| Literature DB >> 35902386 |
Jan W Eriksson1, Björn Eliasson2,3, Louise Bennet4,5, Johan Sundström6,7.
Abstract
This narrative review describes a new approach to navigation in a challenging landscape of clinical drug development in diabetes. Successful outcome studies in recent years have led to new indications and guidelines in type 2 diabetes, yet the number of clinical trials in diabetes is now declining. This is due to many environmental factors acting in concert, including the prioritisation of funding for other diseases, high costs of large randomised clinical trials, increase in regulatory requirements and limited entry of novel candidate drugs. There is a need for novel and cost-effective paradigms of clinical development to meet these and other challenges. The concept of registry-based randomised clinical trials (RRCTs) is an attractive option. In this review we focus on type 2 diabetes and the prevention of cardiovascular and microvascular comorbidities and mortality, using the Swedish SMARTEST trial as an example of an RRCT. We also give some examples from other disease areas. The RRCT concept is a novel, cost-effective and scientifically sound approach for conducting large-scale diabetes trials in a real-world setting.Entities:
Keywords: Clinical outcomes; First-line treatment; Glucose-lowering drugs; Healthcare registry; Macrovascular complications; Microvascular complications; Mortality; Randomised trial; Review; Type 2 diabetes
Mesh:
Substances:
Year: 2022 PMID: 35902386 PMCID: PMC9334551 DOI: 10.1007/s00125-022-05762-x
Source DB: PubMed Journal: Diabetologia ISSN: 0012-186X Impact factor: 10.460
Fig. 1Number of registered clinical trials in diabetes worldwide, 2015–2021. Data were obtained from the WHO [1]. This figure is available as part of a downloadable slideset
Advantages and disadvantages of RRCTs and traditional RCTs performed in normal clinical care and in designated study centres, respectively
| RRCTs | RCTs | |
|---|---|---|
| Characteristics favouring RCTs | Potential bias because of (usually) open label treatment | Minimal bias; masked treatment |
| Only interventions with low safety surveillance needs | Interventions with unknown safety profiles can be studied | |
| Variable delivery of interventions as in routine care | Controlled delivery of fixed interventions | |
| Low control of adherence and compliance | Strict monitoring of adherence and compliance | |
| Varying quality of registry-based outcome data | Standardised and detailed outcome collectiona | |
| Varying resources, competence and study experience at study sites | Well-educated, experienced study staff | |
| Varying methods for laboratory measures | Standardised laboratory measures | |
| Feasible mainly in selected jurisdictions | Can be performed in most regions | |
| Characteristics favouring RRCTs | Generalisable; high external validity | Not generalisable; low external validity |
| Real-world clinical setting | ‘Artificial’ setting | |
| Participants are ‘all comers’ | Participants are highly selected | |
| Low costb | High cost | |
| Simple delivery of study drugsc | Complex delivery of study drugs, on-site; double-masking | |
| Performed in normal clinical care; decentralised | Requires experienced study sites and staff | |
| Automated data collection | Labour-intensive individual data collection | |
| Stimulates quality improvements in routine clinical care | No immediate impact on clinical care | |
| Broad healthcare involvement | Only specialised trial centres are involved | |
| Fast recruitment | Recruitment often challenging and slow | |
| Consent procedures may be simplified (e.g. electronic) | Consent procedures are standardised and tedious |
aFor outcomes that are obtained at trial centre visits but not necessarily for outcomes based on health records or laboratory analyses
bThe cost of the SMARTEST trial [34] has been estimated to be about 10% of the cost of a traditional RCT addressing a similar research question
cTypically, study treatments are not masked in RRCTs; this is, however, possible but has higher costs and a higher degree of complexity
Fig. 2Data capture and flow in an RRCT. Examples of sources of data in an RRCT using multiple registries, here exemplified by the SMARTEST trial [34]. Socialstyrelsen, Swedish National Board of Health and Welfare. This figure is available as part of a downloadable slideset
Fig. 3Procedures for data capture and management in an RRCT. This example is from the SMARTEST study [34] and illustrates that data flow can be complex and requires careful planning. The NDR is a quality-of-care register and is used to obtain endpoints. The Swedish Board of Health and Welfare (Socialstyrelsen [SoS]) administers national healthcare registries, used for obtaining endpoints and adverse events. AEs, adverse events; DMC, data monitoring committee; eCRF, electronic case report form; EOS, end of study; f/u, follow-up; IC, informed consent; IPD, individual patient data; PNR, personal ID number; PROMs, patient-reported outcome measures; Rx, randomised treatment; UCR, Uppsala Clinical Research Center (an academic clinical research organisation run jointly by Uppsala University and Uppsala University Hospital); UU, Uppsala University. This figure is available as part of a downloadable slideset
Fig. 4Schematic overview of the SMARTEST trial. Type 2 diabetes patients with less than 4 years since diagnosis are randomly assigned 1:1 to metformin or dapagliflozin treatment. They are followed until 844 events of the primary composite endpoint have occurred, and the time in the study for each participant is estimated to be 2–6 years. Other treatments are according to routine care and glucose-lowering agents can be amended as needed, while avoiding the introduction of either study drug class. PROMs, patient-reported outcome measures; SGLT2i, sodium–glucose cotransporter 2 inhibitors. This figure is available as part of a downloadable slideset