Factors associated with COVID-19-related death using OpenSAFELY.

Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide1. There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches for the timely analysis of large datasets. Working on behalf of NHS England, we created OpenSAFELY-a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records. Here we used OpenSAFELY to examine factors associated with COVID-19-related death. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19-related deaths. COVID-19-related death was associated with: being male (hazard ratio (HR) 1.59 (95% confidence interval 1.53-1.65)); greater age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared with people of white ethnicity, Black and South Asian people were at higher risk, even after adjustment for other factors (HR 1.48 (1.29-1.69) and 1.45 (1.32-1.58), respectively). We have quantified a range of clinical factors associated with COVID-19-related death in one of the largest cohort studies on this topic so far. More patient records are rapidly being added to OpenSAFELY, we will update and extend our results regularly.

Sustained Hypothetical Interventions on Midlife Alcohol Consumption in Relation to All-Cause and Cancer Mortality: The Australian Longitudinal Study on Women's Health.

No randomized controlled trial has evaluated the effect of long-term alcohol interventions on mortality. Results reported in existing observational studies may be subject to selection bias and time-varying confounding. Using data from the Australian Longitudinal Study on Women's Health 1946-1951 birth cohort, collected regularly from 1996-2016, we estimated all-cause and cancer mortality had women been assigned various alcohol interventions (in categories ranging from 0 to >30 g/day ethanol, or reduced to ≤20 g/day if higher) at baseline, and had they maintained these levels of consumption. The cumulative risks for all-cause and cancer mortality were 5.6% (10,118 women followed for 20 years) and 2.9% (18 years), respectively. For all-cause and cancer mortality, baseline ethanol up to 30 g/day showed lower risk and >30 g/day showed higher risk relative to abstention. Had women sustainedly followed the interventions, a similar relationship was observed for all-cause mortality. However, the negative association observed for intakes ≤30 g/day and positive association for intakes >30 g/day was not evident for cancer mortality. Our findings suggest that all-cause mortality could have been lower than observed if this cohort of women had consumed some alcohol (no more than 30 g/day) rather than no consumption, but cancer mortality might not.

Effectiveness of mRNA COVID-19 Vaccines as First Booster Doses in England: An Observational Study in OpenSAFELY-TPP.

BACKGROUND: The UK delivered its first "booster" COVID-19 vaccine doses in September 2021, initially to individuals at high risk of severe disease, then to all adults. The BNT162b2 Pfizer-BioNTech vaccine was used initially, then also Moderna mRNA-1273. METHODS: With the approval of the National Health Service England, we used routine clinical data to estimate the effectiveness of boosting with BNT162b2 or mRNA-1273 compared with no boosting in eligible adults who had received two primary course vaccine doses. We matched each booster recipient with an unboosted control on factors relating to booster priority status and prior COVID-19 immunization. We adjusted for additional factors in Cox models, estimating hazard ratios up to 182 days (6 months) following booster dose. We estimated hazard ratios overall and within the following periods: 1-14, 15-42, 43-69, 70-97, 98-126, 127-152, and 155-182 days. Outcomes included a positive SARS-CoV-2 test, COVID-19 hospitalization, COVID-19 death, non-COVID-19 death, and fracture. RESULTS: We matched 8,198,643 booster recipients with unboosted controls. Adjusted hazard ratios over 6-month follow-up were: positive SARS-CoV-2 test 0.75 (0.74, 0.75); COVID-19 hospitalization 0.30 (0.29, 0.31); COVID-19 death 0.11 (0.10, 0.14); non-COVID-19 death 0.22 (0.21, 0.23); and fracture 0.77 (0.75, 0.78). Estimated effectiveness of booster vaccines against severe COVID-19-related outcomes peaked during the first 3 months following the booster dose. By 6 months, the cumulative incidence of positive SARS-CoV-2 test was higher in boosted than unboosted individuals. CONCLUSIONS: We estimate that COVID-19 booster vaccination, compared with no booster vaccination, provided substantial protection against COVID-19 hospitalization and COVID-19 death but only limited protection against positive SARS-CoV-2 test. Lower rates of fracture in boosted than unboosted individuals may suggest unmeasured confounding. Observational studies should report estimated vaccine effectiveness against nontarget and negative control outcomes.

On variance estimation of the inverse probability-of-treatment weighting estimator: A tutorial for different types of propensity score weights.

