Pregled bibliografske jedinice broj: 115493
Holistic approach to analysis of medical data: vulvar cancer
Holistic approach to analysis of medical data: vulvar cancer // Collegium Antropologicum, 21 (1997), 1; 175-184 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 115493 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Holistic approach to analysis of medical data: vulvar cancer
Autori
Buković, Damir ; Rudan, Igor ; Ivanišević, Marina ; Šoštarić, Slavko ; Rubala, Drago
Izvornik
Collegium Antropologicum (0350-6134) 21
(1997), 1;
175-184
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
multidisciplinarity; complexity; cancer; vulva; etiology
Sažetak
This paper continues the series of studies introducing holistic approach to analysis of clinical data. Namely, 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 holistic approach to analysis of medical data, in this case clinical data regarding cancer of the vulva. Such approach requires the collection of data regarding different aspects of the cancer patients, 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. In this study, the authors have processed the data regarding 25 characteristics of all 755 vulvar cancer patients treated between 1938 and 1990 at the Department for Gynecological Oncology of the University Hospital for Gynecology and Obstetrics, Zagreb, Croatia. In factor analysis, the principal components were rotated after the initial extraction (the authors recommended the use of oblimin rotation) in order to obtain better ground for interpretation of the obtained results. The next step in this approach was the stepwise exclusion of characteristics with smallest commonality 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 was reduced to 3-4 and 7-10, respectively, the ultimate interpretations and conclusions were made. This approach outlined some clusters of correlations between medical data which are difficult to identify using other statistical procedures, primarily the impacts of various socioeconomic and hereditary-constitutional variables on overall survival.
Izvorni jezik
Engleski
Znanstvena područja
Kliničke medicinske znanosti
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Social Science Citation Index (SSCI)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE
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