained on TCIA and TCIA + EGD datasets achieved an overall accuracy of 91.0% and 92.8% with AUCs of 0.94 and 0.96, respectively. We developed reliable, high-performing deep learning algorithms for IDH classification using both a T2-image-only and a multi-contrast approach. The networks were tested on more than 1100 subjects from diverse databases, making this the largest study on image-based IDH classification to date.

Modeling gamma knife radiosurgical toxicity for multiple brain metastases.

BACKGROUND AND PURPOSE: Radiation oncology protocols for single fraction radiosurgery recommend setting dosing criteria based on assumed risk of radionecrosis, which can be predicted by the 12 Gy normal brain volume (V12). In this study, we show that tumor surface area (SA) and a simple power-law model using only preplan variables can estimate and minimize radiosurgical toxicity. MATERIALS AND METHODS: A 245-patient cohort with 1217 brain metastases treated with single or distributed Gamma Knife sessions was reviewed retrospectively. Univariate and multivariable linear regression models and power-law models determined which modeling parameters best predicted V12. The V12 power-law model, represented by a product of normalized Rx dose Rxn, and tumor longest axial dimension LAD (V12 âˆ¼ Rxn1.5*LAD2), was independently validated using a secondary 63-patient cohort with 302 brain metastases. RESULTS: Surface area was the best univariate linear predictor of V12 (adjR2 = 0.770), followed by longest axial dimension (adjR2 = 0.755) and volume (adjR2 = 0.745). The power-law model accounted for 90% variance in V12 for 1217 metastatic lesions (adjR2 = 0.906) and 245 patients (adjR2 = 0.896). The average difference ΔV12 between predicted and measured V12s was (0.28 ± 0.55) cm3 per lesion and (1.0 ± 1.2) cm3 per patient. The power-law predictive capability was validated using a secondary 63-patient dataset (adjR2 = 0.867) with 302 brain metastases (adjR2 = 0.825). CONCLUSION: Surface area was the most accurate univariate predictor of V12 for metastatic lesions. We developed a preplan model for brain metastases that can help better estimate radionecrosis risk, determine prescription doses given a target V12, and provide safe dose escalation strategies without the use of any planning software.

Relation of Gender to Atherosclerotic Plaque Characteristics by Differing Angiographic Stenosis Severity.

It is unknown whether gender influences the atherosclerotic plaque characteristics (APCs) of lesions of varying angiographic stenosis severity. This study evaluated the imaging data of 303 symptomatic patients from the derivation arm of the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial, all of whom underwent coronary computed tomographic angiography and clinically indicated nonemergent invasive coronary angiography upon study enrollment. Index tests were interpreted by 2 blinded core laboratories, one of which performed quantitative coronary computed tomographic angiography using an artificial intelligence application to characterize and quantify APCs, including percent atheroma volume (PAV), low-density noncalcified plaque (LD-NCP), noncalcified plaque (NCP), calcified plaque (CP), lesion length, positive arterial remodeling, and high-risk plaque (a combination of LD-NCP and positive remodeling ≥1.10); the other classified lesions as obstructive (≥50% diameter stenosis) or nonobstructive (<50% diameter stenosis) based on quantitative invasive coronary angiography. The relation between APCs and angiographic stenosis was further examined by gender. The mean age of the study cohort was 64.4 ± 10.2 years (29.0% female). In patients with obstructive disease, men had more LD-NCP PAV (0.5 ± 0.4 vs 0.3 ± 0.8, p = 0.03) and women had more CP PAV (11.7 ± 1.6 vs 8.0 ± 0.8, p = 0.04). Obstructive lesions had more NCP PAV compared with their nonobstructive lesions in both genders, however, obstructive lesions in women also demonstrated greater LD-NCP PAV (0.4 ± 0.5 vs 1.0 ± 1.8, p = 0.03), and CP PAV (17.4 ± 16.5 vs 25.9 ± 18.7, p = 0.03) than nonobstructive lesions. Comparing the composition of obstructive lesions by gender, women had more CP PAV (26.3 ± 3.4 vs 15.8 ± 1.5, p = 0.005) whereas men had more NCP PAV (33.0 ± 1.6 vs 26.7 ± 2.5, p = 0.04). Men had more LD-NCP PAV in nonobstructive lesions compared with women (1.2 ± 0.2 vs 0.6 ± 0.2, p = 0.02). In conclusion, there are gender-specific differences in plaque composition based on stenosis severity.

