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Holistic approach to analysis of medical data - ovarian cancer (CROSBI ID 90013)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Rudan, Igor ; Buković, Damir ; Ivanišević, Marina ; Rubala, Drago ; Rudan, Diana Holistic approach to analysis of medical data - ovarian cancer // Collegium antropologicum, 20 (1996), 2; 469-478-x

Podaci o odgovornosti

Rudan, Igor ; Buković, Damir ; Ivanišević, Marina ; Rubala, Drago ; Rudan, Diana

engleski

Holistic approach to analysis of medical data - ovarian cancer

Besides the information regarding his/her disease, each hospitalized cancer patient also provides the variety of data regarding his/her psychological, cultural, social, economical, genetic, constitutional and medical background The aim of this study was to introduce a model for holistic approach to analysis of medical data, in this case clinical ovarian cancer data. The model requires the collection of as many such data as possible for each patient in the sample, and after the satisfactory sample size is obtained (which should be at least five times greater than the number of examined patient characteristics), the performance of factor analysis. As the example of the application, the authors have processed the data regarding 25 characteristics of 500 ovarian cancer patients treated between 1980 and 1990 at the Department for Gynecological Oncology of the University Hospital for Gynecology and Obstetrics, Zagreb, Croatia. In factor analysis the principal components should be rotated after the initial extraction (the authors recommend the use of oblimin rotation) in, order to obtain better ground for interpretation of the obtained results. The next step in this model is the stepwise exclusion of characteristics with smallest communalities according to Kaiser-Meyer-Olkin criteria, and retaining the characteristics and components with the most significant impact on the explained system variance. When the number of principal components and initial analyzed characteristics is reduced to 3-4 and 7-10, respectively, the ultimate interpretations and conclusions should be made.

medical data analysis; ovarian cancer; population genetics; anthropology

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Podaci o izdanju

20 (2)

1996.

469-478-x

objavljeno

0350-6134

Povezanost rada

Kliničke medicinske znanosti, Etnologija i antropologija

Indeksiranost