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 Table of Contents  
PERSPECTIVE
Year : 2022  |  Volume : 6  |  Issue : 3  |  Page : 96-100

Methodological attributes and statistical tools in Ayurveda clinical trials—Are we missing something?


Central Council for Research in Ayurvedic Sciences, Janakpuri, New Delhi, India

Date of Submission07-Sep-2022
Date of Acceptance21-Sep-2022
Date of Web Publication01-Nov-2022

Correspondence Address:
Dr. Adarsh Kumar
Central Council for Research in Ayurvedic Sciences, Janakpuri, New Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jras.jras_131_22

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  Abstract 

In recent decades, few uncertainties have been expressed about the quality of research in Ayurveda, based on aspects such as the rationale for undertaking the study, accurate research gap analysis, study methodology, data collection, data analysis, and relevant interpretation of the findings. It might be argued that the principles and practice of different systems of medicine vary too much to allow universal application of existing methodological or reporting guidelines that predominantly cater to contemporary medicine. In the present-day research, many researchers find it difficult to provide an accurate and reliable assessment of the outcomes that can form a scientific evidence base for Ayurveda. ICH E9 (R1) addendum to the guidelines on statistical principles for clinical trials and methods in 2020 has revamped the approaches to designing clinical trials and the effective use of statistical tools to convey the study outcomes. This article attempts to present the statistical implications and various methodological aspects that are often missed, misinterpreted, or left unaddressed by researchers in Ayurveda clinical research. Insight on the vital components of good clinical research such as designing aspects, sampling, randomization, and data analysis is provided in brief.

Keywords: Ayurveda, clinical relevance, research, statistical implications


How to cite this article:
Kumar A. Methodological attributes and statistical tools in Ayurveda clinical trials—Are we missing something?. J Res Ayurvedic Sci 2022;6:96-100

How to cite this URL:
Kumar A. Methodological attributes and statistical tools in Ayurveda clinical trials—Are we missing something?. J Res Ayurvedic Sci [serial online] 2022 [cited 2022 Dec 9];6:96-100. Available from: http://www.jrasccras.com/text.asp?2022/6/3/96/360157




  Introduction Top


The main objective behind designing a clinical trial is to design a study that would derive meaningful outcomes that would offer greater benefit to the ailing mankind. A systematically planned and well-designed clinical research depends on methodological soundness, identifying valid outcome measures along with precise tools for its measurement and application of appropriate statistical tests, in an ethical way addressing the World Medical Association Declaration of Helsinki 2013. Explanatory clinical trials are the most common type of clinical trials taken up in Ayurveda research, most probably because generating evidence on the efficacy and safety of Ayurveda interventions is the major objective for planning research in Ayurveda. The components of the clinical trial that lends robustness and reliability to the study are the study hypothesis, rationale for the selection of study interventions, study design, study population identified by well-defined selection criteria, control group, randomization, blinding, sample size estimated on appropriate statistical methods, type, dose, and duration of intervention, well-defined and measurable outcome measures, and the judicious use of statistical methods to effectively derive the results.

Data collection is an important aspect for further data analysis to derive outcomes based on the research and unbiased data reporting as per the protocol, and impeccable arrangements of observations are critical requirements in data collection. The collected data are meaningless unless it is analyzed using suitable statistical methods. The statistical analysis output is a numeric expression of the research outcome, which further needs to be understood, correlated, and presented for the assessment of its hypothesized efficacy, effectiveness, and safety. Major issues encountered in clinical trials include the failure in the critical assessment of the existing literature to identify knowledge gaps, delineating specific selection criteria to enroll target population, failure of specifying the level of significance (called the alpha level) that is acceptable and the exact statistical tests methods used, inadequate and underpowered sample size, inadequate bias control measures, failure in recruiting and retaining target participants, lacunae in conceptualizing and designing a clinical trial design and methodology including statistical analysis plans, inadequate and improper reporting of dropped-out participants, missing data, etc., that have the potential to alter the study outcomes. The proper utilization of statistics, for sample-size calculation, data collection, and analysis by applying proper statistical tests, is the cornerstone in translating research outcomes into clinical setting.

According to Singh, the last 50 years’ worth of Ayurveda studies has not yielded very effective results except the very productive literary research exercise.[1] Several clinical studies reported an insufficient sample size, a lack of valid statistical basis to support the sample size, and poor relevance to outcomes.[2],[3],[4],[5] Such issues may be a cause regarding the acceptability concerns of Ayurveda researchers at the global level.[6] A good proportion of Ayurveda clinical research is conducted in academic settings but still has the potential to generate evidence base in support of Ayurveda formulations, therapy, and practices.

