An Evidence-Based Approach to

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An Evidence-Based Approach to TCM Patient Class
Definition and Differentiation
Nevin L. Zhang The Hong Kong Univ. of Sci.
Tech. http//www.cse.ust.hk/lzhang

• Joint Work with
• HKUST Yuan Shihong, Chen
  Tao, Wang Yi, Liu Tengfei, Poon Kin Man, Liu Hua
• Beijing TCM U Wang Tianfang, Zhao Yan, Xu
  Wenjie, Wang Qingguo
• Shanghai TCM U Xu Zhaoxia, Wang Yiqing
• Academy of TCM Zhou Xuezhong, Zhang Runshun,
  Gong Yanbin, He Liyun, Wang Jie, Liu Baoyan
• Beijing Dongfang Hospital Zhang Yongling, Chen
  Boxing, Fu Chen

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TCM is Worthy of Research

• Traditional Chinese Medicine (TCM) is important
  to the Chinese people.
• Culture tradition
• Health care
• It is used by many others. WHO report
• Global herbal medicine market US60 billion
• Traditional medicine treatment at least once in
  life
• 90 of Canadian, 49 of French people,
• 48 of Australians, 42 of Americans.

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Spectrum of TCM Research
A visit to TCM Doctor
Patient Information Collection Inspection (?)) Auscultation Olfaction (?)) Inquiry (?)) Palpation (?))
Patient Classification Syndrome differentiation (??) Determine pattern of disharmony
Treatment Herbal medicine Acupuncture Tui Na, Cupping, Qigong, .., etc
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Spectrum of TCM Research
A visit to TCM Doctor Research
Patient Information Collection Inspection (?)) Auscultation Olfaction (?)) Inquiry (?)) Palpation (?)) Instruments .
Patient Classification Syndrome differentiation (??) Determine pattern of disharmony
Treatment Herbal medicine Acupuncture Tui Na, Cupping, Qigong, .., etc
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Spectrum of TCM Research
A visit to TCM Doctor Research
Patient Information Collection Inspection (?)) Auscultation Olfaction (?)) Inquiry (?)) Palpation (?)) Instruments .
Patient Classification Syndrome differentiation (??) Determine pattern of disharmony
Treatment Herbal medicine Acupuncture Tui Na, Cupping, Qigong, .., etc Efficacy Effective component of herbs Action mechanism Safety .
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Spectrum of TCM Research
A visit to TCM Doctor Research
Patient Information Collection Inspection (?)) Auscultation Olfaction (?)) Inquiry (?)) Palpation (?)) Instruments .
Patient Classification Syndrome differentiation (??) Determine pattern of disharmony Supervised learning Labeled Data Symptoms signs, class labels assigned by expert
Treatment Herbal medicine Acupuncture Tui Na, Cupping, Qigong, .., etc Efficacy Effective component of herbs Action mechanism Safety .
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Spectrum of TCM Research
A visit to TCM Doctor Research
Patient Information Collection Inspection (?)) Auscultation Olfaction (?)) Inquiry (?)) Palpation (?)) Instruments .
Patient Classification Syndrome differentiation (??) Determine pattern of disharmony Supervised learning Labeled Data Symptoms signs, class labels assigned by expert Our work cluster analysis Unlabeled Data symptoms signs
Treatment Herbal medicine Acupuncture Tui Na, Cupping, Qigong, .., etc Efficacy Effective component of herbs Action mechanism Safety .
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Western Medicine vs TCM A Layman view

• Western Medicine (Modern Biomedical Medicine )
• Human body A machine with different parts,
  viewed at different levels anatomic,
  biochemical, genetic
• Disease malfunction of some part
• TCM
• Human body Dynamic system of energy and
  functions, holistic view
• Disease Disharmony
• Among yin, yang, qi, xue, zàng-fu, meridians etc.
  and/or
• Between of the human body and the environment

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Patient Classes

• Both Modern Medicine and TCM divide patients into
  classes
• Patient classes in modern medicine
• Correspond to diseases at certain stages E.g.,
  Stage 4 COPD
• Clearly defined
• Have gold standard for differentiation
• Patient classes in TCM
• Correspond to pattern of disharmony (syndrome)
  Yang Deficiency
• Not clearly defined
• Differentiation heavily influenced by subjectivity

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Data-Driven Research on Syndrome Differentiation

• Supervised learning
• Labeled Data Symptoms signs, class labels
  assigned by experts
• Provides quantitative summarization of experts
  know-hows
• Conducive to the improvement of TCM service.
  Reduce variance.
• However, it does not solve the subjectivity
  problem.
• Our work cluster analysis
• Unlabeled Data symptoms signs only
• Aim at finding natural clusters among patient
  population, which
• Can be used as objective evidence for patient
  class definition.

