Citations

NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non–Small Cell Lung Cancer (NSCLC) provide recommended management for patients with NSCLC, including diagnosis, primary treatment, surveillance for relapse, and subsequent treatment. Patients with metastatic lung cancer who are eligible for targeted therapies or immunotherapies are now surviving longer. This selection from the NCCN Guidelines for NSCLC focuses on targeted therapies for patients with metastatic NSCLC and actionable mutations.

Chronic obstructive pulmonary disease (COPD) is a disease with marked metabolic disturbance. Previous studies have shown the association between single metabolites and lung function for COPD, but whether a combination of metabolites could predict phenotype is unknown. We developed metabolomic severity scores using plasma metabolomics from the Metabolon platform from two US cohorts of ever-smokers: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) (n = 648; training/testing cohort; 72% non-Hispanic, white; average age 63 years) and the COPDGene Study (n = 1120; validation cohort; 92% non-Hispanic, white; average age 67 years). Separate adaptive LASSO (adaLASSO) models were used to model forced expiratory volume at one second (FEV1) and MESA-adjusted lung density using 762 metabolites common between studies. Metabolite coefficients selected by the adaLASSO procedure were used to create a metabolomic severity score (metSS) for each outcome. A total of 132 metabolites were selected to create a metSS for FEV1. The metSS-only models explained 64.8% and 31.7% of the variability in FEV1 in the training and validation cohorts, respectively. For MESA-adjusted lung density, 129 metabolites were selected, and metSS-only models explained 59.0% of the variability in the training cohort and 17.4% in the validation cohort. Regression models including both clinical covariates and the metSS explained more variability than either the clinical covariate or metSS-only models (53.4% vs. 46.4% and 31.6%) in the validation dataset. The metabolomic pathways for arginine biosynthesis; aminoacyl-tRNA biosynthesis; and glycine, serine, and threonine pathway were enriched by adaLASSO metabolites for FEV1. This is the first demonstration of a respiratory metabolomic severity score, which shows how a metSS can add explanation of variance to clinical predictors of FEV1 and MESA-adjusted lung density. The advantage of a comprehensive metSS is that it explains more disease than individual metabolites and can account for substantial collinearity among classes of metabolites. Future studies should be performed to determine whether metSSs are similar in younger, and more racially and ethnically diverse populations as well as whether a metabolomic severity score can predict disease development in individuals who do not yet have COPD.

Abstract BRAF plus MEK inhibitor combinations are currently FDA-approved for melanoma, non–small cell lung cancer, and anaplastic thyroid cancer. The lack of clinical benefit with BRAF inhibition in BRAF V600–mutated colorectal cancer has prevented its tissue-agnostic drug development. We reviewed the AACR GENIE database for the prevalence of BRAF V600 mutations across tumor types. We reviewed the literature for case reports of clinical responses, outcomes in patients with BRAF V600 mutation—positive nonmelanoma malignancies who received BRAF inhibitor therapy, and data from published adult and pediatric trials. BRAF V600 mutations are prevalent across multiple nonmelanoma malignancies (>40 different tumor types), lead to oncogene addiction, and are clinically actionable in a broad range of adult and pediatric nonmelanoma rare malignancies. Continued tissue-agnostic drug development is warranted beyond the current BRAF plus MEK approved cancers.

The aim of the NCCN Guidelines for Management of Immunotherapy-Related Toxicities is to provide guidance on the management of immune-related adverse events resulting from cancer immunotherapy. The NCCN Management of Immunotherapy-Related Toxicities Panel is an interdisciplinary group of representatives from NCCN Member Institutions, consisting of medical and hematologic oncologists with expertise across a wide range of disease sites, and experts from the areas of dermatology, gastroenterology, endocrinology, neurooncology, nephrology, cardio-oncology, ophthalmology, pulmonary medicine, and oncology nursing. The content featured in this issue is an excerpt of the recommendations for managing toxicities related to CAR T-cell therapies and a review of existing evidence. For the full version of the NCCN Guidelines, including recommendations for managing toxicities related to immune checkpoint inhibitors, visitNCCN.org.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Background: Women and African Americans with atrial fibrillation (AF) experience higher rates of stroke compared to men and white AF patients, respectively. However, sex and race differences for cardiovascular outcomes other than stroke have not been specifically evaluated in patients with AF. Methods: We studied patients with AF in the Optum Clinformatics database between 2009 and 2015 with at least 6 months of enrollment before AF diagnosis. The Optum Clinformatics database includes medical and pharmacy claims and sociodemographic information on privately insured and Medicare Advantage enrollees throughout the US. Endpoints (hospitalizations for ischemic stroke, heart failure (HF), myocardial infarction (MI)) and covariates were defined using validated algorithms. Multivariable Cox models were used to study the association of race and sex with endpoints of interest. Results: The analysis included 380,636 eligible participants (mean age 73, women 45%). Of them, 82% were white, 9% African American, 7% Hispanic and 2% Asian American. During a mean follow-up of 23 months, 7,235 suffered ischemic stroke, 17,258 HF, and 5,585 MI. Crude rates of ischemic stroke and HF were higher in women than men, while men had higher rates of MI than women (Table). African Americans and Hispanics had higher rates of all studied outcomes than whites and Asian Americans. In models including age, sex, race, education and CHA 2 DS 2 -VASc score, women had higher risk of ischemic stroke and lower risk of HF and MI compared to men. Compared to whites, African Americans had 1.4 times the rate of HF and stroke, and 1.1 times the rate of MI, while Asian Americans had 16% lower rates of HF. No major differences were observed between rates in whites and Hispanics (Table). Conclusion: In a large insured population of patients with AF, we observed differences in rates of selected cardiovascular outcomes by sex and race. Additional research should explore the mechanisms underlying these differences and develop strategies to eliminate them.