The Case for Access to Data Monitoring Committee Charters.

AbstractClinical trials investigating novel or high-risk interventions often use data monitoring committees (DMCs) to ensure that the participants' best interests are safeguarded. The typical DMC charter describes procedures by which the DMC operates, including important details concerning organizational structure, membership, meeting frequency, statistical monitoring guidelines, and contents of DMC reports for interim review. These charters, however, are not routinely publicly available; in some cases, their access could be important to the interpretation of trial results. We recommend including DMC charters for such trials in ClinicalTrials.gov at the time of trial completion; trial protocols, informed consent documents, and statistical analysis plans are already available in this repository.

New statistical approach shows that hydroxy-methionine is noninferior to DL-Methionine in 35-day-old broiler chickens.

The efficacy of a new molecule is assessed in the pharmaceutical industry through noninferiority tests to establish that it is not unacceptably less efficient than the reference. This method was proposed to compare DL-Methionine (DL-Met) as reference and DL-Hydroxy-Methionine (OH-Met) as alternative, in broiler chickens. The research hypothesized that OH-Met is inferior to DL-Met. Noninferiority margins were determined using 7 datasets comparing broiler growth response between a sulfur amino acid deficient and adequate diet from 0 to 35 d. The datasets were selected from the literature and internal records of the company. The noninferiority margins were then fixed as the largest loss of effect (inferiority) acceptable when OH-Met is compared to DL-Met. Three corn/soybean meal-based experimental treatments were offered to 4,200 chicks (35 replicates of 40 birds). Birds received from 0 to 35 d 1) a negative control diet deficient in Met and Cys; the negative control treatment supplemented on equimolar basis with 2) DL-Met or 3) OH-Met in amounts allowing to reach Aviagen Met+Cys recommendations. The three treatments were adequate in all other nutrients. Growth performance, which was analysed with one-way ANOVA, showed no significant difference between DL-Met and OH-Met. The supplemented treatments improved (P < 0.0001) the performance parameters compared to the negative control. The lower limits of the confidence intervals of the difference between means for the feed intake [-1.34; 1.41], body weight [-57.3; 9.8] and daily growth [-1.64; 0.28], did not exceed the noninferiority margins. This demonstrates that OH-Met was non-inferior to DL-Met.

Clinical development strategy for a candidate group A streptococcal vaccine.

GroupA streptococci (GAS) cause a wide spectrum of diseases ranging from benign pharyngitis and skin infections to severe invasive disease and the immune sequelae rheumatic fever and rheumatic heart disease. Pharyngitis, one of the most frequent diseases caused by GAS, is highly prevalent in school-age children in temperate climates and a major cause of antibiotic use. An efficacious vaccine would reduce disease burden associated with pharyngitis and the need of care for sick children. Importantly, GAS pharyngitis is recognised as the main precursor for acute rheumatic fever so a vaccine that is efficacious against GAS pharyngitis should also prevent acute rheumatic fever and rheumatic heart disease. It may also prevent post-streptococcal glomerulonephritis and invasive disease since GAS pharyngitis is one of the precursors for these clinical syndromes. There has been no clearly articulated pathway for clinical trial design leading to GAS vaccine registration. This review outlines a clinical development strategy detailing the phases of development required for registration of a candidate GAS vaccine for GAS pharyngitis initially, followed by impetigo and associated sequelae. The major advantages of a strategy first focused on GAS pharyngitis is an early proof of principle, that can be followed by studies for other clinical syndromes. The end goal being the availability of a preventive tool for the most prevalent GAS-associated diseases globally.

The impact of kidney function on outcomes following high risk myocardial infarction: findings from 27 610 patients.

