dataesr/scientific-paragraphs-categorization huggingface dataset:
In addition, early consideration of an interventions pathway to impact has been advocated. The aim of this exploratory study was to examine the Cochrane Database of Trials over the last six years to determine the level of utilisation of PPI, process evaluation and theoretical frameworks alongside dental trials, whilst concurrently exploring whether the pathway to impact and implementation was being considered. The Cochrane Database of Trials was searched for reports on Randomised Controlled trials (RCTs) and protocols of RCTs over a five year period (2010-2016). As the aim of this exploratory study was to get a 'snap-shot' of current activity, other subscription databases, open access databases and the grey literature were not searched. Any dental intervention that would have utilised psycho-social mechanisms explicitly or implicitly was included, whilst any intervention that acted through a pharmacological mechanism was excluded.
Included studies were assessed to determine whether they reported on any of the 'meta-processes' detailed above. Titles and abstracts identified by the electronic search were downloaded to a reference management database and duplicates were removed. 582 of 932,577 records had the term 'dental' , 'oral' and 'trials' in the Title, Abstract or Keyword. 56 studies related to psycho-social interventions or had psycho-social pathways to implementation. The proportion of trials that reported PPI, process evaluation, theoretical framework or mentioned implementation 0%, 21. 7%, 43. 5% and 4. 3% respectively, whilst the proportion of protocols was higher (46. 7%, 60. 0%, 73. 3% and 6. 7%). The use of 'meta-processes, in trial design and conduct has improved, although considerations about pathway to impact and the implementation of the research evidence, once generated, appears to remain poor.
As review and publication of design articles typically require expenditure of as much or more resources as other types of articles, a question of interest is whether the frequency of citation of design articles has been similar to frequency of citation of articles of other types. Methods All issues of Clinical Trials published from 2004 through 2015 were searched to identify design and all other articles. We excluded papers published as part of proceedings of meetings, letters, editorials, invited commentaries, columns, etc. For our preliminary estimates of citation frequency, we randomly selected 20 articles of each type. We searched the Web of Science and Google Scholar databases to determine the number of citations per article as of October 31, 2016. We summarized the distribution of number of citations for each article type and each citation database by the median and interquartile range (IQR).
Methods A search for Non-inferiority trials in Pub Med database that published between 1/1/2015 and 31/12/2015 was performed. The inclusion criteria were; Non-inferiority trials that were randomised clinical trials, done on adult humans, published in English and with the full text available. From this search, 387articles were retrieved. Only 45 articles published in the Lancet, BMJ, JAMA and NEJM, 37 of them were analysed.
We envisage this work will then guide future research into the use of pilot and feasibility studies to better inform full studies. Methods Data on pilot and feasibility studies have been collected from the International Standard Randomised Controlled Trial Number (ISRCTN) registry website. As the website does not provide a downloadable database, a web scraping methodology was adopted and implemented using the R programme. Pilot and feasibility studies were identified using a keyword search on the main title. Unique trial records were extracted using regular expressions and collated in an Excel spreadsheet.
Results Out of the 658 unique trials that were found within the ISRCTN database, 456 (69%) of these were labelled as pilot studies, 196 (30%) as feasibility studies and six (1%) considered both a pilot and feasibility study. The overall prevalence of all pilot or feasibility studies does not seem to be showing any particular trend over time. Initially, pilot studies were much more common; however, in recent years feasibility studies have increased in popularity and are now on a par with pilot studies. The median number of target participants for each trial was 50 (range: 5-130,000). When considered separately, pilot studies had a target of 44 (range: 5-130,000) with feasibility studies being slightly larger with a target of 60 (range: 6-1,600). On average, the trials ran for a period of 18 months with pilot studies reporting a slightly shorter time (17 months) than feasibility studies (18.
5 months), which aligns with the larger sample size target. Mental and behavioural disorders accounted for the highest proportion of studies (20%), followed by cancer studies (13%). The majority of the studies within the data were interventional (96%) and defined as randomised controlled trials (85%). A hospital environment is the most likely setting for the studies (45%) and in most cases, the recruitment was in a single country (97%). This is consistent between the pilot and feasibility studies within the database.
O3 Using routinely recorded data in a clinical trial: the feasibility, agreement and additional benefits compared to standard prospective data collection methods Graham Powell 1 , Laura Bonnett 1 , Catrin Tudur-Smith 1 , Dyfrig Hughes Routinely recorded data used in clinical research is potentially cost and resource-use effective. Clinical sources of data such as HES and CPRD are commonly accessed to provide data for retrospective observational and record-linkage studies and provide a valid dataset for this purpose. Routinely recorded data may also present advantages to prospective clinical research such as randomised controlled trials (RCTs). For example, routinely recorded data have been used to inform judgements about the feasibility of sample size and recruitment targets and measure participant outcomes.
