| Literature DB >> 28314597 |
F H Cafferty1, C Coyle2, S Rowley2, L Berkman3, M MacKensie4, R E Langley2.
Abstract
Opportunities to enter patients into more than one clinical trial are not routinely considered in cancer research and experiences with co-enrolment are rarely reported. Potential benefits of allowing appropriate co-enrolment have been identified in other settings but there is a lack of evidence base or guidance to inform these decisions in oncology. Here, we discuss the benefits and challenges associated with co-enrolment based on experiences in the Add-Aspirin trial - a large, multicentre trial recruiting across a number of tumour types, where opportunities to co-enrol patients have been proactively explored and managed. The potential benefits of co-enrolment include: improving recruitment feasibility; increased opportunities for patients to participate in trials; and collection of robust data on combinations of interventions, which will ensure the ongoing relevance of individual trials and provide more cohesive evidence to guide the management of future patients. There are a number of perceived barriers to co-enrolment in terms of scientific, safety and ethical issues, which warrant consideration on a trial-by-trial basis. In many cases, any potential effect on the results of the trials will be negligible - limited by a number of factors, including the overlap in trial cohorts. Participant representatives stress the importance of autonomy to decide about trial enrolment, providing a compelling argument for offering co-enrolment where there are multiple trials that are relevant to a patient and no concerns regarding safety or the integrity of the trials. A number of measures are proposed for managing and monitoring co-enrolment. Ensuring acceptability to (potential) participants is paramount. Opportunities to enter patients into more than one cancer trial should be considered more routinely. Where planned and managed appropriately, co-enrolment can offer a number of benefits in terms of both scientific value and efficiency of study conduct, and will increase the opportunities for patients to participate in, and benefit from, clinical research.Entities:
Keywords: Adjuvant; aspirin; cancer; co-enrolment; randomised controlled trial
Mesh:
Year: 2017 PMID: 28314597 PMCID: PMC5479364 DOI: 10.1016/j.clon.2017.02.014
Source DB: PubMed Journal: Clin Oncol (R Coll Radiol) ISSN: 0936-6555 Impact factor: 4.126
Fig 1The Add-Aspirin trial.
Fig 2Factors affecting the potential effect of co-enrolment on power. *Intervention being evaluated in the second trial.
Proposed measures for trial teams managing co-enrolment within a randomised controlled trial
| Proposed measure | Purpose | |
|---|---|---|
| Design | Identify trials where co-enrolment may be considered | Assess potential impact and agree where co-enrolment is appropriate in advance |
| Develop appropriate consent process | Ensure that being approached about multiple studies will be acceptable to patients | |
| Ensure compatibility of follow-up schedules, allowing flexibility where possible/appropriate | Minimise extra visits/assessments, ensuring that participation in multiple studies will be acceptable to patients | |
| Provide guidance on co-enrolment in the protocol (and trial website/other documents as appropriate) | Ensure only appropriate co-enrolment takes place and follows the strategy developed for consent and follow-up | |
| Consider stratifying by treatment arm in the first trial in the randomisation algorithm for the second trial (where significant overlap is expected) | Ensure treatment allocation in the second trial is balanced (in terms of those individuals who | |
| Conduct | Implement eligibility checks around co-enrolment at entry | Ensure only appropriate co-enrolment takes place |
| Consider implementation of screening logs | Identify any recruitment issues as a result of co-enrolment decisions or any barriers to co-enrolment | |
| Monitoring | Collect and regularly review co-enrolment information, including treatment allocation in the other trial, on case report forms | Active monitoring with the potential to take action – by capping recruitment from one arm, for example – if a large imbalance occurs (although this is unlikely) |
| Establish agreements to share information between data monitoring committees (blinded trials) | It may be appropriate for monitoring to be carried out by data monitoring committees in the case of blinded trials | |
In discussion with participant representatives and/or patient and public involvement groups.
This will not ensure balance overall if participants from the different treatment arms of the first trial enter the second trial at different rates. Thus, careful monitoring is still required.
