Testing the causal relationships of physical activity and sedentary behaviour with mental health and substance use disorders: a Mendelian randomisation study.

Observational studies suggest that physical activity can reduce the risk of mental health and substance use disorders. However, it is unclear whether this relationship is causal or explained by confounding bias (e.g., common underlying causes or reverse causality). We investigated the bidirectional causal relationship of physical activity (PA) and sedentary behaviour (SB) with ten mental health and substance use disorders, applying two-sample Mendelian Randomisation (MR). Genetic instruments for the exposures and outcomes were derived from the largest available, non-overlapping genome-wide association studies (GWAS). Summary-level data for objectively assessed PA (accelerometer-based average activity, moderate activity, and walking) and SB and self-reported moderate-to-vigorous PA were obtained from the UK Biobank. Data for mental health/substance use disorders were obtained from the Psychiatric Genomics Consortium and the GWAS and Sequencing Consortium of Alcohol and Nicotine Use. MR estimates were combined using inverse variance weighted meta-analysis (IVW). Sensitivity analyses were conducted to assess the robustness of the results. Accelerometer-based average PA was associated with a lower risk of depression (b = -0.043, 95% CI: -0.071 to -0.016, effect size[OR] = 0.957) and cigarette smoking (b = -0.026; 95% CI: -0.035 to -0.017, effect size[ß] = -0.022). Accelerometer-based SB decreased the risk of anorexia (b = -0.341, 95% CI: -0.530 to -0.152, effect size[OR] = 0.711) and schizophrenia (b = -0.230; 95% CI: -0.285 to -0.175, effect size[OR] = 0.795). However, we found evidence of reverse causality in the relationship between SB and schizophrenia. Further, PTSD, bipolar disorder, anorexia, and ADHD were all associated with increased PA. This study provides evidence consistent with a causal protective effect of objectively assessed but not self-reported PA on reduced depression and cigarette smoking. Objectively assessed SB had a protective relationship with anorexia. Enhancing PA may be an effective intervention strategy to reduce depressive symptoms and addictive behaviours, while promoting sedentary or light physical activities may help to reduce the risk of anorexia in at-risk individuals.

Hepatectomy risk assessment with functional magnetic resonance imaging (HEPARIM).

BACKGROUND: Post hepatectomy liver failure (PHLF) remains a significant risk in patients undergoing curative liver resection for cancer, however currently available PHLF risk prediction investigations are not sufficiently accurate. The Hepatectomy risk assessment with functional magnetic resonance imaging trial (HEPARIM) aims to establish if quantitative MRI biomarkers of liver function & perfusion can be used to more accurately predict PHLF risk and FLR function, measured against indocyanine green (ICG) liver function test. METHODS: HEPARIM is an observational cohort study recruiting patients undergoing liver resection of 2 segments or more, prior to surgery patients will have both Dynamic Gadoxetate-enhanced (DGE) liver MRI and ICG testing. Day one post op ICG testing is repeated and R15 compared to the Gadoxetate Clearance (GC) of the future liver remnant (FLR-GC) as measure by preoperative DGE- MRI which is the primary outcome, and preoperative ICG R15 compared to GC of whole liver (WL-GC) as a secondary outcome. Data will be collected from medical records, biochemistry, pathology and radiology reports and used in a multi-variate analysis to the value of functional MRI and derive multivariant prediction models for future validation. DISCUSSION: If successful, this test will potentially provide an efficient means to quantitatively assess FLR function and PHLF risk enabling surgeons to push boundaries of liver surgery further while maintaining safe practice and thereby offering chance of cure to patients who would previously been deemed inoperable. MRI has the added benefit of already being part of the routine diagnostic pathway and as such would have limited additional burden on patients time or cost to health care systems. (Hepatectomy Risk Assessment With Functional Magnetic Resonance Imaging - Full Text View - ClinicalTrials.gov , n.d.) TRIAL REGISTRATION: ClinicalTrials.gov, ClinicalTrials.gov NCT04705194 - Registered 12th January 2021 - Retrospectively registered.

The Association Between Childhood Leukemia and Population Mixing: An Artifact of Focusing on Clusters?

