Enhancing clarity of clinical trial safety reports for data monitoring committees.

A Data Monitoring Committee (DMC) evaluates patient safety in a clinical trial of an investigational intervention through periodic review of adverse events (AEs) and clinical safety assessments. Our aim was to construct DMC report displays to enhance the DMC safety review through use of graphics and clear identification and adjustment for missing data caused by early discontinuations and ongoing study participation. Suggested displays include a study snapshot graph, enhanced adverse event incidence tables including the incidence density and plotted incidence proportions, line graphs in place of by-patient listings, and trend plots in place of tables for continuous assessments.

Temporal trends in validated ischaemic stroke hospitalizations in the USA.

BACKGROUND: Accurate assessment of the burden of stroke, a major cause of disability and death, is crucial. We aimed to estimate rates of validated ischaemic stroke hospitalizations in the USA during 1998-2011. METHODS: We used the Atherosclerosis Risk in Communities (ARIC) study cohort's adjudicated stroke data for participants aged ≥55 years, to construct validation models for each International Classification of Diseases (ICD)-code group and patient covariates. These models were applied to the Nationwide Inpatient Sample (NIS) data to estimate the probability of validated ischaemic stroke for each eligible hospitalization. Rates and trends in NIS using ICD codes vs estimates of validated ischaemic stroke were compared. RESULTS: After applying validation models, the estimated annual average rate of validated ischaemic stroke hospitalizations in the USA during 1998-2011 was 3.37 [95% confidence interval (CI): 3.31, 3.43) per 1000 person-years. Validated rates declined during 1998-2011 from 4.7/1000 to 2.9/1000; however, the decline was limited to 1998-2007, with no further decline subsequently through 2011. Validation models showed that the false-positive (∼23% of strokes) and false-negative rates of ICD-9-CM codes in primary position for ischaemic stroke approximately cancel. Therefore, estimates of ischaemic stroke hospitalizations did not substantially change after applying validation models. CONCLUSIONS: Overall, ischaemic stroke hospitalization rates in the USA have declined during 1998-2007, but no further decline was observed from 2007 to 2011. Validated ischaemic stroke hospitalizations estimates were similar to published estimates of hospitalizations with ischaemic stroke ICD codes in primary position. Validation of national discharge data using prospective chart review data is important to estimate the accuracy of reported burden of stroke.

BNP and obesity in acute decompensated heart failure with preserved vs. reduced ejection fraction: The Atherosclerosis Risk in Communities Surveillance Study.

BACKGROUND: Levels of B-type natriuretic peptide (BNP), a prognostic marker in patients with heart failure (HF), are lower among HF patients with obesity or preserved Left Ventricular Ejection Fraction (LVEF). We examined the distribution and prognostic value of BNP across BMI categories in acute decompensated heart failure (ADHF) patients with preserved vs. reduced LVEF. METHODS: We analyzed data from the Atherosclerosis Risk in Communities (ARIC) HF surveillance study which sampled and adjudicated ADHF hospitalizations in patients aged ≥55years from 4 US communities (2005-2009). We examined 5 BMI categories: underweight (<18.5kg/m2), normal weight (18.5-<25), overweight (25-<30), obese (30-<40) and morbidly obese (≥40) in HF with preserved LVEF (HFpEF) and reduced LVEF (HFrEF). The outcome was 1-year mortality from admission. We used ANCOVA to model log BNP and logistic regression for 1-year mortality, both adjusted for demographics and clinical characteristics. RESULTS: The cohort included 9820 weighted ADHF hospitalizations (58% HFrEF; 42% HFpEF). BNP levels were lower in HFpEF compared to HFrEF (p<0.001) and decreased as BMI increased within the LVEF groups (p<0.001). After adjustment for covariates, log10 BNP independently predicted 1-year mortality (adjusted OR 1.62 (95% CI 1.17-2.24)) with no significant interaction by BMI or LVEF groups. CONCLUSIONS: BNP levels correlated inversely with BMI, and were higher in HFrEF compared to HFpEF. Obese patients with HFpEF and ADHF had a significant proportion with BNP levels below clinically accepted thresholds. Nevertheless, BNP was a predictor of mortality in ADHF across groups of BMI in HFpEF and HFrEF.

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD.

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10-10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10-392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group.