Introduction The National Heart, Lung, and Blood Institute (NHLBI) established the Biologic Specimen and Data Repositories Information Coordinating Center (BioLINCC) www. biolincc. nhlbi. nih. gov in 2008 to provide online access to NHLBI data and biospecimen resources. To assist non-study investigators' use of the datasets, each study's BioLINCC webpage provides information on the study design and results, including documents that provide insight into the study data. Given the recent interest by journal editors in the rapid release of publication data, the need for efficient curation methods is becoming more important. The procedures that have been developed by BioLINCC to review and prepare study datasets and documents for sharing with secondary users are one example of how this can be accomplished.
Background Managing drug supply for large clinical trials presents significant logistical challenges. The MRC CTU at UCL has used either an external drug supply management system (DSMS) or in-house tools (spreadsheets or MS Access databases). However, there are challenges integrating these systems with internal study databases to work seamlessly. Add-Aspirin is a phase III double-blind, randomised trial with over 180 sites in the UK, aiming to recruit 10,000 patients. The size of the trial and the use of double-blinded drug as part of the trial design led to a decision to develop an in-house DSMS. Methods We will describe the key considerations that influenced the design of the DSMS, whilst focussing on scalability, as the DSMS was intended to be a cost-effective solution that could be used by a number of trials within the unit.
The key activity was building a forecasting-and-site-refill algorithm to minimise drug wastage whilst optimising shipment quantities, therefore reducing shipping costs. To achieve the required scalability, the first consideration was introduction of flexibility into the algorithm. It was developed with many inputs/parameters to cater for variation across future trials and sites in terms of number of patients, recruitment rates, site capacity and location. Each shipment request is reviewed and approved by the trial team, which further allows the process to be fine-tuned for each study. Integration with internal and external contract research organization (CRO) systems was fundamental to building a successful system. The DSMS is a web-based system (C#/MVC. NET/SQL Server database) and has been integrated with an existing randomisation system and study database.
The resulting discrepancies between CDISC and non-CDISC analyses took considerable effort to resolve. In subsequent studies, whether or not regulatory submissions are planned, a more systematic approach has been used. Collected data is mapped to SDTM datasets, from which Analysis Data Model (ADaM) datasets are derived. All analyses and complex reports, both during and at the end of the trial, are performed on these ADaM datasets. This approach has been successfully employed for a number of large trials at different stages (completed, currently undergoing analysis and ongoing), which together have randomized over 70,000 participants, and more recently to partially convert some legacy studies to CDISC for particular analyses. Benefits (1) CDISC standards eliminate the need for an organisation to develop its own data standards, and, since they are developed by a wide range of stakeholders over many years, are more comprehensive and coherent than any single organisation is likely to achieve.
(2) Analysis and validation tools are available which support CDISC standards. (3) CDISC-compliant datasets are well documented, so statisticians, data analysts and researchers can easily switch between studies without having to learn a new data schema. (4) The effort required to respond to queries about CDISC-compliant data is consistently less than that for non-compliant data. (5) CDISC standards provide a useful common framework for data sharing and long term data and metadata storage. (6)  The large CDISC user community is a valuable source of support.
Conclusion Despite the global problem of inadequate recruitment to randomised trials, there is little evidence to guide researchers on decisions about how patients are recruited. A comprehensive, rigorous and inclusive process has been undertaken, with participation from key stakeholders, including members of the public. Priority areas of focus in trial recruitment methodology have been identified by those for whom it matters most. The Top 10 list should inform the scope and future activities of funders and researchers in the area of trial recruitment methodology. Sponsorship This project was funded by the Health Research Board (Ireland) Knowledge Exchange and Dissemination Scheme Award 2015 and was supported by the James Lind Alliance and NIHR.
Results Interviews conducted with the current trial coordinator, current trial statistician, and a clinician involved throughout the trial's history revealed the 14-year lifespan of the trial and regulation changes in this time to be the main challenge. AspECT was begun before the current clinical trials regulations were published as Statutory Instrument 2004/1031. The regulations are set to change again soon. Themes reported included the difficulty in maintaining knowledge of the trial with changing PI's and study nurses in the hospital sites, maintaining and auditing a high quality database over the trial lifespan, handing over study roles, dealing with an ever-evolving and sceptical clinical world, and adapting to the changing processes for obtaining national regulatory and local R&D approval and multicentre trial set-up.
