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Losses to Follow-up in Clinical Trials

Threats to the Interpretation of Clinical Trials. Inadequately powered studiesSurrogate markers and short follow-upPoor follow-upAbsence of pre-specified monitoring plans. . In order to carry out a proper intention-to-treat analysis all patients must be followed. Intention-to-treat - an analysis which includes all randomized patients in the groups to which they were randomly assigned, regardless of their compliance with the entry criteria, regardless of the treatment they actually receive1146

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Losses to Follow-up in Clinical Trials

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    1. Losses to Follow-up in Clinical Trials

    3. In order to carry out a proper intention-to-treat analysis all patients must be followed Intention-to-treat - an analysis which includes all randomized patients in the groups to which they were randomly assigned, regardless of their compliance with the entry criteria, regardless of the treatment they actually received, and regardless of subsequent withdrawal from treatment or deviation from protocol.

    4. SMART Study Design

    5. Primary Endpoint Findings of SMART

    6. Lost-to-Follow-up A trial participant for whom the outcome of interest is not known – MISSING DATA at the time routine reports are prepared for sites, Executive Committee and Protocol Team at the time of interim analyses for Data and Safety Monitoring Committee for final report prepared by protocol team

    7. Losses Can Be Due To: A patient moving and leaving no contact, withdrawal of consent. Competing events, e.g., a patient who dies in a trial where the primary endpoint is a non-fatal event or a follow-up measurement (not relevant for primary endpoint of SMART). Protocols that do not require collection of some or all data after treatment is discontinued (in general treatment discontinuation should not equate with study discontinuation).

    8. Loss Definition Depends on Outcome Primary Endpoint AIDS or death Death 48 week HIV RNA Definition Unknown event status at end of trial Unknown vital status at end of trial Death prior to 48 weeks, missed 48 week visit, no blood test

    9. Operational Definition of Loss for Trials Like SMART For interim analyses – more than 6 months with no data (no patient forms) At end of trial -- event status unknown at closing date (the calendar date chosen to ensure the target number of events has been achieved) – usually established via a closeout visit.

    10. Key Points Advantages of randomization are threatened when major outcomes are missing – no longer comparing like with like on average. Missing data can lead to biased estimates of treatment differences. Models for handling missing data involve unverifiable assumptions since reasons for missing data may not be known. Therefore, focus must be on preventing missing data (losses).

    11. Etiology of Losses

    12. Predictors of Losses to Follow-up in Other Studies Patient characteristics: Younger age Smokers Socioeconomic status – employment, stable housing, education Trial characteristics: Duration of follow-up and endpoint Clinical research site (experience, number of patients enrolled, staff turnover) Protocol data collection plan after treatment is discontinued

    13. Implications of Losses Loss of power due to smaller effective sample size Wrong answer (bias) Findings which are not credible

    14. Reality of Long-Term Field Work Some losses are inevitable. So what do we do?

    15. Planning for Losses Design - easily ascertainable endpoints - target population - plan for treatment failures - inflate sample size Training to ensure local systems are established for minimizing losses and tracking patients Trial monitoring to identify problem areas (predictors)

    18. SMART Protocol According to Data Analysis Plan: “The primary analysis will be intention-to-treat”. Implication: All patients must be followed for the primary endpoint (AIDS or death) until the end of the study.

    19. SMART Protocol According to Trial Design: “…the study will continue until 910 events occur in order to provide the desired power”. ”Based on the assumptions…6,000 patients… followed for an average of 7.5 years are required”. Implication of losses: if there are losses, sample size will have to be larger or trial duration longer.

    20. SMART Protocol According to Data Monitoring Guidelines: “The trial may be terminated or modified…if 1 year lost-to-follow-up is > 2.5%, or projected overall 3-year lost-to-follow-up is > 10% or the absolute difference between treatment groups is more than 7.5%”. Implication: routine, timely reports for sites and discussion at regular meetings with investigators are important.

    21. Etiology Suggests the Following for Primary Prevention Write protocol with minimization of losses in mind (do not overburden patients and staff). Avoid complicated and cumbersome record keeping. Make it easy to obtain prescriptions. Choose easily ascertainable endpoints. Select sites in a convenient location with demonstrated record of excellent follow-up. Train study staff on the importance of follow-up, communications and negotiations with patients Reimburse investigators for follow-up, not just enrollment Fully inform patients of trial requirements during consent process.

    22. Etiology Suggests the Following for Primary Prevention (cont.) Collect contact information at entry. Adopt a flexible appointment schedule. Remind patients about appointments and follow-up immediately after missed appointments. Minimize waiting time during appointments. Provide reports to staff to monitor follow-up completeness. Insist on the highest standards – no losses.

    23. After Trouble Begins – Secondary Prevention Telephone contacts and home visits. “Data collection only” (reduce demands of participation). Collect locator information at entry and regularly update it in order to contact friends and to use central registries for vital status.

    25. How bad can the lost to follow-up rate be and still have valid results? Anything but zero is bad (this should be the goal) If number of losses exceeds number of events, results are questionable < 5% is okay, but if > 20%, do not believe the results If > 0% and differential by group, question the results If > 0%, and different assumptions concerning losses yield different trial results, e.g., P<0.05 to P> 0.05.

    26. Flow Diagram for SMART Study

    27. ADAPT Study (PLoS Clinical Trials Nov. 2006)

    28. Recommendations: Design and Monitoring Establish high standards Consider the possibility of losses in the design, e.g., choice of endpoint, run-in period, adjustment (inflation) of sample size Ensure sites have systems for minimizing losses – prevention is always best! Monitor progress, and if necessary, take corrective action

    29. Recommendations: Reporting Define losses in trial reports and report them separately for major safety and efficacy outcomes. Report number (%) of missed follow-up visits by treatment group Discuss implications of missing data

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