Genetic Predictors of Response to Serotonergic and Noradrenergic Antidepressants in Major Depressive Disorder: A Genome-Wide Analysis of Individual-Level Data and a Meta-Analysis

Background

It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way.

Methods and Findings

The NEWMEDS consortium, an academia–industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10⁻⁸). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10⁻⁸) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D.

Conclusions

No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see later in the article for the Editors'' Summary     

Comparative Efficacy and Acceptability of Antidepressants in Parkinson's Disease: A Network Meta-Analysis

Background

Depression is a common non-motor symptom in patients with Parkinson''s disease (PD). There are many kinds of antidepressants being used, such as tricyclic antidepressants (TCAs), selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and Dopamine agonists which are suggested as alternative antidepressants for the treatment of depression in PD. Which one should we choose first? Literatures have shown inconsistent results.

Methods

We conducted a network meta-analysis of randomized controlled trials to compare the efficacy and acceptability of therapeutic methods for the treatment of depression in Parkinson''s disease.

Results

We used the odds ratios (OR) as effect size firstly and the results indicated no statistical significance between each compared intervention. Then we used the logarithm of the individual odds ratios as effect size. With efficacy of TCAs as the standard of comparison, the degree of incoherence (a measure of how closely the entire network fits together) was small (ω =  4.824827e-05). The logor were: SSRIs −0.69 (95% CI −1.28– −0.10); Pramipexole −0.73 (−1.71– −0.26); Pergolide −1.97 (−3.67– 0.27); SNRIs −0.86 (−1.86– 0.15); Placebo −1.24 (−1.99– −0.50). With Placebo as the standard of comparison, the logor were: TCAs 1.24 (0.50– 1.99); SSRIs 0.55 (−0.03– 1.13); Pramipexole 0.51 (−0.12– 1.15); Pergolide −0.73 (−2.25– 0.80); SNRIs 0.38 (−0.42– 1.19); TCAs, pramipexole, pergolide and SNRIs showed better profile of acceptability, leading to significant fewer discontinuations than that of SSRIs.

Conclusions

There is insufficient evidence to support antidepressant efficacy for SSRIs, pramipexole, pergolide and SNRIs. TCAs might be the best choice when starting antidepressant treatment in patients of Parkinson''s disease because it has the most favorable balance between benefits and acceptability, followed by pramipexole and SNRIs, SSRIs might be the last choice.     

Addressing Dichotomous Data for Participants Excluded from Trial Analysis: A Guide for Systematic Reviewers

Introduction

Systematic reviewer authors intending to include all randomized participants in their meta-analyses need to make assumptions about the outcomes of participants with missing data.

Objective

The objective of this paper is to provide systematic reviewer authors with a relatively simple guidance for addressing dichotomous data for participants excluded from analyses of randomized trials.

Methods

This guide is based on a review of the Cochrane handbook and published methodological research. The guide deals with participants excluded from the analysis who were considered ‘non-adherent to the protocol’ but for whom data are available, and participants with missing data.

Results

Systematic reviewer authors should include data from ‘non-adherent’ participants excluded from the primary study authors'' analysis but for whom data are available. For missing, unavailable participant data, authors may conduct a complete case analysis (excluding those with missing data) as the primary analysis. Alternatively, they may conduct a primary analysis that makes plausible assumptions about the outcomes of participants with missing data. When the primary analysis suggests important benefit, sensitivity meta-analyses using relatively extreme assumptions that may vary in plausibility can inform the extent to which risk of bias impacts the confidence in the results of the primary analysis. The more plausible assumptions draw on the outcome event rates within the trial or in all trials included in the meta-analysis. The proposed guide does not take into account the uncertainty associated with assumed events.

Conclusions

This guide proposes methods for handling participants excluded from analyses of randomized trials. These methods can help in establishing the extent to which risk of bias impacts meta-analysis results.     

Alcohol Consumption and the Neoplastic Progression in Barrett's Esophagus: A Systematic Review and Meta-Analysis

Purpose

In the developed countries, the incidence of esophageal adenocarcinoma (EAC) is increasing over recent decades. The purpose of this meta-analysis was to arrive at quantitative conclusions about the contribution of alcohol intakes and the progression of Barrett''s esophagus.

Methods

A comprehensive, systematic bibliographic search of medical literature published up to Oct 2013 was conducted to identify relevant studies. A meta-analysis was conducted for alcohol consumption on the Barrett''s esophagus progression.