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Our Objective

• In clinic practice, syndrome differentiation is
  heavily influenced by objectivity.
• Our objective to provide evidence to make
  syndrome differentiation as objective as possible.

Status Quo Of Syndrome Differentiation
Ideal Case
Our Goal
Subjective
Objective Gold Standard
Reference Standard Objective Evidence
Subjective Judgment
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Outline

• Introduction
• Statistical validation of TCM postulates
• Providing evidence for TCM patient class
  definition and differentiation
• Concluding remarks

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TCM Postulates

• TCM has postulates to explain occurrence of
  symptoms
• Kidney yang is the basis of all yang in the
  body. When kidney yang is in deficiency, it
  cannot warm the body and the patient feels cold,
  resulting in intolerance to cold, cold limbs, and
  cold lumbus and back.
• Key question
• Do concepts such as kidney yang deficiency have
  scientific contents or are pure subjective
  notion?
• Efforts to provide objective evidence would be in
  vain in the latter case.

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Research on Objectivity of TCM Syndrome

• For more than 50 years, researchers have tried to
  show that
• TCM syndrome factors correspond to real entities
  by means of biomedical laboratory tests,
  (recently genetic method also)
• but there has been little success.
• We take a data-analysis approach

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TCM syndromes are latent variables

• TCM postulate
• Kidney yang is the basis of all yang in the
  body. When kidney yang is in deficiency, it
  cannot warm the body and the patient feels cold,
  resulting in intolerance to cold, cold limbs, and
  cold lumbus and back.
• Manifest variablesDirectly observed
• Feel cold, cold limbs, intolerance to cold.
• Latent variable Not directly observed
• Kidney Yang deficiency
• Similar to concepts such as intelligence
• Latent Structure
• Relationships between latent variables and
  manifest variables

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Collective Cognition

• How did concepts such as Intelligence come into
  being?
• Conjecture From correlation between observed
  variables.
• How do we possibly prove this?
• LampPrinciple applet interactive demo
• Shows that human beings tend to introduce latent
  variables to explain co-occurrence in
  observations
• Conjecture about TCM the formation postulates
• Co-occurrence of cold symptoms gt Kidney Yang
  deficiency

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Statistical Validation of TCM Postulates
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Data Analysis Tool

• Latent tree models
• Each node represents a discrete random variable
• Arrows represent dependence
• Leaves observed (manifest variables)
• Internal nodes latent (latent variables)
• Links quantify by probability distributions
  P(Y1), P(Y2Y1), P(X1Y2), P(X2Y2),

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Data Analysis Tool

• Learning latent tree models Determine
• Number of latent variables
• Cardinality of each latent variable
• Model Structure
• Conditional probability distributions

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Data Analysis Tool

• How to learn latent tree models from data
• Statistical Principle (BIC score) Search

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Case Study
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• Kidney data
• Population Seniors aged 60 or above from
  residential communities
• Variables 34 symptoms associated with kidney
  deficiency
• Sample size 2600

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• Latent structure matches relevant TCM
  postulates
• We have not shown yang deficiency corresponds
  to real entity
• We have shown that the postulate of a yang
  deficiency entity would explain the
  co-occurrence patterns observed in data well.

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Match between Model and TCM Postulates

• TCM
• Kidney yang deficiency,
• failing to warm body
• ?intolerance to cold, cold limbs, cold lumbus and
  back,
• ? Spleen disorders
• ? loose stools, indigested grain in the stool

Good Match
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Match between Model and TCM Postulates

• TCM
• When kidney fails to control the urinary bladder,
  
• frequent urination, urine leakage after
  urination, frequent nocturnal urination,
• (in severe cases) urinary incontinence and
  nocturnal enuresis.

Good Match
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Match between Model and TCM Postulates

• TCM
• kidney essence insufficiency
• ?premature baldness, tinnitus, deafness, poor
  memory, trance, declination of intelligence,
  fatigue, weakness, and so on.

Good Match
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Match between Model and TCM Postulates

• TCM
• kidney yin deficiency
• ? dry throat, tidal fever or hectic fever,
  fidgeting, hot sensation in the five
  centers,insomnia, yellow urine, rapid and thready
  pulse, and so on.