Propensity score methods, such as inverse probability-of-treatment weighting (IPTW), have been increasingly used for covariate balancing in both observational studies and randomized trials, allowing the control of both systematic and chance imbalances. Approaches using IPTW are based on two steps: (i) estimation of the individual propensity scores (PS), and (ii) estimation of the treatment effect by applying PS weights. Thus, a variance estimator that accounts for both steps is crucial for correct inference. Using a variance estimator which ignores the first step leads to overestimated variance when the estimand is the average treatment effect (ATE), and to under or overestimated estimates when targeting the average treatment effect on the treated (ATT). In this article, we emphasize the importance of using an IPTW variance estimator that correctly considers the uncertainty in PS estimation. We present a comprehensive tutorial to obtain unbiased variance estimates, by proposing and applying a unifying formula for different types of PS weights (ATE, ATT, matching and overlap weights). This can be derived either via the linearization approach or M-estimation. Extensive R code is provided along with the corresponding large-sample theory. We perform simulation studies to illustrate the behavior of the estimators under different treatment and outcome prevalences and demonstrate appropriate behavior of the analytical variance estimator. We also use a reproducible analysis of observational lung cancer data as an illustrative example, estimating the effect of receiving a PET-CT scan on the receipt of surgery.

OpenSAFELY: A platform for analysing electronic health records designed for reproducible research.

Electronic health records (EHRs) and other administrative health data are increasingly used in research to generate evidence on the effectiveness, safety, and utilisation of medical products and services, and to inform public health guidance and policy. Reproducibility is a fundamental step for research credibility and promotes trust in evidence generated from EHRs. At present, ensuring research using EHRs is reproducible can be challenging for researchers. Research software platforms can provide technical solutions to enhance the reproducibility of research conducted using EHRs. In response to the COVID-19 pandemic, we developed the secure, transparent, analytic open-source software platform OpenSAFELY designed with reproducible research in mind. OpenSAFELY mitigates common barriers to reproducible research by: standardising key workflows around data preparation; removing barriers to code-sharing in secure analysis environments; enforcing public sharing of programming code and codelists; ensuring the same computational environment is used everywhere; integrating new and existing tools that encourage and enable the use of reproducible working practices; and providing an audit trail for all code that is run against the real data to increase transparency. This paper describes OpenSAFELY's reproducibility-by-design approach in detail.

Prevalent new user designs: A literature review of current implementation practice.

PURPOSE: Prevalent new user (PNU) designs extend the active comparator new user design by allowing for the inclusion of initiators of the study drug who were previously on a comparator treatment. We performed a literature review summarising current practice. METHODS: PubMed was searched for studies applying the PNU design since its proposal in 2017. The review focused on three components. First, we extracted information on the overall study design, including the database used. We summarised information on implementation of the PNU design, including key decisions relating to exposure set definition and estimation of time-conditional propensity scores. Finally, we reviewed the analysis strategy of the matched cohort. RESULTS: Nineteen studies met the criteria for inclusion. Most studies (73%) implemented the PNU design in electronic health record or registry databases, with the remaining using insurance claims databases. Of 15 studies including a class of prevalent users, 40% deviated from the original exposure set definition proposals in favour of a more complex definition. Four studies did not include prevalent new users but used other aspects of the PNU framework. Several studies lacked details on exposure set definition (n = 2), time-conditional propensity score model (n = 2) or integration of complex analytical techniques, such as the high-dimensional propensity score algorithm (n = 3). CONCLUSION: PNU designs have been applied in a range of therapeutic and disease areas. However, to encourage more widespread use of this design and help shape best practice, there is a need for improved accessibility, specifically through the provision of analytical code alongside guidance to support implementation and transparent reporting.

Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: A cohort study using linked primary care, secondary care, and death registration data in the OpenSAFELY platform.

