Are routinely collected NHS administrative records suitable for endpoint identification in clinical trials? Evidence from the West of Scotland coronary prevention study

Background: Routinely collected electronic patient records are already widely used in epidemiological research. In this work we investigated the potential for using them to identify endpoints in clinical trials.<p></p> Methods: The events recorded in the West of Scotland Coronary Prevention Study (WOSCOPS), a large clinical trial of pravastatin in middle-aged hypercholesterolaemic men in the 1990s, were compared with those in the record-linked deaths and hospitalisations records routinely collected in Scotland.<p></p> Results: We matched 99% of fatal study events by date. We showed excellent matching (97%) of the causes of fatal endpoint events and good matching (.80% for first events) of the causes of nonfatal endpoint events with a slightly lower rate of mismatching of record linkage than study events (19% of first study myocardial infarctions (MI) and 4% of first record linkage MIs not matched as MI). We also investigated the matching of non-endpoint events and showed a good level of matching, with .78% of first stroke/TIA events being matched as stroke/TIA. The primary reasons for mismatches were record linkage data recording readmissions for procedures or previous events, differences between the diagnoses in the routinely collected data and the conclusions of the clinical trial expert adjudication committee, events occurring outside Scotland and therefore being missed by record linkage data, miscoding of cardiac events in hospitalisations data as ‘unspecified chest pain’, some general miscoding in the record linkage data and some record linkage errors.<p></p> Conclusions: We conclude that routinely collected data could be used for recording cardiovascular endpoints in clinical trials and would give very similar results to rigorously collected clinical trial data, in countries with unified health systems such as Scotland. The endpoint types would need to be carefully thought through and an expert endpoint adjudication committee should be involved.<p></p&gt

Clinical Trials: Minimising source data queries to streamline endpoint adjudication in a large multi-national trial

Abstract Background The UK Clinical Trial Regulations and Good Clinical Practice guidelines specify that the study sponsor must ensure clinical trial data are accurately reported, recorded and verified to ensure patient safety and scientific integrity. The methods that are utilised to assess data quality and the results of any reviews undertaken are rarely reported in the literature. We have recently undertaken a quality review of trial data submitted to a Clinical Endpoint Committee for adjudication. The purpose of the review was to identify areas that could be improved for future clinical trials. The results are reported in this paper. Methods Throughout the course of the study, all data queries were logged. Following study close out, queries were coded and categorised. A descriptive and comparative analysis was conducted to determine the frequency of occurrence for each category by country of origin. Results From 1595 endpoint packages reviewed, 782 queries were generated. No source data queries were generated for countries with ≤ 25 recruited subjects, but both low recruiting and high recruiting countries had a high number of queries relating to subject identifiers. Conclusions The implementation of some simple measures could help improve data quality and lead to significant savings.</p

Archiving approach in the UK: the proper storage of research documents remains an essential aspect of the clinical trials process

Clinical trials involve a complex series of steps from inception through protocol design, recruitment, follow-up, data collection, analysis, and the final presentation of results. An important final component of this process is the archiving of the trial documents. Unfortunately, this is an often neglected function that is dealt with as an afterthought. Despite this, archiving is a legal and regulatory requirement that should be planned and carried out with the same attention to detail as every other aspect of the trial. It can also be a very labor intensive and expensive exercise. In this article what exactly is meant by archiving, what needs to be done to archive, and how it should be executed will be examined. We will focus on the practicalities and will draw upon our experience of archiving large clinical trials in the United Kingdom

Matching of WOSCOPS first and subsequent MI events with corresponding Record Linkage events.

<p>WOSCOPS first and subsequent MI events matched with Record Linkage events by cause and date (MI = myocardial infarction; CHD = Coronary Heart Disease; CVD = other cardiovascular disease; CP = non-cardiac chest pain). ‘Other’ matches are for a 'date matched' event with a diagnosis other than MI, CHD, CVD or CP and non-matches have no near date match.</p

Matching of Record Linkage first and subsequent MI events with corresponding WOSCOPS events.

<p>Record Linkage first and subsequent MI events matched with WOSCOPS events. ‘Other’ matches correspond to a date match with events adjudicated by the adjudication committee as not being MI, and non-matches had no near date match.</p

Matching of the Record Linkage strokes and TIAs.

<p>Matching of Record Linkage events for stroke and TIA with WOSCOPS events. The ‘other’ WOSCOPS events were date matches that were originally recorded as MI in WOSCOPS but were adjudicated by the expert committee as not being an MI, and non-matches had no near date match. A first event was defined as <i>either</i> a stroke <i>or</i> a TIA event and could match with a first or subsequent event of the opposing type.</p

Original WOSCOPS results and corresponding results using hospitalised WOSCOPS and Record Linkage events.

<p>Original results from the WOSCOPS study (combining definite and suspect coronary events) compared with those omitting non-hospitalised myocardial infarction (MI) and with results based entirely on record linkage. Data shown are numbers and rates (%) of events for each treatment group, p-value and % risk reduction (RR) for the outcomes of coronary heart disease (CHD) death or MI, non fatal MI and CHD death.</p