An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types.

MOTIVATION: Identification of altered pathways that are clinically relevant across human cancers is a key challenge in cancer genomics. Precise identification and understanding of these altered pathways may provide novel insights into patient stratification, therapeutic strategies and the development of new drugs. However, a challenge remains in accurately identifying pathways altered by somatic mutations across human cancers, due to the diverse mutation spectrum. We developed an innovative approach to integrate somatic mutation data with gene networks and pathways, in order to identify pathways altered by somatic mutations across cancers. RESULTS: We applied our approach to The Cancer Genome Atlas (TCGA) dataset of somatic mutations in 4790 cancer patients with 19 different types of tumors. Our analysis identified cancer-type-specific altered pathways enriched with known cancer-relevant genes and targets of currently available drugs. To investigate the clinical significance of these altered pathways, we performed consensus clustering for patient stratification using member genes in the altered pathways coupled with gene expression datasets from 4870 patients from TCGA, and multiple independent cohorts confirmed that the altered pathways could be used to stratify patients into subgroups with significantly different clinical outcomes. Of particular significance, certain patient subpopulations with poor prognosis were identified because they had specific altered pathways for which there are available targeted therapies. These findings could be used to tailor and intensify therapy in these patients, for whom current therapy is suboptimal. AVAILABILITY AND IMPLEMENTATION: The code is available at: http://www.taehyunlab.org CONTACT: jhcheong@yuhs.ac or taehyun.hwang@utsouthwestern.edu or taehyun.cs@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pre-treatment factors associated with detecting additional brain metastases at stereotactic radiosurgery.

The number of brain metastases identified on diagnostic magnetic resonance imaging (MRI) is a key factor in consideration of stereotactic radiosurgery (SRS). However, additional lesions are often detected on high-resolution SRS-planning MRI. We investigated pre-treatment clinical characteristics that are associated with finding additional metastases at SRS. Patients treated with SRS for brain metastases between the years of 2009-2014 comprised the study cohort. All patients underwent frame-fixed, 1 mm thick MRI on the day of SRS. Patient, tumor, and treatment characteristics were analyzed for an association with increase in number of metastases identified on SRS-planning MRI. 289 consecutive SRS cases were analyzed. 725 metastases were identified on pre-treatment MRI and 1062 metastases were identified on SRS-planning MRI. An increase in the number of metastases occurred in 34 % of the cases. On univariate analysis, more than four metastases and the diameter of the largest lesion were significantly associated with an increase in number of metastases on SRS-planning MRI. When stratified by the diameter of the largest lesion into <2, 2-3, or ≥3 cm, additional metastases were identified in 37, 29, and 18 %, respectively. While this increase in the number of metastases is largely due to the difference in imaging technique, the number and size of the metastases were also associated with finding additional lesions. These clinical factors may be considered when determining treatment options for brain metastases.

Novel radiotherapeutic strategies in the management of brain metastases: Challenging the dogma.

The role of radiation therapy in the management of brain metastasis is evolving. Advancements in machine learning techniques have improved our ability to both detect brain metastasis and our ability to contour substructures of the brain as critical organs at risk. Advanced imaging with PET tracers and magnetic resonance imaging-based artificial intelligence models can now predict tumor control and differentiate tumor progression from radiation necrosis. These advancements will help to optimize dose and fractionation for each patient's lesion based on tumor size, histology, systemic therapy, medical comorbidities/patient genetics, and tumor molecular features. This review will discuss the current state of brain directed radiation for brain metastasis. We will also discuss future directions to improve the precision of stereotactic radiosurgery and optimize whole brain radiation techniques to improve local tumor control and prevent cognitive decline without forming necrosis.

Where Does Auto-Segmentation for Brain Metastases Radiosurgery Stand Today?

Detection and segmentation of brain metastases (BMs) play a pivotal role in diagnosis, treatment planning, and follow-up evaluations for effective BM management. Given the rising prevalence of BM cases and its predominantly multiple onsets, automated segmentation is becoming necessary in stereotactic radiosurgery. It not only alleviates the clinician's manual workload and improves clinical workflow efficiency but also ensures treatment safety, ultimately improving patient care. Recent strides in machine learning, particularly in deep learning (DL), have revolutionized medical image segmentation, achieving state-of-the-art results. This review aims to analyze auto-segmentation strategies, characterize the utilized data, and assess the performance of cutting-edge BM segmentation methodologies. Additionally, we delve into the challenges confronting BM segmentation and share insights gleaned from our algorithmic and clinical implementation experiences.

