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      Atmospheric fine particulate matter and breast cancer mortality: a population-based cohort study

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          Abstract

          Objectives

          Atmospheric fine particulate matter (PM 2.5) has multiple adverse effects on human health. Global atmospheric levels of PM 2.5 increased by 0.55 μg/m 3/year (2.1%/year) from 1998 through 2012. There is evidence of a causal relationship between atmospheric PM 2.5 and breast cancer (BC) incidence, but few studies have investigated BC mortality and atmospheric PM 2.5. We investigated BC mortality in relation to atmospheric PM 2.5 levels among patients living in Varese Province, northern Italy.

          Methods

          We selected female BC cases, archived in the local population-based cancer registry, diagnosed at age 50–69 years, between 2003 and 2009. The geographic coordinates of each woman's place of residence were identified, and individual PM 2.5 exposures were assessed from satellite data. Grade, stage, age at diagnosis, period of diagnosis and participation in BC screening were potential confounders. Kaplan-Meir and Nelson-Aalen methods were used to test for mortality differences in relation to PM 2.5 quartiles. Multivariable Cox proportional hazards modelling estimated HRs and 95% CIs of BC death in relation to PM 2.5 exposure.

          Results

          Of 2021 BC cases, 325 died during follow-up to 31 December 2013, 246 for BC. Risk of BC death was significantly higher for all three upper quartiles of PM 2.5 exposure compared to the lowest, with HRs of death: 1.82 (95% CI 1.15 to 2.89), 1.73 (95% CI 1.12 to 2.67) and 1.72 (95% CI 1.08 to 2.75).

          Conclusions

          Our study indicates that the risk of BC mortality increases with PM 2.5 exposure. Although additional research is required to confirm these findings, they are further evidence that PM 2.5 exposure is harmful and indicate an urgent need to improve global air quality.

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          Most cited references14

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          Air pollution and lung cancer incidence in 17 European cohorts: prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE).

          Ambient air pollution is suspected to cause lung cancer. We aimed to assess the association between long-term exposure to ambient air pollution and lung cancer incidence in European populations. This prospective analysis of data obtained by the European Study of Cohorts for Air Pollution Effects used data from 17 cohort studies based in nine European countries. Baseline addresses were geocoded and we assessed air pollution by land-use regression models for particulate matter (PM) with diameter of less than 10 μm (PM10), less than 2·5 μm (PM2·5), and between 2·5 and 10 μm (PMcoarse), soot (PM2·5absorbance), nitrogen oxides, and two traffic indicators. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effects models for meta-analyses. The 312 944 cohort members contributed 4 013 131 person-years at risk. During follow-up (mean 12·8 years), 2095 incident lung cancer cases were diagnosed. The meta-analyses showed a statistically significant association between risk for lung cancer and PM10 (hazard ratio [HR] 1·22 [95% CI 1·03-1·45] per 10 μg/m(3)). For PM2·5 the HR was 1·18 (0·96-1·46) per 5 μg/m(3). The same increments of PM10 and PM2·5 were associated with HRs for adenocarcinomas of the lung of 1·51 (1·10-2·08) and 1·55 (1·05-2·29), respectively. An increase in road traffic of 4000 vehicle-km per day within 100 m of the residence was associated with an HR for lung cancer of 1·09 (0·99-1·21). The results showed no association between lung cancer and nitrogen oxides concentration (HR 1·01 [0·95-1·07] per 20 μg/m(3)) or traffic intensity on the nearest street (HR 1·00 [0·97-1·04] per 5000 vehicles per day). Particulate matter air pollution contributes to lung cancer incidence in Europe. European Community's Seventh Framework Programme. Copyright © 2013 Elsevier Ltd. All rights reserved.
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            Variables with time-varying effects and the Cox model: Some statistical concepts illustrated with a prognostic factor study in breast cancer

