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D. Zucker, C. Schmid, M. McIntosh, R. D’Agostino, H. Selker, Joseph Lau (1997)
Combining single patient (N-of-1) trials to estimate population treatment effects and to evaluate individual patient responses to treatment.Journal of clinical epidemiology, 50 4
Deborah Caldwell, A. Ades, J. Higgins (2005)
Simultaneous comparison of multiple treatments: combining direct and indirect evidenceBMJ : British Medical Journal, 331
G. Guyatt, David Sackett, Jonathan Adachi, R. Roberts, J. Chong, D. Rosenbloom, D. Pharm., J. Keller (1988)
A clinician's guide for conducting randomized trials in individual patients.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne, 139 6
A. Glenny, D. Altman, F. Song, C. Sakarovitch, J. Deeks, R. D'amico, M. Bradburn, A. Eastwood (2005)
Indirect comparisons of competing interventions.Health technology assessment, 9 26
G. Lu, A. Ades (2004)
Combination of direct and indirect evidence in mixed treatment comparisonsStatistics in Medicine, 23
H. Kraemer, E. Frank, D. Kupfer (2006)
Moderators of treatment outcomes: clinical, research, and policy importance.JAMA, 296 10
To the Editor: In their Commentary, Dr Kraemer and colleagues1 draw attention to the importance of moderators of treatment outcomes, the often unsatisfactory way these are dealt with (if at all) in randomized clinical trials (RCTs), and the potentially serious consequences of this neglect on patient care. They propose that every RCT should include a search for putative moderators of treatment outcome. Although acknowledging that positive results of such analyses rarely provide proof of the existence of these moderators, they stress that the importance resides in the hypotheses that the analyses generate. These hypotheses can then be tested in subsequent adequately powered and populated RCTs. However, it may take years to design, acquire adequate funding for, and execute such an RCT. As an alternative, conducting N-of-1 trials2 can be valuable to further investigate information on moderators of treatment outcome. As a hypothetical example, suppose an RCT had been conducted to test the efficacy of drug treatment of primary Raynaud phenomenon, that no overall benefit of the drug had been found, but analysis of putative moderators of treatment outcome had suggested that women might respond favorably, although this result was not statistically significant. Women with Raynaud phenomenon could then be included in N-of-1 trials, in which they would be treated in a double-blind crossover design with multiple treatment pairs with either the drug or a placebo in random order.2 The presence or absence of differences in symptom scores during treatment would then prove or disprove the effectiveness of this drug for the patient. Pooling the results of all of these N-of-1 trials may substantiate that sex is a moderator of treatment outcome.3 Moreover, comparison of responders and nonresponders in these N-of-1 trials may be used to identify additional moderators of treatment outcome. This approach may obviate the need for RCTs, which would be a great boon in the case of rare chronic diseases. It has an additional advantage in that daily patient care can be integrated with clinical research. N-of-1 trials have their own limitations. They are not applicable to surgical or acute medical conditions. However, for chronic medical conditions, they may be invaluable in the quest for “tailored therapy,” one of the holy grails of clinical medicine. Back to top Article Information Financial Disclosures: None reported. References 1. Kraemer HC, Frank E, Kupfer DJ. Moderators of treatment outcomes: clinical, research, and policy importance. JAMA. 2006;296:1286-128916968853Google ScholarCrossref 2. Guyatt G, Sackett D, Adachi J. et al. A clinician's guide for conducting randomized trials in individual patients. CMAJ. 1988;139:497-5033409138Google Scholar 3. Zucker DR, Schmid CH, McIntosh MW, D'Agostino RB, Selker HP, Lau J. Combining single patient (N-of-1) trials to estimate population treatment effects and to evaluate individual patient responses to treatment. J Clin Epidemiol. 1997;50:401-4109179098Google ScholarCrossref
JAMA – American Medical Association
Published: Jan 10, 2007
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