The finding of reduced estimated glomerular filtration rate is associated with increased mortality in a large UK population

BACKGROUND: CKD as defined by KDIGO/KDOQI has been shown to affect ~ 8.5% of the UK population. The prevalence of CKD in the UK is similar to that in the USA, yet incident dialysis rates are dramatically different. This retrospective cohort study investigates the association between reduced kidney function and mortality in a large UK population. METHODS: All serum creatinine results covering Northern Ireland's 1.7 million population were collected between 1 January 2001 and 31 December 2002. Estimated glomerular filtration rates (eGFR) were calculated for all serum creatinine measurements using four-variable MDRD equation (IDMS aligned). Patients were followed up for both all-cause and cardiovascular mortality data until the end of December 2006. Patients on renal replacement therapy were excluded. Subgroup analysis in the 75 345 subjects enrolled within a parallel primary care study permitted additional survival analysis with adjustment for traditional cardiovascular risk factors. RESULTS: A total of 1 967 827 serum creatinine results from 533 798 patients were collected. During the period of follow-up, 59 980 deaths occurred. In multivariate survival analysis, using eGFR as a time-varying covariate, a graded association between CKD (defined by eGFR) and all-cause mortality was identified. Compared with participants with an eGFR of > 60 mL/min/1.73 m(2), the adjusted hazard ratios (and 95% confidence intervals) for participants with an eGFR of 45-59 mL/min/1.73 m(2) was 1.02 (0.99-1.04), an eGFR of 30-44 mL/min/1.73 m(2) was 1.44 (1.40-1.47), an eGFR of 15-29 mL/min/1.73 m(2) was 2.12 (2.05-2.20) and an eGFR of

Quantifying Alcohol-Related Mortality: Should Alcohol-Related Contributory Causes of Death be Included?

Aims: The aim of the study was to assess whether alcohol-related mortality data in the UK should be extended to include contributory as well as underlying cause of death. Methods: A total of 101,320 deaths registered in Northern Ireland between 2001 and 2007 were analysed to determine the quantity and characteristics of those with an underlying or contributory alcohol-related cause of death. Results: Alcohol was found to be an underlying cause of death in 1690 cases (1.7% of deaths) and a contributory cause in a further 1105 cases. Analyses show that the addition of alcohol-related contributory causes of deaths would increase the male-female ratio, result in steeper socio-economic gradients and amplify the apparent rate of increase of alcohol-related deaths. The significant contribution of alcohol to external causes of death, such as accidents and suicide, is also more evident. Conclusions: Using only underlying cause of death undoubtedly underestimates the burden of alcohol-related harm and may provide an inaccurate picture of those most likely to suffer from an alcohol-related death, especially among younger men.

Explaining young mortality

Stochastic modeling of mortality rates focuses on fitting linear models to logarithmically adjusted mortality data from the middle or late ages. Whilst this modeling enables insurers to project mortality rates and hence price mortality products it does not provide good fit for younger aged mortality. Mortality rates below the early 20's are important to model as they give an insight into estimates of the cohort effect for more recent years of birth. It is also important given the cumulative nature of life expectancy to be able to forecast mortality improvements at all ages. When we attempt to fit existing models to a wider age range, 5-89, rather than 20-89 or 50-89, their weaknesses are revealed as the results are not satisfactory. The linear innovations in existing models are not flexible enough to capture the non-linear profile of mortality rates that we see at the lower ages. In this paper we modify an existing 4 factor model of mortality to enable better fitting to a wider age range, and using data from seven developed countries our empirical results show that the proposed model has a better fit to the actual data, is robust, and has good forecasting ability.

A Dynamic Factor Approach to Mortality Modelling

Longevity risk has become one of the major risks facing the insurance and pensions markets globally. The trade in longevity risk is underpinned by accurate forecasting of mortality rates. Using techniques from macroeconomic forecasting, we propose a dynamic factor model of mortality that fits and forecasts mortality rates parsimoniously.We compare the forecasting quality of this model and of existing models and find that the dynamic factor model generally provides superior forecasts when applied to international mortality data. We also show that existing multifactorial models have superior fit but their forecasting performance worsens as more factors are added. The dynamic factor approach used here can potentially be further improved upon by applying an appropriate stopping rule for the number of static and dynamic factors. 