Regulatory guidelines such as the International Conference on Harmonization guideline on Good Clinical Practice (ICH GCP) can be effectively used for ensuring ethical and scientific quality for the design, conduct, and reporting of clinical trials involving human subjects. Many novice researchers may feel at odds when the research outcomes are unanticipated, especially when studies are conducted in resource- or time-limited settings.

In Ayurveda research settings, many things are often inaddressed or missed while adopting the contemporary methods to address the complex and confounding mechanisms of Ayurveda holistic science. This article attempts to address the methodological and statistical implications to be considered while planning clinical trials in Ayurveda.


  Choosing a Topic for Research Top


Clinical research is a unique area that desires exceptional contributions to patient care and translating it into policy and decision-making for the greater good of mankind. The first step in any type of research is identifying the research area and defining the research problem precisely. The source for identifying a research question may be literary sources, clinical experiences, knowledge from codified information available in classical treatises, existing theories, and available evidence in the form of publications. A research topic shall be finalized by addressing its relevance, gap identified in existing knowledge, feasibility of study addressing the ethical, financial, and time aspects, availability of resources, and applicablicability and acceptability of the study. Much of Ayurveda clinical research aims to explore various aspects of Ayurveda or to generate evidence of the clinical efficacy of different Ayurveda formulations in treating common diseases.[7] However, there are wider range of areas where research in Ayurveda is much relevant in the present era, such as in the areas such as cost-effectiveness, tool development, pharmacoepidemiology, systematic reviews, public health, and implementation research.


  Literature Review Top


Literature review is very important to avoid duplication of already done work, to refine the research question, and to explore research approaches that might be effectively used in deriving the desired outcomes proposed in the clinical study. In Ayurveda, the source of literature review includes classical texts, monographs, surveys, technical reports, original articles, review articles, existing guidelines for diagnosis and practice, internet sources, databases, and relevant information from national and international guidelines pertaining to research.


  Formulation of Research Question, Hypothesis, and Objectives Top


Optimizing time and resources to formulating a good research question is very vital to the subsequent finalization of the research protocol. The process of developing a research question generally stems from unmet needs or identified knowledge gaps in clinical practice and research. Most often, researchers work with a PICOT framework (population, intervention, comparator, outcome, and time frame), also considering the criteria of feasibility, novelty, ethics, and relevance. Accordingly, hypothesis shall be specific, capable of being tested, unambiguous, and appropriately designed stating the expected relationship between the independent and dependent variables. The objectives should be defined in logical, coherent manner phrased in operational terms that would enable it to be narrowed to an area of interest, thereby avoiding unnecessary data collection.


  Methodological Aspects Top


Study designs

Descriptive studies are conducted to generate/formulate hypothesis, whereas experimental studies are done to prove the hypothesis. Ayurveda clinical research most often uses experimental/interventional designs. A good research design should be flexible, appropriate, economical, and efficient in deriving outcomes. Although nonrandomized studies are conducted in Ayurveda for exploratory trials or in studies conducted on a pilot basis to assess feasibility or generate preliminary data for a larger study, randomized controlled trials are considered as the gold standard for contemporary research, though it does have many methodological constraints when customized for clinical trials in Ayurveda. Randomized controlled trials randomize the study participants into the trial group and placebo/standard of care/control group to derive the efficacy or effectiveness of an Ayurveda intervention. randomised controlled trials (RCTs)in Ayurveda can employ any of the designs such as parallel group design or crossover designs. Appropriate protocol development, selection of experimental and control group population, randomization, allocation, follow-up, and assessment as per the protocol are vital for the execution of a planned RCT.

Study population

The specific subject population shall be selected based on the selection criteria that align with the study variables. The protocol for clinical studies shall delineate inclusion, exclusion, and withdrawal criteria during the designing stage itself.

Control group

A control group (either active or placebo or no treatment control groups) enables the comparison of the effect of the trial interventions over the control group. Placebo control is technically a very difficult aspect in Ayurveda clinical studies because of the characteristic nature, odor, consistency, and taste of Ayurveda interventions. Moreover, there are ethical aspects to be considered while selecting the control for diseases with effective established treatment. However, Ayurveda interventions can be compared with the standard of care treatment in stand-alone mode or can be assessed for its efficacy as an add-on to the standard care.