Example power calculations to assess the potential impact of co-enrolment
| Modelling assumptions | Estimated impact on trial X | ||||||
|---|---|---|---|---|---|---|---|
| Effect of aspirin on 5 year survival | Participation rates in Add-Aspirin | 5 year survival in trial X with co-enrolment | Power (loss/gain in power) | Extra patients (OR follow-up) needed for 80% power | |||
| Control | Intervention | Control | Intervention | Difference | |||
| Trial X result is positive (5 year survival 55% control versus 45% intervention) in the absence of co-enrolment | |||||||
| 6% | 10% | 10% | 45.4% | 55.4% | 10.0% | 79.9% | 2 (1 month) |
| 20% | 20% | 45.8% | 55.8% | 10.0% | 79.9% | 3 (1 month) | |
| 30% | 30% | 46.2% | 56.2% | 10.0% | 79.8% | 5 (1 month) | |
| 10% | 15% | 45.4% | 55.6% | 10.2% | 81.5% | – | |
| 10% | 20% | 45.4% | 55.8% | 10.4% | 82.9% | – | |
| 15% | 30% | 45.6% | 56.2% | 10.6% | 84.3% | – | |
| 15% | 10% | 45.6% | 55.4% | 9.8% | 78.3% | 44 (3 months) | |
| 20% | 10% | 45.8% | 55.4% | 9.6% | 76.6% | 89 (5 months) | |
| 30% | 15% | 46.2% | 55.6% | 9.4% | 74.8% | 138 (8 months) | |
| 10% | 10% | 10% | 45.7% | 55.7% | 10.0% | 79.9% | 3 (1 month) |
| 20% | 20% | 46.3% | 56.3% | 10.0% | 79.8% | 5 (1 month) | |
| 30% | 30% | 47.0% | 57.0% | 10.0% | 79.8% | 7 (1 month) | |
| 10% | 15% | 45.7% | 56.0% | 10.3% | 82.4% | – | |
| 10% | 20% | 45.7% | 56.3% | 10.7% | 84.7% | – | |
| 15% | 30% | 46.0% | 57.0% | 11.0% | 86.8% | – | |
| 15% | 10% | 46.0% | 55.7% | 9.7% | 77.2% | 75 (5 months) | |
| 20% | 10% | 46.3% | 55.7% | 9.3% | 74.2% | 154 (9 months) | |
| 30% | 15% | 47.0% | 56.0% | 9.0% | 71.1% | 244 (15 months) | |
| Trial X result is negative (5 year survival 45% in both arms) in the absence of co-enrolment | |||||||
| 6% | 10% | 10% | 45.4% | 45.4% | 0.0% | ||
| 20% | 20% | 45.8% | 45.8% | 0.0% | |||
| 30% | 30% | 46.2% | 46.2% | 0.0% | |||
| 10% | 15% | 45.4% | 45.6% | 0.2% | |||
| 10% | 20% | 45.4% | 45.8% | 0.4% | |||
| 15% | 30% | 45.6% | 46.2% | 0.6% | |||
| 15% | 10% | 45.6% | 45.4% | −0.2% | |||
| 20% | 10% | 45.8% | 45.4% | −0.4% | |||
| 30% | 15% | 46.2% | 45.6% | −0.6% | |||
| Trial X result is negative (5 year survival 45% in both arms) in the absence of co-enrolment | |||||||
| 10% | 10% | 10% | 45.7% | 45.7% | 0.0% | ||
| 20% | 20% | 46.3% | 46.3% | 0.0% | |||
| 30% | 30% | 47.0% | 47.0% | 0.0% | |||
| 10% | 15% | 45.7% | 46.0% | 0.3% | |||
| 10% | 20% | 45.7% | 46.3% | 0.7% | |||
| 15% | 30% | 46.0% | 47.0% | 1.0% | |||
| 15% | 10% | 46.0% | 45.7% | −0.3% | |||
| 20% | 10% | 46.3% | 45.7% | −0.7% | |||
| 30% | 15% | 47.0% | 46.0% | −1.0% | |||
The table illustrates the potential impact of co-enrolment into Add-Aspirin on the power of a hypothetical study, trial X. Selected results are shown from models performed under a range of assumptions about the factors listed in Figure 2, including scenarios felt to illustrate the largest plausible impact on power.
Trial X: A hypothetical two-arm superiority randomised controlled trial of a new peri-operative chemotherapy regimen versus standard in gastro-oesophageal patients. Designed with 80% power to detect a 10% improvement (from 45% to 55%) in survival at 5 years, requiring 500 patients per arm. Patients who are disease free at the end of treatment may become eligible for Add-Aspirin.
A 6% survival benefit at 5 years is hypothesised in Add-Aspirin (gastro-oesophageal). Models are repeated for larger benefits to illustrate potential effects on power.
A range of participation rates are used to assess potential impact – actual rates are unlikely to reach 30% (limited by overlap in recruiting centres and recruitment periods, as well as trial X participants being ineligible or unwilling to participate in Add-Aspirin). Differences in rates between arms are also unlikely to be as large as illustrated here.