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).

Radiotherapy Plan Quality Assurance in NRG Oncology Trials for Brain and Head/Neck Cancers: An AI-Enhanced Knowledge-Based Approach.

The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials.

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.

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).

Impact of Cochlear Dose on Hearing Preservation Following Stereotactic Radiosurgery in Treatment of Vestibular Schwannomas: A Multi-Center Study.

OBJECTIVE: Stereotactic radiosurgery (SRS) is a well-established treatment for vestibular schwannomas (VS). Hearing loss remains a main morbidity of VS and its treatments, including SRS. The effects of radiation parameters of SRS on hearing remain unknown. The goal of this study is to determine the effect of tumor volume, patient demographics, pretreatment hearing status, cochlear radiation dose, total tumor radiation dose, fractionation, and other radiotherapy parameters on hearing deterioration. METHODS: Multicenter retrospective analysis of 611 patients who underwent SRS for VS from 1990-2020 and had pre- and post-treatment audiograms. RESULTS: Pure tone averages (PTAs) increased and word recognition scores (WRSs) decreased in treated ears at 12-60 months while remaining stable in untreated ears. Higher baseline PTA, higher tumor radiation dose, higher maximum cochlear dose, and usage of single fraction resulted in higher post radiation PTA; WRS was only predicted by baseline WRS and age. Higher baseline PTA, single fraction treatment, higher tumor radiation dose, and higher maximum cochlear dose resulted in a faster deterioration in PTA. Below a maximum cochlear dose of 3 Gy, there were no statistically significant changes in PTA or WRS. CONCLUSIONS: Decline of hearing at one year in VS patients after SRS is directly related to maximum cochlear dose, single versus 3-fraction treatment, total tumor radiation dose, and baseline hearing level. The maximum safe cochlear dose for hearingtbrowd preservation at one year is 3 Gy, and the use of 3 fractions instead of one fraction was better at preserving hearing.

Giant cell tumor of a lumbar vertebra in a 7-year-old child: a case report.

STUDY DESIGN: This case provides a rare occurrence of a giant cell tumor (GCT) in posterior elements of a lumbar vertebra in a 7-year-old child with successful outcome after surgical excision and regular follow-ups. OBJECTIVE: To present a unique case report of a pediatric GCT in the vertebral column and results. SUMMARY OF BACKGROUND DATA: GCT is a rare bone tumor seen in 3% to 5% of primary bone neoplasm. Approximately 7% of GCTs are found in the vertebral column. GCT of the spine is found in only 5% to 7% of cases and can occur in any region of the spine but are believed to be predominantly in the sacrum. Despite its benign nature, expansion in a confined space makes early detection of spinal GCTs important to prevent occurrence of compressive myelopathy/radiculopathy. The presence of a GCT in a child younger than 10 years of age, in posterior elements of a lumbar vertebral body, has not been reported earlier. METHODS: On the basis of the clinical history, radiograph of the thoracolumbar spine, computed tomography of lumbar spine, and magnetic resonance imaging, a preliminary diagnosis of osteoblastoma was made. RESULTS: The patient presented with a lytic lesion with involvement of posterior elements, 1 side the pedicle extending into the body of a lumbar vertebra (L3) and had extension into the paraspinal muscles. Intraoperative exploration and frozen section showed the presence of a typical histologic picture of a GCT. Ipsilateral pedicle, posterior elements, and the superior articular facet were excised. En bloc resection was found not to be feasible due to the friable nature of the tumor and involvement of the soft tissues. In addition, fusion was avoided with consideration of the young age of the patient. CONCLUSIONS: The patient has been free of any recurrence as of his last follow-up visit.

Dose kernel decomposition for spot-based radiotherapy treatment planning.

