Literature DB >> 17128427

Active-controlled, non-inferiority trials in oncology: arbitrary limits, infeasible sample sizes and uninformative data analysis. is there another way?

Kevin J Carroll1.   

Abstract

In oncology, it may not always be possible to evaluate the efficacy of new medicines in placebo-controlled trials. Furthermore, while some newer, biologically targeted anti-cancer treatments may be expected to deliver therapeutic benefit in terms of better tolerability or improved symptom control, they may not always be expected to provide increased efficacy relative to existing therapies. This naturally leads to the use of active-control, non-inferiority trials to evaluate such treatments. In recent evaluations of anti-cancer treatments, the non-inferiority margin has often been defined in terms of demonstrating that at least 50% of the active control effect has been retained by the new drug using methods such as those described by Rothmann et al., Statistics in Medicine 2003; 22:239-264 and Wang and Hung Controlled Clinical Trials 2003; 24:147-155. However, this approach can lead to prohibitively large clinical trials and results in a tendency to dichotomize trial outcome as either 'success' or 'failure' and thus oversimplifies interpretation. With relatively modest modification, these methods can be used to define a stepwise approach to design and analysis. In the first design step, the trial is sized to show indirectly that the new drug would have beaten placebo; in the second analysis step, the probability that the new drug is superior to placebo is assessed and, if sufficiently high in the third and final step, the relative efficacy of the new drug to control is assessed on a continuum of effect retention via an 'effect retention likelihood plot'. This stepwise approach is likely to provide a more complete assessment of relative efficacy so that the value of new treatments can be better judged.

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Year:  2006        PMID: 17128427     DOI: 10.1002/pst.218

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  3 in total

1.  Creative trial design in RA: optimizing patient outcomes.

Authors:  Maya H Buch; Sue Pavitt; Mahesh Parmar; Paul Emery
Journal:  Nat Rev Rheumatol       Date:  2013-02-05       Impact factor: 20.543

2.  Modelling of the outcome of non-inferiority trials by integration of historical data.

Authors:  Alberto Russu; Erik van Zwet; Giuseppe De Nicolao; Oscar Della Pasqua
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-08-21       Impact factor: 2.745

Review 3.  Antimicrobial agents for complicated skin and skin-structure infections: justification of noninferiority margins in the absence of placebo-controlled trials.

Authors:  Brad Spellberg; George H Talbot; Helen W Boucher; John S Bradley; David Gilbert; W Michael Scheld; John Edwards; John G Bartlett
Journal:  Clin Infect Dis       Date:  2009-08-01       Impact factor: 9.079

  3 in total

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