Structural Breaks in Mortality Models and their Consequences

In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

Identifying Structural Breaks in Stochastic Mortality Models

In recent years, the issue of life expectancy has become of utmost importance to pension providers, insurance companies, and government bodies in the developed world. Significant and consistent improvements in mortality rates and hence life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data to anticipate future life expectancy and hence quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age, and cohort and forecast these trends into the future by using standard statistical methods. These approaches rely on the assumption that structural breaks in the trend do not exist or do not have a significant impact on the mortality forecasts. Recent literature has started to question this assumption. In this paper, we carry out a comprehensive investigation of the presence or of structural breaks in a selection of leading mortality models. We find that structural breaks are present in the majority of cases. In particular, we find that allowing for structural break, where present, improves the forecast result significantly.

Excess mortality in Type 1 diabetes diagnosed in childhood and adolescence: a systematic review of population-based cohorts

Aims: Systematic review of mortality in childhood-/adolescent-diagnosed Type 1 diabetes and examination of factors explaining the mortality variation between studies. 
Methods: Relevant studies were identified from systematic searches of MEDLINE and EMBASE. Observed and expected numbers of deaths were extracted, and standardised mortality ratios (SMRs) and 95 % confidence intervals (CIs) were calculated. Negative binomial regression was used to investigate association between mortality and study/country characteristics.
Results: Thirteen relevant publications with mortality data were identified describing 23 independent studies. SMRs varied markedly ranging from 0 to 854 (chi-squared = 70.68,df = 21, p<0.0001). Significant associations were observed between SMR and mid-year of follow-up [incidence rate ratio (IRR) 0.95, 95 % CI 0.91–0.99 equivalent to a 5 % decrease per year], between SMR and infant mortality rate (IRR 1.07, 95 % CI 1.02–1.12, a 7 % increase for each death per 1,000 live births) and, after omitting an outlier, between SMR and health expenditure as a percentage of gross domestic product (GDP) (IRR 0.79, 95 % CI 0.68–0.93, a 21 % decrease for each one percent increase in GDP). No relationship was detected between SMR and a country’s childhood diabetes incidence rate or GDP.
Conclusions: Excess mortality in childhood-/adolescent diagnosed Type 1 diabetes is apparent across countries worldwide. Excesses were less marked in more recent studies and in countries with lower infant mortality and higher health expenditure.

The association between glucose lowering drug use and mortality among breast cancer patients with type 2 diabetes.

This study assessed the association between glucose-lowering drug (GLD) use, including metformin, sulphonylurea derivatives and insulin, after breast cancer diagnosis and breast cancer-specific and all-cause mortality. 1763 breast cancer patients, diagnosed between 1998 and 2010, with type 2 diabetes were included. Cancer information was retrieved from English cancer registries, prescription data from the UK Clinical Practice Research Datalink and mortality data from the Office of National Statistics (up to January 2012). Time-varying Cox regression models were used to calculate HRs and 95 % CIs for the association between GLD use and breast cancer-specific and all-cause mortality. In 1057 patients with diabetes before breast cancer, there was some evidence that breast cancer-specific mortality decreased with each year of metformin use (adjusted HR 0.88; 95 % CI 0.75–1.04), with a strong association seen with over 2 years of use (adjusted HR 0.47; 95 % CI 0.26–0.82). Sulphonylurea derivative use for less than 2 years was associated with increased breast cancer-specific mortality (adjusted HR 1.70; 95 % CI 1.18–2.46), but longer use was not (adjusted HR 0.94; 95 % CI 0.54–1.66). In 706 patients who developed diabetes after breast cancer, similar patterns were seen for metformin, but sulphonylurea derivative use was strongly associated with cancer-specific mortality (adjusted HR 3.64; 95 % CI 2.16–6.16), with similar estimates for short- and long-term users. This study provides some support for an inverse association between, mainly long-term, metformin use and (breast cancer-specific) mortality. In addition, sulphonylurea derivative use was associated with increased breast cancer-specific mortality, but this should be interpreted cautiously, as it could reflect selective prescribing in advanced cancer patients.