Two Listeria monocytogenes outbreaks in a cancer centre: onsite food premises and their potential health risk to patients.

BACKGROUND: This report describes two L. monocytogenes outbreak investigations that occurred in March and September of 2018 and that linked illness to a food premises located in an Ontario cancer centre. The cancer centre serves patients from across the province. METHODS: In Ontario, local public health agencies follow up with all reported laboratory-confirmed cases of listeriosis to identify possible sources of disease acquisition and to carry out investigations, including at suspected food premises. The Canadian Food Inspection Agency (CFIA) is notified of any Listeria-positive food product collected in relation to a case. The CFIA traces Listeria-positive product through the food distribution system to identify the contamination source and ensure the implicated manufacturing facility implements corrective measures. RESULTS: Outbreaks one and two each involved three outbreak-confirmed listeriosis cases. All six cases were considered genetically related by whole genome sequencing (WGS). In both outbreaks, outbreak-confirmed cases reported consuming meals at a food premises located in a cancer centre (food premises A) before illness onset. Various open deli meat samples and, in outbreak two, environmental swabs (primarily from the meat slicer) collected from food premises A were genetically related to the outbreak-confirmed cases. Food premises A closed as a result of the investigations. CONCLUSIONS: When procuring on-site food premises, healthcare facilities and institutions serving individuals with immuno-compromising conditions should consider the potential health risk of foods available to their patient population.

Risk Factors for Progression and Toxic Effects After Preoperative Stereotactic Radiosurgery for Patients With Resected Brain Metastases.

Importance: Preoperative stereotactic radiosurgery (SRS) has been demonstrated as a feasible alternative to postoperative SRS for resectable brain metastases (BMs) with potential benefits in adverse radiation effects (AREs) and meningeal disease (MD). However, mature large-cohort multicenter data are lacking. Objective: To evaluate preoperative SRS outcomes and prognostic factors from a large international multicenter cohort (Preoperative Radiosurgery for Brain Metastases-PROPS-BM). Design, Setting, and Participants: This multicenter cohort study included patients with BMs from solid cancers, of which at least 1 lesion received preoperative SRS and a planned resection, from 8 institutions. Radiosurgery to synchronous intact BMs was allowed. Exclusion criteria included prior or planned whole-brain radiotherapy and no cranial imaging follow-up. Patients were treated between 2005 and 2021, with most treated between 2017 and 2021. Exposures: Preoperative SRS to a median dose to 15 Gy in 1 fraction or 24 Gy in 3 fractions delivered at a median (IQR) of 2 (1-4) days before resection. Main Outcomes and Measures: The primary end points were cavity local recurrence (LR), MD, ARE, overall survival (OS), and multivariable analysis of prognostic factors associated with these outcomes. Results: The study cohort included 404 patients (214 women [53%]; median [IQR] age, 60.6 [54.0-69.6] years) with 416 resected index lesions. The 2-year cavity LR rate was 13.7%. Systemic disease status, extent of resection, SRS fractionation, type of surgery (piecemeal vs en bloc), and primary tumor type were associated with cavity LR risk. The 2-year MD rate was 5.8%, with extent of resection, primary tumor type, and posterior fossa location being associated with MD risk. The 2-year any-grade ARE rate was 7.4%, with target margin expansion greater than 1 mm and melanoma primary being associated with ARE risk. Median OS was 17.2 months (95% CI, 14.1-21.3 months), with systemic disease status, extent of resection, and primary tumor type being the strongest prognostic factors associated with OS. Conclusions and Relevance: In this cohort study, the rates of cavity LR, ARE, and MD after preoperative SRS were found to be notably low. Several tumor and treatment factors were identified that are associated with risk of cavity LR, ARE, MD, and OS after treatment with preoperative SRS. A phase 3 randomized clinical trial of preoperative vs postoperative SRS (NRG BN012) has began enrolling (NCT05438212).

Hypercoagulable State and Thrombosis of Bioprosthetic Transcatheter Aortic Valve Replacement (TAVR) Refractory to Common Anticoagulation Methods in the Setting of Protein S Deficiency.

