Clinical Significance And Clinical Equivalence

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As indicated in the hypotheses of (2.6.1), the objective of most clinical trials is to detect the existence of predefined clinical difference using a statistical testing procedure such as unpaired two-sample t-test. If this predefined difference is clinically meaningful, then it is of clinical significance. If the null hypothesis in (2.6.1) is rejected at the a level of significance, then we conclude that a statistically significant difference exists between treatments. In other words, an observed difference that is unlikely to occur by chance alone is considered a statistically significant difference. However, a statistically significant difference depends on the sample size of the trial. A trial with a small sample size usually provides little information regarding the efficacy and safety of the test drug under investigation. On the other hand, a trial with a large sample size provides substantial evidence of the efficacy of the safety of the test drug product. An observed statistically significant difference, which is of little or no clinical meaning and interpretation, will not be able to address the scientific/clinical questions that a clinical trial was intended to answer in the first place.

The magnitude of a clinically significant difference varies. In practice, no precise definition exists for the clinically significant difference, which depends on the disease, indication, therapeutic area, class of drugs, and primary efficacy and safety endpoints. For example, for antidepressant agents (e.g., Serzone), a change from a baseline of 8 in the Hamilton depression (Ham-D) scale or a 50% reduction from baseline in the Hamilton depression (Ham-D) scale with a baseline score over 20 may be considered of clinical importance. For antimicrobial agents (e.g., Cefil), a 15% reduction in bacteriologic eradication rate could be considered a significant improvement. Similarly, we could also consider a reduction of 10 mm Hg in sitting diastolic blood pressure as clinically significant for ACE inhibitor agents in treating hypertensive patients.

The examples of clinical significance on antidepressant or antihypertensive agents are those of individual clinical significance, which can be applied to evaluation of the treatment for individual patients in usual clinical practice. Because individual clinical significance only reflects the clinical change after the therapy, it cannot be employed to compare the clinical change of a therapy to that of no therapy or of a different therapy. Temple (1982) pointed out that in evaluation of one of phase II clinical trials for an ACE inhibitor, although the ACE inhibitor at 150 mg t.i.d. can produce a mean reduction from baseline in diastolic blood pressure of 16 mm Hg, the corresponding mean reduction from baseline for the placebo is also 9 mm Hg. It is easy to see that a sizable proportion of the patients in the placebo group reached the level of individual clinical significance of 10 mm Hg . Therefore, this example illustrates a fact that individual clinical significance alone cannot be used to establish the effectiveness of a new treatment.

For assessment of efficacy/safety of a new treatment modality, it is, within the same trial, compared with either a placebo or another treatment, usually the standard therapy. If the concurrent competitor in the same study is placebo, the effectiveness of the new modality can then be established, based on some primary endpoints, by providing the evidence of an average difference between the new modality and placebo that is larger than some prespeci-fied difference of clinical importance to investigators or to the medical/scientific community. This observed average difference is said to be of the comparative clinical significance. The ability of a placebo-controlled clinical trial to provide such observed difference of both comparative clinical significance and statistical significance is referred to as assay sensitivity. A similar definition of assay sensitivity is also given in the ICH E10 guidance entitled, Choice of Control Group in Clinical Trials (ICH, 1999).

On the other hand, when the concurrent competitor in the trial is the standard treatment or other active treatment, then efficacy of the new treatment can be established by showing that the test treatment is as good as or at least no worse than standard treatment. However, under this situation, the proof of efficacy for the new treatment is based on a crucial assumption that the standard treatment or active competitor has established its own efficacy by demonstrating a difference of comparative clinical significance with respect to placebo in adequate placebo-controlled studies. This assumption is referred to as the sensitivity-to-drug-effects (ICH E10, 1999).

Table 2.7.1 presents the results first reported in Leber (1989), which was again used by Temple (1983) and Temple and Ellenberg (2000) to illustrate the issues and difficulties in

Table 2.7.1 Summary of Means of Hamilton Depression Scales of Six Trials Comparing Nomifensine, Imipramine, and Placebo

Common Baseline Four-week Adjusted Mean (Number of Subjects)

Table 2.7.1 Summary of Means of Hamilton Depression Scales of Six Trials Comparing Nomifensine, Imipramine, and Placebo

Common Baseline Four-week Adjusted Mean (Number of Subjects)






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