The use of clinical study reports to enhance the quality of systematic reviews: a survey of systematic review authors

Background: Clinical study reports (CSRs) are produced for marketing authorisation applications. They often contain considerably more information about, and data from, clinical trials than corresponding journal publications. Use of data from CSRs might help circumvent reporting bias, but many researchers appear to be unaware of their existence or potential value. Our survey aimed to gain insight into the level of familiarity, understanding and use of CSRs, and to raise awareness of their potential within the systematic review community. We also aimed to explore the potential barriers faced when obtaining and using CSRs in systematic reviews. Methods: Online survey of systematic reviewers who (i) had requested or used CSRs, (ii) had considered but not used CSRs and (iii) had not considered using CSRs was conducted. Cochrane reviewers were contacted twice via the Cochrane monthly digest. Non-Cochrane reviewers were reached via journal and other website postings. Results: One hundred sixty respondents answered an open invitation and completed the questionnaire; 20/ 160 (13%) had previously requested or used CSRs and other regulatory documents, 7/160 (4%) had considered but not used CSRs and 133/160 (83%) had never considered this data source. Survey respondents mainly sought data from the European Medicines Agency (EMA) and/or the Food and Drug Administration (FDA). Motivation for using CSRs stemmed mainly from concerns about reporting bias 11/20 (55%), specifically outcome reporting bias 11/20 (55%) and publication bias 5/20 (25%). The barriers to using CSRs noted by all types of respondents included current limited access to these documents (43 respondents), the time and resources needed to obtain and include these data in evidence syntheses (n = 25) and lack of guidance about how to use these sources in systematic reviews (n = 26). Conclusions: Most respondents (irrespective of whether they had previously used them) agreed that access to CSRs is important, and suggest that further guidance on how to use and include these data would help to promote their use in future systematic reviews. Most respondents who received CSRs considered them to be valuable in their systematic review and/or meta-analysis

The incidence and prevalence of diabetes in patients with serious mental illness in North West Wales: Two cohorts, 1875–1924 & 1994–2006 compared

<p>Abstract</p> <p>Background</p> <p>Against a background of interest in rates of diabetes in schizophrenia and related psychoses and claims that data from historical periods demonstrate a link that antedates modern antipsychotics, we sought to establish the rate of diabetes in first onset psychosis and subsequent prevalence in historical and contemporary cohorts.</p> <p>Methods</p> <p>Analysis of two epidemiologically complete databases of individuals admitted for mental illness. 3170 individuals admitted to the North Wales Asylum between 1875–1924 and tracked over 18,486 patient years and 394 North West Wales first admissions for schizophrenia and related psychoses between 1994 and 2006 and tracked after treatment.</p> <p>Results</p> <p>The prevalence of Type 2 diabetes among patients with psychoses at time of first admission in both historical and contemporary samples was 0%. The incidence of diabetes remained 0% in the historical sample throughout 15 years of follow-up but rose in the contemporary sample after 3, 5 and 6 years of treatment with an incidence rate double the expected population rate so that the 15 year prevalence is likely to be over 8%.</p> <p>Conclusion</p> <p>No association was found between diabetes and serious mental illness, but there may be an association between diabetes and treatment.</p

Reporting of Adverse Events in Published and Unpublished Studies of Health Care Interventions : A Systematic Review

BACKGROUND: We performed a systematic review to assess whether we can quantify the underreporting of adverse events (AEs) in the published medical literature documenting the results of clinical trials as compared with other nonpublished sources, and whether we can measure the impact this underreporting has on systematic reviews of adverse events. METHODS AND FINDINGS: Studies were identified from 15 databases (including MEDLINE and Embase) and by handsearching, reference checking, internet searches, and contacting experts. The last database searches were conducted in July 2016. There were 28 methodological evaluations that met the inclusion criteria. Of these, 9 studies compared the proportion of trials reporting adverse events by publication status. The median percentage of published documents with adverse events information was 46% compared to 95% in the corresponding unpublished documents. There was a similar pattern with unmatched studies, for which 43% of published studies contained adverse events information compared to 83% of unpublished studies. A total of 11 studies compared the numbers of adverse events in matched published and unpublished documents. The percentage of adverse events that would have been missed had each analysis relied only on the published versions varied between 43% and 100%, with a median of 64%. Within these 11 studies, 24 comparisons of named adverse events such as death, suicide, or respiratory adverse events were undertaken. In 18 of the 24 comparisons, the number of named adverse events was higher in unpublished than published documents. Additionally, 2 other studies demonstrated that there are substantially more types of adverse events reported in matched unpublished than published documents. There were 20 meta-analyses that reported the odds ratios (ORs) and/or risk ratios (RRs) for adverse events with and without unpublished data. Inclusion of unpublished data increased the precision of the pooled estimates (narrower 95% confidence intervals) in 15 of the 20 pooled analyses, but did not markedly change the direction or statistical significance of the risk in most cases. The main limitations of this review are that the included case examples represent only a small number amongst thousands of meta-analyses of harms and that the included studies may suffer from publication bias, whereby substantial differences between published and unpublished data are more likely to be published. CONCLUSIONS: There is strong evidence that much of the information on adverse events remains unpublished and that the number and range of adverse events is higher in unpublished than in published versions of the same study. The inclusion of unpublished data can also reduce the imprecision of pooled effect estimates during meta-analysis of adverse events

Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

BACKGROUND: Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation. The first crucial step is to obtain correct elemental compositions. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas. RESULTS: An algorithm for filtering molecular formulas is derived from seven heuristic rules: (1) restrictions for the number of elements, (2) LEWIS and SENIOR chemical rules, (3) isotopic patterns, (4) hydrogen/carbon ratios, (5) element ratio of nitrogen, oxygen, phosphor, and sulphur versus carbon, (6) element ratio probabilities and (7) presence of trimethylsilylated compounds. Formulas are ranked according to their isotopic patterns and subsequently constrained by presence in public chemical databases. The seven rules were developed on 68,237 existing molecular formulas and were validated in four experiments. First, 432,968 formulas covering five million PubChem database entries were checked for consistency. Only 0.6% of these compounds did not pass all rules. Next, the rules were shown to effectively reducing the complement all eight billion theoretically possible C, H, N, S, O, P-formulas up to 2000 Da to only 623 million most probable elemental compositions. Thirdly 6,000 pharmaceutical, toxic and natural compounds were selected from DrugBank, TSCA and DNP databases. The correct formulas were retrieved as top hit at 80–99% probability when assuming data acquisition with complete resolution of unique compounds and 5% absolute isotope ratio deviation and 3 ppm mass accuracy. Last, some exemplary compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and by gas chromatography-time of flight mass spectrometry. In each case, the correct formula was ranked as top hit when combining the seven rules with database queries. CONCLUSION: The seven rules enable an automatic exclusion of molecular formulas which are either wrong or which contain unlikely high or low number of elements. The correct molecular formula is assigned with a probability of 98% if the formula exists in a compound database. For truly novel compounds that are not present in databases, the correct formula is found in the first three hits with a probability of 65–81%. Corresponding software and supplemental data are available for downloads from the authors' website

Studies of new Higgs boson interactions through nonresonant HH production in the b¯bγγ fnal state in pp collisions at √s = 13 TeV with the ATLAS detector

A search for nonresonant Higgs boson pair production in the b ¯bγγ fnal state is performed using 140 fb−1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. This analysis supersedes and expands upon the previous nonresonant ATLAS results in this fnal state based on the same data sample. The analysis strategy is optimised to probe anomalous values not only of the Higgs (H) boson self-coupling modifer κλ but also of the quartic HHV V (V = W, Z) coupling modifer κ2V . No signifcant excess above the expected background from Standard Model processes is observed. An observed upper limit µHH &lt; 4.0 is set at 95% confdence level on the Higgs boson pair production cross-section normalised to its Standard Model prediction. The 95% confdence intervals for the coupling modifers are −1.4 &lt; κλ &lt; 6.9 and −0.5 &lt; κ2V &lt; 2.7, assuming all other Higgs boson couplings except the one under study are fxed to the Standard Model predictions. The results are interpreted in the Standard Model efective feld theory and Higgs efective feld theory frameworks in terms of constraints on the couplings of anomalous Higgs boson (self-)interactions

Search for non-resonant Higgs boson pair production in the 2b+2l+ETmiss final state in pp collisions at s = 13 TeV with the ATLAS detector

A search for non-resonant Higgs boson pair (HH) production is presented, in which one of the Higgs bosons decays to a b-quark pair (bb ̄) and the other decays to WW*, ZZ*, or τ+τ−, with in each case a final state with l+l−+ neutrinos (l = e, μ). The analysis targets separately the gluon-gluon fusion and vector boson fusion production modes. Data recorded by the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider, corresponding to an integrated luminosity of 140 fb−1, are used in this analysis. Events are selected to have exactly two b-tagged jets and two leptons with opposite electric charge and missing transverse momentum in the final state. These events are classified using multivariate analysis algorithms to separate the HH events from other Standard Model processes. No evidence of the signal is found. The observed (expected) upper limit on the cross-section for non-resonant Higgs boson pair production is determined to be 9.7 (16.2) times the Standard Model prediction at 95% confidence level. The Higgs boson self-interaction coupling parameter κλ and the quadrilinear coupling parameter κ2V are each separately constrained by this analysis to be within the ranges [−6.2, 13.3] and [−0.17, 2.4], respectively, at 95% confidence level, when all other parameters are fixed