PURPOSE: Pre-calculation of accurate dose deposition kernels for treatment planning of spot-based radiotherapies, such as Gamma Knife (GK) and Gamma Pod (GP), can be very time-consuming and may require large data storage with an enormous number of possible spots. We proposed a novel kernel decomposition (KD) model to address accurate and fast (real-time) dose calculation with reduced data storage requirements for spot-based treatment planning. The application of the KD model was demonstrated for clinical GK and GP radiotherapy platforms. METHODS: The dose deposition kernel at each spot (shot position) is modeled as the product of a shift-invariant kernel based on a reference kernel and spatially variant scale factor. The reference kernel, one for each collimator, is defined at the center of the commissioning phantom for GK and at the center of the treatment target for GP and calculated using the Monte Carlo (MC) method. The spatially variant scale factor is defined as the ratio of the mean tissue maximum ratio (TMR) at the candidate shot position to that at the reference kernel position, and the mean TMR map is calculated within the entire volume through parallel beam ray tracing on the density image followed by averaging over all source directions. The proposed KD dose calculations were compared with the MC method and with the GK and GP treatment planning system (TPS) computations for various shot positions and collimator sizes utilizing a phantom and 14 and 12 clinical plans for GK and GP, respectively. RESULTS: For the phantom study, the KD Gamma index (3%/1 mm) passing rates were greater than 99% (median 100%) relative to the MC doses, except for the shots close to the boundary. The passing rates dropped below 90% for 8 mm (16 mm) shots positioned within ∼1 cm (∼2 cm) of the boundary. For the clinical GK plans, the KD Gamma passing rates were greater than 99% (median 100%) compared to the MC and greater than 92% (median 99%) compared to the TPS. For the clinical GP plans, the KD Gamma passing rates were greater than 95% (median 98%) compared to the MC and greater than 91% (median 97%) compared to the TPS. The scale factors were calculated in sub-seconds with GPU implementation and only need to be calculated once before treatment plan optimization. The calculation of the dose kernel was also within sub-seconds without requiring beam-by-beam calculation commonly done in the TPS. CONCLUSION: The proposed model can provide an accurate dose and enables real-time dose and derivative calculations by kernel shifting and scaling without pre-calculating or requiring large data storage for GK and GP dose deposition kernels during treatment planning. This model could be useful for spot-based radiotherapy treatment planning by allowing an efficient global fine search for optimal spots.

Vestibular Schwannoma Tumor Size and Growth Rate Predict Response with Gamma Knife Stereotactic Radiosurgery.

Objective The aim of this study is to determine if pretreatment growth of sporadic vestibular schwannomas (VS) predicts postradiosurgery response. Methods This study was a retrospective chart review at a tertiary referral center of patients with VS that had at least two pretreatment magnetic resonance imaging (MRI) studies at least 6 months apart and underwent Gamma Knife radiosurgery with a minimum of 14 months postradiosurgery imaging surveillance. Tumor linear measurements and volumetric segmentation were assessed before and after radiosurgery. The main outcome measure was persistent enlargement following radiosurgery, defined as 2 mm enlargement in greatest axial diameter or 20% enlargement in volume without size regression. Results Thirty-five patients met the inclusion criteria. Patients were observed for median pre- and posttreatment intervals of 29.5 and 40.6 months, respectively. Median dose to the tumor margin was 13 Gy. Postradiosurgery enlargement occurred in six (17.1%) and nine (25.7%) patients based on linear and volumetric enlargement definitions, respectively. Pseudoprogression-defined as tumor enlargement-followed by linear or volumetric regression that occurred in 34.3% of tumors, reaching a maximum size at a median time of 6.3 months (3.3-8.4) postradiosurgery. When controlling for age, gender, and radiation dose, preradiosurgery tumor volume less than 0.3 cm 3 (odds ratio [OR]: 59.7, p = 0.012) and preradiosurgery tumor diameter growth rate greater than or equal to 2.5 mm/year (OR: 19.3, p = 0.045) were associated with persistent postradiosurgery tumor enlargement. Conclusion Smaller pretreatment tumor volume and greater linear tumor growth rates were associated with postradiosurgery tumor enlargement when controlling for age, gender, and radiation dose. Level of Evidence This study indicates that the level of evidence is V.

Ensemble learning for glioma patients overall survival prediction using pre-operative MRIs.