  The Sample Size Top


Statistics plays a crucial role in designing clinical trials. Many studies in academic set-ups, especially for postgraduate and doctoral purposes, often are reported to have insufficient sample size, owing to time, resource and financial constraints, and inappropriate sample size calculation. An appropriate sample size will produce results that can be applied to the wider population. The adequacy of the sample size will be dependent on many factors such as the anticipated difference between two groups, effect size, level of significance (type I error), the power of the study, and expected drop-outs/noncompliance to the study procedure. The study may lose its validity if sample size is compromised. According to the Consolidated Standards Of Reporting Trials (CONSORT) statement, reporting of sample size calculations is mandatory and shall be justified in all RCTs.[8]


  Statistical Methods Top


Randomization

It should be understood that the appropriately generated randomization sequence is the soul of robust and sound clinical research. Randomization allows comparability with precision and validity while eliminating bias between the groups. It also guarantees valid significance levels for statistical tests. Simple randomization, block randomization, and stratified randomization are the most commonly used techniques that can be utilized for Ayurveda clinical trials, and the selection of method may be made considering the merits and demerits of each technique and its suitability for the study, addressing the size of the clinical trial, and the need for balance in the sample size.


  Allocation Concealment Top


It is done to prevent the selection and confounding bias and to ensure that the implementation of random allocation of trial participants occurs without the prior knowledge of the research team. The use of either central randomization or sequentially numbered, opaque, sealed envelopes is considered adequate for allocation concealment.

Blinding

Blinding is a methodological characteristic to minimize measurement bias. Because of the distinctive sensory attributes of the Ayurveda medicines, blinding is very difficult to achieve in Ayurveda clinical trials. Though blinding is an important attribute, reporting in publications is infrequent and inadequately described. Blinding, if possible, should be done if it is feasible to develop matching placebo, which is inert.


  Screening and Participant Recruitment Top


The screening of study participants shall be conducted as per the ICH Guidelines (General considerations for clinical studies E8 (R1), in accordance with the prespecified eligibility criteria after obtaining the informed consent. All clinical trials, irrespective of whether they are using Ayurveda or contemporary interventions, shall follow the Indian Council of Medical Research (ICMR) National ethical guidelines (2017). Participant recruitment is the most critical, yet challenging part of clinical trials. A careful plan involving multiple strategies for target sample size recruitment with enough scope for establishing interim goals while maintaining enough flexibility and adhering to timelines is very vital in every clinical trial.


  Data Collection Top


The process of data capture shall be done as per the objectives and outcomes of the study with the GCP guidelines. Whatever instrument is used for the process of data capture, the form and content of the information collected should be in full accordance with the protocol and should be established in advance of the conduct of the clinical trial. The documentation of demographic details and baseline characteristics is useful in every clinical study, and it should be ensured that complete data are collected. During all phases of study, sufficient effort shall be spared to ensure the collection of quality data as the inferences from the trial are based on accurate and valid data. Incorrect data, missing data, and data with too much variability are the major problems encountered in data collection. This can be minimized by ensuring that all personnel involved in the trial are adequately trained on the standard procedures and through the establishment of a monitoring or surveillance mechanism.

Statistical analysis

A necessary aspect to well-designed clinical trial is its appropriate statistical analysis and was acknowledged as essential in “Good Clinical Practice: Consolidated Guideline” (ICH E6). A statistical analysis plan shall be well sought out a priori depending upon the nature of trial such as confirmatory or exploratory and specific objectives and outcomes. Every clinical study conducted in Ayurveda shall ensure that the principal aspects of the planned analysis are clearly delineated in such a way that the data derived are sufficient to satisfy the hypothesis of proposed efficacy and safety of Ayurveda interventions. It shall also be kept in mind that only the results from analysis proposed in the protocol that was approved through Institutional Ethics Committee (IEC) and registered with the Clinical Trial Registry of India (CTRI) can be regarded as confirmatory. The statistical tests for each clinical trial should be logically decided based on the nature of dependent and independent variables, type of variable, and after checking the normality of the data.