Post-diagnostic oral bisphosphonate use and colorectal cancer mortality: a population-based cohort study within the UK Clinical Practice Research Datalink

Background:We conducted the first study to investigate post-diagnostic oral bisphosphonates use and colorectal cancer-specific mortality.

Methods:Colorectal cancer patients were identified from the National Cancer Data Repository (1998–2007) and linked to the UK Clinical Practice Research Datalink, providing prescription records, and Office of National Statistics mortality data. Time-dependent Cox regression models investigated colorectal cancer-specific mortality in post-diagnostic bisphosphonate users.

Results:Overall, in 4791 colorectal cancer patients, there was no evidence of an association between bisphosphonate use and colorectal cancer-specific mortality (adjusted hazard ratio=1.11; 95% confidence interval 0.80, 1.54) or with drug frequency or type.

Conclusions:In this novel population-based cohort study, post-diagnostic bisphosphonate use was not associated with longer rates of colorectal cancer survival.

Clopidogrel use and cancer-specific mortality: a population-based cohort study of colorectal, breast and prostate cancer patients

PURPOSE: Concerns were raised about the safety of antiplatelet thienopyridine derivatives after a randomized control trial reported increased risks of cancer and cancer deaths in prasugrel users. We investigate whether clopidogrel, a widely used thienopyridine derivative, was associated with increased risk of cancer-specific or all-cause mortality in cancer patients.

METHODS: Colorectal, breast and prostate cancer patients, newly diagnosed from 1998 to 2009, were identified from the National Cancer Data Repository. Cohorts were linked to the UK Clinical Practice Research Datalink, providing prescription records, and to the Office of National Statistics mortality data (up to 2012). Unadjusted and adjusted hazard ratios (HRs) for cancer-specific and all-cause mortality in post-diagnostic clopidogrel users were calculated using time-dependent Cox regression models.

RESULTS: The analysis included 10 359 colorectal, 17 889 breast and 13 155 prostate cancer patients. There was no evidence of an increase in cancer-specific mortality in clopidogrel users with colorectal (HR = 0.98 95% confidence interval (CI) 0.77, 1.24) or prostate cancer (HR = 1.03 95%CI 0.82, 1.28). There was limited evidence of an increase in breast cancer patients (HR = 1.22 95%CI 0.90, 1.65); however, this was attenuated when removing prescriptions in the year prior to death.

CONCLUSIONS: This novel study of large population-based cohorts of colorectal, breast and prostate cancer patients found no evidence of an increased risk of cancer-specific mortality among colorectal, breast and prostate cancer patients using clopidogrel.

Physiological stress responses in the edible crab, Cancer pagurus, to the fishery practice of de-clawing

We examined physiological stress responses in the edible crab, Cancer pagurus, subjected to the commercial fishery practice of manual de-clawing. We measured haemolymph glucose and lactate, plus muscular glycogen and glycogen mobilisation, in three experiments where the crabs had one claw removed. In the first, crabs showed physiological stress responses when 'de-clawed' as compared to 'handled only over the short term of 1-10 min. In the second, de-clawing and the presence of a conspecific both increased the physiological stress responses over the longer term of 24 h. In the third, de-clawing was shown to be more stressful than 'induced autotomy' of claws. Further, the former practice caused larger wounds to the body and significantly higher mortality than the latter. Since the fishery practice is to remove both claws, the stress response observed and mortality data reported are conservative.

Geographical Influences on Long-Run Development

We show that geographical factors influence long-run per capita income directly, as well as indirectly, through the quality of institutions. The direct influence of geography on per capita incomes is robust to the inclusion of a sub-Saharan Africa dummy and other tests. We obtain our results by replacing the usual instrument (settlers’ mortality (SM)) by stronger instruments for institutional quality (latitude, the share of the country in the temperate climatic zone). We also provide evidence that SM suffers from endogeneity with respect to institutional quality for early colonies, because of its dependence on nineteenth-century mortality data.