Background The COMET (Core Outcome Measures in Effectiveness Trials, http:// www. comet-initiative. org. uk) Initiative brings together people interested in the development and application of agreed standardised sets of outcomes, known as "core outcome sets" (COS). These sets represent the minimum that should be measured and reported in all clinical trials of a specific condition, and are also suitable for use in clinical audit or research other than randomised trials. One of the successes of COMET has been the development of a publicly available searchable database of completed and ongoing projects in COS development. This database is currently searchable by population, intervention and condition, but as yet has not been categorised according to outcome (the fourth of the essential elements that should be defined for a trial, according to the PICO model).
Similarly, outcomes in trials registries (including the EU Clinical Trials Register, ClinicalTrials. gov and ISRCTN registry) can be entered as free text only, leading to inconsistencies. Ninety percent of queries related to requests to register a trial relate to outcomes (Alison Cuff, ISRCTN, personal communication). Standardised terminology to describe outcomes is starting to come into use in pre-clinical research (Robinson et al. "The Human Phenotype Ontology: A Tool for Annotating and Analyzing Human Hereditary Disease" (2008) The American Journal of Human Genetics 8: 610-615), but there is currently no consensus on how trial outcomes should be classified. The lack of a standard taxonomy relating to trial outcomes impedes the ability to efficiently and effectively search the literature.
Methods The COS outcome classification project involves the extraction of all core outcomes/domains from existing COS through the COMET database and reviewing the systematic reviews of outcomes in the COMET database to determine how outcomes were classified. Existing conceptual models (including The International Classification of Functioning, Disability and Health (ICF), Patient-Reported Outcome Measurement Information System (PROMIS) and the Wilson and Cleary framework) will be reviewed for suitability, with a view towards developing a standardised ontology for classification of research outcomes.
O40 Quality control of SDTM domain mappings from electronic case report forms Noga Lewin, Miebi Eradiri, Sheena Aris, Angela Soriano, Gaurav Sharma, Jill Barrett, Heather Hill, Marian Ewell, Noble Shore, Abigail G. Matthews Emmes Corporation Correspondence: Noga Lewin Trials 2017, 18(Suppl 1):O40 The Study Data Tabulation Model (SDTM) defines a standard structure for submission of electronic clinical trial data to a regulatory authority, such as the FDA. These electronic listings of individual observations comprise the essential data reported from a clinical trial and are submitted with the analysis datasets. The Clinical Data Interchange Standards Consortium (CDISC) team at the Emmes Corporation, developed a novel process to map data collected in electronic case report forms (eCRFs) to the SDTM paradigm with these unique advantages: the mapping specifications are developed alongside the design of the CDASH conformant CRFs; Advantage eClinicalSM, Emmes' form building and data capture and management suite, provides an intuitive user interface that permits a non-programmer to specify the mapping to SDTM -this process is completed before the initiation of data collection; then the mapping is executed on the production data in an automated fashion at least daily while the trial is accumulating data, and the results are written to a tabulation database.
This enables the use of SDTM data structures for oversight and safety reporting. The use of standardized data tables throughout the life cycle of the study yields efficiencies in statistical reporting and reduces the timeframe required for delivery of the final databases and code at the end of the study. Quality control of the mapping process is partially automated. The proposed automated QC report algorithm reduces the amount of work involved in validating the mapping against a discrete set of rules (e. g. every variable is mapped, no cell in the mapping tool is left blank, each required variable in the domain is mapped, compare mapping to a gold standard -a protocol that was tested and can serve as a template, all fields in the mapping entries start with the form code, all subjects belong to the protocol).
The protocol specifies that users should log into the randomization system at the beginning of surgery. The user is then either given the allocation or asked to log in again after wound closure to obtain the allocation. When logging in again, the user has to enter the time of wound closure. Acceptability of the double randomization is assessed from three sources of information: times for system log-on, knife-to-skin and wound closure from the trial database; in-depth interviews with health care professionals; feedback from participating centres about their ways of working.
Practical issues, such as limited internet access in theatre or no one available to log into the database, were also reported. Feedback from two centres suggested that theatre staff are ringing a research nurse outside theatre to log-on when required. On at least one occasion, a surgeon first logged in after wound closure, to avoid having to log-on twice. Centres have also reported occasional difficulties in accessing the database from theatres. Generic usernames for randomization only, accessible using a mobile phone, were offered to improve access. Conclusions Timings collected during the trial demonstrate good adherence to the double randomization. Methods adopted by research personnel in order to adhere may not be practicable in a large trial. Generic access for randomization may facilitate theatre personnel doing this task.
