Circulating fibrinogen is a prognostic and predictive biomarker in malignant pleural mesothelioma.

Background:To investigate the clinical utility of pretreatment plasma fibrinogen levels in malignant pleural mesothelioma (MPM) patients.Methods:A retrospective multicenter study was performed in histologically proven MPM patients. All fibrinogen levels were measured at the time of diagnosis and clinical data were retrospectively collected after approval of the corresponding ethics committees.Results:In total, 176 MPM patients (mean age: 63.5 years+/-10.4 years, 38 females and 138 males) were analysed. Most patients (n=154, 87.5%) had elevated (>/=390 mg dl-1) plasma fibrinogen levels. When patients were grouped by median fibrinogen, patients with low level (</=627 mg dl-1) had significantly longer overall survival (OS) (19.1 months, confidence interval (CI) 14.5-23.7 months) when compared with those with high level (OS 8.5; CI 6.2-10.7 months). In multivariate survival analyses, fibrinogen was found to be an independent prognostic factor (hazard ratio 1.81, CI 1.23-2.65). Most interestingly, fibrinogen (cutoff 75th percentile per 750 mg dl-1) proved to be a predictive biomarker indicating treatment benefit achieved by surgery within multimodality therapy (interaction term: P=0.034). Accordingly, only patients below the 75th percentile benefit from surgery within multimodality therapy (31.3 vs 5.3 months OS).Conclusions:Fibrinogen is a novel independent prognostic biomarker in MPM. Most importantly, fibrinogen predicted treatment benefit achieved by surgery within multimodality therapy.British Journal of Cancer advance online publication, 16 January 2014; doi:10.1038/bjc.2013.815 www.bjcancer.com

Estimating the burden of antimicrobial resistance: a systematic literature review.

Background: Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establish the alternative methodologies used in estimating AMR burden in order to appraise the current evidence base. Methods: MEDLINE, EMBASE, Scopus, EconLit, PubMed and grey literature were searched. English language studies evaluating the impact of AMR (from any microbe) on patient, payer/provider and economic burden published between January 2013 and December 2015 were included. Independent screening of title/abstracts followed by full texts was performed using pre-specified criteria. A study quality score (from zero to one) was derived using Newcastle-Ottawa and Philips checklists. Extracted study data were used to compare study method and resulting burden estimate, according to perspective. Monetary costs were converted into 2013 USD. Results: Out of 5187 unique retrievals, 214 studies were included. One hundred eighty-seven studies estimated patient health, 75 studies estimated payer/provider and 11 studies estimated economic burden. 64% of included studies were single centre. The majority of studies estimating patient or provider/payer burden used regression techniques. 48% of studies estimating mortality burden found a significant impact from resistance, excess healthcare system costs ranged from non-significance to $1 billion per year, whilst economic burden ranged from$21,832 per case to over $3 trillion in GDP loss. Median quality scores (interquartile range) for patient, payer/provider and economic burden studies were 0.67 (0.56-0.67), 0.56 (0.46-0.67) and 0.53 (0.44-0.60) respectively. Conclusions: This study highlights what methodological assumptions and biases can occur dependent on chosen outcome and perspective. Currently, there is considerable variability in burden estimates, which can lead in-turn to inaccurate intervention evaluations and poor policy/investment decisions. Future research should utilise the recommendations presented in this review. Trial registration: This systematic review is registered with PROSPERO (PROSPERO CRD42016037510)