BACKGROUND: Studies investigating the population-mixing hypothesis in childhood leukemia principally use two analytical approaches: (1) nonrandom selection of areas according to specific characteristics, followed by comparisons of their incidence of childhood leukemia with that expected based on the national average; and (2) regression analyses of region-wide data to identify characteristics associated with the incidence of childhood leukemia. These approaches have generated contradictory results. We compare these approaches using observed and simulated data. METHODS: We generated 10,000 simulated regions using the correlation structure and distributions from a United Kingdom dataset. We simulated cases using a Poisson distribution with the incidence rate set to the national average assuming the null hypothesis that only population size drives the number of cases. Selection of areas within each simulated region was based on characteristics considered responsible for elevated infection rates (population density and inward migration) and/or elevated leukemia rates. We calculated effect estimates for 10,000 simulations and compared results to corresponding observed data analyses. RESULTS: When the selection of areas for analysis is based on apparent clusters of childhood leukemia, biased assessments occur; the estimated 5-year incidence of childhood leukemia ranged between zero and eight per 10,000 children in contrast to the simulated two cases per 10,000 children, similar to the observed data. Performing analyses on region-wide data avoids these biases. CONCLUSIONS: Studies using nonrandom selection to investigate the association between childhood leukemia and population mixing are likely to have generated biased findings. Future studies can avoid such bias using a region-wide analytical strategy. See video abstract at, http://links.lww.com/EDE/B431.

Excess mortality and guideline-indicated care following non-ST-elevation myocardial infarction.

BACKGROUND: Adherence to guideline-indicated care for the treatment of non-ST-elevation myocardial infarction (NSTEMI) is associated with improved outcomes. We investigated the extent and consequences of non-adherence to guideline-indicated care across a national health system. METHODS: A cohort study ( ClinicalTrials.gov identifier: NCT02436187) was conducted using data from the Myocardial Ischaemia National Audit Project ( n = 389,057 NSTEMI, n = 247 hospitals, England and Wales, 2003-2013). Accelerated failure time models were used to quantify the impact of non-adherence on survival according to dates of guideline publication. RESULTS: Over a period of 1,079,044 person-years (median 2.2 years of follow-up), 113,586 (29.2%) NSTEMI patients died. Of those eligible to receive care, 337,881 (86.9%) did not receive one or more guideline-indicated intervention; the most frequently missed were dietary advice ( n = 254,869, 68.1%), smoking cessation advice ( n = 245,357, 87.9%), P2Y12 inhibitors ( n = 192,906, 66.3%) and coronary angiography ( n = 161,853, 43.4%). Missed interventions with the strongest impact on reduced survival were coronary angiography (time ratio: 0.18, 95% confidence interval (CI): 0.17-0.18), cardiac rehabilitation (time ratio: 0.49, 95% CI: 0.48-0.50), smoking cessation advice (time ratio: 0.53, 95% CI: 0.51-0.57) and statins (time ratio: 0.56, 95% CI: 0.55-0.58). If all eligible patients in the study had received optimal care at the time of guideline publication, then 32,765 (28.9%) deaths (95% CI: 30,531-33,509) may have been prevented. CONCLUSION: The majority of patients hospitalised with NSTEMI missed at least one guideline-indicated intervention for which they were eligible. This was significantly associated with excess mortality. Greater attention to the provision of guideline-indicated care for the management of NSTEMI will reduce premature cardiovascular deaths.

Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort.

