Adams, Clive E.

Shokraneh, Farhad

Nottingham eTheses

Gallstone, snake venom and witchcraft for schizophrenia: the challenges of classifying [schizophrenia] trials

Nottingham ePrints

Abstracts: Oral SessionsEuropean Federation of Pharmaceutical Industries and Associa-tions (EFPIA) and Pharmaceutical Research and Manufacturersof America (PhRMA).Results In total, 323 clinical trial sponsors were listed in Trial-sTracker, of which 69 were pharmaceutical industry sponsorsand 31 were ranked in the top 50 pharmaceutical companies.Of these, 25/31 were EFPIA/PhRMA members and 6/31 werenon-members. The disclosure rate for each year from 2006 to2015 was 42.9%, 54.4%, 81.0%, 86.1%, 84.6%, 87.2%,89.3%, 82.1%, 84.1% and 73.4%; reporting of clinical trialresults became mandatory in 2008. The disclosure rate (dis-closed trials/eligible trials) between 2006 and 2015 was greaterfor all pharmaceutical industry sponsors (7037/9511 [74.0%])than for non-industry sponsors (9074/19866 [45.7%])(p<0.01). For the top 50 companies, results were disclosedfor 4761/6235 trials (76.4%) between 2006 and 2015, withsimilar disclosure rates for EFPIA/PhRMA members (4336/5697 [76.1%]) and non-members (425/538 [79.0%]).Conclusions According to TrialsTracker, the pharmaceuticalindustry has disclosed the results of three quarters of trialscompleted between 2006 and 2015. The disclosure rate forpharmaceutical industry sponsors is greater than for non-indus-try sponsors. Because TrialsTracker excludes sources other thanClinicalTrials.gov (e.g. company websites), this figure may bean underestimate.38 IS HONESTY THE BEST POLICY? THE ADEQUACY OFDISCLOSURE AS A STRATEGY FOR ADDRESSINGCOMPETING INTERESTS IN PATIENT DECISION AIDDEVELOPMENT1Gabrielle Stevens*, 2Regan Theiler, 3Hillary Washburn, 4Elisabeth Woodhams,1Jane Lindahl, 1Rachel Thompson. 1Dartmouth College, Hanover, USA; 2Mayo Clinic,Rochester, USA; 3Patient Partner, Keene, USA; 4Boston University School of Medicine,Boston, USA10.1136/bmjebm-2018-111024.38Objectives Competing interests among patient decision aiddevelopers have the potential to undermine the capacity ofthese tools to support patients and others to make informedhealth decisions. Prominent decision aid quality frameworks(e.g., the International Patient Decision Aids Standards(IPDAS), the (United States) National Standards for the Certif-ication of Patient Decision Aids) attempt to address this issueby advocating disclosure of decision aid funding sources anddevelopers’ competing interests. Although the adequacy of thisapproach has been questioned on more than one occasion, weare aware of no empirical evidence pertaining to patients’understanding of and reactions to competing interest disclo-sure statements. Here we present a secondary analysis of datacollected in the process of developing a patient decision aidon postpartum contraception to shed light on this issue.Method We administered an online survey of people whowere currently pregnant and/or £24 months postpartum, couldread and write English, and resided in the United States. Par-ticipants were recruited using a commercial panel service. Aspart of the survey, we presented participants with a list of sixinformation elements and solicited their views on whethereach ought to be included in the decision aid itself or in asupporting document. One of the information elements was,‘information about whether those who wrote the guide willmake money based on what decisions people make after usingthe guide’. Other elements pertained to decision aiddevelopment and user testing, evidence sources, update policy,readability, and authors and their qualifications. Immediatelyafter this, an open text question invited participants to elabo-rate on their responses or make additional suggestions.Results Of the 286 eligible participants, 46% responded thatinformation on competing interests should be included in thedecision aid itself, while 54% felt that it should be includedin a supporting document. Notably, competing interest infor-mation was endorsed for inclusion in the decision aid less fre-quently than most other information elements. Someparticipants’ open text responses reiterated the perceivedimportance of competing interest information (‘Full disclosureof who is to profit from choices presented by the guide.’)However, other participants’ comments suggested a limitedunderstanding of its relevance and/or little interest in it (‘Idon’t think people need information about what is going tohappen with money when