BackgroundDespite a large increase in Clostridium difficile infection (CDI) severity, morbidity and mortality in the US since the early 2000s, CDI burden estimates have had limited generalizability and comparability due to widely varying clinical settings, populations, or study designs.MethodsA decision-analytic model incorporating key input parameters important in CDI epidemiology was developed to estimate the annual number of initial and recurrent CDI cases, attributable and all-cause deaths, economic burden in the general population, and specific number of high-risk patients in different healthcare settings and the community in the US. Economic burden was calculated adopting a societal perspective using a bottom-up approach that identified healthcare resources consumed in the management of CDI.ResultsAnnually, a total of 606,058 (439,237 initial and 166,821 recurrent) episodes of CDI were predicted in 2014: 34.3 % arose from community exposure. Over 44,500 CDI-attributable deaths in 2014 were estimated to occur. High-risk susceptible individuals representing 5 % of the total hospital population accounted for 23 % of hospitalized CDI patients. The economic cost of CDI was $5.4 billion ($4.7 billion (86.7 %) in healthcare settings; $725 million (13.3 %) in the community), mostly due to hospitalization.ConclusionsA modeling framework provides more comprehensive and detailed national-level estimates of CDI cases, recurrences, deaths and cost in different patient groups than currently available from separate individual studies. As new treatments for CDI are developed, this model can provide reliable estimates to better focus healthcare resources to those specific age-groups, risk-groups, and care settings in the US where they are most needed. (Trial Identifier ClinicaTrials.gov: NCT01241552)Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-1610-3) contains supplementary material, which is available to authorized users.

ObjectiveThe aim of this study was to assess the cost effectiveness of silicone and alginate impressions for complete dentures.MethodsCost effectiveness analyses were undertaken alongside a UK single centre, double blind, controlled, crossover clinical trial. Taking the perspective of the healthcare sector, effectiveness is measured using the EuroQol (EQ-5D-3L) which provides a single index value for health status that may be combined with time to produce quality adjusted life years (QALYs); and Oral Health Impact Profile (OHIP-EDENT). Incremental cost effectiveness ratios are presented representing the additional cost per one unit gained.ResultsMean cost was higher in the silicone impression group (£388.57 vs. £363.18). Negligible between-group differences were observed in QALY gains; the silicone group had greater mean OHIP-EDENT gains. The additional cost using silicone was £3.41 per change of one point in the OHIP-EDENT.ConclusionsThe silicone group was more costly, driven by the cost of materials. Changes in the EQ-5D and QALY gains over time and between arms were not statistically significant. Change in OHIP-EDENT score showed greater improvement in the silicone group and the difference between arms was statistically significant. Given negligible QALY gains and low level of resource use, results must be treated with caution. It is difficult to make robust claims about the comparative cost-effectiveness.Clinical significanceSilicone impressions for complete dentures improve patients’ quality of life (OHIP-EDENT score). The extra cost of silicone impressions is £30 per patient. Dentists, patients and health care funders need to consider the clinical and financial value of silicone impressions. Different patients, different dentists, different health funders will have individual perceptions and judgements.ISRCTN01528038.NIHR-RfPB grant PB-PG-0408-16300.

This article forms part of a project for which the author (TPH) won the Senior Clinical Unilever Hatton Award of the International Assocation for Dental Research, Capetown, South Africa, June 2014.

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Mean EQ-5D utility weights can be estimated from the EORTC QLQ-C30/QLQ-MY20 for use in CEAs. Frequentist and Bayesian methods produced effectively identical models. However, the Bayesian models provide distributions describing the uncertainty surrounding the estimated utility values and are thus more suited informing analyses for probabilistic CEAs.

Purpose Glaucoma is an important disease, the impacts of which on vision have been shown to have implications for patients' health-related quality of life (HRQoL). The primary aim of this study is to estimate a mapping algorithm to predict EQ-5D and SF-6D utility values based on the vision-specific measure, the 25-item Visual Functioning Questionnaire (VFQ-25), as well as the clinical measures of visual function, that is, integrated visual field, visual acuity, and contrast sensitivity. Methods Ordinary least squares (OLS), Tobit, and censored least absolute deviations were compared using data taken from the Moorfields Eye Hospital in London, to assess mapping functions to predict the EQ-5D and SF-6D from the VFQ-25, and tests of visual function. These models were compared using root mean square error (RMSE), R 2 , and mean absolute error (MAE). Results OLS was the best-performing model of the three compared, as this produced the lowest RMSE and MAE, and the highest R 2 . Conclusions The models provided initial algorithms to convert the VFQ-25 to the EQ-5D and SF-6D. Further analysis would be needed to validate the models or algorithms.