Comparison of NITAG policies and working processes in selected developed countries

BACKGROUND: Vaccines are specific medicines characterized by two country-specific market access processes: (1) a recommendation by National Immunization Technical Advisory Group (NITAG), and (2) a funding policy decision. OBJECTIVES: The objective of this study was to compare and analyze NITAGs of 13 developed countries by describing vaccination committees' bodies and working processes. METHODS: Information about NITAGs bodies and working processes was searched from official sources from June 2011 to November 2012. Retrieved information was completed from relevant articles identified through a systematic literature review and by information provided by direct contact with NITAGs or parent organizations. An expert panel was also conducted to discuss, validate, and provide additional input on obtained results. RESULTS: While complete information, defined as 100%, was retrieved only for the UK, at least 80% of data was retrieved for 9 countries out of the 13 selected countries. Terms of references were identified in 7 countries, and the main mission for all NITAGs was to provide advice for National immunization programs. However, these terms of references did not fully encompass all the actual missions of the NITAGs. Decision analysis frameworks were identified for 10 out of the 13, and all NITAGs considered at least four criteria for decision-making: disease burden, efficacy/effectiveness, safety and cost-effectiveness. Advices were published by most NITAGs, but few NITAGs published meeting agendas and minutes. Only the United States had open meetings. CONCLUSIONS: This study supports previous findings about the disparities in NITAGs processes which could potentially explain the disparity in access to vaccinations and immunization programs across Europe. With NITAGs recommendations being used by policy decision makers for implementation and funding of vaccine programs, guidances should be well-informed and transparent to ensure National Immunization Programs' (NIP) credibility among the public and health care professionals

The “RCT augmentation”: a novel simulation method to add patient heterogeneity into phase III trials

Abstract Background Phase III randomized controlled trials (RCT) typically exclude certain patient subgroups, thereby potentially jeopardizing estimation of a drug’s effects when prescribed to wider populations and under routine care (“effectiveness”). Conversely, enrolling heterogeneous populations in RCTs can increase endpoint variability and compromise detection of a drug’s effect. We developed the “RCT augmentation” method to quantitatively support RCT design in the identification of exclusion criteria to relax to address both of these considerations. In the present manuscript, we describe the method and a case study in schizophrenia. Methods We applied typical RCT exclusion criteria in a real-world dataset (cohort) of schizophrenia patients to define the “RCT population” subgroup, and assessed the impact of re-including each of the following patient subgroups: (1) illness duration 1–3 years; (2) suicide attempt; (3) alcohol abuse; (4) substance abuse; and (5) private practice management. Predictive models were built using data from different “augmented RCT populations” (i.e., subgroups where patients with one or two of such characteristics were re-included) to estimate the absolute effectiveness of the two most prevalent antipsychotics against real-world results from the entire cohort. Concurrently, the impact on RCT results of relaxing exclusion criteria was evaluated by calculating the comparative efficacy of those two antipsychotics in virtual RCTs drawing on different “augmented RCT populations”. Results Data from the “RCT population”, which was defined with typical exclusion criteria, allowed for a prediction of effectiveness with a bias < 2% and mean squared error (MSE) = 5.8–6.8%. Compared to this typical RCT, RCTs using augmented populations provided improved effectiveness predictions (bias < 2%, MSE = 5.3–6.7%), while returning more variable comparative effects. The impact of augmentation depended on the exclusion criterion relaxed. Furthermore, half of the benefit of relaxing each criterion was gained from re-including the first 10–20% of patients with the corresponding real-world characteristic. Conclusions Simulating the inclusion of real-world subpopulations into an RCT before running it allows for quantification of the impact of each re-inclusion upon effect detection (statistical power) and generalizability of trial results, thereby explicating this trade-off and enabling a controlled increase in population heterogeneity in the RCT design

Replication of genetic associations as pseudoreplication due to shared genealogy

The genotypes of individuals in replicate genetic association studies have some level of correlation due to shared descent in the complete pedigree of all living humans. As a result of this genealogical sharing, replicate studies that search for genotype-phenotype associations using linkage disequilibrium between marker loci and disease-susceptibility loci can be considered as “pseudoreplicates” rather than true replicates. We examine the size of the pseudoreplication effect in association studies simulated from evolutionary models of the history of a population, evaluating the excess probability that both of a pair of studies detect a disease association compared to the probability expected under the assumption that the two studies are independent. Each of nine combinations of a demographic model and a penetrance model leads to a detectable pseudoreplication effect, suggesting that the degree of support that can be attributed to a replicated genetic association result is less than that which can be attributed to a replicated result in a context of true independence. Genet. Epidemiol. 33:479–487, 2009. © 2009 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63606/1/20400_ftp.pd

Impact of warming on phyto-bacterioplankton coupling and bacterial community composition in experimental mesocosms

Global warming is assumed to alter the trophic interactions and carbon flow patterns of aquatic food webs. The impact of temperature on phyto-bacterioplankton coupling and bacterial community composition (BCC) was the focus of the present study, in which an indoor mesocosm experiment with natural plankton communities from the western Baltic Sea was conducted. A 6°C increase in water temperature resulted, as predicted, in tighter coupling between the diatom-dominated phytoplankton and heterotrophic bacteria, accompanied by a strong increase in carbon flow into bacterioplankton during the phytoplankton bloom phase. Suppressed bacterial development at cold in situ temperatures probably reflected lowered bacterial production and grazing by protists, as the latter were less affected by low temperatures. BCC was strongly influenced by the phytoplankton bloom stage and to a lesser extent by temperature. Under both temperature regimes, Gammaproteobacteria clearly dominated during the phytoplankton peak, with Glaciecola sp. as the single most abundant taxon. However, warming induced the appearance of additional bacterial taxa belonging to Betaproteobacteria and Bacteroidetes. Our results show that warming during an early phytoplankton bloom causes a shift towards a more heterotrophic system, with the appearance of new bacterial taxa suggesting a potential for utilization of a broader substrate spectrum