            Background The Cox model relies on the proportional hazards (PH) assumption, implying that the factors investigated have a constant impact on the hazard - or risk - over time. We emphasize the importance of this assumption and the misleading conclusions that can be inferred if it is violated; this is particularly essential in the presence of long follow-ups. Methods We illustrate our discussion by analyzing prognostic factors of metastases in 979 women treated for breast cancer with surgery. Age, tumour size and grade, lymph node involvement, peritumoral vascular invasion (PVI), status of hormone receptors (HRec), Her2, and Mib1 were considered. Results Median follow-up was 14 years; 264 women developed metastases. The conventional Cox model suggested that all factors but HRec, Her2, and Mib1 status were strong prognostic factors of metastases. Additional tests indicated that the PH assumption was not satisfied for some variables of the model. Tumour grade had a significant time-varying effect, but although its effect diminished over time, it remained strong. Interestingly, while the conventional Cox model did not show any significant effect of the HRec status, tests provided strong evidence that this variable had a non-constant effect over time. Negative HRec status increased the risk of metastases early but became protective thereafter. This reversal of effect may explain non-significant hazard ratios provided by previous conventional Cox analyses in studies with long follow-ups. Conclusions Investigating time-varying effects should be an integral part of Cox survival analyses. Detecting and accounting for time-varying effects provide insights on some specific time patterns, and on valuable biological information that could be missed otherwise.
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              Healthy lifestyle and risk of breast cancer among postmenopausal women in the European Prospective Investigation into Cancer and Nutrition cohort study.

              Breast cancer is the most common cancer among women and prevention strategies are needed to reduce incidence worldwide. A healthy lifestyle index score (HLIS) was generated to investigate the joint effect of modifiable lifestyle factors on postmenopausal breast cancer risk. The study included 242,918 postmenopausal women from the multinational European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, with detailed information on diet and lifestyle assessed at baseline. The HLIS was constructed from five factors (diet, physical activity, smoking, alcohol consumption and anthropometry) by assigning scores of 0-4 to categories of each component, for which higher values indicate healthier behaviours. Hazard ratios (HR) were estimated by Cox proportional regression models. During 10.9 years of median follow-up, 7,756 incident breast cancer cases were identified. There was a 3% lower risk of breast cancer per point increase of the HLIS. Breast cancer risk was inversely associated with a high HLIS when fourth versus second (reference) categories were compared [adjusted HR = 0.74; 95% confidence interval (CI): 0.66-0.83]. The fourth versus the second category of the HLIS was associated with a lower risk for hormone receptor double positive (adjusted HR = 0.81, 95% CI: 0.67-0.98) and hormone receptor double negative breast cancer (adjusted HR = 0.60, 95% CI: 0.40-0.90). Findings suggest having a high score on an index of combined healthy behaviours reduces the risk of developing breast cancer among postmenopausal women. Programmes which engage women in long term health behaviours should be supported.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2016
                14 November 2016
                : 6
                : 11
                : e012580
                Affiliations
                [1 ]Cancer Registry Unit, Fondazione IRCCS Istituto Nazionale dei Tumori , Milan, Italy
                [2 ]Environmental Epidemiology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori , Milan, Italy
                [3 ]Department of Physics and Atmospheric Science, Dalhousie University , Halifax, Nova Scotia, Canada
                [4 ]Harvard-Smithsonian Center for Astrophysics , Cambridge, Massachusetts, USA
                [5 ]Local Health Unit, Province of Sondrio, Sondrio, Italy
                Author notes
                [Correspondence to ] Dr Paolo Contiero; paolo.contiero@ 123456istitutotumori.mi.it
                Article
                bmjopen-2016-012580
                10.1136/bmjopen-2016-012580
                5129133
                28076275
                5dd878e0-8be0-4138-8113-48038e9db78a
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 10 May 2016
                : 15 September 2016
                : 13 October 2016
                Categories
                Occupational and Environmental Medicine
                Research
                1506
                1716
                1717
                1692

                Medicine
                particulate matter,environment,prognosis,survival,cancer registry
                Medicine
                particulate matter, environment, prognosis, survival, cancer registry

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