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How should homeopathy be assessed?

Explore the assessment of homeopathy within the framework of conventional science, discussing the challenges, biases, and potential improvements. Learn how likelihood ratio research can enhance the effectiveness of homeopathic treatment.

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How should homeopathy be assessed?

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  1. How should homeopathy be assessed? Still applying conventional science Lex Rutten, the Netherlands

  2. Belief or science Belief: conventional medicine works; homeopathy does not. Homeopathy cannot succeed in Randomised Controlled Trial

  3. Scientific mirror Homeopathy - conventional medicine: same results in RCT Hypothesis: selection bias, low quality, heterogeneity Shang, the Lancet aug. 2005 RCT works only for conventional medicine (????)

  4. ‘It works’ doesn’t mean it works • Allen Roses (GSK, December 2003):90% of conventional medicines work in 30-50% of all patients • Pharmacogenetics: not only the disease, but the whole person: genotype • Homeopathy: same, but phenotype

  5. Why not 100% success? RCT side-effects diagnosis therapy-result co-morbidity circumstances Unreal certainty

  6. From complaint towards result diagnostic research RCT symptom A symptom B test X test Y diagnosis result chances placebo < 0.05 probability of diagnosis

  7. Homeopathic ‘diagnosis’ symptom A symptom B symptom C symptom D Diagnostic/prognostic research Diagnosis Result Probability of result Diagnosis

  8. Effect modification Diagnostic/prognostic research comorbidity age > 65 Result sex social status Probability of result suicidal?

  9. Bayes method • Knowledge from experience • Direct results in practice • Handling of complex clinical symptoms • Probability instead of certainty • Step-by-step increasing certainty by adding data

  10. Bayes and homeopathy • More symptoms more certainty • Peculiar symptoms are more important • Vagueness is no problem • Disadvantage: difficult calculations (use a calculator)

  11. Likelihood Ratio (LR) Occurrence in target population LR+ = Occurrence in rest-population Odds = chance / (1-chance) Chance = odds / (1+odds) Bayes’ rule: posterior odds = LR x prior odds

  12. Prior chance 1% 10% 30% 50% 80% Posterior chance 4.8% 35.7% 68.1% 83.3% 95.2% Prior to posterior chance (LR+=5)

  13. Homeopathic diagnosis stepwise Lachesis in menopausal complaints

  14. Repertory with LR Partly hypothetical rubric ‘Fear of death’:

  15. Practical homeopathic research • Relation between symptom and success • No conflict with daily practice • Takes a few seconds during each consultation • Outcome: a reliable repertory

  16. Prospective research • Check the presence of 6 symptoms in each new patient • Keep record of medicines and results • a=occurrence of symptom in Lachesis-population • b=occurrence of symptom in rest-population • Likelihood Ratio = a / b

  17. A few seconds of each consultation

  18. Results fear of death Fear of death in whole population: 3.8% Does this lead us to a more reliable repertory? Repertory: Anac., Ars., Calc.

  19. Results after 15 months, n=1634

  20. Lachesis in menopausal complaints • LR+ loquacity - Lachesis = 5 (1,8-12,3) • succes by Lachesis in menopausal complaints with loquacity goes from 10%(?) to 35%. Dear GP, Treat your most loquacious patients with menopausal complaints with Lachesis

  21. Conclusions • Homeopathy (and conventional medicine) is bayesian science • LR research is easy, cheap and rewarding • Effectiveness of homeopathy can be much improved by LR research

  22. Vagueness Herpes lip Loquacity

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