Methods The COMET (Core Outcome Measures in Effectiveness Trials) Initiative promotes the development and application of COS, by including pertinent individual studies in a publically available online database. The COMET database is a unique inventory containing references of planned, ongoing and completed work relating to COS development. In total, there are more than 300 published and ongoing COS registered in the COMET database. The COMET database was searched to identify published and ongoing COS that might be relevant to the 25 conditions with the highest global prevalence of chronic sequelae identified in the Global Burden of Disease Study.
The software was adapted to randomise women in batches to intervention or control, and display the cases in the desired order. A total of 1,194,147 women were randomised and analysed. A standard Crystal report was designed to extract trial outcomes from the NBSS computer system. Data extraction was delayed until after each centre completed their annual reports for routine quality assurance, as the datasets are cleaned in preparation for these. Further data cleaning was conducted in collaboration with each centre. As a result there was very little missing data, making up less than 0. 1% of the final dataset. This is an example of implementing a successful pragmatic integrated trial in screening. Such trials are effective in situations where some of the following conditions are met: individual informed consent for the trial is not necessary, the intervention itself is inexpensive, trial outcomes are already routinely recorded in a standard way, routine data collection is accurate and audited, and management pathways are standardized and the intervention does not require major changes to these.
O52 Maximising trial efficiency in the airways-2 trial using a multi-functional database Lauren Scott 1 , Jodi Taylor 1 , David Hutton Background Airways-2 is a cluster randomised trial comparing two airway management devices for the treatment of out-of-hospital cardiac arrest. Participating paramedics from four UK ambulance trusts are randomised to manage the patient's airway using either an i-gel device or intubation. We are aiming to recruit 1,500 paramedics, screen approximately 60,000 patients and enrol more than 9,000 patients over a two year period. As patient recruitment takes place in an emergency setting and patients who survive to hospital admission could be admitted to one of 100 hospitals, data collection needs to be as efficient and streamlined as possible.
Methods We designed a multi-functional database to track patients' progress through the trial, as well as capture the trial data. Data collection has been organised in sections reflecting the different stages of the patient journey. Access to the different sections is dependent on the outcome of the previous section, e. g. it is not possible to access the area of the database that captures hospital admission data if the patient died at the scene of the arrest. Access is also restricted according to role and location, e. g. hospital based researchers cannot access the sections relating to pre-hospital paramedic data collection. User access is via a secure NHS web server. Data quality is maximised by validation checks on data items; the database allows users to save invalid data or leave items blank but such instances generate queries.
Results The Airways-2 database has approximately 300 users undertaking one of five different roles. So far, over 44,000 patients have been screened and nearly 6,000 patients have been enrolled. Data queries, along with regular central monitoring, have enabled successful patient tracking and over 99% data completeness for the primary outcome. User feedback has been positive. The system is intuitive and easy to use. Discussion When running a large complex trial involving a diverse range of staff and researchers working across different health care settings, it is important to consider using IT solutions to optimise efficiency and data quality. Database features developed for the Airways-2 trial are now being implemented in other studies.
Potential Impact We can draw together conclusions from the previous conference, compare and contrast the abstract views from the two conferences and highlight any changes or consistent themes. Also, just as crucially, we will be tracking abstracts views over time beyond the end of the conference and ensuring access is available to both authors and external researchers, both on the website and in dataset format. This will ensure that interested parties from the 2017 conference can clearly gauge the impact of their own work and any promotional efforts they make.
We also report on whether reviewers could have deduced or approximated the missing SD in primary papers or imputed the SDs by those reported in other studies in the same meta-analysis. Methods We used the whole Cochrane Database of Systematic Reviews issued in January 2008 (Davey et al. , 2011) to identify studies omitted with a missing SD from 6672 continuous-outcome meta-analyses. A subsample of these, published since 2006, was selected and enabled hand-searching and extracting to assess whether SDs could have been deduced or approximated and to calculate the influence statistic. We report on fixed effect meta-analyses.
The aim of this study was to systematically review the methodological challenges and limitations in musculoskeletal RCTs which compare a surgical and non-operative interventions (e. g. drug treatment or physiotherapy). Methods A search of the MEDLINE and CENTRAL databases between 2010 and 2015 was conducted. Randomised orthopaedic clinical trials which had a surgical and non-operative comparison such as physiotherapy were included. Data were extracted and summarised on the study characteristics such as target and actual recruitment, adherence to randomisation allocation, and in addition reported challenges to successfully conducting the trial amongst other details. A quality assessment was also conducted using the Cochrane Risk of Bias tool.