Results

A total of 882 cases in 6,867 individuals from 14 observational studies were indemnified in this meta-analysis. The result of this current meta-analysis, including 10 case-control and 4 cohort studies, indicated that alcohol consumption was not associated with the neoplastic progression in Barrett''s esophagus (RR, 1.17; 95% CI, 0.93–1.48). When stratified by the study designs, no significant association was detected in either high vs low group or ever vs never group.

Conclusions

Alcohol drinking is not associated with risk of neoplastic progression in Barrett''s esophagus. Further well designed studies are needed in this area.     

Meta-analyses of adverse effects data derived from randomised controlled trials as compared to observational studies: methodological overview

Background

There is considerable debate as to the relative merits of using randomised controlled trial (RCT) data as opposed to observational data in systematic reviews of adverse effects. This meta-analysis of meta-analyses aimed to assess the level of agreement or disagreement in the estimates of harm derived from meta-analysis of RCTs as compared to meta-analysis of observational studies.

Methods and Findings

Searches were carried out in ten databases in addition to reference checking, contacting experts, citation searches, and hand-searching key journals, conference proceedings, and Web sites. Studies were included where a pooled relative measure of an adverse effect (odds ratio or risk ratio) from RCTs could be directly compared, using the ratio of odds ratios, with the pooled estimate for the same adverse effect arising from observational studies. Nineteen studies, yielding 58 meta-analyses, were identified for inclusion. The pooled ratio of odds ratios of RCTs compared to observational studies was estimated to be 1.03 (95% confidence interval 0.93–1.15). There was less discrepancy with larger studies. The symmetric funnel plot suggests that there is no consistent difference between risk estimates from meta-analysis of RCT data and those from meta-analysis of observational studies. In almost all instances, the estimates of harm from meta-analyses of the different study designs had 95% confidence intervals that overlapped (54/58, 93%). In terms of statistical significance, in nearly two-thirds (37/58, 64%), the results agreed (both studies showing a significant increase or significant decrease or both showing no significant difference). In only one meta-analysis about one adverse effect was there opposing statistical significance.

Conclusions

Empirical evidence from this overview indicates that there is no difference on average in the risk estimate of adverse effects of an intervention derived from meta-analyses of RCTs and meta-analyses of observational studies. This suggests that systematic reviews of adverse effects should not be restricted to specific study types. Please see later in the article for the Editors'' Summary     

Do Interventions Designed to Support Shared Decision-Making Reduce Health Inequalities? A Systematic Review and Meta-Analysis

Background

Increasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities.

Objective

To evaluate the impact of SDM interventions on disadvantaged groups and health inequalities.

Design

Systematic review and meta-analysis of randomised controlled trials and observational studies.

Data Sources

CINAHL, the Cochrane Register of Controlled Trials, the Cochrane Database of Systematic Reviews, EMBASE, HMIC, MEDLINE, the NHS Economic Evaluation Database, Open SIGLE, PsycINFO and Web of Knowledge were searched from inception until June 2012.

Study Eligibility Criteria

We included all studies, without language restriction, that met the following two criteria: (1) assess the effect of shared decision-making interventions on disadvantaged groups and/or health inequalities, (2) include at least 50% of people from disadvantaged groups, except if a separate analysis was conducted for this group.

Results

We included 19 studies and pooled 10 in a meta-analysis. The meta-analyses showed a moderate positive effect of shared decision-making interventions on disadvantaged patients. The narrative synthesis suggested that, overall, SDM interventions increased knowledge, informed choice, participation in decision-making, decision self-efficacy, preference for collaborative decision making and reduced decisional conflict among disadvantaged patients. Further, 7 out of 19 studies compared the intervention''s effect between high and low literacy groups. Overall, SDM interventions seemed to benefit disadvantaged groups (e.g. lower literacy) more than those with higher literacy, education and socioeconomic status. Interventions that were tailored to disadvantaged groups'' needs appeared most effective.

Conclusion

Results indicate that shared decision-making interventions significantly improve outcomes for disadvantaged patients. According to the narrative synthesis, SDM interventions may be more beneficial to disadvantaged groups than higher literacy/socioeconomic status patients. However, given the small sample sizes and variety in the intervention types, study design and quality, those findings should be interpreted with caution.     