Objective: Gliomas are the most common primary brain tumors. Approximately 70% of the glioma patients diagnosed with glioblastoma have an averaged overall survival (OS) of only ∼16 months. Early survival prediction is essential for treatment decision-making in glioma patients. Here we proposed an ensemble learning approach to predict the post-operative OS of glioma patients using only pre-operative MRIs.Approach: Our dataset was from the Medical Image Computing and Computer Assisted Intervention Brain Tumor Segmentation challenge 2020, which consists of multimodal pre-operative MRI scans of 235 glioma patients with survival days recorded. The backbone of our approach was a Siamese network consisting of twinned ResNet-based feature extractors followed by a 3-layer classifier. During training, the feature extractors explored traits of intra and inter-class by minimizing contrastive loss of randomly paired 2D pre-operative MRIs, and the classifier utilized the extracted features to generate labels with cost defined by cross-entropy loss. During testing, the extracted features were also utilized to define distance between the test sample and the reference composed of training data, to generate an additional predictor via K-NN classification. The final label was the ensemble classification from both the Siamese model and the K-NN model.Main results: Our approach classifies the glioma patients into 3 OS classes: long-survivors (>15 months), mid-survivors (between 10 and 15 months) and short-survivors (<10 months). The performance is assessed by the accuracy (ACC) and the area under the curve (AUC) of 3-class classification. The final result achieved an ACC of 65.22% and AUC of 0.81.Significance: Our Siamese network based ensemble learning approach demonstrated promising ability in mining discriminative features with minimal manual processing and generalization requirement. This prediction strategy can be potentially applied to assist timely clinical decision-making.

Deep-learning and radiomics ensemble classifier for false positive reduction in brain metastases segmentation.

Stereotactic radiosurgery (SRS) is now the standard of care for brain metastases (BMs) patients. The SRS treatment planning process requires precise target delineation, which in clinical workflow for patients with multiple (>4) BMs (mBMs) could become a pronounced time bottleneck. Our group has developed an automated BMs segmentation platform to assist in this process. The accuracy of the auto-segmentation, however, is influenced by the presence of false-positive segmentations, mainly caused by the injected contrast during MRI acquisition. To address this problem and further improve the segmentation performance, a deep-learning and radiomics ensemble classifier was developed to reduce the false-positive rate in segmentations. The proposed model consists of a Siamese network and a radiomic-based support vector machine (SVM) classifier. The 2D-based Siamese network contains a pair of parallel feature extractors with shared weights followed by a single classifier. This architecture is designed to identify the inter-class difference. On the other hand, the SVM model takes the radiomic features extracted from 3D segmentation volumes as the input for twofold classification, either a false-positive segmentation or a true BM. Lastly, the outputs from both models create an ensemble to generate the final label. The performance of the proposed model in the segmented mBMs testing dataset reached the accuracy (ACC), sensitivity (SEN), specificity (SPE) and area under the curve of 0.91, 0.96, 0.90 and 0.93, respectively. After integrating the proposed model into the original segmentation platform, the average segmentation false negative rate (FNR) and the false positive over the union (FPoU) were 0.13 and 0.09, respectively, which preserved the initial FNR (0.07) and significantly improved the FPoU (0.55). The proposed method effectively reduced the false-positive rate in the BMs raw segmentations indicating that the integration of the proposed ensemble classifier into the BMs segmentation platform provides a beneficial tool for mBMs SRS management.

Hearing Preservation After Intervention in Vestibular Schwannoma.

OBJECTIVE: This study aimed to assess the durability of audiological outcomes after radiation and surgery in the management of vestibular schwannoma. STUDY DESIGN: Retrospective review. SETTING: Tertiary academic center. PATIENTS: Adults with sporadic vestibular schwannoma and serviceable hearing at the time of intervention. INTERVENTIONS: Gamma Knife, middle cranial fossa, or retrosigmoid approaches. MAIN OUTCOME MEASURES: Pure-tone audiometry and speech discrimination scores. RESULTS: Postintervention serviceable hearing (class A/B) was preserved in 70.4% (n = 130; mean follow-up, 3.31 yr; range, 0-15.25 yr). Of the 49 patients treated with radiation, 19 (39.6%) had serviceable hearing at last follow-up, compared with 38 (46.9% of 81) who underwent retrosigmoid (n = 36 [44.4%]) and middle cranial fossa (n = 45 [55.6%]) approaches (odds ratio [OR], 1.40; 95% confidence interval [CI], 0.67-2.82; p = 0.47). A matched analysis by age, tumor volume, and preintervention hearing (n = 38) also found no difference in hearing preservation (HP) likelihood between surgery and radiation (OR, 2.33; 95% CI, 0.24-35.91; p = 0.59). After initial HP, 4 (9.5%) surgical versus 10 (37.0%) radiated patients subsequently lost residual serviceable (A/B) hearing (OR, 0.18; 95% CI, 0.06-0.69; p = 0.01) at a mean 3.74 ± 3.58 and 4.73 ± 3.83 years after surgery and radiation, respectively. Overall, 5- and 10-year HP rates (A/B) after initially successful HP surgery were 84.4 and 63.0%, respectively. However, survival estimates declined to 48.9% at 5 years and 32.7% at 10 years when patients with immediate postoperative serviceable hearing loss were also included, which were comparable to radiation-HP rates at 5 and 10 years of 28.0 and 14.2%, respectively ( p = 0.75). CONCLUSIONS: After vestibular schwannoma intervention, overall HP was similar between radiated and surgical cohorts. However, when successful, surgical approaches offered more durable hearing outcomes at long-term follow-up.