BACKGROUND: There is concern about medium to long-term adverse outcomes following acute Coronavirus Disease 2019 (COVID-19), but little relevant evidence exists. We aimed to investigate whether risks of hospital admission and death, overall and by specific cause, are raised following discharge from a COVID-19 hospitalisation. METHODS AND FINDINGS: With the approval of NHS-England, we conducted a cohort study, using linked primary care and hospital data in OpenSAFELY to compare risks of hospital admission and death, overall and by specific cause, between people discharged from COVID-19 hospitalisation (February to December 2020) and surviving at least 1 week, and (i) demographically matched controls from the 2019 general population; and (ii) people discharged from influenza hospitalisation in 2017 to 2019. We used Cox regression adjusted for age, sex, ethnicity, obesity, smoking status, deprivation, and comorbidities considered potential risk factors for severe COVID-19 outcomes. We included 24,673 postdischarge COVID-19 patients, 123,362 general population controls, and 16,058 influenza controls, followed for ≤315 days. COVID-19 patients had median age of 66 years, 13,733 (56%) were male, and 19,061 (77%) were of white ethnicity. Overall risk of hospitalisation or death (30,968 events) was higher in the COVID-19 group than general population controls (fully adjusted hazard ratio [aHR] 2.22, 2.14 to 2.30, p < 0.001) but slightly lower than the influenza group (aHR 0.95, 0.91 to 0.98, p = 0.004). All-cause mortality (7,439 events) was highest in the COVID-19 group (aHR 4.82, 4.48 to 5.19 versus general population controls [p < 0.001] and 1.74, 1.61 to 1.88 versus influenza controls [p < 0.001]). Risks for cause-specific outcomes were higher in COVID-19 survivors than in general population controls and largely similar or lower in COVID-19 compared with influenza patients. However, COVID-19 patients were more likely than influenza patients to be readmitted or die due to their initial infection or other lower respiratory tract infection (aHR 1.37, 1.22 to 1.54, p < 0.001) and to experience mental health or cognitive-related admission or death (aHR 1.37, 1.02 to 1.84, p = 0.039); in particular, COVID-19 survivors with preexisting dementia had higher risk of dementia hospitalisation or death (age- and sex-adjusted HR 2.47, 1.37 to 4.44, p = 0.002). Limitations of our study were that reasons for hospitalisation or death may have been misclassified in some cases due to inconsistent use of codes, and we did not have data to distinguish COVID-19 variants. CONCLUSIONS: In this study, we observed that people discharged from a COVID-19 hospital admission had markedly higher risks for rehospitalisation and death than the general population, suggesting a substantial extra burden on healthcare. Most risks were similar to those observed after influenza hospitalisations, but COVID-19 patients had higher risks of all-cause mortality, readmission or death due to the initial infection, and dementia death, highlighting the importance of postdischarge monitoring.

Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform.

BACKGROUND: COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England. METHODS: We conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region. FINDINGS: Of 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07-1·09]), Black group (1·08 [1·06-1·09]), and mixed ethnicity group (1·04 [1·02-1·05]) and was decreased in the other ethnicity group (0·77 [0·76-0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94-2·04]), Black group (1·69 [1·62-1·77]), mixed ethnicity group (1·49 [1·39-1·59]), and other ethnicity group (1·20 [1·14-1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41-1·55], Black group 1·78 [1·67-1·90], mixed ethnicity group 1·63 [1·45-1·83], other ethnicity group 1·54 [1·41-1·69]), COVID-19-related ICU admission (2·18 [1·92-2·48], 3·12 [2·65-3·67], 2·96 [2·26-3·87], 3·18 [2·58-3·93]), and death (1·26 [1·15-1·37], 1·51 [1·31-1·71], 1·41 [1·11-1·81], 1·22 [1·00-1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories. INTERPRETATION: Some minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination. FUNDING: Medical Research Council.

Transparency of high-dimensional propensity score analyses: Guidance for diagnostics and reporting.

PURPOSE: The high-dimensional propensity score (HDPS) is a semi-automated procedure for confounder identification, prioritisation and adjustment in large healthcare databases that requires investigators to specify data dimensions, prioritisation strategy and tuning parameters. In practice, reporting of these decisions is inconsistent and this can undermine the transparency, and reproducibility of results obtained. We illustrate reporting tools, graphical displays and sensitivity analyses to increase transparency and facilitate evaluation of the robustness of analyses involving HDPS. METHODS: Using a study from the UK Clinical Practice Research Datalink that implemented HDPS we demonstrate the application of the proposed recommendations. RESULTS: We identify seven considerations surrounding the implementation of HDPS, such as the identification of data dimensions, method for code prioritisation and number of variables selected. Graphical diagnostic tools include assessing the balance of key confounders before and after adjusting for empirically selected HDPS covariates and the identification of potentially influential covariates. Sensitivity analyses include varying the number of covariates selected and assessing the impact of covariates behaving empirically as instrumental variables. In our example, results were robust to both the number of covariates selected and the inclusion of potentially influential covariates. Furthermore, our HDPS models achieved good balance in key confounders. CONCLUSIONS: The data-adaptive approach of HDPS and the resulting benefits have led to its popularity as a method for confounder adjustment in pharmacoepidemiological studies. Reporting of HDPS analyses in practice may be improved by the considerations and tools proposed here to increase the transparency and reproducibility of study results.

