| Literature DB >> 22315246 |
Tjeerd-Pieter van Staa1, Ben Goldacre, Martin Gulliford, Jackie Cassell, Munir Pirmohamed, Adel Taweel, Brendan Delaney, Liam Smeeth.
Abstract
Entities:
Mesh:
Year: 2012 PMID: 22315246 PMCID: PMC3934788 DOI: 10.1136/bmj.e55
Source DB: PubMed Journal: BMJ ISSN: 0959-8138
Research questions, interventions, and measurements in two feasibility REACT trials initiated within the GPRD
|
| |
| Research questions | Feasibility of REACT trials; pilot for comparative effectiveness of simvastatin and atorvastatin in patients with primary hypercholesterolemia and high cardiovascular disease risk |
| Intervention | Randomisation between simvastatin and atorvastatin in 300 patients; non-blinded |
| Outcome measures | Recruitment rates and technical challenges; changes in lipid levels at three months; duration of statin treatment over time; long term incidence of myocardial infarction, stroke, and death (as measured in the GPRD, linked hospital data, disease registry data, or death certificates) |
|
| |
| Research questions | Feasibility of REACT trials; pilot for comparative effectiveness of antibiotics in patients with an exacerbation of chronic obstructive pulmonary disease and non-purulent sputum |
| Intervention | Randomisation between antibiotic (whichever the general practitioner uses as first line) or usual care in 150 patients; non-blinded |
| Outcome measures | Recruitment rates and technical challenges; patient diary over four weeks of the exacerbations of chronic pulmonary disease tool (EXACT-PRO) as completed on an electronic device; hospital admission over three months (as measured in GPRD and linked hospital data); long term incidence of mortality (as measured in GPRD or linked death certificates) |
Potential opportunities and challenges with REACT trials conducted within EHR databases
| Opportunities | Challenges |
|---|---|
| Long term follow-up at low cost—EHR database and linked datasets can be used to follow study participants over the long term for major clinical outcomes and mortality | Ethical and regulatory approvals—Approval has been achieved for pilot studies; risk adapted regulatory processes may expedite approval for trials of routine treatments in future |
| Easy identification of eligible patients—Candidates are identified automatically through the EHR database from a pool of all patients: clinician is alerted when a patient they are treating meets eligibility criteria | Lengthy consent process—Ongoing research is necessary into the optimum length of consent processes for informed patients; current practice will adversely affect recruitment of clinicians and patients |
| Highly representative study populations—Randomisation at point of routine care means safety and effectiveness of intervention is assessed in usual clinical practice | Research approval at multiple local sites—Different regions have varying requirements for research approval, which is resource intensive |
| Representativeness is measurable—Study population can be compared to patients not enrolled in the trial | Availability of desired outcome data in EHR—Feasibility of collecting additional patient outcome data being assessed (eg, an electronic diary); REACT trials not suited for studies that require major study specific data collection |
| Adverse event monitoring—Daily transfer of EHR records into database: (i) analyses in trial centre of suspected unexpected serious adverse reactions; (ii) comparisons of event rates with those in patients not enrolled in trial | Data quality of EHR data—Recruitment can be restricted to patients with baseline completeness of key covariates; linkages to external data sources permits validation; outcomes can be restricted to outcomes well recorded in EHR |
| Evaluation of research questions of direct relevance to clinicians—Trials only of treatments already in routine use | Trial drug supplies—Research focus is on current therapies prescribed as usual by clinicians: no special supplies needed |
| Validation of major clinical outcomes—Confirmation of outcomes through the linkages and/or by the patient’s clinician; blinded review of complete EHR by experts | Compliance with conventional good clinical practice (GCP) quality standard requirements—With electronic records, there is no difference between data held centrally and locally; a review is ongoing into optimum scrutiny methods for dispersed electronic trials |
| Recruitment for rarer conditions—Multiple sites offer a broader pool of potentially eligible patients | Clinician training in protocol and GCP—Online GCP training package is provided for participating GPs |
| Adaptive designs—Potential to incorporate minimisation during treatment allocation | Clinician time to recruit patients—New IT systems and strategies minimise time and disruption; qualitative research of participating GP feedback is ongoing |
| Testing of study strategies—Cluster randomisation of sites will allow evaluation of study strategies (such as method of collection of additional data) | Lack of blinding of treatment allocation—REACT trials are best suited to measuring major clinical outcomes with clear diagnostic criteria (such as death) |
| Fraud prevention—Newly registered patients not eligible; eligibility and recruitment checks all recorded in the trial IT system; strategy to recruit few patients at many sites | Cross over of study treatments over time—A challenge in most long term trials; cross over may be outcome of interest (indicating treatment failure); statistical techniques may partly deal with this |
| Fraud detection—Clinical records of participants prior to and after the trial are available to the trial investigators; outcomes from linked external sources not controlled by local investigators (such as hospital episodes, mortality register) | Local prescribing rules and performance indicators—GPs may operate under mandatory or incentivised prescribing rules, without any exception for research studies |
| Reduced loss to follow-up—Linkages will ensure that outcomes leading to hospitalisation or death will be captured, even after a patient has left study site | Poor recognition of uncertainty by clinicians—If clinicians are unaware that current practice lacks good quality evidence this may be a challenge for recruitment |
| Linkage of patient data to EHR—Information collected by patients (for example, using smart devices or electronic diaries) could be linked to outcome data recorded in EHR | Uncertainty faced by clinicians not recognised by researchers or funding agencies—Clinicians need to be involved in setting a relevant research agenda |