Early termination of cardiovascular trials as a consequence of poor accrual: analysis of ClinicalTrials.gov 2006-2015

OBJECTIVES: To present a snapshot of experimental cardiovascular research with a focus on geographical and temporal patterns of early termination due to poor accrual. SETTING: The Aggregate Analysis of ClinicalTrials.gov (AACT) database, reflecting ClinicalTrials.gov as of 27 March 2016. DESIGN: The AACT database was searched for all cardiovascular clinical trials that started from January 2006 up to December 2015. RESULTS: Thirteen thousand and seven hundred twenty-nine cardiovascular trials were identified. Of these, 8900 (65%) were classified as closed studies. Globally, 11% of closed trials were terminated. This proportion varied from 9.6% to 14% for trials recruiting from Europe and Americas, respectively, with a slightly decreasing trend (p=0.02) over the study period. The most common reason for trials failing to complete was poor accrual (41%). Intercontinental trials exhibited lower figures of poor accrual as the reason for their early stopping, as compared with trials recruiting in a single continent (28% vs 44%, p=0.002). CONCLUSIONS: Poor accrual significantly challenges the successful completion of cardiovascular clinical trials. Findings are suggestive of a positive effect of globalisation of cardiovascular clinical research on the achievement of enrolment goals within a reasonable time frame

Comorbidity-adjusted relative survival in newly hospitalized heart failure patients: A population-based study

Background This study aims to identify comorbidities through various sources and assess their short-term impact on relative survival in a cohort of heart failure (HF) patients. Methods Newly hospitalized HF patients were identified from hospital discharge abstracts (HDA) of Lombardy Region, Italy, from 2008 to 2010. Charlson comorbidities were assessed using the HDA and supplemented with drug prescriptions and disease-specific exemptions. A Cox model was fit for the one-year relative survival from HF. Results The cohort consisted of 51,061 HF patients (53% women; median age 80\uc2\ua0years). After integrating information from all sources, the prevalence rates of diabetes, chronic pulmonary disease and renal disease were 27.6%, 26.2% and 14.2%, respectively. The prevalence of comorbidity increased to 78%. Survival in the HF cohort was worse with increasing number of comorbidities and was inferior to that in the reference population. Notably, the overall performance of the relative survival models was similar regardless of the strategy used to ascertain comorbidity. Conclusions Comorbidities cluster in hospitalized HF patients, and increasing comorbidity burden is associated with worse survival. Integration of a comprehensive search of electronic records to supplement HDA improves the prevalence estimates of comorbidities, although it does not improve discrimination of the risk prediction model

Handling missing continuous outcome data in a Bayesian network meta-analysis

Background: A Bayesian network meta-analysis (NMA) model is a statistical method aimed at estimating the relative effects of multiple interventions against the same disease. The method has recently gained prominence, leading to the synthesis of the evidence regarding rank probabilities for each treatment. In several cases, an NMA is performed excluding incomplete data of studies retrieved through a systematic review, resulting in a loss of precision and power.  Methods: There are several methods for handling missing or incomplete data in an NMA framework, especially for continuous outcomes. In certain cases, only baseline and follow-up measurements are available; in this framework, to obtain data regarding mean changes, it is necessary to consider the pre-post study correlation. In this context, in a Bayesian setting, several authors suggest imputation strategies for pre-post correlation. In other cases, a variability measure associated with a mean change score might be unavailable. Different imputation methods have been suggested, such as those based on maximum standard deviation imputation. The purpose of this study is to verify the robustness of Bayesian NMA models concerning different imputation strategies through simulations.  Results: Simulation results show that the bias is notably small for every scenario, confirming that rankings provided by models are robust concerning different imputation methods in several heterogeneity-correlation settings.  Conclusions: This NMA method seems to be more robust to missing data imputation when data reported in different studies are generated in a low-heterogeneity scenario. The NMA method seems to be more robust to missing value imputation if the expectation of the prior distribution, defined on the heterogeneity parameter, approaches the true value of the variability across studies.&nbsp

Nutritional behavior and attitudes in food allergic children and their mothers

BACKGROUND: Avoidance of food allergens requires adapting dietetic habits, changing nutritional approach. A restriction of food choice can result in a monotonous diet and impact social life. This study investigated the impact of food allergy on nutritional behavior and attitudes of patients and their families. METHODS: A survey involving mothers of food allergic children aged 0–16 years was carried out. We primarily studied the variables related to the child (age, gender, clinical history, food and social events attitudes). In addition, Spielberg Trait-Anxiety Inventory (STAI-T) test was applied to the mothers. We assessed separately the associations between characteristics of child-mother pairs and diet monotony, and attendance to social events, by means of proportional odds regression models. RESULTS: Nearly 10% of the 124 participants completely banned allergenic foods at home and 15.3% consumed their meals separately. More than one fourth attended parties rarely or never. Most of the participants reported a “monotonous diet”. Model results suggested significant associations between child age (p = 0.05), mother age (p = 0.05), number of excluded foods (p = 0.003) and monotony of the diet. The attendance of social events was inversely associated with the number of excluded foods (p = 0.04) and the mother’s STAI-T T-score (p = 0.04). CONCLUSIONS: The results highlighted the impact of food allergy in reducing interest about food and influencing patients’ approach to social life. It is important to support families in managing allergens avoidance

Comparative Effectiveness of DPP-4 Inhibitors Versus Sulfonylurea for the Treatment of Type 2 Diabetes in Routine Clinical Practice: A Retrospective Multicenter Real-World Study

Introduction: DPP-4 inhibitors (DPP4i) and sulfonylureas are popular second-line therapies for type 2 diabetes (T2D), but there is a paucity of real-world studies comparing their effectiveness in routine clinical practice. Methods: This was a multicenter retrospective study on diabetes outpatient clinics comparing the effectiveness of DPP4i versus gliclazide extended release. The primary endpoint was change from baseline in HbA1c. Secondary endpoints were changes in fasting plasma glucose, body weight, and systolic blood pressure. Automated software extracted data from the same clinical electronic chart system at all centers. Propensity score matching (PSM) was used to generate comparable cohorts to perform outcome analysis. Results: We included data on 2410 patients starting DPP4i and 1590 patients starting gliclazide (mainly 30–60 mg/day). At baseline, the two groups differed in disease duration, body weight, blood pressure, HbA1c, fasting glucose, HDL cholesterol, triglycerides, liver enzymes, eGFR, prevalence of microangiopathy, and use of metformin. Among DPP4i molecules, no difference in glycemic effectiveness was detected. In matched cohorts (n = 1316/group), patients starting DPP4i, as compared with patients starting gliclazide, experienced greater reductions in HbA1c (− 0.6% versus − 0.4%; p < 0.001), fasting glucose (− 14.1 mg/dl versus − 8.8 mg/dl; p = 0.007), and body weight (− 0.4 kg versus − 0.1 kg; p = 0.006) after an average 6 months follow-up. DPP4i improved glucose control more than gliclazide, especially in patients who had failed with other glucose-lowering medications or were on basal insulin. Conclusions: This large retrospective real-world study shows that, in routine clinical practice, starting a DPP4i allows better glycemic control than starting low-dose gliclazide. Funding: The Italian Diabetes Society, with external support from AstraZeneca