using the guide, it has nothing todo with birth control,’ ‘The information is more importantthan who is making money off it because someone is alwaysmaking money off something’).Conclusions Relying on mere disclosure of competing interestsamong patient decision aid developers may not adequatelymitigate the negative effects of those interests for all decisionaid users. Further research dedicated to exploring diversepatients’ understanding of and attitudes toward competinginterest disclosure statements, as well as if and how suchstatements modify patients’ interpretation of the content andperceived trustworthiness of the decision aid, is warranted.39 USING DATA TO IMPROVE CARE AND HEALTHOUTCOMES IN RESOURCE-LIMITED SETTINGS:REFLECTIONS FROM KNOWLEDGE TO WISDOM ANDIMPLICATIONS AT CHILDREN’S CANCER HOSPITAL57357 – EGYPT1Ranin Soliman*, 1Alaa Elhaddad, 1Wael Eweida, 2Jason Oke, 2Carl Heneghan. 1Children’sCancer Hospital 57357 – Egypt, Cairo, Egypt; 2University of Oxford, Oxford, UK10.1136/bmjebm-2018-111024.39Objectives Using data to improve care and outcomes is partic-ularly important for developing countries with high burden ofdisease and inferior health outcomes. However, there is lim-ited use of data in resource-limited settings based on evidence.The aim of this work is to highlight the significant role ofdata to improve care and outcomes in resource-limited settingsand outline the barriers and potential solutions to use datafor evidence-based decision-making in developing countries.The study also aims to reflect on a practical example of usingreal-world data at the Children’s Cancer Hospital 57357 –Egypt (CCHE) and proposes the use of predictive analytics/modelling to improve care delivery and outcomes for childrenwith cancer in Egypt through building learning health systems.Method We reviewed the literature on the use of health dataand analytics to improve care and health outcomes inresource-limited settings, to determine available applications,barriers and potential solutions for implementation in develop-ing countries. We searched on PubMed, Google, and GoogleScholar using search terms ‘health data’, ‘data-driven improve-ments’, ‘big data’, ‘advanced analytic’, ‘resource-limited set-tings’, ‘developing countries’, ‘improving outcomes’, ‘barriers’,‘potential solutions’, and ‘EMR’. This was followed by reflec-tion on a practical example of using real world data toimprove care delivery and outcomes at CCHE and a proposedEvid Based Med 2018;23(Suppl 1):A1–A37 A19Conclusions This study provides an overview of differentmethods used to and/or reported on identifying gaps, deter-mining research priorities and displaying both gaps andresearch priorities. These study findings can be adapted toinform the development of methodological guidance on waysto advance methods to identify, prioritise and display gaps toinform research and evidence-based decision-making.35 EXTRACTING LARGE SETS OF DATA FROM SYSTEMATICREVIEWS: DEVELOPING A BASIS FOR SEPARATING,STORING AND USING INFORMATION ON TRIALS1Lena Schmidt*, 2Clive Adams. 1Hochschule Furtwangen University, Furtwangen imSchwarzwald, Germany; 2University of Nottingham, Nottingham, UK10.1136/bmjebm-2018-111024.35Objectives Qualitative and quantitative data relevant to rando-mised controlled trials (RCT), manually extracted and analysedwithin Cochrane reviews, are available to those who haveaccess to the Cochrane Library. If, however, one wished to re-use these data, all information has to be extracted from thatreview before that process can start. There are great benefitsof widely sharing data – and drawbacks in not sharing. Thiswork explores whether it is possible to i. extract all trial datafrom the systematic reviews; and prepare these data to bewidely accessed. Therefore, the aim is to make the process oftransposing data from RCTs into a web-based curated, accessi-ble database easy.Method Resources for this work are 200 systematic reviews ofthe Cochrane Schizophrenia Group (Nottingham) and opensource software.We produced a Java-based app with functionality to extractall trial data from a list of systematic reviews. (The reviews,available in ReviewManager5 format, are parsed as the appaccesses relevant parts of the reviews; in turn the data withinthe included studies are parsed into a format that can bedownloaded, uploaded and reused).This creates the possibility for results to be stored in a waythat:. all relevant data are ready to be used by others. data can be auto–tidied and re–planted back