Most antidepressant use in primary care is justified; results of the Netherlands Study of Depression and Anxiety

Background

Depression is a common illness, often treated in primary care. Many studies have reported undertreatment with antidepressants in primary care. Recently, some studies also reported overtreatment with antidepressants. The present study was designed to assess whether treatment with antidepressants in primary care is in accordance with current guidelines, with a special focus on overtreatment.

Methodology

We used baseline data of primary care respondents from the Netherlands Study of Depression and Anxiety (NESDA) (n = 1610). Seventy-nine patients with treatment in secondary care were excluded. We assessed justification for treatment with antidepressant according to the Dutch primary care guidelines for depression and for anxiety disorders. Use of antidepressants was based on drug-container inspection or, if unavailable, on self-report. Results were recalculated to the original population of primary care patients from which the participants in NESDA were selected (n = 10,677).

Principal Findings

Of 1531 included primary care patients, 199 (13%) used an antidepressant, of whom 188 (94.5%) (possibly) justified. After recalculating these numbers to the original population (n = 10,677), we found 908 (95% CI 823 to 994) antidepressant users. Forty-nine (95% CI 20 to 78) of them (5.4%) had no current justification for an antidepressant, but 27 of them (54.5%) had a justified reason for an antidepressant at some earlier point in their life.

Conclusions

We found that overtreatment with antidepressants in primary care is not a frequent problem. Too long continuation of treatment seems to explain the largest proportion of overtreatment as opposed to inappropriate initiation of treatment.     

Meta-Analyses of the 5-HTTLPR Polymorphisms and Post-Traumatic Stress Disorder

Objective

To conduct a meta-analysis of all published genetic association studies of 5-HTTLPR polymorphisms performed in PTSD cases

Methods Data Sources

Potential studies were identified through PubMed/MEDLINE, EMBASE, Web of Science databases (Web of Knowledge, WoK), PsychINFO, PsychArticles and HuGeNet (Human Genome Epidemiology Network) up until December 2011. Study Selection: Published observational studies reporting genotype or allele frequencies of this genetic factor in PTSD cases and in non-PTSD controls were all considered eligible for inclusion in this systematic review. Data Extraction: Two reviewers selected studies for possible inclusion and extracted data independently following a standardized protocol. Statistical analysis: A biallelic and a triallelic meta-analysis, including the total S and S'' frequencies, the dominant (S+/LL and S''+/L''L'') and the recessive model (SS/L+ and S''S''/L''+), was performed with a random-effect model to calculate the pooled OR and its corresponding 95% CI. Forest plots and Cochran''s Q-Statistic and I² index were calculated to check for heterogeneity. Subgroup analyses and meta-regression were carried out to analyze potential moderators. Publication bias and quality of reporting were also analyzed.

Results

13 studies met our inclusion criteria, providing a total sample of 1874 patients with PTSD and 7785 controls in the biallelic meta-analyses and 627 and 3524, respectively, in the triallelic. None of the meta-analyses showed evidence of an association between 5-HTTLPR and PTSD but several characteristics (exposure to the same principal stressor for PTSD cases and controls, adjustment for potential confounding variables, blind assessment, study design, type of PTSD, ethnic distribution and Total Quality Score) influenced the results in subgroup analyses and meta-regression. There was no evidence of potential publication bias.

Conclusions

Current evidence does not support a direct effect of 5-HTTLPR polymorphisms on PTSD. Further analyses of gene-environment interactions, epigenetic modulation and new studies with large samples and/or meta-analyses are required.     

Contribution of Polymorphisms in IKZF1 Gene to Childhood Acute Leukemia: A Meta-Analysis of 33 Case-Control Studies

Objective

Two common polymorphisms in the IKZF1 gene (rs4132601 and rs11978267 variants) have been reported to be associated with childhood acute leukemia (AL) risk, however the results were inconsistent. Here, we conducted a meta-analysis to generate large-scale evidence on whether IKZF1 variants are risk factors for childhood AL.

Methods

The PubMed, Embase, EBSCO, and Web of Science were searched up to June 2, 2014 for studies on the association of IKZF1 polymorphisms with childhood AL risk. Data were extracted and the odd ratios (ORs) and95% confidence intervals (95% CIs) were calculated by a fixed-effects orrandom-effects model. Subgroup analysis by ethnicity and leukemia subtype, sensitivity and cumulative meta-analyses were performed. Moreover, publication bias was assessed by Begg''s and Egger''s tests.

