HOLISTIC APPROACH TO ANALYSIS OF MEDICAL DATA - OVARIAN-CANCER

Besides the information regarding his/her disease, each hospitalized c ancer patient also provides the variety of data regarding his/her psyc hological, cultural, social, economical, genetic, constitutional and m edical background The aim of this study was to introduce a model for h olistic approach to analysis of medical data, in this case clinical ov arian cancer data. The model requires the collection of as many such d ata as possible for each patient in the sample, and after the satisfac tory sample size is obtained (which should be at least five times grea ter than the number of examined patient characteristics), the performa nce of factor analysis. As the example of the application, the authors have processed the data regarding 25 characteristics of 500 ovarian c ancer patients treated between 1980 and 1990 at the Department for Gyn ecological Oncology of the University Hospital for Gynecology and Obst etrics, Zagreb, Croatia. In factor analysis the principal components s hould be rotated after the initial extraction (the authors recommend t he use of oblimin rotation) in, order to obtain better ground for inte rpretation of the obtained results. The next step in this model is the stepwise exclusion of characteristics with smallest communalities acc ording to Kaiser-Meyer-Olkin criteria, and retaining the characteristi cs and components with the most significant impact on the explained sy stem variance. When the number of principal components and initial ana lyzed characteristics is reduced to 3-4 and 7-10, respectively, the ul timate interpretations and conclusions should be made.