AIMS: Renal dysfunction is associated with poor cardiovascular outcome. We investigated the relationship of kidney function and long-term cardiovascular outcomes in patients with high risk myocardial infarction. METHODS AND RESULTS: We studied 27 610 patients from four randomized trials of acute myocardial infarction complicated by heart failure and/or LV dysfunction (LVEF ≤40%). Two trials excluded patients with serum creatinine ≥2.5 mg/dL. Patients were grouped by estimated glomerular filtration rate (eGFR) using the four-component Modification of Diet in Renal Disease equation. We used adjusted Cox proportional hazard models to compare mortality and composite cardiovascular events among eGFR groups. Median follow-up was 23 months. The eGFR was approximately normally distributed, with a mean ± SD of 69.1 ± 20.2 mL/min/1.73 m(2) . Co-morbidities were more prevalent with lower eGFR. The risk of death or composite outcome of cardiovascular death, myocardial infarction, stroke, or heart failure hospitalization increased with declining eGFR. Below 75 mL/min/1.73 m(2) , each 10 unit reduction of eGFR was associated with an adjusted hazard ratio for death of 1.13 (95% confidence interval, 1.11-1.15) and composite cardiovascular outcome of 1.09 (95% confidence interval, 1.08-1.10). Older patients (≥75 years) with low LVEF (<30%) had a higher incidence of mortality and adverse cardiovascular events across eGFR categories. CONCLUSIONS: Reduced eGFR is strongly and independently associated with poor cardiovascular outcome following high risk myocardial infarction. In these patients, the combination of older age and poor LV systolic function is associated with increased risk of adverse events.

Some thoughts on sample size: a Bayesian-frequentist hybrid approach.

BACKGROUND: Traditional calculations of sample size do not formally incorporate uncertainty about the likely effect size. Use of a normal prior to express that uncertainty, as recently recommended, can lead to power that does not approach 1 as the sample size approaches infinity. PURPOSE: To provide approaches for calculating sample size and power that formally incorporate uncertainty about effect size. The relevant formulas should ensure that power approaches one as sample size increases indefinitely and should be easy to calculate. METHODS: We examine normal, truncated normal, and gamma priors for effect size computationally and demonstrate analytically an approach to approximating the power for a truncated normal prior. We also propose a simple compromise method that requires a moderately larger sample size than the one derived from the fixed effect method. RESULTS: Use of a realistic prior distribution instead of a fixed treatment effect is likely to increase the sample size required for a Phase 3 trial. The standard fixed effect method for moving from estimates of effect size obtained in a Phase 2 trial to the sample size of a Phase 3 trial ignores the variability inherent in the estimate from Phase 2. Truncated normal priors appear to require unrealistically large sample sizes while gamma priors appear to place too much probability on large effect sizes and therefore produce unrealistically high power. LIMITATIONS: The article deals with a few examples and a limited range of parameters. It does not deal explicitly with binary or time-to-failure data. CONCLUSIONS: Use of the standard fixed approach to sample size calculation often yields a sample size leading to lower power than desired. Other natural parametric priors lead either to unacceptably large sample sizes or to unrealistically high power. We recommend an approach that is a compromise between assuming a fixed effect size and assigning a normal prior to the effect size.

Through the looking glass: understanding non-inferiority.

Non-inferiority trials test whether a new product is not unacceptably worse than a product already in use. This paper introduces concepts related to non-inferiority, and discusses the regulatory views of both the European Medicines Agency and the United States Food and Drug Administration.

Glucose and insulin responses to dietary chromium supplements: a meta-analysis.

BACKGROUND: Several authors, mostly on the basis of nonrandomized studies, have suggested dietary trivalent chromium supplementation as an attractive option for the management of type 2 diabetes and for glycemic control in persons at high risk of type 2 diabetes. OBJECTIVE: The study aimed to determine the effect of chromium on glucose and insulin responses in healthy subjects and in individuals with glucose intolerance or type 2 diabetes. DESIGN: The study design was a systematic review and meta-analysis of randomized clinical trials (RCTs). RESULTS: The authors identified 20 reports of RCTs assessing the effect of chromium on glucose, insulin, or glycated hemoglobin (Hb A(1c)). This review summarizes data on 618 participants from the 15 trials that reported adequate data: 193 participants had type 2 diabetes and 425 were in good health or had impaired glucose tolerance. The meta-analysis showed no association between chromium and glucose or insulin concentrations among nondiabetic subjects. A study of 155 diabetic subjects in China showed that chromium reduced glucose and insulin concentrations; the combined data from the 38 diabetic subjects in the other studies did not. Three trials reported data on Hb A(1c): one study each of persons with type 2 diabetes, persons with impaired glucose tolerance, and healthy subjects. The study of diabetic subjects in China was the only one to report that chromium significantly reduced Hb A(1c). CONCLUSIONS: Data from RCTs show no effect of chromium on glucose or insulin concentrations in nondiabetic subjects. The data for persons with diabetes are inconclusive. RCTs in well-characterized, at-risk populations are necessary to determine the effects of chromium on glucose, insulin, and Hb A(1c).