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BACKGROUND: Socioeconomic factors influence access to cancer care and survival. This study investigated the role of socioeconomic status on the risk of breast cancer recurrence and on the delivery of appropriate cancer care (sentinel lymph node biopsy and breast-conserving surgery plus radiotherapy), by patients' age and hormone receptor status. METHODS: 3,462 breast cancer cases diagnosed in 2003-2005 were selected from 7 Italian cancer registries and assigned to a socioeconomic tertile on the basis of the deprivation index of their census tract. Multivariable models were applied to assess the delivery of sentinel lymph node biopsy and of breast-conserving surgery plus radiotherapy within socioeconomic tertiles. RESULTS: In the 1,893 women younger than 65 years, the 5-year risk of recurrence was higher in the most deprived group than in the least deprived, but this difference was not significant (16.4% vs. 12.9%, log-rank p=0.08); no difference was seen in women ≥65 years. Among the 2,024 women with hormone receptor-positive cancer, the 5-year risk was significantly higher in the most deprived group than in the least deprived one (13.0% vs. 8.9%, p=0.04); no difference was seen in cases of hormone receptor-negative cancer. The most deprived women were less likely than the least deprived women to receive sentinel lymph node biopsy (adjusted odds ratio (ORa), 0.69; 95% CI, 0.56-0.86) and to undergo breast-conserving surgery plus radiotherapy (ORa=0.66; 95% CI, 0.51-0.86). Conclusions: Socioeconomic inequalities affect the risk of recurrence, among patients with hormone receptor-positive cancer, and the opportunity to receive standard care.

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Obesity and metabolic syndrome are risk and prognostic factors for breast cancer (BC) and are associated with chronic inflammation. We investigated the association between distinct BC subtypes and markers of adiposity, dysmetabolisms, and inflammation. We analyzed 1779 patients with primary invasive BC treated at a single institution, for whom anthropometric and clinical-pathological data were archived. BC subtypes were classified by immunohistochemical staining of ER, PR, HER2, and Ki67, and their relations with the study markers were assessed by multinomial logistic regression. Adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated taking luminal A as reference. All subtypes more aggressive than luminal A were significantly more frequent in younger (<45 years) than older women. Before menopause, luminal B HER2-negative tumors were positively associated with large waist (OR 2.55, 95 % CI 1.53-4.24) and insulin resistance (OR 1.90, 95 % CI 1.05-3.41); luminal B HER2-positive tumors with large waist (OR 2.11, 95 % CI 1.03-4.35) and triple-negative tumors with overweight (OR 3.04, 95 % CI 1.43-6.43) and high C-reactive protein (p trend = 0.026). In postmenopausal women aged <65, luminal B HER2-negative (OR 1.94, 95 % CI 1.16-3.24) and luminal B HER2-positive tumors (OR 2.48, 95 % CI 1.16-5.27) were positively related with metabolic syndrome. Dysmetabolisms and inflammation may be related to different BC subtypes. Before menopause, triple-negative cancers were related to obesity and chronic inflammation, and aggressive luminal subtypes to abdominal adiposity. After menopause, in women aged <65 these latter subtypes were related to metabolic syndrome. Control of adiposity and dysmetabolism can reduce the risk of aggressive BC subtypes, improving the prognosis.

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In clinical research, many potentially useful variables are available via the routine activity of cancer center-based clinical registries (CCCR). We present the experience of the breast cancer clinical registry at Fondazione IRCCS "Istituto Nazionale dei Tumori" to give an example of how a CCCR can be planned, implemented, and used. Five criteria were taken into consideration while planning our CCCR: (a) available clinical and administrative databases ought to be exploited to the maximum extent; (b) open source software should be used; (c) a Web-based interface must be designed; (d) CCCR data must be compatible with population-based cancer registry data; (e) CCCR must be an open system, able to be connected with other data repositories. The amount of work needed for the implementation of a CCCR is inversely linked with the amount of available coded data: the fewer data are available in the input databases as coded variables, the more work will be necessary, for information technology staff, text mining analysis, and registrars (for collecting data from clinical records). A cancer registry in a comprehensive cancer center can be used for several research aspects, such as estimate of the number of cases needed for clinical studies, assessment of biobank specimens with specific characteristics, evaluation of clinical practice and adhesion to clinical guidelines, comparative studies between clinical and population sets of patients, studies on cancer prognosis, and studies on cancer survivorship.

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