OBJECTIVE: Data-driven approaches to dietary patterns are under-utilized; latent class analyses (LCA) are particularly rare. The present study used an LCA to identify subgroups of people with similar dietary patterns, explore changes in dietary patterns over a 10-year period and relate these dynamics to sociodemographic factors and health outcomes. DESIGN: The 1998 baseline and 2008 follow-up of the Cork and Kerry Diabetes and Heart Disease Study. Diets were assessed with a standard FFQ. LCA, under the assumption of conditional independence, was used to identify mutually exclusive subgroups with different dietary patterns, based on food group consumption. SETTING: Republic of Ireland. SUBJECTS: Men and women aged 50-69 years at baseline (n 923) and at 10-year follow-up (n 320). RESULTS: Three dietary classes emerged: Western, Healthy and Low-Energy. Significant differences in demographic, lifestyle and health outcomes were associated with class membership. Between baseline and follow-up most people remained 'stable' in their dietary class. Most of those who changed class moved to the Healthy class. Higher education was associated with transition to a healthy diet; lower education was associated with stability in an unhealthy pattern. Transition to a healthy diet was associated with higher CVD risk factors at baseline: respondents were significantly more likely to be smokers, centrally obese and to have hypertension (non-significant). CONCLUSIONS: LCA is useful for exploring dietary patterns transitions. Understanding the predictors of longitudinal stability/transitions in dietary patterns will help target public health initiatives by identifying subgroups most/least likely to change and most/least likely to sustain a change.

Time to begin adjuvant chemotherapy and survival in breast cancer patients: a retrospective observational study using latent class analysis.

The analysis of time to treatment data and the evaluation of subsequent effects on health outcomes can be complex due to the nature of the data and the relationships amongst the variables. This study proposes an alternative method of analyzing such data using latent class analysis (LCA). The association between time to begin adjuvant chemotherapy after breast cancer surgery and survival was investigated using both "traditional" regression analysis and LCA. Women with breast cancer undergoing surgery and subsequent adjuvant chemotherapy in two English regions between January 01, 1998 and December 31, 2004 were identified from a linked cancer registry-Hospital Episode Statistics dataset (n = 10,366). Patient, tumor, and treatment information were extracted. A Cox proportional hazards model was used to analyze 5-year survival using regression analysis and LCA. Using "traditional" regression analysis, women beginning chemotherapy >10 weeks after surgery had worse survival in region 1 (HR = 1.49, 95% CI 1.13-1.95 compared to <3 weeks) but not region 2. LCA split the women into three groups representing short, medium, and long waits. The median time to begin chemotherapy in the "long" wait group was 70 (region 1) and 57 (region 2) days. In this group, increased time to begin chemotherapy was associated with worse survival (region 1 HR = 1.15, 95% CI 1.11-1.18; region 2 HR = 1.08, 95% CI 1.03-1.13 per week increase). LCA identified a group of 13-15% of women for whom a longer time to begin chemotherapy had an adverse effect on survival. This methodology provides an excellent framework in which to examine complex associations between the delivery of patient care and patient outcomes.

Platelet-derived growth factor maintains stored calcium through a nonclustering Orai1 mechanism but evokes clustering if the endoplasmic reticulum is stressed by store depletion.

RATIONALE: Calcium entry through Orai1 channels drives vascular smooth muscle cell migration and neointimal hyperplasia. The channels are activated by the important growth factor platelet-derived growth factor (PDGF). Channel activation is suggested to depend on store depletion, which redistributes and clusters stromal interaction molecule 1 (STIM1), which then coclusters and activates Orai1. OBJECTIVE: To determine the relevance of STIM1 and Orai1 redistribution in PDGF responses. METHODS AND RESULTS: Vascular smooth muscle cells were cultured from human saphenous vein. STIM1 and Orai1 were tagged with green and red fluorescent proteins to track them in live cells. Under basal conditions, the proteins were mobile but mostly independent of each other. Inhibition of sarco-endoplasmic reticulum calcium ATPase led to store depletion and dramatic redistribution of STIM1 and Orai1 into coclusters. PDGF did not evoke redistribution, even though it caused calcium release and Orai1-mediated calcium entry in the same time period. After chemical blockade of Orai1-mediated calcium entry, however, PDGF caused redistribution. Similarly, mutagenic disruption of calcium flux through Orai1 caused PDGF to evoke redistribution, showing that calcium flux through the wild-type channels had been filling the stores. Acidification of the extracellular medium to pH 6.4 caused inhibition of Orai1-mediated calcium entry and conferred capability for PDGF to evoke complete redistribution and coclustering. CONCLUSIONS: The data suggest that PDGF has a nonclustering mechanism by which to activate Orai1 channels and maintain calcium stores replete. Redistribution and clustering become important, however, when the endoplasmic reticulum stress signal of store depletion arises, for example when acidosis inhibits Orai1 channels.