Recording of 'COVID-19 vaccine declined': a cohort study on 57.9 million National Health Service patients' records in situ using OpenSAFELY, England, 8 December 2020 to 25 May 2021.

BackgroundPriority patients in England were offered COVID-19 vaccination by mid-April 2021. Codes in clinical record systems can denote the vaccine being declined.AimWe describe records of COVID-19 vaccines being declined, according to clinical and demographic factors.MethodsWith the approval of NHS England, we conducted a retrospective cohort study between 8 December 2020 and 25 May 2021 with primary care records for 57.9 million patients using OpenSAFELY, a secure health analytics platform. COVID-19 vaccination priority patients were those aged ≥ 50 years or ≥ 16 years clinically extremely vulnerable (CEV) or 'at risk'. We describe the proportion recorded as declining vaccination for each group and stratified by clinical and demographic subgroups, subsequent vaccination and distribution of clinical code usage across general practices.ResultsOf 24.5 million priority patients, 663,033 (2.7%) had a decline recorded, while 2,155,076 (8.8%) had neither a vaccine nor decline recorded. Those recorded as declining, who were subsequently vaccinated (n = 125,587; 18.9%) were overrepresented in the South Asian population (32.3% vs 22.8% for other ethnicities aged ≥ 65 years). The proportion of declining unvaccinated patients was highest in CEV (3.3%), varied strongly with ethnicity (black 15.3%, South Asian 5.6%, white 1.5% for ≥ 80 years) and correlated positively with increasing deprivation.ConclusionsClinical codes indicative of COVID-19 vaccinations being declined are commonly used in England, but substantially more common among black and South Asian people, and in more deprived areas. Qualitative research is needed to determine typical reasons for recorded declines, including to what extent they reflect patients actively declining.

Common Methods for Handling Missing Data in Marginal Structural Models: What Works and Why.

Marginal structural models (MSMs) are commonly used to estimate causal intervention effects in longitudinal nonrandomized studies. A common challenge when using MSMs to analyze observational studies is incomplete confounder data, where a poorly informed analysis method will lead to biased estimates of intervention effects. Despite a number of approaches described in the literature for handling missing data in MSMs, there is little guidance on what works in practice and why. We reviewed existing missing-data methods for MSMs and discussed the plausibility of their underlying assumptions. We also performed realistic simulations to quantify the bias of 5 methods used in practice: complete-case analysis, last observation carried forward, the missingness pattern approach, multiple imputation, and inverse-probability-of-missingness weighting. We considered 3 mechanisms for nonmonotone missing data encountered in research based on electronic health record data. Further illustration of the strengths and limitations of these analysis methods is provided through an application using a cohort of persons with sleep apnea: the research database of the French Observatoire Sommeil de la Fédération de Pneumologie. We recommend careful consideration of 1) the reasons for missingness, 2) whether missingness modifies the existing relationships among observed data, and 3) the scientific context and data source, to inform the choice of the appropriate method(s) for handling partially observed confounders in MSMs.

Association between circulating 25-hydroxyvitamin D concentrations and hip replacement for osteoarthritis: a prospective cohort study.