Protein S deficiency is a form of thrombophilia in which the anticoagulant protein S is underproduced or not produced at all by the body. Lifelong anticoagulation is the mainstay of treatment. Transcatheter aortic valve replacement (TAVR) is a current treatment modality for patients with severe aortic stenosis. We are reporting the case of a patient with this disease who underwent a TAVR procedure and experienced valve leaflet thrombosis and large arterial thrombosis in the following months while fully anticoagulated with typical anticoagulation methods including warfarin, apixaban, and enoxaparin. Literature-based guidance is lacking with regard to anticoagulation in the setting of TAVR patients, especially in those with protein S deficiency. Based on our observations, warfarin was the better long-term prophylactic management method for our patient's protein S deficiency. Enoxaparin was most useful during periods of elevated thrombosis risk, including intra-/post-operative care and prolonged hospitalization periods. In the setting of her TAVR, we observed that warfarin use with a target international normalized ratio (INR) of 2.5-3.5 was the most effective outpatient treatment for the reversal of thrombosed bioprosthetic valve and improvement of cardiac ejection fraction. It is also possible that initial post-operative warfarin use would have been the most effective means of preventing valve thrombosis entirely in our protein S-deficient patient.

Errata: Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction.

[This corrects the article DOI: 10.1117/1.JMI.9.1.016001.].

Corrigendum to: A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas.

[This corrects the article DOI: 10.1093/noajnl/vdaa066.].

NCCN Guidelines® Insights: Central Nervous System Cancers, Version 2.2022.

The NCCN Guidelines for Central Nervous System (CNS) Cancers focus on management of the following adult CNS cancers: glioma (WHO grade 1, WHO grade 2-3 oligodendroglioma [1p19q codeleted, IDH-mutant], WHO grade 2-4 IDH-mutant astrocytoma, WHO grade 4 glioblastoma), intracranial and spinal ependymomas, medulloblastoma, limited and extensive brain metastases, leptomeningeal metastases, non-AIDS-related primary CNS lymphomas, metastatic spine tumors, meningiomas, and primary spinal cord tumors. The information contained in the algorithms and principles of management sections in the NCCN Guidelines for CNS Cancers are designed to help clinicians navigate through the complex management of patients with CNS tumors. Several important principles guide surgical management and treatment with radiotherapy and systemic therapy for adults with brain tumors. The NCCN CNS Cancers Panel meets at least annually to review comments from reviewers within their institutions, examine relevant new data from publications and abstracts, and reevaluate and update their recommendations. These NCCN Guidelines Insights summarize the panel's most recent recommendations regarding molecular profiling of gliomas.

Impact of CDKN2A/B, MTAP, and TERT Genetic Alterations on Survival in IDH Wild Type Glioblastomas.

PURPOSE: Poor outcomes in IDH wild-type (IDHwt) glioblastomas indicate the need to determine which genetic alterations can indicate poor survival and guidance of patient specific treatment options. We sought to identify the genetic alterations in these patients that predict for survival when adjusting particularly for treatments and other genetic alterations. METHODS: A cohort of 167 patients with pathologically confirmed IDHwt glioblastomas treated at our institution was retrospectively reviewed. Next generation sequencing was performed for each patient to determine tumor genetic alterations. Multivariable cox proportional hazards analysis for overall survival (OS) was performed to control for patient variables. RESULTS: CDKN2A, CDKN2B, and MTAP deletion predict for worse OS independently of other genetic alterations and patient characteristics (hazard ratio [HR] 2.192, p = 0.0017). Patients with CDKN2A copy loss (HR 2.963, p = 0.0037) or TERT mutated (HR 2.815, p = 0.0008) glioblastomas exhibited significant associations between radiation dose and OS, while CDKN2A and TERT wild type patients did not. CDKN2A deleted patients with NF1 mutations had worse OS (HR 1.990, p = 0.0540), while CDKN2A wild type patients had improved OS (HR 0.229, p = 0.0723). Patients with TERT mutated glioblastomas who were treated with radiation doses < 45 Gy (HR 3.019, p = 0.0010) but not those treated with ≥ 45 Gy exhibited worse OS compared to those without TERT mutations. CONCLUSION: In IDHwt glioblastomas, CDKN2A, CDKN2B, and MTAP predict for poor prognosis. TERT and CDKN2A mutations are associated with worse survival only when treated with lower radiation doses, thus potentially providing a genetic marker that can inform clinicians on proper dose-fractionation schemes.

