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Homeopathy
DOI: 10.1055/a-2544-2807
Commentary Article

How to Assess Variation in Homeopathic Prognostic Factor Research?

Lex Rutten 
1   Independent researcher, Breda, The Netherlands
,
José E. Eizayaga
2   Department of Homeopathy Maimonides University, Buenos Aires, Argentina
,
Harleen Kaur
3   Department of Homeopathy, Central Council of Research in Homeopathy, Janakpuri, New Delhi, India
,
Shalini Rao
3   Department of Homeopathy, Central Council of Research in Homeopathy, Janakpuri, New Delhi, India
,
Anurag Bajpai
3   Department of Homeopathy, Central Council of Research in Homeopathy, Janakpuri, New Delhi, India
,
Chetna Deep Lamba
3   Department of Homeopathy, Central Council of Research in Homeopathy, Janakpuri, New Delhi, India
,
Jyoti Sachdeva
3   Department of Homeopathy, Central Council of Research in Homeopathy, Janakpuri, New Delhi, India
,
Vinitha E. R.
4   Department of Homeopathy, National Homoeopathy Research Institute in Mental Health (NHRIMH) Kottayam, Kerala, India
,
Sonia Raizada
5   Department of Homeopathy, Dr. D.P. Rastogi Central Research Institute (Homoeopathy), Noida, Gautambudh Nagar, Uttar Pradesh, India
,
Rompicherla Gr. Kiranmayee
6   Department of Homeopathy, Extension Clinical Research Unit of DSU, Princess Durru Shehvar Children's & General Hospital, Purani Haveli, Hyderabad, Andhra Pradesh, India
,
Bondarkar Rajashekhar
7   Department of Homeopathy, Regional Research Institute for Homoeopathy. Dr. GGH Medical College Campus, Andhra Pradesh, India
,
Chittranjan Kundu
8   Department of Homeopathy, Dr. Anjali Chatterjee Regional Research Institute of Homoeopathy, Kolkata, Bengal, India
,
Vaishali Shinde
9   Department of Homeopathy, Regional Research Institute (Homoeopathy), Belapur, Navi Mumbai, India
,
Sujata Choudhury
10   Department of Homeopathy, Regional Research Institute (H), Puri, Odisha, India
,
Amulya Ratan Sahoo
11   Department of Homeopathy, Drug Proving Unit, Dr. Abhin Chandra Homoeopathic Medical College & Hospital, Unit-Iii, Bhubaneswar, Odisha, India
,
Ratan Chandra Shil
12   Department of Homeopathy, Regional Research Institute for Homoeopathy, Jirania, Agartala, Tripura, India
,
Abhijit Chakma
12   Department of Homeopathy, Regional Research Institute for Homoeopathy, Jirania, Agartala, Tripura, India
,
Nidhi Mahajan
13   Department of Homeopathy, Regional Research Institute for Homoeopathy, MPK Homoeopathic Medical College, Hospital & Research Centre Campus, Jaipur, Rajasthan, India
,
Alok Mishra
8   Department of Homeopathy, Dr. Anjali Chatterjee Regional Research Institute of Homoeopathy, Kolkata, Bengal, India
,
Anil Khurana
3   Department of Homeopathy, Central Council of Research in Homeopathy, Janakpuri, New Delhi, India
,
Praveen Oberai
3   Department of Homeopathy, Central Council of Research in Homeopathy, Janakpuri, New Delhi, India
,
Raj K. Manchanda
14   Department of Homeopathy, Noida, Uttar Pradesh, India
15   Nehru Homoeopathic Medical College and Hospital, New Delhi
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Abstract

Background

We need to classify the outcome of prognostic factor research (PFR), especially regarding polar symptoms (PS) — symptoms with opposite values such as amelioration/desire and aggravation/aversion. For instance, in a data collection project 22.9% of the patients responding well to Arsenicum album (Ars) had ‘Desire salt’ and 5.7% ‘Aversion salt’. Can such differences be explained by statistical variation?

Methods

Frequency distributions of PS were analysed and compared with previous research to reveal differences. Cumulative binomial probability (CBP) and 95% confidence intervals (95% CIs) were calculated to assess the influence of statistical variation on the difference between the medicine population and the remainder of the population and the difference between opposite poles. CBP and 95% CI were compared regarding usefulness for daily practice. 95% CIs were used to calibrate the CBP. Corroboration by comparable symptoms was also used to validate outcomes.

Findings

In several PS, there was asymmetry between opposite poles and a difference compared with previous research. The most probable cause was using questionnaires, disregarding clinical expertise. This results in asymmetrical frequency distributions when symptoms are common and the criterion ‘more than average’ was ignored. This, in turn, results in relatively low likelihood ratios (LRs) caused by a ‘ceiling effect’.

The CBP correlates with 95% CI, indicates the amount of overlap of 95% CIs, and is useful to classify the statistical certainty of PFR outcome. Based on CBP and difference of CBP for opposite symptoms, LR outcome was classified as statistically ‘Certain’, ‘Probable’, ‘Possible’ or ‘Questionable’. Cut-offs between classes were based on expert estimates. Part of the outcome could be corroborated by the outcome of similar or opposite symptoms.

Conclusion

Asymmetry of symptom frequency distributions in PS can be caused by practitioners not using their expert knowledge while assessing symptoms. A classification of reliability of data based on cumulative binomial chance is more informative and is better understood by experts in homeopathy. Nevertheless, classification of reliability remains partly subjective. Corroboration of outcome and clinical judgment are indispensable for estimating clinical validity of PFR outcomes. Practitioners and researchers participating in PFR need training in statistics and homeopathy respectively.

Keywords

homeopathy - prognostic factor research - polar symptoms - statistical variance - expert opinion


Publication History

Received: 19 November 2024

Accepted: 21 February 2025

Article published online:
30 May 2025

© 2025. Faculty of Homeopathy. This article is published by Thieme.

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

 

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