Drugs affecting the renin-angiotensin system and survival from cancer: a population based study of breast, colorectal and prostate cancer patient cohorts

Background: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are commonly prescribed to the growing number of cancer patients (more than two million in the UK alone) often to treat hypertension. However, increased fatal cancer in ARB users in a randomized trial and increased breast cancer recurrence rates in ACEI users in a recent observational study have raised concerns about their safety in cancer patients. We investigated whether ACEI or ARB use after breast, colorectal or prostate cancer diagnosis was associated with increased risk of cancer-specific mortality.

Methods: Population-based cohorts of 9,814 breast, 4,762 colorectal and 6,339 prostate cancer patients newly diagnosed from 1998 to 2006 were identified in the UK Clinical Practice Research Datalink and confirmed by cancer registry linkage. Cancer-specific and all-cause mortality were identified from Office of National Statistics mortality data in 2011 (allowing up to 13 years of follow-up). A nested case–control analysis was conducted to compare ACEI/ARB use (from general practitioner prescription records) in cancer patients dying from cancer with up to five controls (not dying from cancer). Conditional logistic regression estimated the risk of cancer-specific, and all-cause, death in ACEI/ARB users compared with non-users.

Results: The main analysis included 1,435 breast, 1,511 colorectal and 1,184 prostate cancer-specific deaths (and 7,106 breast, 7,291 colorectal and 5,849 prostate cancer controls). There was no increase in cancer-specific mortality in patients using ARBs after diagnosis of breast (adjusted odds ratio (OR) = 1.06 95% confidence interval (CI) 0.84, 1.35), colorectal (adjusted OR = 0.82 95% CI 0.64, 1.07) or prostate cancer (adjusted OR = 0.79 95% CI 0.61, 1.03). There was also no evidence of increases in cancer-specific mortality with ACEI use for breast (adjusted OR = 1.06 95% CI 0.89, 1.27), colorectal (adjusted OR = 0.78 95% CI 0.66, 0.92) or prostate cancer (adjusted OR = 0.78 95% CI 0.66, 0.92).

Conclusions: Overall, we found no evidence of increased risks of cancer-specific mortality in breast, colorectal or prostate cancer patients who used ACEI or ARBs after diagnosis. These results provide some reassurance that these medications are safe in patients diagnosed with these cancers.

Keywords: Colorectal cancer; Breast cancer; Prostate cancer; Mortality; Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.

Post-diagnostic prescriptions for low-dose aspirin and breast cancer-specific survival: a nested case-control study in a breast cancer cohort from the UK Clinical Practice Research Datalink

INTRODUCTION: Recent observational studies indicate that post-diagnostic use of aspirin in breast cancer patients may protect against cancer progression perhaps by inhibiting cyclooxygenase-2 dependent mechanisms. Evidence also supports a crucial role for interactions between tumour cells and circulating platelets in cancer growth and dissemination, therefore, use of low-dose aspirin may reduce the risk of death from cancer in breast cancer patients.

METHODS: A cohort of newly diagnosed breast cancer patients (1998 to 2006) were identified in the UK Clinical Practice Research Datalink (and confirmed by cancer registry linkage). Cancer-specific deaths were identified up to 2011 from Office for National Statistics mortality data. A nested case-control analysis was conducted using conditional logistic regression to compare post-diagnostic aspirin exposure using General Practice prescription data in 1,435 cases (breast cancer deaths) with 5,697 controls (matched by age and year of diagnosis).

RESULTS: After breast cancer diagnosis, 18.3% of cancer-specific deaths and 18.5% of matched controls received at least one prescription for low-dose aspirin, corresponding to an odds ratio (OR) of 0.98 (95% CI 0.83, 1.15). Adjustment for potential confounders (including stage and grade) had little impact on this estimate. No dose response relationship was observed when the number of tablets was investigated and no associations were seen when analyses were stratified by receipt of prescriptions for aspirin in the pre-diagnostic period, by stage at diagnosis or by receipt of prescriptions for hormone therapy.

CONCLUSIONS: Overall, in this large population-based cohort of breast cancer patients, there was little evidence of an association between receipt of post-diagnostic prescriptions for low-dose aspirin and breast cancer-specific death. However, information was not available on medication compliance or over-the-counter use of aspirin, which may have contributed to the null findings.