Results

In total, 33 case control studies were finally included in this meta-analysis. For rs4132601 polymorphism, significantly increased AL risk was observed in all genetic models (the association was still significant when the p value was Bonferroni adjusted to 0.025). In the subgroup analysis by tumor type, statistical association was observed in B-cell precursor ALL (BCP-ALL). Additionally, when stratified by ethnicity, significantly increased AL risk was only observed in European subgroup, but not among African or mixed population subgroups. Finally, similar results were found forrs11978267 polymorphism.

Conclusion

In summary, this meta-analysis provides evidence that rs4132601 and rs11978267 polymorphisms in the IKZF1 gene mightcontribute to the occurrence of BCP-ALL, especially in European populations. Moreover, further studies with large sample size are required to clarify possibleroles of IKZF1 variants in other ethnic groups (e.g., Asians and Africans).     

Cost-Effectiveness of a Community Pharmacist Intervention in Patients with Depression: A Randomized Controlled Trial (PRODEFAR Study)

Background

Non-adherence to antidepressants generates higher costs for the treatment of depression. Little is known about the cost-effectiveness of pharmacist''s interventions aimed at improving adherence to antidepressants. The study aimed to evaluate the cost-effectiveness of a community pharmacist intervention in comparison with usual care in depressed patients initiating treatment with antidepressants in primary care.

Methods

Patients were recruited by general practitioners and randomized to community pharmacist intervention (87) that received an educational intervention and usual care (92). Adherence to antidepressants, clinical symptoms, Quality-Adjusted Life-Years (QALYs), use of healthcare services and productivity losses were measured at baseline, 3 and 6 months.

Results

There were no significant differences between groups in costs or effects. From a societal perspective, the incremental cost-effectiveness ratio (ICER) for the community pharmacist intervention compared with usual care was €1,866 for extra adherent patient and €9,872 per extra QALY. In terms of remission of depressive symptoms, the usual care dominated the community pharmacist intervention. If willingness to pay (WTP) is €30,000 per extra adherent patient, remission of symptoms or QALYs, the probability of the community pharmacist intervention being cost-effective was 0.71, 0.46 and 0.75, respectively (societal perspective). From a healthcare perspective, the probability of the community pharmacist intervention being cost-effective in terms of adherence, QALYs and remission was of 0.71, 0.76 and 0.46, respectively, if WTP is €30,000.

Conclusion

A brief community pharmacist intervention addressed to depressed patients initiating antidepressant treatment showed a probability of being cost-effective of 0.71 and 0.75 in terms of improvement of adherence and QALYs, respectively, when compared to usual care. Regular implementation of the community pharmacist intervention is not recommended.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00794196","term_id":"NCT00794196"}}NCT00794196     

How Often Does an Individual Trial Agree with Its Corresponding Meta-Analysis? A Meta-Epidemiologic Study

Objective

A meta-analysis may provide more conclusive results than a single trial. The major cost of meta-analysis is the time of waiting before the meta-analysis becomes available and resources spent on consequent trials that may not be necessary. The objective of this study is to address how often the result of a single trial, in particular the first trial, differs from that of its corresponding meta-analysis so as to reduce unnecessary waiting time and subsequent trials.

Study Design and Settings

A meta-epidemiologic study was conducted by collecting meta-analyses from the Cochrane Database of Systematic Reviews and five major medical journals. Effect size of a single trial was compared with that of its corresponding meta-analysis. The single trial includes the first trial, last trial and any trial randomly selected from the meta-analysis.

Results

647 meta-analyses are included and the median number of trials in a meta-analysis is 5. 233 (36.0%) meta-analyses have the first trial with a statistically significant result. When the first trial is statistically significant, 84.1% (95% CI: 79.4%, 88.8%) of the corresponding meta-analyses is both in the same direction and statistically significant. When the first trial is statistically insignificant, 57.9% (95% CI: 53.2%, 62.8%) of the meta-analysis is also statistically insignificant regardless of direction. The median number of years is 6.5 years from the first to the 5^th trial.

Conclusion

The conclusion of the first trial that the treatment is effective or harmful is mostly likely correct. A statistically significant trial agrees more often with its corresponding meta-analysis than a large trial. These findings imply that particularly in some urgent, life-saving or other critical circumstances for which no other effective methods are available, cautious recommendation based on the significant result of the first trial seems justifiable and could start use of an effective intervention by 5–8 years earlier.     

