Venous thromboembolism and intracranial hemorrhage after craniotomy for primary malignant brain tumors: a National Surgical Quality Improvement Program analysis

Venous thromboembolism (VTE), including deep venous thrombosis (DVT) and pulmonary embolism (PE), frequently complicates the postoperative course of primary malignant brain tumor patients. Thromboprophylactic anticoagulation is commonly used to prevent VTE at the risk of intracranial hemorrhage (ICH). We extracted all patients who underwent craniotomy for a primary malignant brain tumor from the National Surgical Quality Improvement Program (NSQIP) registry (2005–2015) to perform a time-to-event analysis and identify relevant predictors of DVT, PE, and ICH within 30 days after surgery. Among the 7376 identified patients, the complication rates were 2.6, 1.5, and 1.3% for DVT, PE, and ICH, respectively. VTE was the second-most common major complication and third-most common reason for readmission. ICH was the most common reason for reoperation. The increased risk of VTE extends beyond the period of hospitalization, especially for PE, whereas ICH occurred predominantly within the first days after surgery. Older age and higher BMI were overall predictors of VTE. Dependent functional status and longer operative times were predictive for VTE during hospitalization, but not for post-discharge events. Admission two or more days before surgery was predictive for DVT, but not for PE. Preoperative steroid usage and male gender were predictive for post-discharge DVT and PE, respectively. ICH was associated with various comorbidities and longer operative times. This multicenter study demonstrates distinct critical time periods for the development of thrombotic and hemorrhagic events after craniotomy. Furthermore, the VTE risk profile depends on the type of VTE (DVT vs. PE) and clinical setting (hospitalized vs. post-discharge patients)

Minimal residual disease in Myeloma: Application for clinical care and new drug registration

The development of novel agents has transformed the treatment paradigm for multiple myeloma, with minimal residual disease (MRD) negativity now achievable across the entire disease spectrum. Bone marrow–based technologies to assess MRD, including approaches using next-generation flow and next-generation sequencing, have provided real-time clinical tools for the sensitive detection and monitoring of MRD in patients with multiple myeloma. Complementary liquid biopsy–based assays are now quickly progressing with some, such as mass spectrometry methods, being very close to clinical use, while others utilizing nucleic acid–based technologies are still developing and will prove important to further our understanding of the biology of MRD. On the regulatory front, multiple retrospective individual patient and clinical trial level meta-analyses have already shown and will continue to assess the potential of MRD as a surrogate for patient outcome. Given all this progress, it is not surprising that a number of clinicians are now considering using MRD to inform real-world clinical care of patients across the spectrum from smoldering myeloma to relapsed refractory multiple myeloma, with each disease setting presenting key challenges and questions that will need to be addressed through clinical trials. The pace of advances in targeted and immune therapies in multiple myeloma is unprecedented, and novel MRD-driven biomarker strategies are essential to accelerate innovative clinical trials leading to regulatory approval of novel treatments and continued improvement in patient outcomes

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

FDA Analysis: Impact of Body Mass Index (BMI) on Outcomes in Relapsed-Refractory Multiple Myeloma

Background: Obesity has been implicated as a risk factor for the development of certain types of cancers, including multiple myeloma (Wallin 2011). In a report published in NEJM in 2016, the relative risk of multiple myeloma for overweight to class 1 obese individuals was 1.2, versus a relative risk of 1.5 for class 2 to 3 obese individuals (Lauby-Secretan 2016). Recent reports indicate that BMI may impact prognosis in patients with newly diagnosed multiple myeloma (Beason 2013). Minimal information is available on impact of BMI and prognosis in patients with relapsed-refractory multiple myeloma. We analyzed the association between BMI and clinical outcomes in patients with relapsed/refractory multiple myeloma to determine if there is a difference in outcomes based on body weight. Methods: We conducted a retrospective analysis of four clinical trials evaluating novel therapeutics. These trials enrolled patients with relapsed/refractory multiple myeloma who had received one or more prior therapies. Patients were categorized into four groups, underweight (BMI 30.0 kg/m2). The Kaplan-Meier method was used to estimate progression free survival and overall survival. Results: A total of 2392 subjects were included in this analysis. The median age was 65 years (range 30-91 years). A total of 28 (1.2%) subjects were underweight, 733 (30.6%) were normal weight, 1032 (43.1%) were overweight, and 599 (25.0%) were obese. More of the underweight subjects were female (82.1%), whereas more of the overweight and obese subjects were male (62.9% and 56.6%, respectively). The median PFS and OS K-M curves are displayed below. In this univariate analysis, there were no differences in PFS (p=0.61) or OS (p=0.7) among the four groups. There were some differences in the underweight population; however, the small sample size of this group precludes any meaningful conclusions. Univariate analyses by gender did not reveal any differences in outcomes based on body weight. Conclusion: In patients with relapsed/refractory multiple myeloma, body weight had no impact on outcomes, as measured by PFS and OS. These results are consistent with previous findings on the effect of BMI on survival in subjects with multiple myeloma after autologous stem cell transplant (Kocoglu 2018). Limitations of this analysis include the use of a univariate analysis, the small sample size for patients who were underweight, heterogeneity in the treatment regimens, and immaturity of the OS data. Future studies are needed to evaluate other variables such as the relationship between cytogenetics and body weight, as well as analyses of safety based on body weight in this relapsed/refractory patient population. Figure Disclosures Shah: Physicians' Education Resource: Honoraria. Mailankody:Juno: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Takeda Oncology: Research Funding; CME activity by Physician Education Resource: Honoraria. Landgren:Sanofi: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Merck: Other: IDMC; Theradex: Other: IDMC; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding

Summary of the Second Annual BMT CTN Myeloma Intergroup Workshop on Minimal Residual Disease and Immune Profiling

•Summary from the second annual BMT CTN Myeloma Intergroup minimal residual disease (MRD)/immune profiling (IP) workshop.•MRD is currently considered a prognostic biomarker from a regulatory perspective.•Additional prospective studies are required to develop MRD as a surrogate endpoint.•Standardization of immunophenotyping/IP studies is needed. The second annual Blood and Marrow Transplant Clinical Trials Network (BMT CTN) Myeloma Intergroup Workshop on Minimal Residual Disease and Immune Profiling was convened on December 7, 2017, at the American Society of Hematology (ASH) meeting. During this workshop, investigators from around the world presented their latest research involving assessment of minimal residual disease (MRD) and immune profiling (IP) in myeloma. This document summarizes the workshop presentations as well as relevant ASH abstracts and focuses on the regulatory issues involved in the integration of MRD and IP assessment in clinical trial design and practice