Chinchilli, Vernon M

Abstract Acute pancreatitis (AP) is a disease characterized by an acute inflammatory phase followed by a convalescent phase. Diabetes mellitus (DM) was historically felt to be a transient phenomenon related to acute inflammation; however, it is increasingly recognized as an important late and chronic complication. There are several challenges that have prevented precisely determining the incidence rate of DM after AP and understanding the underlying mechanisms. The DREAM (Diabetes RElated to Acute Pancreatitis and its Mechanisms) Study is a prospective cohort study designed to address these and other knowledge gaps to provide the evidence needed to screen for, prevent, and treat DM after AP. In the following article, we summarize literature regarding the epidemiology of DM after AP and provide the rationale and an overview of the DREAM study.

AbstractBackgroundBiomarkers of eosinophilic disease activity, especially in the context of novel therapies that reduce blood eosinophil counts, are an unmet need. Absolute eosinophil count (AEC) does not accurately reflect tissue eosinophilia or eosinophil activation. Therefore, the aims of this study were to compare the reliability of plasma and urine eosinophil major basic protein 1, eosinophil cationic protein, eosinophil‐derived neurotoxin (EDN), and eosinophil peroxidase measurement and to evaluate the usefulness of eosinophil granule protein (EGP) measurement for the assessment of disease activity in patients with eosinophil‐associated diseases treated with mepolizumab, benralizumab, or dexpramipexole.MethodsEosinophil granule protein concentrations were measured in serum, plasma, and urine from healthy volunteers and patients with hypereosinophilic syndrome (HES), eosinophilic granulomatosis with polyangiitis (EGPA), and eosinophilic asthma using a multiplex assay.ResultsUrine EGP concentrations remained stable, whereas serum and plasma EGP concentrations increased significantly with delayed processing. Plasma (p) EDN, but not urine (u) EDN, concentration correlated with AEC and negatively correlated with prednisone dose. Both pEDN and uEDN decreased significantly following treatment of HES patients with benralizumab and EGPA patients with mepolizumab. uEDN appeared to increase with clinical relapse in both patient groups.ConclusionsMeasurement of EGP in urine is noninvasive and unaffected by cellular lysis. Although plasma and urine EDN concentrations showed a similar pattern following benralizumab and mepolizumab treatment, the lack of correlation between AEC or prednisone dose and uEDN concentrations suggests that measurement of uEDN may provide a potential biomarker of disease activity in patients with HES and EGPA.

AbstractAlthough cancer is highly heterogeneous, all metastatic cancer is considered American Joint Committee on Cancer (AJCC) Stage IV disease. The purpose of this project was to redefine staging of metastatic cancer. Internal validation of nationally representative patient data from the National Cancer Database (n = 461 357; 2010‐2013), and external validation using the Surveillance, Epidemiology and End Results database (n = 106 595; 2014‐2015) were assessed using the concordance index for evaluation of survival prediction. A Cox proportional hazards model was used for overall survival by considering identified phenotypes (latent classes) and other confounding variables. Latent class analysis was performed for phenotype identification, where Bayesian information criterion (BIC) and sample‐size‐adjusted BIC were used to select the optimal number of distinct clusters. Kappa coefficients assessed external cluster validation. Latent class analysis identified five metastatic phenotypes with differences in overall survival (P < .0001): (Stage IVA) nearly exclusive bone‐only metastases (n = 59 049, 12.8%; median survival 12.7 months; common in lung, breast and prostate cancers); (IVB) predominant lung metastases (n = 62 491, 13.5%; 11.4 months; common in breast, stomach, kidney, ovary, uterus, thyroid, cervix and soft tissue cancers); (IVC) predominant liver/lung metastases (n = 130 014, 28.2%; 7.0 months; common in colorectum, pancreatic, lung, esophagus and stomach cancers); (IVD) bone/liver/lung metastases predominant over brain (n = 61 004, 13.2%; 5.9 months; common in lung and breast cancers); and (IVE) brain/lung metastases predominant over bone/liver (n = 148 799, 32.3%; 5.7 months; lung cancer and melanoma). Long‐term survivors were identified, particularly in Stages IVA‐B. A pan‐cancer nomogram model to predict survival (STARS: site, tumor, age, race, sex) was created, validated and provides 13% better prognostication than AJCC: 1‐month concordance index of 0.67 (95% confidence interval [CI]: 0.66‐0.67) vs 0.61 (95% CI: 0.60‐0.61). STARS is simple, uses easily accessible variables, better prognosticates survival outcomes and provides a platform to develop novel metastasis‐directed clinical trials.