Translating the BDI and BDI-II into the HAMD and vice versa with equipercentile linking

Abstract Aims The Hamilton Depression Rating Scale (HAMD) and the Beck Depression Inventory (BDI) are the most frequently used observer-rated and self-report scales of depression, respectively. It is important to know what a given total score or a change score from baseline on one scale means in relation to the other scale. Methods We obtained individual participant data from the randomised controlled trials of psychological and pharmacological treatments for major depressive disorders. We then identified corresponding scores of the HAMD and the BDI (369 patients from seven trials) or the BDI-II (683 patients from another seven trials) using the equipercentile linking method. Results The HAMD total scores of 10, 20 and 30 corresponded approximately with the BDI scores of 10, 27 and 42 or with the BDI-II scores of 13, 32 and 50. The HAMD change scores of −20 and −10 with the BDI of −29 and −15 and with the BDI-II of −35 and −16. Conclusions The results can help clinicians interpret the HAMD or BDI scores of their patients in a more versatile manner and also help clinicians and researchers evaluate such scores reported in the literature or the database, when scores on only one of these scales are provided. We present a conversion table for future research

ROB-MEN: a tool to assess risk of bias due to missing evidence in network meta-analysis

Background Selective outcome reporting and publication bias threaten the validity of systematic reviews and meta-analyses and can affect clinical decision-making. A rigorous method to evaluate the impact of this bias on the results of network meta-analyses of interventions is lacking. We present a tool to assess the Risk Of Bias due to Missing Evidence in Network meta-analysis (ROB-MEN). Methods ROB-MEN first evaluates the risk of bias due to missing evidence for each of the possible pairwise comparison that can be made between the interventions in the network. This step considers possible bias due to the presence of studies with unavailable results (within-study assessment of bias) and the potential for unpublished studies (across-study assessment of bias). The second step combines the judgements about the risk of bias due to missing evidence in pairwise comparisons with (i) the contribution of direct comparisons to the network meta-analysis estimates, (ii) possible small-study effects evaluated by network meta-regression, and (iii) any bias from unobserved comparisons. Then, a level of “low risk”, “some concerns”, or “high risk” for the bias due to missing evidence is assigned to each estimate, which is our tool’s final output. Results We describe the methodology of ROB-MEN step-by-step using an illustrative example from a published NMA of non-diagnostic modalities for the detection of coronary artery disease in patients with low risk acute coronary syndrome. We also report a full application of the tool on a larger and more complex published network of 18 drugs from head-to-head studies for the acute treatment of adults with major depressive disorder. Conclusions ROB-MEN is the first tool for evaluating the risk of bias due to missing evidence in network meta-analysis and applies to networks of all sizes and geometry. The use of ROB-MEN is facilitated by an R Shiny web application that produces the Pairwise Comparisons and ROB-MEN Table and is incorporated in the reporting bias domain of the CINeMA framework and software

Changes in the prevalence of mental health problems during the first year of the pandemic: a systematic review and dose-response meta-analysis

Aim: To describe the pattern of the prevalence of mental health problems during the first year of the COVID-19 pandemic and examine the impact of containment measures on these trends. Methods: We identified articles published until 30 August 2021 that reported the prevalence of mental health problems in the general population at two or more time points. A crowd of 114 reviewers extracted data on prevalence, study and participant characteristics. We collected information on the number of days since the first SARS-CoV-2 infection in the study country, the stringency of containment measures and the number of cases and deaths. We synthesised changes in prevalence during the pandemic using a random-effects model. We used dose-response meta-analysis to evaluate the trajectory of the changes in mental health problems. Results: We included 41 studies for 7 mental health conditions. The average odds of symptoms increased during the pandemic (mean OR ranging from 1.23 to 2.08). Heterogeneity was very large and could not be explained by differences in participants or study characteristics. Average odds of psychological distress, depression and anxiety increased during the first 2 months of the pandemic, with increased stringency of the measures, reported infections and deaths. The confidence in the evidence was low to very low. Conclusions: We observed an initial increase in the average risk of psychological distress, depression-related and anxiety-related problems during the first 2 months of the pandemic. However, large heterogeneity suggests that different populations had different responses to the challenges imposed by the pandemic

