Citations

Abstract Background Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. Methods We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. Results Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). Conclusions In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.

While the rupture rate of cerebral aneurysms is only 1% per year, ruptured aneurysms are associated with significant morbidity and mortality, while aneurysm treatments have their own associated risk of morbidity and mortality. Conventional markers for aneurysm rupture include patient-specific and aneurysm-specific characteristics, with the development of scoring systems to better assess rupture risk. These scores, however, rely heavily on aneurysm size, and their accuracy in assessing risk in smaller aneurysms is limited. While the individual risk of rupture of small aneurysms is low, due to their sheer number, the largest proportion of ruptured aneurysms are small aneurysms. Conventional imaging techniques are valuable in characterizing aneurysm morphology; however, advanced imaging techniques assessing the presence of inflammatory changes within the aneurysm wall, hemodynamic characteristics of blood flow within aneurysm sacs, and imaging visualization of irregular aneurysm wall motion have been used to further determine aneurysm instability that otherwise cannot be characterized by conventional imaging techniques. The current manuscript reviews conventional imaging techniques and their value and limitations in cerebral aneurysm characterization, and evaluates the applications, value and limitations of advanced aneurysm imaging and post-processing techniques including intracranial vessel wall MRA, 4D-flow, 4D-CTA, and computational fluid dynamic simulations.

OBJECTIVE Diabetes that arises from chronic pancreatitis (CP) is associated with increased morbidity and mortality. Methods to predict which patients with CP are at greatest risk for diabetes are urgently needed. We aimed to examine independent risk factors for diabetes in a large cohort of patients with CP. RESEARCH DESIGN AND METHODS This cross-sectional study comprised 645 individuals with CP enrolled in the PROCEED study, of whom 276 had diabetes. We conducted univariable and multivariable regression analyses of potential risk factors for diabetes. Model performance was assessed by area under the receiver operating characteristic curve (AUROC) analysis, and accuracy was evaluated by cross validation. Exploratory analyses were stratified according to the timing of development of diabetes relative to the diagnosis of pancreatitis. RESULTS Independent correlates of diabetes in CP included risk factors for type 2 diabetes (older age, overweight/obese status, male sex, non-White race, tobacco use) as well as pancreatic disease–related factors (history of acute pancreatitis complications, nonalcoholic etiology of CP, exocrine pancreatic dysfunction, pancreatic calcification, pancreatic atrophy) (AUROC 0.745). Type 2 diabetes risk factors were predominant for diabetes occurring before pancreatitis, and pancreatic disease–related factors were predominant for diabetes occurring after pancreatitis. CONCLUSIONS Multiple factors are associated with diabetes in CP, including canonical risk factors for type 2 diabetes and features associated with pancreatitis severity. This study lays the groundwork for the future development of models integrating clinical and nonclinical data to identify patients with CP at risk for diabetes and identifies modifiable risk factors (obesity, smoking) on which to focus for diabetes prevention.

Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source.

Abstract Durable overall response rate (ORR) remains a meaningful endpoint in recurrent GBM; however, the target ORR for single arm recurrent GBM trials has not been based on historic information or tied to patient outcomes. The current study reviewed past trials in recurrent GBM in order to judiciously define target ORRs for use in recurrent GBM trials. After reviewing 69 treatment arms comprising 4,971 patients, ORR was 6.1%[95% CI 4.23; 8.76%] for cytotoxic chemotherapies (ORR=7.59% for CCNU, 7.57% for TMZ, 0.64% for CPT-11, and 5.32% for other agents), 3.37% for biologic agents, 7.97% for immunotherapies (select trials), and 26.8% for anti-angiogenic agents. ORRs were significantly correlated with median overall survival (mOS) across chemotherapy (R2=0.4078, P< 0.0001), biologics (R2=0.4003, P=0.0003), and immunotherapy trials (R2=0.8994, P< 0.0001), but not anti-angiogenic agents (R2=0, P=0.8937). Pooling data from chemotherapy, biologics, and immunotherapy trials, a meta-analysis indicated a strong correlation between ORR and mOS (R2=0.3164, P< 0.0001; mOS[weeks]=0.6xORR+28.9), suggesting an ORR >20% results in an mOS of > 40.9 weeks, which is double the survival estimate of a treatment with ORR=0% and ≥ 2 months longer than treatments with ORR=5%. Assuming an ineffective therapy (control) has ORR=5%, a trial of 32 patients with a target ORR=20% leads to the 95% confidence interval higher than the control group. We conclude that single arm phase II studies in recurrent GBM with ≥ 32 patients should have a target ORR ≥ 20%. This was associated with a median OS of approximately 1 year. Importantly, durability of response should also be considered and was not assessed in the current meta-analysis.

Abstract Despite major strides in cancer research, care, and therapy, these advances have not been equitable across race and ethnicity. Groups underrepresented in medicine (URM) are more likely to have inadequate preventive screening, increased delays in diagnosis, and poor representation in clinical trials. Notably, Black and Latino Americans represent 29% of the population but only reflect 8% of oncology clinical trial participants. Recent studies have shown that this disparity is also present in neuro-oncology as women, Black, and Latino Americans remain under-accrued in clinical trials. Brain tumor patients already face unique barriers to clinical trial enrollment and completion due to disease-specific conditions–such as impaired motor function, cognition, language deficits, and caregiver dependency–which pose additional difficulties in clinical trial consent, enrollment, and adherence. As part of this collaborative initiative, we evaluated the impact of how a lack of diversity in cancer research is detrimental to scientific discovery and propose interventions focused on improving URM engagement with clinical research. Recommendations include the creation of inclusive trial design at the onset, decreasing barriers to care, expanding trial eligibility, and equitable access to tumor profiling for personalized medical trials. Additionally, setting reasonable metrics and goals for accrual and engagement with patient and community stakeholders will ultimately help to diversify trial participants. Lastly, diversification and inclusion practices within the neuro-oncology workforce, including all personnel involved in clinical research, will help to minimize bias, promote concordant care, and assist with developing sustainable solutions. The diversification of participation in neuro-oncology clinical trials is imperative. The lack of diversity in clinical trials can contribute to improper generalizability of treatment efficacy, resulting in potentially harmful practices. Equitable access and inclusion of URM brain tumor patients will not only enhance research discoveries but will also result in improved patient care for all cancer patients.