In order to identify high risk groups for breast cancer, unconditional multiple logistic regression models based on 5 widely recognized and easily identifiable risk factors (age at menarche, at menopause and at first birth, family history of breast cancer and body mass index) were applied to a large dataset including 2085 cases and 1936 controls aged 50 or over derived from two unmatched hospital-based case-control studies conducted in Italy. Although various models provided an excellent fitting, both on the whole dataset and using a training-testing approach to a priori identified separate subset, the observed extent of variation in breast cancer risk between highest and lowest decile of the distribution was limited to a factor 2. This indicates that the 5 variables considered did not allow identification of subgroups with substantially elevated risk of breast cancer to have practical implications for screening/prophylactic treatment purposes.
Identification of high risk groups for breast cancer by means of logistic models / E. Negri, A. Decarli, C. La Vecchia, E. Marubini. - In: JOURNAL OF CLINICAL EPIDEMIOLOGY. - ISSN 0895-4356. - 43:5(1990), pp. 413-418.
|Titolo:||Identification of high risk groups for breast cancer by means of logistic models|
DECARLI, ADRIANO (Secondo)
LA VECCHIA, CARLO VITANTONIO BATTISTA (Penultimo)
MARUBINI, ETTORE (Ultimo)
|Parole Chiave:||Age at first live-birth; Body weight; Breast neoplasms; High risk groups; Menarche; Menopause|
|Settore Scientifico Disciplinare:||Settore MED/01 - Statistica Medica|
|Data di pubblicazione:||1990|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/0895-4356(90)90128-C|
|Appare nelle tipologie:||01 - Articolo su periodico|