If we accept that Ayurvedic medicines are likely to be safer, economical and easy to access and use, then efficacy wise an “equivalence trial” may suffice. The conventional argument in support of “equivalence trials” goes like this:[6
In conventional superiority drug trial design, the null hypothesis (Ho) states that both the treatments have no difference, whereas the alternate hypothesis (H1) states that they are not equal.
Ho: effect of Treatment A = effect of Treatment B, i.e., Ho: A = B and H1: A is not equal to B (two-sided H1) or A > B or A < B (one-sided H1), where “A” is some Ayurvedic drug and “B” standard drug (modern active comparator) available/used currently for this same disorder.
This Ho is tested (by appropriate test). If we do not reject Ho (i.e., test statistic is not significant at the given alpha level), we say that “evidence is not enough to prove A = B”. This is “lack of evidence” of equivality. However, “absence of evidence is not evidence of absence”. Therefore, if we intend to prove “equivality”, the answer is “Equivalence Trial” as the aim of equivalence trial is to show the therapeutic equivalence of two treatments.
Quite often it is seen in the literature that the authors conclude “equivalence” after a nonsignificant result (‘negative trial’) is found in a trial that was actually designed to demonstrate real difference. It is important to note that nonsignificance does not mean equivalence. An equivalence trial is designed to confirm the absence of a meaningful difference between treatments. Though the absolute equivalence can never be demonstrated, it is possible to assert that the true difference is unlikely to be outside the “equivalence” range. In this case, it is more informative to conduct the analysis by computing the CI of the difference between the two treatments although there are closely related methods, using significance test procedures. A margin of clinical equivalence is chosen by defining the largest difference that is clinically acceptable, so that a difference bigger than this would matter in practice. If we have a predefined range of equivalence as an interval from –
, we can then simply check whether the CI centered on the observed difference lies entirely between –
and +. If it does, equivalence is demonstrated;[7
] if it does not, there is still room for doubt. Possible results of the comparison of a CI with a predefined range of equivalence are shown in .
Clinical approach for analysis of equivalence trials
Any CI which does not include zero corresponds to a statistically significant difference. In equivalence testing, the relevant null hypothesis is that a difference of at least
exists, and the trial is targeted at disproving this in favor of the alternative that no difference exists (i.e., the difference is clinically unimportant). This formulation is important in validating the intuitive CI procedure, and it also helps in calculating sample sizes. Claim for equivalence must be based in an equivalence design and not inferred after a negative result of a trial designed to show difference.[8
Values need to be specified for the range of equivalence (
) and the probabilities of type I and II errors [α (alpha), and β (beta), respectively]. The choice of
is difficult and requires extensive debate with knowledgeable clinical experts. The selection of α and follows similar lines as for comparative trials. The use of a 95% CI in an equivalence trial, as recommended by the European Committee for Proprietary Medicinal Products (FDA also approves this design) in its note for guidance on biostatistics, corresponds to a value for α of 0.025. However, is treated identically, and is generally set to 0.1 (to give a power of 90%) or 0.2 (to give a power of 80%). The distinction between one-sided and two-sided tests of statistical significance also carries over into the CI approach. For a one-sided test, equivalence is declared if the lower one-sided confidence limit exceeds –
. This approach is indicated when the objective is to ensure that the new agent is not inferior to the standard and then the trial is called “non-inferiority”. E9[4
] Guideline of ICH defines “non-inferiority trial” as “a trial with the primary objective of showing that the response to the investigational product is not clinically inferior to a comparative agent”. It also highlights the fact that there are well-known difficulties associated with the use of the active control equivalence (or non-inferiority) trials that do not incorporate a placebo. These relate to the implicit lack of any measure of internal validity (in contrast to superiority trials), thus making external validation necessary. Moreover, active comparators should be chosen with care. An example of a suitable active comparator would be a widely used therapy whose efficacy in the relevant indication has been clearly established and quantified in well-designed and well-documented superiority trial(s) and which can be reliably expected to exhibit similar efficacy in the contemplated active control trial. To this end, the new trial should have the same important design features (primary variables, the dose of the active comparator, eligibility criteria, etc.) as the previously conducted superiority trials in which the active comparator clearly demonstrated clinically relevant efficacy, taking into account advances in medical or statistical practice relevant to the new trial. It is prudent to add that in equivalence (or non-inferiority) trials, the comparator should be a well-accepted standard of care; otherwise, the conclusion may be confounded by “assay sensitivity”. This important issue is discussed at length in the ICH’s E10.[9
The most common approaches to the analysis of randomized trials are “intention to treat (ITT)” and “per protocol (PP)” analyses. In an ITT analysis, patients are analyzed according to their randomized treatment, whereas PP analysis compares patients according to the treatment actually received and includes only those patients who satisfied the entry criteria and properly followed the protocol. In an equivalence trial, it is probably best to carry out both the types of analysis and hope to show equivalence in either case. ICH’s E9[4
] states that in superiority trials, ITT is used in the primary analysis; but in equivalence or non-inferiority trial, use of ITT is generally not conservative. Subjects who withdraw or drop out of the treatment group or the comparator group will tend to have lack of response, and hence the results of using ITT may be biased toward demonstrating equivalence.[4
] With respect to other aspects of design (like double blinding of medication, randomization) and analysis, equivalence trials are similar in nature to comparative trials. More details of equivalence trials can be found in literature.[10
The utility of this philosophy was demonstrated in one of the randomized, double-blind, multicenter equivalent design drug trials conducted under a sponsorship by the Council of Scientific and Industrial Research, Government of India, New millennium Indian technology leadership initiative (NMITLI) Arthritis project. We have reported a therapeutic equivalence between standardized Ayurvedic drugs, celecoxib and glucosamine, to treat symptomatic osteoarthritis of the knees. This trial also showed good safety profile for the Ayurvedic drugs.
There could be more than one active comparator and new drug formulations to be tested in one trial which was the case in the NMITLI drug trial cited above. In any case, analysis should be based on “CIs” and this also carries implications for the estimation of the required number of patients at the design stage.
Pragmatic trials and “black-box” design
A case is made for the appropriate use and relevance of pragmatic trials in the evaluation of alternative and complementary medicine in the article by Hugh MacPheron.[13
] The main strength of pragmatic trials is that they can evaluate a therapy as it is used in normal practice. Pragmatic trial could be used to test an overall “package” of care (similar to WHO’s “black-box” design) and it is easier to grant the practitioners the freedom to treat the patients normally, allowing them to use individual approaches for different patients. It may be specifically noted that pragmatic trial philosophy goes well with the equivalence trial.
In short, the pragmatic trial concept is useful in view of the complexity of Ayurveda intervention. For such concept, trial could be equivalence and this fact is just pointed out here.