Antidepressant Utilization and Suicide in Europe: An Ecological Multi-National Study

Background

Research concerning the association between use of antidepressants and incidence of suicide has yielded inconsistent results and is the subject of considerable controversy. The first aim is to describe trends in the use of antidepressants and rates of suicide in Europe, adjusted for gross domestic product, alcohol consumption, unemployment, and divorce. The second aim is to explore if any observed reduction in the rate of suicide in different European countries preceded the trend for increased use of antidepressants.

Methods

Data were obtained for 29 European countries between 1980 and 2009. Pearson correlations were used to explore the direction and magnitude of associations. Generalized linear mixed models and Poisson regression distribution were used to clarify the effects of antidepressants on suicide rates, while an autoregressive adjusted model was used to test the interaction between antidepressant utilization and suicide over two time periods: 1980–1994 and 1995–2009.

Findings

An inverse correlation was observed in all countries between recorded Standardised Death Rate (SDR) for suicide and antidepressant Defined Daily Dosage (DDD), with the exception of Portugal. Variability was marked in the association between suicide and alcohol, unemployment and divorce, with countries depicting either a positive or a negative correlation with the SDR for suicide. Every unit increase in DDD of an antidepressant per 1000 people per day, adjusted for these confounding factors, reduces the SDR by 0.088. The correlation between DDD and suicide related SDR was negative in both time periods considered, albeit more pronounced between 1980 and 1994.

Conclusions

Suicide rates have tended to decrease more in European countries where there has been a greater increase in the use of antidepressants. These findings underline the importance of the appropriate use of antidepressants as part of routine care for people diagnosed with depression, therefore reducing the risk of suicide.     

Accumulating Research: A Systematic Account of How Cumulative Meta-Analyses Would Have Provided Knowledge,Improved Health,Reduced Harm and Saved Resources

Background

“Cumulative meta-analysis” describes a statistical procedure to calculate, retrospectively, summary estimates from the results of similar trials every time the results of a further trial in the series had become available. In the early 1990s, comparisons of cumulative meta-analyses of treatments for myocardial infarction with advice promulgated through medical textbooks showed that research had continued long after robust estimates of treatment effects had accumulated, and that medical textbooks had overlooked strong, existing evidence from trials. Cumulative meta-analyses have subsequently been used to assess what could have been known had new studies been informed by systematic reviews of relevant existing evidence and how waste might have been reduced.

Methods and Findings

We used a systematic approach to identify and summarise the findings of cumulative meta-analyses of studies of the effects of clinical interventions, published from 1992 to 2012. Searches were done of PubMed, MEDLINE, EMBASE, the Cochrane Methodology Register and Science Citation Index. A total of 50 eligible reports were identified, including more than 1,500 cumulative meta-analyses. A variety of themes are illustrated with specific examples. The studies showed that initially positive results became null or negative in meta-analyses as more trials were done; that early null or negative results were over-turned; that stable results (beneficial, harmful and neutral) would have been seen had a meta-analysis been done before the new trial; and that additional trials had been much too small to resolve the remaining uncertainties.

Conclusions

This large, unique collection of cumulative meta-analyses highlights how a review of the existing evidence might have helped researchers, practitioners, patients and funders make more informed decisions and choices about new trials over decades of research. This would have led to earlier uptake of effective interventions in practice, less exposure of trial participants to less effective treatments, and reduced waste resulting from unjustified research.     

Major Depressive Disorder and Stroke Risks: A 9-Year Follow-Up Population-Based,Matched Cohort Study

Background and Purpose

Major depressive disorder (MDD) is characterized by recurrent depressive episodes and one of the treatment choices is antidepressants. Patients with MDD are at greater risk of developing major metabolic diseases that may in turn lead to stroke. Moreover, both depressive symptoms and taking antidepressant medications are associated with higher risk of stroke. However, whether and how clinical depression increases stroke risk remains an unanswered question. Our aim was to provide answers to this question.

Methods

A matched cohort study of 5015 subjects (1003 MDD patients and 4012 control subjects) was conducted using a nationwide database. Subjects were followed to a maximum of 9 years to determine rates of newly-developed strokes, and controls and MDD groups with different levels of antidepressant refractoriness were compared to determine the temporal relation between stroke and three major metabolic comorbidities (i.e., diabetes mellitus, hypertension and hyperlipidemia). The levels of depressive symptoms and the antidepressant medications before stroke onset were investigated.

Results

Patients with MDD had significantly higher rates of stroke (4.3% vs. 2.8%, p<0.05) during the follow-up. Mediation regression analyses revealed that the occurrence of stroke in the MDD subjects was significantly mediated by the development of major metabolic diseases. Greater severity of depression, but not greater use of antidepressants, preceded the occurrence of stroke.

