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BackgroundBehaviours such as smoking, poor diet, physical inactivity, and unhealthy alcohol consumption are leading risk factors for death. We assessed the Canadian burden attributable to these behaviours by developing, validating, and applying a multivariable predictive model for risk of all-cause death.MethodsA predictive algorithm for 5 y risk of death—the Mortality Population Risk Tool (MPoRT)—was developed and validated using the 2001 to 2008 Canadian Community Health Surveys. There were approximately 1 million person-years of follow-up and 9,900 deaths in the development and validation datasets. After validation, MPoRT was used to predict future mortality and estimate the burden of smoking, alcohol, physical inactivity, and poor diet in the presence of sociodemographic and other risk factors using the 2010 national survey (approximately 90,000 respondents). Canadian period life tables were generated using predicted risk of death from MPoRT. The burden of behavioural risk factors attributable to life expectancy was estimated using hazard ratios from the MPoRT risk model.FindingsThe MPoRT 5 y mortality risk algorithms were discriminating (C-statistic: males 0.874 [95% CI: 0.867–0.881]; females 0.875 [0.868–0.882]) and well calibrated in all 58 predefined subgroups. Discrimination was maintained or improved in the validation cohorts. For the 2010 Canadian population, unhealthy behaviour attributable life expectancy lost was 6.0 years for both men and women (for men 95% CI: 5.8 to 6.3 for women 5.8 to 6.2). The Canadian life expectancy associated with health behaviour recommendations was 17.9 years (95% CI: 17.7 to 18.1) greater for people with the most favourable risk profile compared to those with the least favourable risk profile (88.2 years versus 70.3 years). Smoking, by itself, was associated with 32% to 39% of the difference in life expectancy across social groups (by education achieved or neighbourhood deprivation).ConclusionsMultivariable predictive algorithms such as MPoRT can be used to assess health burdens for sociodemographic groups or for small changes in population exposure to risks, thereby addressing some limitations of more commonly used measurement approaches. Unhealthy behaviours have a substantial collective burden on the life expectancy of the Canadian population.

Background: Recent investigations of breast cancer survival in the United States suggest that patients who receive mastectomy have poorer survival than those who receive breast-conserving surgery (BCS) plus radiotherapy, despite clinically established equivalence. This study investigates breast cancer survival in the publicly funded health care system present in Alberta, Canada.Patients and methods: Surgically treated stage I-III breast cancer cases diagnosed in Alberta from 2002 to 2010 were included. Demographic, treatment and mortality information were collected from the Alberta Cancer Registry. Unadjusted overall and breast cancer-specific mortality was assessed using Kaplan-Meier and cumulative incidence curves, respectively. Cox proportional hazards models were used to calculate stage-specific mortality hazard estimates associated with surgical treatment received.Results: A total of 14 939 cases of breast cancer (14 633 patients) were included in this study. The unadjusted 5-year all-cause survival probabilities for patients treated with BCS plus radiotherapy, mastectomy, and BCS alone were 94% (95% CI 93% to 95%), 83% (95% CI 82% to 84%) and 74% (95% CI 70% to 78%), respectively. Stage II and III patients who received mastectomy had a higher all-cause (stage II HR = 1.36, 95% CI 1.13-1.48; stage III HR = 1.74, 95% CI 1.24-2.45) and breast cancer-specific (stage II HR = 1.39, 95% CI 1.09-1.76; stage III HR = 1.79, 95% CI 1.21-2.65) mortality hazard compared with those who received BCS plus radiotherapy, adjusting for patient and clinical characteristics. BCS alone was consistently associated with poor survival.Conclusions: Stage II and III breast cancer patients diagnosed in Alberta, Canada, who received mastectomy had a significantly higher all-cause and breast cancer-specific mortality hazard compared with those who received BCS plus radiotherapy. We suggest greater efforts toward educating and encouraging patients to receive BCS plus radiotherapy rather than mastectomy when it is medically feasible and appropriate.

ig data" has the potential to support personalized or precision medicine through more complex riskprediction algorithms with more predictors.1-3 These data can be used to accurately assess disease risk across subgroups with distinct characteristics or health profiles -including situations where a health profile represents only a fraction of the overall population.Furthermore, compared with more commonly used clinical data or epidemiology studies, large population health surveys have the potential to generate predictive algorithms that are more patient-oriented, have the potential to perform better across socioeconomic groups, and can be used for both population and clinical purposes.First, population health surveys emphasize sociodemographic profile and health behaviours. These patient-oriented risks are common for multiple chronic diseases. 4 Risks are all ascertained using self-response questions and validated for use in a broad community setting. This allows people to calculate their own risk in a nonclinical setting -reducing the burden on clinicians to collect and perform risk calculation. Second, algorithms developed using entire populations should be better calibrated (i.e., predictive risk closely approximating real or observed risk) and generalizable (i.e., better performing in a wide range of settings). As well, there are opportunities to recalibrate risk algorithms using population data that are not feasible with clinical data. AbstrAct BackgRounD: Routinely collected data from large population health surveys linked to chronic disease outcomes create an opportunity to develop more complex risk-prediction algorithms. We developed a predictive algorithm to estimate 5-year risk of incident cardiovascular disease in the community setting.