Reporting and interpretation of results

The final phase of any clinical trial is to interpret and report the results. In order to communicate the research outcome to the various stakeholders and for it to have any translational value, the outcomes are to be interpreted most appropriately without being lured to over- or underinterpretation. In this regard, the results are to be presented clearly and concisely. It is advocated that any result shall be reported appropriately using P values, point estimates, and confidence intervals. The “Result” section shall present analyzed data in a tabulated or graphical format based on descriptive and inferential statistics. Under the discussion, it is essential to comprehend and present the outcomes that the results section has portrayed to support the hypothesis.[8],[9]


  Discussion—The Soul of the Research Top


Scientific justification of each finding through as many angles as possible with supportive references from reliable primary sources and the systematic and sequential flow creates a scientific and impressive “Discussion.” Indeed, the discussion part is the most challenging step in every research that demands researcher insight, knowledge, experience, data analysis, and interpretation skills. The impact of a study is primarily assessed based on the quality, consistency, integrity, and absoluteness of the discussion. As a result, the need for writing scientific analysis in Ayurveda research from the perspective of international standards is emphasized.[10],[11] Extremely focused, dedicated, and elaborative efforts with utmost care are paramount requisites while creating this soul of the work. Otherwise, the research may not give a feeling of a vital contribution.

It is equally important to explain the clinical relevance of Ayurveda parameters to underline the scientific basis of Ayurveda concepts in clinical research. However, it is noteworthy that attempts should be made to present the clarifications in the standard English language, and the description should avoid using Sanskrit words. For broader dissemination, the presentation needs to be in a way that researchers of any branch can understand. Such a way may increase the acceptability of Ayurveda’s clinical relevance and contribute significantly to generating evidence-based approaches.

Dissemination of research outcome

Every investigator is obligated to timely prepare and submit the trial results, irrespective of the nature of the outcome. The EQUATOR (Enhancing the Quality and Transparency of health Research) initiative hosts over 200 reporting guidelines that specify a certain set of items for reporting that can improve the quality of health-related publications, which can be adopted for Ayurveda publications too, as appropriate.


  Conclusion Top


The research in Ayurveda, in any form, however small or large it may be, ultimately is intended to validate the principles/formulations/practices of Ayurveda and to establish a scientific basis. Attention to methodology is one of the essential requirements to achieve this purpose. The article is intended to provide a brief attempt on the major aspects to be focused while designing and conducting clinical trials in Ayurveda.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.





 
  References Top

1.
Singh RH Exploring issues in the development of Ayurvedic research methodology. J Ayurveda Integr Med 2010;1: 91-5.  Back to cited text no. 1
    
2.
Bhapkar V, Sawant T, Bhalerao S A critical analysis of CTRI registered AYUSH studies for COVID-19. J Ayurveda Integr Med 2022;13:100370.  Back to cited text no. 2
    
3.
Niranjan Y, Baghel MS An overview of postgraduate and doctoral level research conducted in Ayurveda education institutions diabetic neuropathy. J Res Educ Indian Med 2012;18:131-42.  Back to cited text no. 3
    
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Akarshini AM, Baghel MA Comprehensive review of post graduate dissertations on Ayurvedic management of diabetic distal symmetrical polyneuropathy. J Res Educ Indian Med 2013;19:103-19.  Back to cited text no. 4
    
5.
Mahajan V, Sanker MKV, Mathur A Clinical research in Ayurveda—Can statistics as a scientific discipline help the cause? Preprints 2022:2022060101.  Back to cited text no. 5
    
6.
Rajput DS Challenges concerning global acceptance of Ayurveda researches. J Indian Sys Medicine 2020;8:243-5.  Back to cited text no. 6
    
7.
Mukherjee PK, Harwansh RK, Bahadur S, Banerjee S, Kar A, Chanda J, et al. Development of Ayurveda—Tradition to trend. J. Ethnopharmacol 2017;197:10-24.  Back to cited text no. 7
    
8.
Gupta KK, Attri JP, Singh A, Kaur H, Kaur G Basic concepts for sample size calculation: Critical step for any clinical trials! Saudi J Anaesth 2016;10:328-31.  Back to cited text no. 8
    
9.
Rastogi S, Singh RH Transforming Ayurveda: Stepping into the realm of evidence-based practice. In: Evidence-based Practice in Complementary and Alternative Medicine. Rastogi S, Chiappelli F, Ramchandani MH, Singh RH, editors. Berlin, Heidelberg: Springer; 2012. p. 33-49.  Back to cited text no. 9
    
10.
Katiyar CK Ayurpathy: A modern perspective of Ayurveda. Ayu 2011;32:304-5.  Back to cited text no. 10
    
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Rajput DS Approaches for increasing quality of research publications in Ayurveda. J Indian Sys Medicine 2019;7:197-9.  Back to cited text no. 11
    




 

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  In this article
Abstract
Introduction
Choosing a Topic...
Literature Review
Formulation of R...
Methodological A...
The Sample Size
Statistical Methods
Allocation Conce...
Screening and Pa...
Data Collection
Discussion—...
Conclusion
References

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