Unravelling the effects of age, period and cohort on metabolic syndrome components in a Taiwanese population using partial least squares regression.

BACKGROUND: We investigate whether the changing environment caused by rapid economic growth yielded differential effects for successive Taiwanese generations on 8 components of metabolic syndrome (MetS): body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), triglycerides (TG), high-density lipoprotein (HDL), Low-density lipoproteins (LDL) and uric acid (UA). METHODS: To assess the impact of age, birth year and year of examination on MetS components, we used partial least squares regression to analyze data collected by Mei-Jaw clinics in Taiwan in years 1996 and 2006. Confounders, such as the number of years in formal education, alcohol intake, smoking history status, and betel-nut chewing were adjusted for. RESULTS: As the age of individuals increased, the values of components generally increased except for UA. Men born after 1970 had lower FPG, lower BMI, lower DBP, lower TG, Lower LDL and greater HDL; women born after 1970 had lower BMI, lower DBP, lower TG, Lower LDL and greater HDL and UA. There is a similar pattern between the trend in levels of metabolic syndrome components against birth year of birth and economic growth in Taiwan. CONCLUSIONS: We found cohort effects in some MetS components, suggesting associations between the changing environment and health outcomes in later life. This ecological association is worthy of further investigation.

Using routinely collected health data to investigate the association between ethnicity and breast cancer incidence and survival: what is the impact of missing data and multiple ethnicities?

OBJECTIVES: The aims of this study were to: (1) investigate the relationship between ethnicity and breast cancer incidence and survival using cancer registry and Hospital Episode Statistics (HES) data; and (2) assess the impact of missing data and the recording of multiple ethnicities for some patients. DESIGN: A total of 48,234 breast cancer patients diagnosed between 1997 and 2003 in two English regions were identified. Ethnicity was missing in 16% of cases. Multiple imputation (10 iterations) of missing ethnicity was undertaken using a range of predictor variables. Multiple ethnicities for a single patient were recorded in 4% of cases. Three methods of assigning ethnicity were used: 'most popular' code, 'last recorded' code, and proportions calculated using all recorded episodes for each patient. Age-standardised incidence rate ratios (IRR) and 5-year survival were calculated before and after imputation for the three methods of assigning ethnicity. RESULTS: Breast cancer incidence was lower in the South Asian group (IRR=0.59, 95% confidence interval [CI] 0.51-0.69 compared to the White group). In unadjusted analyses, the South Asian group had consistently higher survival compared with the White group (hazard ratio [HR]=0.81, 95% CI 0.68-0.95). After adjustment for age and stage, there were no survival differences amongst the White, South Asian and Black groups. Survival was higher in the 'Other' ethnic group when using the 'last recorded' method to assign ethnicity (HR=0.62, 95% CI 0.45-0.85 compared with the White group). The results were similar before and after imputation, using all three methods of assigning ethnicity. CONCLUSIONS: Breast cancer incidence was lower in the South Asian group than in the White group. After adjusting for casemix there were no consistent survival differences amongst the ethnic groups. Although the impact of missing data and multiple ethnicities was minimal in this study, researchers should always consider these issues, as the results may not be generalisable to other populations and datasets.

Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix.

BACKGROUND: Using routinely collected patient data we explore the utility of multilevel latent class (MLLC) models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs). METHODS: Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640). Patient age, sex, stage-at-diagnosis (Dukes), and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. RESULTS: Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years), and one with better prognosis (39.3% died within 3 years). In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. CONCLUSIONS: A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments) and factors associated with the processes of healthcare delivery (e.g. delays). Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.

Epidemiology of functional dyspepsia and subgroups in the Italian general population: an endoscopic study.

