383 research outputs found

    Associations between lifestyle factors and an unhealthy diet

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    BACKGROUND: Unhealthy dietary patterns have been associated with other unhealthy lifestyle factors such as smoking and physical inactivity. Whether these associations are similar in high- and low-educated individuals is currently unknown. METHODS: We used information of the EPIC-NL cohort, a prospective cohort of 39 393 men and women, aged 20-70 years at recruitment. A lifestyle questionnaire and a validated food frequency questionnaire were administered at recruitment (1993-97). Low adherence to a Mediterranean-style diet was used to determine an unhealthy dietary pattern. Lifestyle-related factors included body mass index, waist circumference, smoking status, physical activity level, dietary supplement use and daily breakfast consumption. Multivariate logistic regression analyses were performed for the total population and by strata of educational level. RESULTS: In total 30% of the study population had an unhealthy dietary pattern: 39% in the lowest educated group and 20% in the highest educated group. Physical inactivity, a large waist circumference, no dietary supplement use and skipping breakfast were associated with an unhealthy dietary pattern in both low and high educated participants. Among low educated participants, current smokers had a greater odds of an unhealthy diet compared with never smokers: OR 1.42 (95% CI: 1.25; 1.61). This association was not observed in the high educated group. CONCLUSIONS: Most associations between lifestyle-related factors and unhealthy diet were consistent across educational levels, except for smoking. Only among low educated participants, current smokers reported an unhealthier dietary pattern in comparison to never smokers. These results can be used in the development of targeted health promotion strategies

    Pancreatic cancer in type 1 and young-onset diabetes: systematic review and meta-analysis

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    We conducted a systematic review of the risk of pancreatic cancer in people with type I and young-onset diabetes. In three cohort and six case–control studies, the relative risk for pancreatic cancer in people with (vs without) diabetes was 2.00 (95% confidence interval 1.37–3.01) based on 39 cases with diabetes

    The significance of tumour microarchitectural features in breast cancer prognosis: a digital image analysis

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    BACKGROUND: As only a minor portion of the information present in histological sections is accessible by eye, recognition and quantification of complex patterns and relationships among constituents relies on digital image analysis. In this study, our working hypothesis was that, with the application of digital image analysis technology, visually unquantifiable breast cancer microarchitectural features can be rigorously assessed and tested as prognostic parameters for invasive breast carcinoma of no special type. METHODS: Digital image analysis was performed using public domain software (ImageJ) on tissue microarrays from a cohort of 696 patients, and validated with a commercial platform (Visiopharm). Quantified features included elements defining tumour microarchitecture, with emphasis on the extent of tumour-stroma interface. The differential prognostic impact of tumour nest microarchitecture in the four immunohistochemical surrogates for molecular classification was analysed. Prognostic parameters included axillary lymph node status, breast cancer-specific survival, and time to distant metastasis. Associations of each feature with prognostic parameters were assessed using logistic regression and Cox proportional models adjusting for age at diagnosis, grade, and tumour size. RESULTS: An arrangement in numerous small nests was associated with axillary lymph node involvement. The association was stronger in luminal tumours (odds ratio (OR) = 1.39, p = 0.003 for a 1-SD increase in nest number, OR = 0.75, p = 0.006 for mean nest area). Nest number was also associated with survival (hazard ratio (HR) = 1.15, p = 0.027), but total nest perimeter was the parameter most significantly associated with survival in luminal tumours (HR = 1.26, p = 0.005). In the relatively small cohort of triple-negative tumours, mean circularity showed association with time to distant metastasis (HR = 1.71, p = 0.027) and survival (HR = 1.8, p = 0.02). CONCLUSIONS: We propose that tumour arrangement in few large nests indicates a decreased metastatic potential. By contrast, organisation in numerous small nests provides the tumour with increased metastatic potential to regional lymph nodes. An outstretched pattern in small nests bestows tumours with a tendency for decreased breast cancer-specific survival. Although further validation studies are required before the argument for routine quantification of microarchitectural features is established, our approach is consistent with the demand for cost-effective methods for triaging breast cancer patients that are more likely to benefit from chemotherapy

    Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models

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    Introduction: Multi-marker molecular assays have impacted management of early stage breast cancer, facilitating adjuvant chemotherapy decisions. We generated prognostic models that incorporate protein-based molecular markers and clinico-pathological variables to improve survival prediction. Methods: We used a quantitative immunofluorescence method to study protein expression of 14 markers included in the Oncotype DX™ assay on a 638 breast cancer patient cohort with 15-year follow-up. We performed cross-validation analyses to assess performance of multivariate Cox models consisting of these markers and standard clinico-pathological covariates, using an average time-dependent Area Under the Receiver Operating Characteristic curves and compared it to nested Cox models obtained by robust backward selection procedures. Results: A prognostic index derived from of a multivariate Cox regression model incorporating molecular and clinico-pathological covariates (nodal status, tumor size, nuclear grade, and age) is superior to models based on molecular studies alone or clinico-pathological covariates alone. Performance of this composite model can be further improved using feature selection techniques to prune variables. When stratifying patients by Nottingham Prognostic Index (NPI), the most prognostic markers in high and low NPI groups differed. Similarly, for the node-negative, hormone receptor-positive sub-population, we derived a compact model with three clinico-pathological variables and two protein markers that was superior to the full model. Conclusions: Prognostic models that include both molecular and clinico-pathological covariates can be more accurate than models based on either set of features alone. Furthermore, feature selection can decrease the number of molecular variables needed to predict outcome, potentially resulting in less expensive assays.This work was supported by a grant from the Susan G Komen Foundation (to YK)

    Association between anthropometry and lifestyle factors and risk of B cell lymphoma: an exposome wide analysis.

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    To better understand the role of individual and lifestyle factors in human disease, an exposome-wide association study was performed to investigate within a single study anthropometry measures and lifestyle factors previously associated with B-cell lymphoma (BCL). Within the European Prospective Investigation into Cancer and nutrition study, 2,402 incident BCL cases were diagnosed from 475,426 participants that were followed-up on average 14 years. Standard and penalized Cox regression models as well as principal component (PC) analysis were used to evaluate 84 exposures in relation to BCL risk. Standard and penalized Cox regression models showed a positive association between anthropometric measures and BCL and multiple myeloma/plasma cell neoplasm (MM). The penalized Cox models additionally showed the association between several exposures from categories of physical activity, smoking status, medical history, socioeconomic position, and diet and BCL and/or the subtypes. PC analyses confirmed the individual associations but also showed additional observations. The PC5 including anthropometry, was positively associated with BCL, diffuse large B-cell lymphoma (DLBCL), and MM. There was a significant positive association between consumption of sugar and confectionary (PC11) and follicular lymphoma risk, and an inverse association between fish and shellfish and Vitamin D (PC15) and DLBCL risk. The PC1 including features of the Mediterranean diet and diet with lower inflammatory score showed an inverse association with BCL risk, while the PC7, including dairy, was positively associated with BCL and DLBCL risk. Physical activity (PC10) was positively associated with DLBCL risk among women. This study provided informative insights on the etiology of BCL
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