BACKGROUND: To examine the association between circulating 25(OH)D concentrations and incidence of total hip replacement for osteoarthritis in a prospective cohort study. METHODS: This study examined a random sample of 2651 participants in the Melbourne Collaborative Cohort Study who had 25(OH)D concentrations measured from dried blood spots collected in 1990-1994. Participants who underwent total hip replacement for osteoarthritis between January 2001 and December 2018 were identified by linking the cohort records to the Australian Orthopaedic Association National Joint Replacement Registry. Cox proportional hazard regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) of total hip replacement for osteoarthritis in relation to 25(OH)D concentrations, adjusted for confounders. RESULTS: Eighty-six men and eighty-seven women had a total hip replacement for osteoarthritis. Compared with men in the lowest (1st) quartile of 25(OH)D concentration, the HR for total hip replacement was 2.32 (95% CI 1.05, 5.13) for those in the 2nd quartile, 2.77 (95% CI 1.28, 6.00) for those in the 3rd quartile, and 1.73 (95% CI 0.75, 4.02) for those in the highest quartile of 25(OH)D concentrations (p for trend 0.02). There was little evidence of an association in women. CONCLUSIONS: Higher circulating 25(OH)D concentrations were associated with an increased risk of total hip replacement for osteoarthritis in men but not in women. Although the underlying mechanism warrants further investigation, our findings highlight the need to determine the optimal levels of circulating 25(OH)D to reduce the risk of hip osteoarthritis.

Propensity scores using missingness pattern information: a practical guide.

Electronic health records are a valuable data source for investigating health-related questions, and propensity score analysis has become an increasingly popular approach to address confounding bias in such investigations. However, because electronic health records are typically routinely recorded as part of standard clinical care, there are often missing values, particularly for potential confounders. In our motivating study-using electronic health records to investigate the effect of renin-angiotensin system blockers on the risk of acute kidney injury-two key confounders, ethnicity and chronic kidney disease stage, have 59% and 53% missing data, respectively. The missingness pattern approach (MPA), a variant of the missing indicator approach, has been proposed as a method for handling partially observed confounders in propensity score analysis. In the MPA, propensity scores are estimated separately for each missingness pattern present in the data. Although the assumptions underlying the validity of the MPA are stated in the literature, it can be difficult in practice to assess their plausibility. In this article, we explore the MPA's underlying assumptions by using causal diagrams to assess their plausibility in a range of simple scenarios, drawing general conclusions about situations in which they are likely to be violated. We present a framework providing practical guidance for assessing whether the MPA's assumptions are plausible in a particular setting and thus deciding when the MPA is appropriate. We apply our framework to our motivating study, showing that the MPA's underlying assumptions appear reasonable, and we demonstrate the application of MPA to this study.

Estimating treatment effects with partially observed covariates using outcome regression with missing indicators.

Missing data is a common issue in research using observational studies to investigate the effect of treatments on health outcomes. When missingness occurs only in the covariates, a simple approach is to use missing indicators to handle the partially observed covariates. The missing indicator approach has been criticized for giving biased results in outcome regression. However, recent papers have suggested that the missing indicator approach can provide unbiased results in propensity score analysis under certain assumptions. We consider assumptions under which the missing indicator approach can provide valid inferences, namely, (1) no unmeasured confounding within missingness patterns; either (2a) covariate values of patients with missing data were conditionally independent of treatment or (2b) these values were conditionally independent of outcome; and (3) the outcome model is correctly specified: specifically, the true outcome model does not include interactions between missing indicators and fully observed covariates. We prove that, under the assumptions above, the missing indicator approach with outcome regression can provide unbiased estimates of the average treatment effect. We use a simulation study to investigate the extent of bias in estimates of the treatment effect when the assumptions are violated and we illustrate our findings using data from electronic health records. In conclusion, the missing indicator approach can provide valid inferences for outcome regression, but the plausibility of its assumptions must first be considered carefully.

Sustained adherence to a Mediterranean diet and physical activity on all-cause mortality in the Melbourne Collaborative Cohort Study: application of the g-formula.

BACKGROUND: Adherence to a traditional Mediterranean diet has been associated with lower mortality and cardiovascular disease risk. The relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time remains unknown. METHODS: We used the parametric G-formula to account for time-dependent confounding, in order to assess the relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time. We included healthy Melbourne Collaborative Cohort Study participants attending a visit during 1995-1999. Questionnaires assessed diet and physical activity at each of three study waves. Deaths were identified by linkage to national registries. We estimated mortality risk over approximately 14 years (1995-2011). RESULTS: Of 22,213 participants, 2163 (9.7%) died during 13.6 years median follow-up. Sustained high physical activity and adherence to a Mediterranean-style diet resulted in an estimated reduction in all-cause mortality of 1.82 per 100 people (95% confidence interval (CI): 0.03, 3.6). The population attributable fraction was 13% (95% CI: 4, 23%) for sustained high physical activity, 7% (95% CI: - 3, 17%) for sustained adherence to a Mediterranean-style diet and 18% (95% CI: 0, 36%) for their combination. CONCLUSIONS: A small reduction in mortality may be achieved by sustained elevated physical activity levels in healthy middle-aged adults, but there may be comparatively little gain from increasing adherence to a Mediterranean-style diet.