BACKGROUND & AIMS: Population-based endoscopic studies are needed to assess the epidemiology of functional dyspepsia (FD) and the newly suggested subgroups of meal-related symptoms and epigastric pain. We evaluated the prevalence of, and risk factors for, FD in the Italian general population. METHODS: A total of 1533 inhabitants of 2 villages were invited to undergo symptom evaluation using a validated questionnaire, esophagogastroduodenoscopy, and (13)C-urea breath test; 1033 subjects (67.4%) took part. RESULTS: Of the 1033 subjects, 156 (15.1%; 95% confidence interval [CI], 12.9-17.3) had dyspepsia, and of these 114 (11%; 95% CI, 9.2-12.9) had FD. Of the 114 subjects with FD, 77 (67.5%) had meal-related symptoms (postprandial fullness and/or early satiation) and 55 (48.2%) had epigastric pain. Only 18 subjects (15.8%) had both meal-related symptoms and epigastric pain; this was fewer than expected by chance alone (P < .001). Unemployment (odds ratio [OR], 5.80; 95% CI, 1.56-21.60), divorce (OR, 2.76; 95% CI, 1.10-6.91), smoking (OR, 1.74; 95% CI, 1.11-2.70), and irritable bowel syndrome (OR, 3.38; 95% CI, 1.85-6.19) were significantly associated with FD. Unemployment, divorce, and irritable bowel syndrome were associated with both meal-related symptoms and epigastric pain, while smoking was associated only with meal-related symptoms. CONCLUSIONS: FD is present in 11% of the Italian general population. Unemployment and divorce seem to increase the risk of FD, and smoking seems to be associated with meal-related symptoms. Two distinct subgroups of FD, as suggested by Rome III, seem to exist in the general population.

Latent class modelling of the association between socioeconomic background and breast cancer survival status at 5 years incorporating stage of disease.

BACKGROUND: Stage of disease and socioeconomic background (SEB) are often used to 'explain' differences in breast cancer outcomes. There are challenges for all types of analysis (eg, survival analysis, logistic regression), including missing data, measurement error and the 'reversal paradox'. This study investigates the association between SEB and survival status within 5 years of breast cancer diagnosis using (1) logistic regression with and without adjustment for stage and (2) logistic latent class analysis (LCA) excluding stage as a covariate but with and without stage as a latent class predictor. METHODS: Women diagnosed with invasive breast cancer between 1998 and 2000 in one UK region were identified (n=11 781). Multilevel logistic regression was performed using standard regression and LCA. Models included SEB (2001 Townsend Index), age and stage ('missing' stage (8.0%) modelled as a separate category). The association of SEB with stage was also assessed. RESULTS: Using standard regression, there was a substantial association between SEB and death within 5 years, with and without adjustment for stage. Using LCA, patients were assigned to a large good prognosis group and a small poor prognosis group. The association between SEB and survival was substantive in both classes for the model without stage, but only in the larger class for the model with stage. Increasing deprivation was associated with more advanced stage at diagnosis. CONCLUSIONS: LCA categorises patients into prognostic groups according to patient and tumour characteristics, providing an alternative strategy to the usual statistical adjustment for stage.

Investigating spatio-temporal similarities in the epidemiology of childhood leukaemia and diabetes.

Childhood acute lymphoblastic leukaemia (ALL) and Type 1 diabetes (T1D) share some common epidemiological features, including rising incidence rates and links with an infectious aetiology. Previous work has shown a significant positive correlation in incidence between the two conditions both at the international and small-area level. The aim was to extend the methodology by including shared spatial and temporal trends using a more extensive dataset among individuals diagnosed with ALL and T1D in Yorkshire (UK) aged 0-14 years from 1978-2003. Cases with ALL and T1D were ascertained from 2 high quality population-based disease registers covering the Yorkshire region of the UK and linked to an electoral ward from the 1991 UK census. A Bayesian model was fitted where similarities and differences in risk profiles of the two diseases were captured by the shared and disease-specific components using a shared-component model, with space-time interactions. The extended model revealed a positive correlation of at least 0.70 between diseases across all time periods, and an increasing risk across time for both diseases, which was more evident for T1D. Furthermore, both diseases exhibited lower rates in the more urban county of West Yorkshire and higher rates in the more rural northern and eastern part of the region. A differential effect of T1D over ALL was found in the south-eastern part of the region, which had a more pronounced association with population mixing than with population density or deprivation. Our approach has demonstrated the utility in modelling temporally and spatially varying disease incidence patterns across small geographical areas. The findings suggest searching for environmental factors that exhibit similar geographical-temporal variation in prevalence may help in the development and testing of plausible aetiological hypotheses. Furthermore, identifying environmental exposures specific to the south-eastern part of the region, especially locally varying risk factors which may differentially affect the development of T1D and ALL, may also be fruitful.

