Sub-Typing of Rheumatic Diseases Based on a Systems Diagnosis Questionnaire

Herman van Wietmarschen, Theo H. Reijmers, Anita J. van der Kooij, Jan Schroën, Heng Wei, Thomas Hankemeier, Jacqueline J. Meulman, Jan van der Greef. 2011. Sub-Typing of Rheumatic Diseases Based on a Systems Diagnosis Questionnaire. PLoS ONE. 9. 6
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Taal/language: Engels
Abstract / summary in English:

Background: The future of personalized medicine depends on advanced diagnostic tools to characterize responders and non-responders to treatment. Systems diagnosis is a new approach which aims to capture a large amount of symptom information from patients to characterize relevant sub-groups.


Methodology: 49 patients with a rheumatic disease were characterized using a systems diagnosis questionnaire containing 106 questions based on Chinese and Western medicine symptoms. Categorical principal component analysis (CATPCA) was used to discover differences in symptom patterns between the patients. Two Chinese medicine experts where subsequently asked to rank the Cold and Heat status of all the patients based on the questionnaires. These rankings were used to study the Cold and Heat symptoms used by these practitioners.


Findings: The CATPCA analysis results in three dimensions. The first dimension is a general factor (40.2% explained variance). In the second dimension (12.5% explained variance) ‘anxious’,  ‘worrying’, ‘uneasy feeling’ and ‘distressed’ were interpreted as the Internal disease stage, and ‘aggravate in wind’, ‘fear of wind’ and ‘aversion to cold’ as the External disease stage. In the third dimension (10.4% explained variance) ‘panting s’, ‘superficial breathing’, ‘shortness of breath s’, ‘shortness of breath f’ and ‘aversion to cold’ were interpreted as Cold and ‘restless’, ‘nervous’, ‘warm feeling’, ‘dry mouth s’ and ‘thirst’ as Heat related. ‘Aversion to cold’, ‘fear of wind’ and ‘pain aggravates with cold’ are most related to the experts Cold rankings and ‘aversion to heat’, ‘fullness of chest’ and ‘dry mouth’ to the Heat rankings.


Conclusions: This study shows that the presented systems diagnosis questionnaire is able to identify groups of symptoms that are relevant for sub-typing patients with a rheumatic disease.

Keywords in English: Traditional chinese medicine, personalized medicine, rheumatic disease, questionnaire, Categorical principal component analysis (CATPCA)