Systematic overview of hepatitis C infection in the Middle East and North Africa

AIM To assess the quality of and to critically synthesize the available data on hepatitis C infections in the Middle East and North Africa(MENA) region to map evidence gaps.METHODS We conducted an overview of systematic reviews(SRs) following an a priori developed protocol(CRD42017076736). Our overview followed the preferred reporting items for systematic reviews and metaanalyses guidelines for reporting SRs and abstracts and did not receive any funding. Two independent reviewers systematically searched MEDLINE and conducted a multistage screening of the identified articles. Out of 5758 identified articles, 37 SRs of hepatitis C virus(HCV) infection in populations living in 20 countries in the MENA region published between 2008 and 2016 were included in our overview. The nine primary outcomes of interest were HCV antibody(anti-) prevalences and incidences in different at-risk populations; the HCV viremic(RNA positive) rate in HCV-positive individuals; HCV viremic prevalence in the general population(GP); the prevalence of HCV co-infection with the hepatitis B virus, human immunodeficiency virus, or schistosomiasis; the HCV genotype/subtype distribution; and the risk factors for HCV transmission. The conflicts of interest declared by the authors of the SRs were also extracted. Good quality outcomes reported by the SRs were defined as having the population, outcome, study time and setting defined as recommended by the PICOTS framework and a sample size 100.RESULTS We included SRs reporting HCV outcomes with different levels of quality and precision. A substantial proportion of them synthesized data from mixed populations at differing levels of risk for acquiring HCV or at different HCV infection stages(recent and prior HCV transmissions). They also synthesized the data over long periods of time(e.g., two decades). Anti-HCV prevalence in the GP varied widely in the MENA region from 0.1%(study dates not reported) in the United Arab Emirates to 2.1%-13.5%(2003-2006) in Pakistan and 14.7%(2008) in Egypt. Data were not identified for Bahrain, Jordan, or Palestine. Good quality estimates of anti-HCV prevalence in the GP were reported for Algeria, Djibouti, Egypt, Iraq, Morocco, Pakistan, Syria, Sudan, Tunisia, and Yemen. Anti-HCV incidence estimates in the GP were reported only for Egypt(0.8-6.8 per 1000 person-year, 1997-2003). In Egypt, Morocco, and the United Arab Emirates, viremic rates in anti-HCV-positive individuals from the GP were approximately 70%. In the GP, the viremic prevalence varied from 0.7%(2011) in Saudi Arabia to 5.8%(2007-2008) in Pakistan and 10.0%(2008) in Egypt. Anti-HCV prevalence was lower in blood donors than in the GP, ranging from 0.2%(1992-1993) in Algeria to 1.7%(2005) in Yemen. The reporting quality of the outcomes in blood donors was good in the MENA countries, except in Qatar where no time framework was reported for the outcome. Some countries had anti-HCV prevalence estimates for children, transfused patients, contacts of HCV-infected patients, prisoners, sex workers, and men who have sex with men.CONCLUSION A substantial proportion of the reported outcomes may not help policymakers to develop micro-elimination strategies with precise HCV infection prevention and treatment programs in the region, as nowcasting HCV epidemiology using these data is potentially difficult. In addition to providing accurate information on HCV epidemiology, outcomes should also demonstrate practical and clinical significance and relevance. Based on the available data, most countries in the region have low to moderate anti-HCV prevalence. To achieve HCV elimination by 2030, up-to-date, good quality data on HCV epidemiology are required for the GP and key populations such as people who inject drugs and men who have sex with men.     

Fear Extinction Retention: Is It What We Think It Is?

There has been an explosion of research on fear extinction in humans in the past 2 decades. This has not only generated major insights, but also brought a new goal into focus: how to maintain extinction memory over time (i.e., extinction retention). We argue that there are still important conceptual and procedural challenges in human fear extinction research that hamper advancement in the field. We use extinction retention and the extinction retention index to exemplarily illustrate these challenges. Our systematic literature search identified 16 different operationalizations of the extinction retention index. Correlation coefficients among these different operationalizations as well as among measures of fear/anxiety show a wide range of variability in four independent datasets, with similar findings across datasets. Our results suggest that there is an urgent need for standardization in the field. We discuss the conceptual and empirical implications of these results and provide specific recommendations for future work.     

Meta-research in pharmacy: Time for a look in the mirror

The volume of the biomedical literature continues to expand at a substantial rate. The research literature surrounding pharmaceutical services is no different. Due in part to events in the recent past, researchers, consumers, funders, and policymakers have raised concerns about the credibility, transparency, and potential waste in the global research enterprise. Meta-research, or research on research, provides a way to examine the efficiency, quality, and potential bias in the overall research ecosystem. The field of meta-research is a relatively new but rapidly growing field that has seen many applications in biomedical research. Applications in pharmacy research, however, are still developing. The goals of this commentary are to introduce pharmacy researchers to the concept of meta-research, discuss several examples of meta-research in pharmacy, and motivate the importance of sustained meta-research efforts in pharmacy.     

A Bayesian analysis of non-significant rehabilitation findings: Evaluating the evidence in favour of truly absent treatment effects

BackgroundRelying solely on null hypothesis significance testing (NHST) to investigate rehabilitation interventions may result in researchers erroneously concluding the absence of a treatment effect.ObjectiveWe aimed to distinguish between truly null treatment effects and data that are insensitive to detecting treatment effects by calculating Bayes factors (BF₀₁s) for non-significant findings in the rehabilitation literature. Additionally, to examine associations between BF₀₁, sample size, and observed P-values.MethodWe searched the Cochrane Database of Systematic Reviews for meta-analyses with “rehabilitation” as a keyword that clearly evaluated a rehabilitation intervention. We extracted means, standard deviations, and sample sizes for treatment and comparison groups for individual findings within 175 meta-analyses. Two independent investigators classified the interventions into 4 categories using the Rehabilitation Treatment Specification System. We calculated t-statistics and associated P-values for each finding in order to extract non-significant results (P > 0.05). We calculated BF₀₁s for 5790 non-significant results and classified BF₀₁s based on the strength of evidence in favour of the null hypothesis (i.e., anecdotal, moderate, and strong) across and within intervention types. We examined correlations between BF₀₁, sample size, and P-values across and within intervention types.ResultsAcross all intervention types, most (71.9%) findings were deemed anecdotal, and this pattern remained within distinct intervention types (58.4–76.0%). Larger sample sizes tended to be associated with greater strength in favour of the null hypothesis, both across and within intervention types. Larger P-values were not associated with greater strength in favour of the null hypothesis; this finding was present both across and within intervention types.ConclusionOur findings indicate that most non-significant rehabilitation findings are unable to distinguish between the true absence of a treatment effect and data that are merely insensitive to detecting a treatment effect. Findings also suggest that rehabilitation researchers may improve the strength of their statistical conclusions by increasing sample size and that Bayes factors may offer unique benefits relative to P-values.