Associations of alcohol intake, smoking, physical activity and obesity with survival following colorectal cancer diagnosis by stage, anatomic site and tumor molecular subtype.

The influence of lifestyle factors on survival following a diagnosis of colorectal cancer (CRC) is not well established. We examined associations between lifestyle factors measured before diagnosis and CRC survival. The Melbourne Collaborative Cohort Study collected data on alcohol intake, cigarette smoking and physical activity, and body measurements at baseline (1990-1994) and wave 2 (2003-2007). We included participants diagnosed to 31 August 2015 with incident stages I-III CRC within 10-years post exposure assessment. Information on tumor characteristics and vital status was obtained. Tumor DNA was tested for microsatellite instability (MSI) and somatic mutations in oncogenes BRAF (V600E) and KRAS. We estimated hazard ratios (HRs) for associations between lifestyle factors and overall and CRC-specific mortality using Cox regression. Of 724 eligible CRC cases, 339 died (170 from CRC) during follow-up (average 9.0 years). Exercise (non-occupational/leisure-time) was associated with higher CRC-specific survival for stage II (HR = 0.25, 95% CI: 0.10-0.60) but not stages I/III disease (p for interaction = 0.01), and possibly for colon and KRAS wild-type tumors. Waist circumference was inversely associated with CRC-specific survival (HR = 1.25 per 10 cm increment, 95% CI: 1.08-1.44), independent of stage, anatomic site and tumor molecular status. Cigarette smoking was associated with lower overall survival, with suggestive evidence of worse survival for BRAF mutated CRC, but not with CRC-specific survival. Alcohol intake was not associated with survival. Survival did not differ by MSI status. We have identified pre-diagnostic predictors of survival following CRC that may have clinical and public health relevance.

Lifetime alcohol intake is associated with an increased risk of KRAS+ and BRAF-/KRAS- but not BRAF+ colorectal cancer.

Ethanol in alcoholic beverages is a causative agent for colorectal cancer. Colorectal cancer is a biologically heterogeneous disease, and molecular subtypes defined by the presence of somatic mutations in BRAF and KRAS are known to exist. We examined associations between lifetime alcohol intake and molecular and anatomic subtypes of colorectal cancer. We calculated usual alcohol intake for 10-year periods from age 20 using recalled frequency and quantity of beverage-specific consumption for 38,149 participants aged 40-69 years from the Melbourne Collaborative Cohort Study. Cox regression was performed to derive hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between lifetime alcohol intake and colorectal cancer risk. Heterogeneity in the HRs across subtypes of colorectal cancer was assessed. A positive dose-dependent association between lifetime alcohol intake and overall colorectal cancer risk (mean follow-up = 14.6 years; n = 596 colon and n = 326 rectal cancer) was observed (HR = 1.08, 95% CI: 1.04-1.12 per 10 g/day increment). The risk was greater for rectal than colon cancer (phomogeneity = 0.02). Alcohol intake was associated with increased risks of KRAS+ (HR = 1.07, 95% CI: 1.00-1.15) and BRAF-/KRAS- (HR = 1.05, 95% CI: 1.00-1.11) but not BRAF+ tumors (HR = 0.89, 95% CI: 0.78-1.01; phomogeneity = 0.01). Alcohol intake is associated with an increased risk of KRAS+ and BRAF-/KRAS- tumors originating via specific molecular pathways including the traditional adenoma-carcinoma pathway but not with BRAF+ tumors originating via the serrated pathway. Therefore, limiting alcohol intake from a young age might reduce colorectal cancer originating via the traditional adenoma-carcinoma pathway.

Tuberculosis in migrants moving from high-incidence to low-incidence countries: a population-based cohort study of 519 955 migrants screened before entry to England, Wales, and Northern Ireland.