Socioeconomic and demographic determinants of radiation treatment and outcomes in glioblastoma patients.

Introduction: Poor outcomes in glioblastoma patients, despite advancing treatment paradigms, indicate a need to determine non-physiologic prognostic indicators of patient outcome. The impact of specific socioeconomic and demographic patient factors on outcomes is unclear. We sought to identify socioeconomic and demographic patient characteristics associated with patient survival and tumor progression, and to characterize treatment options and healthcare utilization. Methods: A cohort of 169 patients with pathologically confirmed glioblastomas treated at our institution was retrospectively reviewed. Multivariable cox proportional hazards analysis for overall survival (OS) and cumulative incidence of progression was performed. Differences in treatment regimen, patient characteristics, and neuro-oncology office use between different age and depressive disorder history patient subgroups were calculated two-sample t-tests, Fisher's exact tests, or linear regression analysis. Results: The median age of all patients at the time of initiation of radiation therapy was 60.5 years. The median OS of the cohort was 13.1 months. Multivariable analysis identified age (Hazard Ratio 1.02, 95% CI 1.00-1.04) and total resection (Hazard Ratio 0.52, 95% CI 0.33-0.82) as significant predictors of OS. Increased number of radiation fractions (Hazard Ratio 0.90, 95% CI 0.82-0.98), depressive disorder history (Hazard Ratio 0.59, 95% CI 0.37-0.95), and total resection (Hazard Ratio 0.52, 95% CI 0.31-0.88) were associated with decreased incidence of progression. Notably, patients with depressive disorder history were observed to have more neuro-oncology physician office visits over time (median 12 vs. 16 visits, p = 0.0121). Patients older than 60 years and those with Medicare (vs. private) insurance were less likely to receive as many radiation fractions (p = 0.0014) or receive temozolomide concurrently with radiation (Odds Ratio 0.46, p = 0.0139). Conclusion: Older glioblastoma patients were less likely to receive as diverse of a treatment regimen as their younger counterparts, which may be partially driven by insurance type. Patients with depressive disorder history exhibited reduced incidence of progression, which may be due to more frequent health care contact during neuro-oncology physician office visits.

Neutrophilia and post-radiation thrombocytopenia predict for poor prognosis in radiation-treated glioma patients.

Introduction: Poor outcomes in glioma patients indicate a need to determine prognostic indicators of survival to better guide patient specific treatment options. While preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) have been suggested as prognostic systemic inflammation markers, the impact of post-radiation changes in these cell types is unclear. We sought to identify which hematologic cell measurements before, during, or after radiation predicted for patient survival. Methods: A cohort of 182 patients with pathologically confirmed gliomas treated at our institution was retrospectively reviewed. Patient blood samples were collected within one month before, during, or within 3 months after radiation for quantification of hematologic cell counts, for which failure patterns were evaluated. Multivariable cox proportional hazards analysis for overall survival (OS) and progression-free survival (PFS) was performed to control for patient variables. Results: Multivariable analysis identified pre-radiation NLR > 4.0 (Hazard ratio = 1.847, p = 0.0039) and neutrophilia prior to (Hazard ratio = 1.706, p = 0.0185), during (Hazard ratio = 1.641, p = 0.0277), or after (Hazard ratio = 1.517, p = 0.0879) radiation as significant predictors of worse OS, with similar results for PFS. Post-radiation PLR > 200 (Hazard ratio = 0.587, p = 0.0062) and a percent increase in platelets after radiation (Hazard ratio = 0.387, p = 0.0077) were also associated with improved OS. Patients receiving more than 15 fractions of radiation exhibited greater post-radiation decreases in neutrophil and platelet counts than those receiving fewer. Patients receiving dexamethasone during radiation exhibited greater increases in neutrophil counts than those not receiving steroids. Lymphopenia, changes in lymphocyte counts, monocytosis, MLR, and changes in monocyte counts did not impact patient survival. Conclusion: Neutrophilia at any time interval surrounding radiotherapy, pre-radiation NLR, and post-radiation thrombocytopenia, but not lymphocytes or monocytes, are predictors of poor patient survival in glioma patients.