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.

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.

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.

Volumetric Modulated Arc Therapy Enabled Total Body Irradiation (VMAT-TBI): Six-year Clinical Experience and Treatment Outcomes.

Total body irradiation is an important part of the conditioning regimens frequently used to prepare patients for allogeneic hematopoietic stem cell transplantation (SCT). Volumetric-modulated arc therapy enabled total body irradiation (VMAT-TBI), an alternative to conventional TBI (cTBI), is a novel radiotherapy treatment technique that has been implemented and investigated in our institution. The purpose of this study is to (1) report our six-year clinical experience in terms of treatment planning strategy and delivery time and (2) evaluate the clinical outcomes and toxicities in our cohort of patients treated with VMAT-TBI. This is a retrospective single center study. Forty-four patients at our institution received VMAT-TBI and chemotherapy conditioning followed by allogeneic SCT between 2014 and 2020. Thirty-two patients (73%) received standard-dose TBI (12-13.2 Gy in 6-8 fractions twice daily), whereas 12 (27%) received low-dose TBI (2-4 Gy in one fraction). Treatment planning, delivery, and treatment outcome data including overall survival (OS), relapse-free survival (RFS), and toxicities were analyzed. The developed VMAT-TBI planning strategy consistently generated plans satisfying our dose constraints, with planning target volume coverage >90%, mean lung dose ∼50% to 75% of prescription dose, and minimal hotspots in critical organs. Most of the treatment deliveries were <100 minutes (range 33-147, mean 72). The median follow-up was 26 months. At the last follow-up, 34 of 44 (77%) of patients were alive, with 1- and 2-year OS of 90% and 79% and RFS of 88% and 71%, respectively. The most common grade 3+ toxicities observed were mucositis (31 patients [71%]) and nephrotoxicity (6 patients [13%]), both of which were deemed multifactorial in cause. Four patients (9%) in standard-dose cohort developed grade 3+ pneumonitis, with 3 cases in the setting of documented respiratory infection and only 1 (2%) deemed likely related to radiation alone. VMAT-TBI provides a safe alternative to cTBI. The dose modulation capability of VMAT-TBI may lead to new treatment strategies, such as simultaneous boost and further critical organ sparing, for better malignant cell eradication, immune suppression, and lower toxicities.

Risk of venous thromboembolism in bone and soft-tissue sarcoma patients undergoing surgical intervention: a report from prior to the initiation of SCIP measures.

BACKGROUND AND OBJECTIVES: This study reviews incidence and risk factors for venous thromboembolism (VTE) in bone/soft-tissue sarcoma patients prior to the initiation of Surgical Care Improvement Program (SCIP) measures in October 2009. METHODS: A retrospective chart review identified 171 cases of bone (51) and soft-tissue (120) sarcoma. Data were extracted on demographics, histology, presence of metastasis at presentation, type of adjuvant therapy, and established risk factors for VTE. Risk factors and outcomes were analyzed using chi-square and logistic regression with the Fisher exact test. RESULTS: The rate of clinically diagnosed VTE was 4.1% (7/171). Only those patients undergoing chemotherapy were found to have a significantly increased risk of VTE (P = 0.04). Chemical prophylaxis showed a trend toward reduction in the risk of VTE (2.4% vs. 9.1%, P = 0.13). The number of individual patient prothrombotic risk factors showed a trend towards increased risk of VTE (P = 0.12). CONCLUSIONS: The current rate of 4.1% is at the lower end of the range of reported incidence for musculoskeletal oncology patients. Furthermore, VTE did not occur only in patients with hip/thigh sarcomas, as previously reported by some. The trend for reduced incidence with chemoprophylaxis favors prophylactic measures but requires further substantiation in larger studies.