BACKGROUND: Tuberculosis elimination in countries with a low incidence of the disease necessitates multiple interventions, including innovations in migrant screening. We examined a cohort of migrants screened for tuberculosis before entry to England, Wales, and Northern Ireland and tracked the development of disease in this group after arrival. METHODS: As part of a pilot pre-entry screening programme for tuberculosis in 15 countries with a high incidence of the disease, the International Organization for Migration screened all applicants for UK visas aged 11 years or older who intended to stay for more than 6 months. Applicants underwent a chest radiograph, and any with results suggestive of tuberculosis underwent sputum testing and culture testing (when available). We tracked the development of tuberculosis in those who tested negative for the disease and subsequently migrated to England, Wales, and Northern Ireland with the Enhanced Tuberculosis Surveillance system. Primary outcomes were cases of all forms of tuberculosis (including clinically diagnosed cases), and bacteriologically confirmed pulmonary tuberculosis. FINDINGS: Our study cohort was 519 955 migrants who were screened for tuberculosis before entry to the UK between Jan 1, 2006, and Dec 31, 2012. Cases notified on the Enhanced Tuberculosis Surveillance system between Jan 1, 2006, and Dec 31, 2013, were included. 1873 incident cases of all forms of tuberculosis were identified, and, on the basis of data for England, Wales, and Northern Ireland, the estimated incidence of all forms of tuberculosis in migrants screened before entry was 147 per 100 000 person-years (95% CI 140-154). The estimated incidence of bacteriologically confirmed pulmonary tuberculosis in migrants screened before entry was 49 per 100 000 person-years (95% CI 45-53). Migrants whose chest radiographs were compatible with active tuberculosis but with negative pre-entry microbiological results were at increased risk of tuberculosis compared with those with no radiographic abnormalities (incidence rate ratio 3·2, 95% CI 2·8-3·7; p<0·0001). Incidence of tuberculosis after migration increased significantly with increasing WHO-estimated prevalence of tuberculosis in migrants' countries of origin. 35 of 318 983 pre-entry screened migrants included in a secondary analysis with typing data were assumed index cases. Estimates of the rate of assumed reactivation tuberculosis ranged from 46 (95% CI 42-52) to 91 (82-102) per 100 000 population. INTERPRETATION: Migrants from countries with a high incidence of tuberculosis screened before being granted entry to low-incidence countries pose a negligible risk of onward transmission but are at increased risk of tuberculosis, which could potentially be prevented through identification and treatment of latent infection in close collaboration with a pre-entry screening programme. FUNDING: Wellcome Trust, UK National Institute for Health Research, UK Medical Research Council, Public Health England, and Department of Health Policy Research Programme.

25-Hydroxyvitamin D concentration and all-cause mortality: the Melbourne Collaborative Cohort Study.

OBJECTIVE: To investigate relationships between mortality and circulating 25-hydroxyvitamin D (25(OH)D), 25-hydroxycholecalciferol (25(OH)D3) and 25-hydroxyergocalciferol (25(OH)D2). DESIGN: Case-cohort study within the Melbourne Collaborative Cohort Study (MCCS). We measured 25(OH)D2 and 25(OH)D3 in archived dried blood spots by LC-MS/MS. Cox regression was used to estimate mortality hazard ratios (HR), with adjustment for confounders. SETTING: General community. SUBJECTS: The MCCS included 29 206 participants, who at recruitment in 1990-1994 were aged 40-69 years, had dried blood spots collected and no history of cancer. For the present study we selected participants who died by 31 December 2007 (n 2410) and a random sample (sub-cohort, n 2996). RESULTS: The HR per 25 nmol/l increment in concentration of 25(OH)D and 25(OH)D3 were 0·86 (95 % CI 0·78, 0·96; P=0·007) and 0·85 (95 % CI 0·77, 0·95; P=0·003), respectively. Of 5108 participants, sixty-three (1·2 %) had detectable 25(OH)D2; their mean 25(OH)D concentration was 11·9 (95 % CI 7·3, 16·6) nmol/l higher (P<0·001). The HR for detectable 25(OH)D2 was 1·80 (95 % CI 1·09, 2·97; P=0·023); for those with detectable 25(OH)D2, the HR per 25 nmol/l increment in 25(OH)D was 1·06 (95 % CI 0·87, 1·29; P interaction=0·02). HR were similar for participants who reported being in good, very good or excellent health four years after recruitment. CONCLUSIONS: Total 25(OH)D and 25(OH)D3 concentrations were inversely associated with mortality. The finding that the inverse association for 25(OH)D was restricted to those with no detectable 25(OH)D2 requires confirmation in populations with higher exposure to ergocalciferol.