Surrogate endpoints and non randomized trials
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Surrogate Endpoints and Non-randomized Trials. Roseann White Humble Biostatistician. Type of non-randomized trials. Diagnostic/Natural History trial Single arm trial that shows superiority/non-inferiority in clinical endpoint Example: Safety concerns for placebo or current practice.

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Surrogate Endpoints and Non-randomized Trials

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Surrogate endpoints and non randomized trials

Surrogate Endpoints and Non-randomized Trials

Roseann White

Humble Biostatistician


Type of non randomized trials

Type of non-randomized trials

  • Diagnostic/Natural History trial

  • Single arm trial that shows superiority/non-inferiority in clinical endpoint

    Example: Safety concerns for placebo or current practice


Motivation

Motivation

  • Chiron Corporation developed a method to measure the amount of HIV-1 virus in the blood

  • To obtain approval from FDA for the device, Chiron needed to demonstrate clinical utility

  • Investigators also saw the potential for Viral Load to be a surrogate for HIV-1 disease progression


Prentice criteria for a surrogate endpoint

Prentice Criteria for a surrogate endpoint

Re-statement of Prentice Criteria for a surrogate endpoint

  • Baseline measurements are predictive of outcome

  • Changes in the measurement over time is predictive of outcome

  • Changes in the measurement to external forces (therapy) is predictive of outcome

What if there is no therapy?


Non randomized trial a prospective analysis of a retrospective cohort

Non-randomized trial – a prospective analysis of a retrospective cohort

  • Description of Cohorts

    • 180 seropositive men studied for more than 10 years from the Pittsburgh portion of Multicenter AIDS Cohort Study (MACS)– Mellors, J.W., et. al. Science, 272

    • 1604 men infected with HIV-1 from four university-based clinical centers participating in MACS – Mellors, J.W. et. al. Annals of Internal Medicine, 126

    • ~250 patients from New York Blood Center as part of a PMA submission for the bDNA diagnostic

  • Analysis

    • Logistic regression using baseline values to predict survival

    • Cox proportional hazards model with HIV-1 viral load as a time dependant covariate

    • Treatment effect?


Predictive in stratified populations

Predictive in stratified populations

  • Reprinted from Plasma Viral Load and CD4+ Lymphocytes as Prognostic Markers of HIV-1 Infection

    • John W. Mellors, et.al.Annals 1997 126: 946-954.


Rest of the story

Rest of the story

  • Viral load was used along with CD4 counts as evidence of efficacy for accelerated approval of the protease inhibitors

  • Many efficacy trials measured viral load along with CD4 count

  • FDA Guidance to the industry (2002) recommended the use of viral load for efficacy in accelerated approvals

  • “The Evaluation of Surrogate Endpoints in Practice: Experience in HIV”* by Michael Hughes

    • Uses several different methods to “validate” HIV viral load and CD4 counts as surrogate endpoints

*Chapter 17 in The Evaluation of Surrogate Endpoints edited by T. Burzykowski, et. al. Springer, 2005


Types of non randomized trials

Types of non-randomized trials

  • Quantitative Diagnostic

  • Single arm trial to show superiority or non-inferiority in clinical endpoint


Motivation1

Motivation

  • Randomization is difficult

    • Cost prohibitive

    • Concerns for the safety of the patient

    • Limited population available for recruitment

  • Potential surrogate endpoints available

what's a statistician to do?


Design considerations

Design Considerations

  • Evaluate the risk associated with the surrogate for the product in question

    • If it’s a second generation product, will the surrogate reflect the improvements in the product AND

    • Will the surrogate reflect potential problems?

      Example: Using angiographic binary restenosis as a surrogate at 6 months for drug eluting stent whose drug has not completely eluted at six months


Design considerations con t

Design Considerations (con’t)

  • Choice of comparison – Historical Control versus Objective Performance Criteria

    • Historical Control provides more of an opportunity to demonstrate that the current trial population is similar to the historical population in which the surrogate was based.

    • When using an objective performance criteria, develop a detailed method in which you will “validate” the current population is reflective of the population that surrogate was based.

      • Subgroup analysis where the surrogate shows difference, e.g. diabetics versus non-diabetics


Design considerations con t1

Design Considerations (con’t)

  • Consider a co-primary clinical endpoint where you demonstrate a trend in the same direction as your surrogate

    • Less stringent alpha for superiority

    • Wider delta for non-inferiority


Conclusion

Conclusion

  • Validation of Surrogates endpoint using non-randomized trials is challenging

    • More work needs to be done to develop techniques that do not necessarily require a very effective treatment

  • Use of surrogates in single arm trials requires:

    • Careful consideration as to whether the surrogate will reflect the true performance of the product

    • Use of a historical control or a detail plan of how to assure the current population reflect the population on which the surrogate was based.


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