Good Match
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Results on other Data Sets from a 973 Project
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Summary
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• We have analyzed many data sets
• Latent variables obtained match the relevant TCM
  postulates in all cases
• Conclusion
• TCM syndrome concepts do have scientific
  contents.
• We have not shown that TCM syndromes corresponds
  to real entities.
• We have shown that the postulate of the
  existence of such entities would explain the
  co-occurrence patterns observed in data.

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Value of Work in View of Others

• D. Haughton and J. Haughton. Living Standards
  Analytics Development through the Lens of
  Household Survey Data. Springer. 2012
• Zhang et al. provide a very interesting
  application of latent class models to diagnoses
  in traditional Chinese medicine (TCM).
• The results tend to confirm known theories in
  Chinese traditional medicine.
• This is a significant advance, since the
  scientific bases for these theories are not
  known.
• The model proposed by the authors provides at
  least a statistical justification for them.

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Value of Work in View of Others

• Review of a recent paperI am very interested
  in what these authors are trying to do. They are
  dealing with an important epistemological
  problem.
• To go from the many symptoms and signs that
  patients present, to construct a consistent and
  other-observer identifiable constellation, is a
  core task of the medical practitioner. A kind of
  feedback occurs between what a practitioner is
  taught/finds listed in books, and what that
  practitioner encounters in the clinic. The better
  the constellation is understood, the more
  accurate the clustering of symptoms, the more
  consistent is the identification of syndromes
  among practitioners and through time. While these
  constellations have been worked into
  widely-accepted disease constructs for
  biomedicine for some time which are widely
  accepted as real, this is not quite as true for
  TCM constellations. This latent variable study is
  interesting not only in itself, but also as
  providing evidence that what TCM says is so,
  shows up during analysis as demonstrably so.

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Outline

• Introduction
• Statistical validation of TCM postulates
• Providing evidence for TCM patient class
  definition and differentiation
• Concluding remarks

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Integration of TCM and Western Medicine

• Common practice in China
• Patients of a WM disease subdivided into several
  TCM classes
• Example
• WM disease Depression
• TCM Classes
• Liver-Qi Stagnation (????), Stagnation of liver
  qi and spleen deficiency (????), Deficiency of
  both heart and spleen (????), Liver depression
  forming fire (????), .
• No agreed sub-classing standard
• 5 different standards proposed by different
  organizations/groups
• Based experts opinions
• Can we provide evidence for the TCM sub-typing of
  WM diseases?

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The Idea
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• Imagine sub-typing Western medicine disease D
  from TCM perspective

• Also providing a basis for defining syndrome Z
  and for differentiating syndrome Z patients from
  other D patients

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Cluster Analysis

• Grouping of objects into clusters so that objects
  in the same cluster are similar in some sense

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How to Cluster Those?
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How to Cluster Those?
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Style of picture
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How to Cluster Those?
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Type of object in picture
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How to Cluster Those?
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• Multidimensional clustering / Multi-Clustering
• How to partition data in multiple ways?
• Latent tree models

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Latent Tree Models Multidimensional Clustering

• Model relationship between
• Observed / Manifest variables
• Math Grade, Science Grade, Literature Grade,
  History Grade
• Latent variables
• Analytic Skill, Literal Skill, Intelligence

• Each latent variable gives a partition
• Intelligence Low, medium, high
• Analytic skill Low, medium, high

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LTM for a Depression Data Set
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Partition given by Y15
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What is the Z?

• We now have the empirical partition.
• What is the Z?
• In TCM, the symptoms shortness of breath etc.
  characterize Qi movement disorder in chest
  (??????).
• So, Z should be whether Qi movement disorder in
  chest

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Patient Class Definition and Differentiation

• Previously, no clear definition for the class
• Qi movement disorder in chest (??????).
• Empirical partition gives us a clear definition
• s1 Qi movement disorder in chest (??????),
• s0 no Qi movement disorder in chest (???????)
• Sizes of the classes 48,52
• Class differentiation Bayes rule, importance of
  symptoms indicated by ratios

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Easy-to-Operate Differentiation Standards

• For clinic convenience, differentiation standards
  are usually given by a scoring system
• Current work
• Derive such scoring systems from results of
  latent tree analysis, particularly the
  probability ratios.

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Concluding Remarks

• Latent tree analysis is tool for
• Systematically identifying co-occurrence
  patterns of symptoms
• Introduce latent structure to explain the
  patterns
• Provide evidence in support of TCM postulates
  about symptom occurrence
• Tool for multidimensional clustering
• Each latent variable represents a partition of
  data
• Provide evidence for TCM patient class definition
  and differentiation

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Application of LTM in Bioinformatics
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• Thank You!