Joint disease mapping using six cancers in the Yorkshire region of England.

OBJECTIVES: The aims of this study were to model jointly the incidence rates of six smoking related cancers in the Yorkshire region of England, to explore the patterns of spatial correlation amongst them, and to estimate the relative weight of smoking and other shared risk factors for the relevant disease sites, both before and after adjustment for socioeconomic background (SEB). METHODS: Data on the incidence of oesophagus, stomach, pancreas, lung, kidney, and bladder cancers between 1983 and 2003 were extracted from the Northern & Yorkshire Cancer Registry database for the 532 electoral wards in the Yorkshire region. Using postcode of residence, each case was assigned an area-based measure of SEB using the Townsend index. Standardised incidence ratios (SIRs) were calculated for each cancer site and their correlations investigated. The joint analysis of the spatial variation in incidence used a Bayesian shared-component model. Three components were included to represent differences in smoking (for all six sites), bodyweight/obesity (for oesophagus, pancreas and kidney cancers) and diet/alcohol consumption (for oesophagus and stomach cancers). RESULTS: The incidence of cancers of the oesophagus, pancreas, kidney, and bladder was relatively evenly distributed across the region. The incidence of stomach and lung cancers was more clustered around the urban areas in the south of the region, and these two cancers were significantly associated with higher levels of area deprivation. The incidence of lung cancer was most impacted by adjustment for SEB, with the rural/urban split becoming less apparent. The component representing smoking had a larger effect on cancer incidence in the eastern part of the region. The effects of the other two components were small and disappeared after adjustment for SEB. CONCLUSION: This study demonstrates the feasibility of joint disease modelling using data from six cancer sites. Incidence estimates are more precise than those obtained without smoothing. This methodology may be an important tool to help authorities evaluate healthcare system performance and the impact of policies.

What do epidemiologists mean by 'population mixing'?

There is growing evidence that some chronic diseases are caused, or promoted, by infectious disease. 'Population mixing' has been used as a proxy for the range and dose of infectious agents circulating in a community. Given the speculation over the role of population mixing in many chronic diseases, we review the various methods used for measuring population mixing, and provide a classification of these. We recommend that authors fulfill two criteria in publications: measures are demonstrably associated with the putative risk factors for which population-mixing is acting as a proxy and fundamental characteristics of the chosen measures are clearly defined.

Do the UK government's new Quality and Outcomes Framework (QOF) scores adequately measure primary care performance? A cross-sectional survey of routine healthcare data.

BACKGROUND: General practitioners' remuneration is now linked directly to the scores attained in the Quality and Outcomes Framework (QOF). The success of this approach depends in part on designing a robust and clinically meaningful set of indicators. The aim of this study was to assess the extent to which measures of health observed in practice populations are correlated with their QOF scores, after accounting for the established associations between health outcomes and socio-demographics. METHODS: QOF data for the period April 2004 to March 2005 were obtained for all general practices in two English Primary Care Trusts. These data were linked to data for emergency hospital admissions (for asthma, cancer, chronic obstructive pulmonary disease, coronary hear disease, diabetes, stroke and all other conditions) and all cause mortality for the period September 2004 to August 2005. Multilevel logistic regression models explored the association between health outcomes (hospital admission and death) and practice QOF scores (clinical, additional services and organisational domains), age, sex and socio-economic deprivation. RESULTS: Higher clinical domain scores were generally associated with lower admission rates and this was significant for cancer and other conditions in PCT 2. Higher scores in the additional services domain were associated with higher admission rates, significantly so for asthma, CHD, stroke and other conditions in PCT 1 and cancer in PCT 2. Little association was observed between the organisational domain scores and admissions. The relationship between the QOF variables and mortality was less clear. Being female was associated with fewer admissions for cancer and CHD and lower mortality rates. Increasing age was mainly associated with an increased number of events. Increasing deprivation was associated with higher admission rates for all conditions and with higher mortality rates. CONCLUSION: The associations between QOF scores and emergency admissions and mortality were small and inconsistent, whilst the impact of socio-economic deprivation on the outcomes was much stronger. These results have implications for the use of target-based remuneration of general practitioners and emphasise the need to tackle inequalities and improve the health of disadvantaged groups and the population as a whole.