Minimally important difference estimates and methods: A protocol

Introduction: Patient-reported outcomes (PROs) are often the outcomes of greatest importance to patients. The minimally important difference (MID) provides a measure of the smallest change in the PRO that patients perceive as important. An anchor-based approach is the most appropriate method for MID determination. No study or database currently exists that provides all anchor-based MIDs associated with PRO instruments; nor are there any accepted standards for appraising the credibility of MID estimates. Our objectives are to complete a systematic survey of the literature to collect and characterise published anchor-based MIDs associated with PRO instruments used in evaluating the effects of interventions on chronic medical and psychiatric conditions and to assess their credibility. Methods and analysis: We will search MEDLINE, EMBASE and PsycINFO (1989 to present) to identify studies addressing methods to estimate anchor-based MIDs of target PRO instruments or reporting empirical ascertainment of anchor-based MIDs. Teams of two reviewers will screen titles and abstracts, review full texts of citations, and extract relevant data. On the basis of findings from studies addressing methods to estimate anchor-based MIDs, we will summarise the available methods and develop an instrument addressing the credibility of empirically ascertained MIDs. We will evaluate the credibility of all studies reporting on the empirical ascertainment of anchorbased MIDs using the credibility instrument, and assess the instrument's inter-rater reliability. We will separately present reports for adult and paediatric populations. Ethics and dissemination: No research ethics approval was required as we will be using aggregate data from published studies. Our work will summarise anchor-based methods available to establish MIDs, provide an instrument to assess the credibility of available MIDs, determine the reliability of that instrument, and provide a comprehensive compendium of published anchor-based MIDs associated with PRO instruments which will help improve the interpretability of outcome effects in systematic reviews and practice guidelines

Tailoring Adjuvant Endocrine Therapy for Postmenopausal Breast Cancer: A CYP2D6 Multiple-Genotype-Based Modeling Analysis and Validation

Purpose: Previous studies have suggested that postmenopausal women with breast cancer who present with wild-type CYP2D6 may actually have similar or superior recurrence-free survival outcomes when given tamoxifen in place of aromatase inhibitors (AIs). The present study established a CYP2D6 multiple-genotype-based model to determine the optimal endocrine therapy for patients harboring wild-type CYP2D6. Methods: We created a Markov model to determine whether tamoxifen or AIs maximized 5-year disease-free survival (DFS) for extensive metabolizer (EM) patients using annual hazard ratio (HR) data from the BIG 1-98 trial. We then replicated the model by evaluating 9-year event-free survival (EFS) using HR data from the ATAC trial. In addition, we employed two-way sensitivity analyses to explore the impact of HR of decreased-metabolizer (DM) and its frequency on survival by studying a range of estimates. Results: The 5-year DFS of tamoxifen-treated EM patients was 83.3%, which is similar to that of genotypically unselected patients who received an AI (83.7%). In the validation study, we further demonstrated that the 9-year EFS of tamoxifentreated EM patients was 81.4%, which is higher than that of genotypically unselected patients receiving tamoxifen (78.4%) and similar to that of patients receiving an AI (83.2%). Two-way sensitivity analyses demonstrated the robustness of the results

Signatures of Selection in the Genomes of Commercial and Non-Commercial Chicken Breeds

Identifying genomics regions that are affected by selection is important to understand the domestication and selection history of the domesticated chicken, as well as understanding molecular pathways underlying phenotypic traits and breeding goals. While whole-genome approaches, either high-density SNP chips or massively parallel sequencing, have been successfully applied to identify evidence for selective sweeps in chicken, it has been difficult to distinguish patterns of selection and stochastic and breed specific effects. Here we present a study to identify selective sweeps in a large number of chicken breeds (67 in total) using a high-density (58 K) SNP chip. We analyzed commercial chickens representing all major breeding goals. In addition, we analyzed non-commercial chicken diversity for almost all recognized traditional Dutch breeds and a selection of representative breeds from China. Based on their shared history or breeding goal we in silico grouped the breeds into 14 breed groups. We identified 396 chromosomal regions that show suggestive evidence of selection in at least one breed group with 26 of these regions showing strong evidence of selection. Of these 26 regions, 13 were previously described and 13 yield new candidate genes for performance traits in chicken. Our approach demonstrates the strength of including many different populations with similar, and breed groups with different selection histories to reduce stochastic effects based on single populations