Conclusions

A clinical diagnosis of major depression leads to stroke indirectly through more intense depressive symptoms and the development of major comorbidities.     

Potential Reporting Bias in fMRI Studies of the Brain

Background

Functional magnetic resonance imaging (fMRI) studies have reported multiple activation foci associated with a variety of conditions, stimuli or tasks. However, most of these studies used fewer than 40 participants.

Methodology

After extracting data (number of subjects, condition studied, number of foci identified and threshold) from 94 brain fMRI meta-analyses (k = 1,788 unique datasets) published through December of 2011, we analyzed the correlation between individual study sample sizes and number of significant foci reported. We also performed an analysis where we evaluated each meta-analysis to test whether there was a correlation between the sample size of the meta-analysis and the number of foci that it had identified. Correlation coefficients were then combined across all meta-analyses to obtain a summary correlation coefficient with a fixed effects model and we combine correlation coefficients, using a Fisher’s z transformation.

Principal Findings

There was no correlation between sample size and the number of foci reported in single studies (r = 0.0050) but there was a strong correlation between sample size and number of foci in meta-analyses (r = 0.62, p<0.001). Only studies with sample sizes <45 identified larger (>40) numbers of foci and claimed as many discovered foci as studies with sample sizes ≥45, whereas meta-analyses yielded a limited number of foci relative to the yield that would be anticipated from smaller single studies.

Conclusions

These results are consistent with possible reporting biases affecting small fMRI studies and suggest the need to promote standardized large-scale evidence in this field. It may also be that small studies may be analyzed and reported in ways that may generate a larger number of claimed foci or that small fMRI studies with inconclusive, null, or not very promising results may not be published at all.     

The Diagnostic Value of DNA Methylation in Leukemia: A Systematic Review and Meta-Analysis

Background

Accumulating evidence supports a role of DNA methylation in the pathogenesis of leukemia. The aim of our study was to evaluate the potential genes with aberrant DNA methylation in the prediction of leukemia risk by a comprehensive meta-analysis of the published data.

Methods

A series of meta-analyses were done among the eligible studies that were harvested after a careful filtration of the searching results from PubMed literature database. Mantel-Haenszel odds ratios and 95% confidence intervals were computed for each methylation event assuming the appropriate model.

Results

A total of 535 publications were initially retrieved from PubMed literature database. After a three-step filtration, we harvested 41 case-control articles that studied the role of gene methylation in the prediction of leukemia risk. Among the involving 30 genes, 20 genes were shown to be aberrantly methylated in the leukemia patients. A further subgroup meta-analysis by subtype of leukemia showed that CDKN2A, CDKN2B, ID4 genes were significantly hypermethylated in acute myeloid leukemia.

Conclusions

Our meta-analyses identified strong associations between a number of genes with aberrant DNA methylation and leukemia. Further studies should be required to confirm the results in the future.     

Effectiveness and cost-effectiveness of antidepressants in primary care: a multiple treatment comparison meta-analysis and cost-effectiveness model

Objective

To determine effectiveness and cost-effectiveness over a one-year time horizon of pharmacological first line treatment in primary care for patients with moderate to severe depression.

Design

A multiple treatment comparison meta-analysis was employed to determine the relative efficacy in terms of remission of 10 antidepressants (citalopram, duloxetine escitalopram, fluoxetine, fluvoxamine mirtazapine, paroxetine, reboxetine, sertraline and venlafaxine). The estimated remission rates were then applied in a decision-analytic model in order to estimate costs and quality of life with different treatments at one year.

Data Sources

Meta-analyses of remission rates from randomised controlled trials, and cost and quality-of-life data from published sources.

Results

The most favourable pharmacological treatment in terms of remission was escitalopram with an 8- to 12-week probability of remission of 0.47. Despite a high acquisition cost, this clinical effectiveness translated into escitalopram being both more effective and having a lower total cost than all other comparators from a societal perspective. From a healthcare perspective, the cost per QALY of escitalopram was €3732 compared with venlafaxine.

Conclusion

Of the investigated antidepressants, escitalopram has the highest probability of remission and is the most effective and cost-effective pharmacological treatment in a primary care setting, when evaluated over a one year time-horizon. Small differences in remission rates may be important when assessing costs and cost-effectiveness of antidepressants.