into the sourcereviewResults The product of this work is a simple end-user app. Byits use Cochrane groups can create a database with all datathey have extracted for their reviews.Conclusions Supporting auto-extraction, auto-curation, widedissemination and re-use of well-extracted data has advantagesfor all. There are many imaginative things that can be donewith these data for all categories of end-users.36 GALLSTONE, SNAKE VENOM AND WITCHCRAFT FORSCHIZOPHRENIA: THE CHALLENGES OF CLASSIFYING[SCHIZOPHRENIA] TRIALSFarhad Shokraneh*, Clive E Adams. Cochrane Schizophrenia Group, the Institute of MentalHealth, University of Nottingham, Nottingham, UK10.1136/bmjebm-2018-111024.36ObjectivesIntroduction Using a study-based register in the process of sys-tematic reviewing reduces waste and makes it possible toshortcut many processes normally undertaken by review teams.However, this works for simple ‘Intervention X vs Interven-tion Y for Condition Z’-style reviews, but the challenge is toprovide the same shortcuts for systematic reviews of classes ofinterventions, overviews or network meta-analyses. As onemight expect an Information Specialist to say, classification isthe answer.Objectives To report experience and progress with specificclassification of healthcare conditions, interventions, and out-comes for the purposes of facilitating systematic reviews.Methods We used the study-based Register of Cochrane Schiz-ophrenia Group (in MS-Access MeerKat 1.6; holds 25 212reports of 18 105 studies – 28 Feb 2018). The PICO meta-data (health care problems, interventions, comparisons, andoutcomes) of each study have been extracted. We used NLM’sMeSH, The British National Formulary, and WHO ATC clas-sification system.Results Health care problems: In the 18 105 studies we identi-fied 266 health care problems within schizophrenia trialswhich were specific focus of the evaluation – amongst whichnegative symptoms (546 trials), treatment resistance (467 tri-als), depression (350 trials), tardive dyskinesia (293 trials) andweight gain (260 trials) were the most common.Interventions: Of the 3910 interventions randomised withinthese trials, we found 155 classes of drugs with antipsychotics,antidepressants, and benzodiazepines being the mostresearched. There are 41 additional specific interventionsrelated to some sort of physical/exercise approach. Classifyingpsychological interventions, and Chinese Traditional Medicine(with its 537 trials with 246 interventions) remains achallenge.Outcomes: We use seven main classes for outcomes withinschizophrenia reviews: Global State, Mental State, AdverseEvents, Functioning, Service Use, Quality of Life, and Cost.We propose to use existing classification of outcome tools toclean and curate the 13 187 outcomes. Classification heaven!Conclusions Better reporting of PICO meta-data would helpand improve classification. However, all current classificationsystems do not really fit the systematic review purpose. Newsystems, designed with systematic review output in mind,greatly enhance the review process (including prioritisation oftitles) and reviewer experience (including prioritisation ofeffort).37 DISCLOSING THE RESULTS OF CLINICAL TRIALS: HOW ISTHE PHARMACEUTICAL INDUSTRY DOING?1Slavka Baronikova, 2Jim Purvis, 2Christopher Winchester*, 2Eric Southam, 2Julie Beeso,1Antonia Panayi. 1Shire International GmbH, Zugerberg, Switzerland; 2Research EvaluationUnit, Oxford PharmaGenesis, Oxford, UK10.1136/bmjebm-2018-111024.37Objectives To evaluate disclosure of clinical trials registered bypharmaceutical companies using an independent, semi-auto-mated tool (TrialsTracker; https://trialstracker.ebmdatalab.net/#/).Method For the top 50 pharmaceutical companies (2014global sales; EvaluatePharma, London, UK), registered inter-ventional phase 2–4 clinical trials completed in 2006–2015were identified in TrialsTracker, which calculates annual disclo-sure rates for sponsors of over 30 studies registered on Clini-calTrials.gov. The proportion of trials with results disclosed byApril 2017 was analysed by company membership of theA18 Evid Based Med 2018;23(Suppl 1):A1–A37 on 18 June 2018 by guest. Protected by copyright.http://ebm.bmj.com/BMJ EBM: first published as 10.1136/bmjebm-2018-111024.36 on 13 June 2018. Downloaded from 

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Gallstone, snake venom and witchcraft for schizophrenia: the challenges of classifying [schizophrenia] trials

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