Automated Workflow for Preparation of cDNA for Cap Analysis of Gene Expression on a Single Molecule Sequencer

Background: Cap analysis of gene expression (CAGE) is a 59 sequence tag technology to globally determine transcriptional starting sites in the genome and their expression levels and has most recently been adapted to the HeliScope single molecule sequencer. Despite significant simplifications in the CAGE protocol, it has until now been a labour intensive protocol. Methodology: In this study we set out to adapt the protocol to a robotic workflow, which would increase throughput and reduce handling. The automated CAGE cDNA preparation system we present here can prepare 96 ‘HeliScope ready ’ CAGE cDNA libraries in 8 days, as opposed to 6 weeks by a manual operator.We compare the results obtained using the same RNA in manual libraries and across multiple automation batches to assess reproducibility. Conclusions: We show that the sequencing was highly reproducible and comparable to manual libraries with an 8 fold increase in productivity. The automated CAGE cDNA preparation system can prepare 96 CAGE sequencing samples simultaneously. Finally we discuss how the system could be used for CAGE on Illumina/SOLiD platforms, RNA-seq and fulllengt

CATCHprofiles: Clustering and Alignment Tool for ChIP Profiles

Chromatin Immuno Precipitation (ChIP) profiling detects in vivo protein-DNA binding, and has revealed a large combinatorial complexity in the binding of chromatin associated proteins and their post-translational modifications. To fully explore the spatial and combinatorial patterns in ChIP-profiling data and detect potentially meaningful patterns, the areas of enrichment must be aligned and clustered, which is an algorithmically and computationally challenging task. We have developed CATCHprofiles, a novel tool for exhaustive pattern detection in ChIP profiling data. CATCHprofiles is built upon a computationally efficient implementation for the exhaustive alignment and hierarchical clustering of ChIP profiling data. The tool features a graphical interface for examination and browsing of the clustering results. CATCHprofiles requires no prior knowledge about functional sites, detects known binding patterns “ab initio”, and enables the detection of new patterns from ChIP data at a high resolution, exemplified by the detection of asymmetric histone and histone modification patterns around H2A.Z-enriched sites. CATCHprofiles' capability for exhaustive analysis combined with its ease-of-use makes it an invaluable tool for explorative research based on ChIP profiling data

Estrogen-Dependent Gene Expression in the Mouse Ovary

Estrogen (E) plays a pivotal role in regulating the female reproductive system, particularly the ovary. However, the number and type of ovarian genes influenced by estrogen remain to be fully elucidated. In this study, we have utilized wild-type (WT) and aromatase knockout (ArKO; estrogen free) mouse ovaries as an in vivo model to profile estrogen dependent genes. RNA from each individual ovary (n = 3) was analyzed by a microarray-based screen using Illumina Sentrix Mouse WG-6 BeadChip (45,281 transcripts). Comparative analysis (GeneSpring) showed differential expression profiles of 450 genes influenced by E, with 291 genes up-regulated and 159 down-regulated by 2-fold or greater in the ArKO ovary compared to WT. Genes previously reported to be E regulated in ArKO ovaries were confirmed, in addition to novel genes not previously reported to be expressed or regulated by E in the ovary. Of genes involved in 5 diverse functional processes (hormonal processes, reproduction, sex differentiation and determination, apoptosis and cellular processes) 78 had estrogen-responsive elements (ERE). These analyses define the transcriptome regulated by E in the mouse ovary. Further analysis and investigation will increase our knowledge pertaining to how E influences follicular development and other ovarian functions