Functional data analysis applied to a randomized controlled clinical trial in hemodialysis patients describes the variability of patient responses in the control of renal anemia.

The achievement of desirable hemoglobin levels in renal anemia that is treated with epoetins is often incomplete and subject to much variation of outcome values and applied dosage. The further development of clinical decision support for renal anemia requires the characterization of patient responses and an analysis of the dynamics of the dosage and response variables. In this methodologic article, the extended data of a randomized, controlled clinical trial comparing two epoetins were examined by the techniques of functional data analysis to establish how precisely the patterns of treatment response might be described and analyzed. The description of the trajectory of hemoglobin values in each patient as a mathematical function allowed the characterization of individual responses, with a wide variety of patterns being revealed. An analysis of the degree of system control in the management of the anemia was then possible through phase plotting. The analysis also allowed an expression of the dynamic characteristics of the entire experimental system, analyzed in summary group waveforms with standard statistical properties. In addition, a quantification of the notional instability of patient responses enabled the determination of a subset of patients for whom control might be improved in a modified management system. It is concluded that functional data analysis does provide the basis for further characterization and experimental study of the control of renal anemia.

A randomized-controlled trial of low-dose doxycycline for periodontitis in smokers.

BACKGROUND/AIM: Tobacco use reduces the effect of non-surgical periodontal therapy. Host-modulation with low-dose doxycycline (LDD) might favour repair and promote an improved treatment response. The aim of this study was to investigate the effect of LDD in smokers on non-surgical periodontal therapy. MATERIAL AND METHODS: This was a parallel arm, randomized, identical placebo-controlled trial with masking of examiner, care-giver, participant and statistician and 6 months of follow-up. Patients received non-surgical therapy and 3 months of test or control drug. Statistical analysis used both conventional methods and multilevel modelling. RESULTS: Eighteen control and 16 test patients completed the study. The velocity of change was statistically greater for the test group for clinical attachment level -0.19 mm/month (95% CI=-0.34, 0.04; p=0.012) and probing depth 0.30 mm/month (95% CI=-0.42, -0.17; p<0.001). However, no differences were observed for absolute change in clinical or biochemical markers at 6 months. CONCLUSIONS: This study does not provide evidence of a benefit of using LDD as an adjunct to non-surgical periodontal therapy in smokers.

Associations between tooth loss and mortality patterns in the Glasgow Alumni Cohort.

OBJECTIVE: To use data from the Glasgow Alumni Cohort to investigate whether oral health in young adulthood is independently associated with later life cardiovascular disease (CVD) and cancer mortality. METHODS AND RESULTS: Of the original cohort (n = 15 322), 12 631 subjects were traced through the National Health Service Central Register. Of these, 9569 men and 2654 women were 30 years or younger at baseline. During up to 57 years of follow-up, 1432 deaths occurred among subjects with complete data, including 509 deaths from CVD and 549 from cancer. After adjusting for potential confounders, no substantial association was found between the number of missing teeth (as a continuous variable) and all-cause mortality (hazard ratio (HR) for each extra missing tooth = 1.01; 95% confidence interval (CI) 1.00 to 1.02), CVD mortality (HR = 1.01; 95% CI 0.99 to 1.03) or cancer mortality (HR = 1.00; 95% CI 0.98 to 1.02). When the number of missing teeth was treated as a categorical variable, there was evidence that students with nine or more missing teeth at baseline had an increased risk of CVD (HR = 1.35; 95% CI 1.03 to 1.77) compared with those with fewer than five missing teeth. When the number of missing teeth was transformed using fractional polynomials, there seemed to be a non-linear relation between missing teeth and CVD mortality. CONCLUSIONS: Although some evidence was found to support the relation between tooth loss and CVD mortality, causal mechanisms underlying this association remain uncertain.