245 research outputs found

    A Model for the Analysis of Caries Occurrence in Primary Molar Tooth Surfaces

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    Recently methods of caries quantification in the primary dentition have moved away from summary ‘whole mouth’ measures at the individual level to methods based on generalised linear modelling (GLM) approaches or survival analysis approaches. However, GLM approaches based on logistic transformation fail to take into account the time-dependent process of tooth/surface survival to caries. There may also be practical difficulties associated with casting parametric survival-based approaches in a complex multilevel hierarchy and the selection of an optimal survival distribution, while non-parametric survival methods are not generally suitable for the assessment of supplementary information recorded on study participants. In the current investigation, a hybrid semi-parametric approach comprising elements of survival-based and GLM methodologies suitable for modelling of caries occurrence within fixed time periods is assessed, using an illustrative multilevel data set of caries occurrence in primary molars from a cohort study, with clustering of data assumed to occur at surface and tooth levels. Inferences of parameter significance were found to be consistent with previous parametric survival-based analyses of the same data set, with gender, socio-economic status, fluoridation status, tooth location, surface type and fluoridation status-surface type interaction significantly associated with caries occurrence. The appropriateness of the hierarchical structure facilitated by the hybrid approach was also confirmed. Hence the hybrid approach is proposed as a more appropriate alternative to primary caries modelling than non-parametric survival methods or other GLM-based models, and as a practical alternative to more rigorous survival-based methods unlikely to be fully accessible to most researchers

    Challenges in modelling the random structure correctly in growth mixture models and the impact this has on model mixtures

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    Lifecourse trajectories of clinical or anthropological attributes are useful for identifying how our early-life experiences influence later-life morbidity and mortality. Researchers often use growth mixture models (GMMs) to estimate such phenomena. It is common to place constrains on the random part of the GMM to improve parsimony or to aid convergence, but this can lead to an autoregressive structure that distorts the nature of the mixtures and subsequent model interpretation. This is especially true if changes in the outcome within individuals are gradual compared with the magnitude of differences between individuals. This is not widely appreciated, nor is its impact well understood. Using repeat measures of body mass index (BMI) for 1528 US adolescents, we estimated GMMs that required variance-covariance constraints to attain convergence. We contrasted constrained models with and without an autocorrelation structure to assess the impact this had on the ideal number of latent classes, their size and composition. We also contrasted model options using simulations. When the GMM variance-covariance structure was constrained, a within-class autocorrelation structure emerged. When not modelled explicitly, this led to poorer model fit and models that differed substantially in the ideal number of latent classes, as well as class size and composition. Failure to carefully consider the random structure of data within a GMM framework may lead to erroneous model inferences, especially for outcomes with greater within-person than between-person homogeneity, such as BMI. It is crucial to reflect on the underlying data generation processes when building such models

    The impact of the Calman–Hine report on the processes and outcomes of care for Yorkshire's colorectal cancer patients

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    The 1995 Calman–Hine plan outlined radical reform of the UK's cancer services with the aim of improving outcomes and reducing inequalities in NHS cancer care. Its main recommendation was to concentrate care into the hands of site-specialist, multi-disciplinary teams. This study aimed to determine if the implementation of Calman–Hine cancer teams was associated with improved processes and outcomes of care for colorectal cancer patients. The design included longitudinal survey of 13 colorectal cancer teams in Yorkshire and retrospective study of population-based data collected by the Northern and Yorkshire Cancer Registry and Information Service. The population was all colorectal cancer patients diagnosed and treated in Yorkshire between 1995 and 2000. The main outcome measures were: variations in the use of anterior resection and preoperative radiotherapy in rectal cancer, chemotherapy in Dukes stage C and D patients, and five-year survival. Using multilevel models, these outcomes were assessed in relation to measures of the extent of Calman–Hine implementation throughout the study period, namely: (i) each team's degree of adherence to the Manual of Cancer Service Standards (which outlines the specification of the ‘ideal’ colorectal cancer team) and (ii) the extent of site specialisation of each team's surgeons. Variation was observed in the extent to which the colorectal cancer teams in Yorkshire had conformed to the Calman–Hine recommendations. An increase in surgical site specialisation was associated with increased use of preoperative radiotherapy (OR=1.43, 95% CI=1.04–1.98, P<0.04) and anterior resection (OR=1.43, 95% CI=1.16–1.76, P<0.01) in rectal cancer patients. Increases in adherence to the Manual of Cancer Service Standards was associated with improved five-year survival after adjustment for the casemix factors of age, stage of disease, socioeconomic status and year of diagnosis, especially for colon cancer (HR=0.97, 95% CI=0.94–0.99 P<0.01). There was a similar trend of improved survival in relation to increased surgical site specialisation for rectal cancer, although the effect was not statistically significant (HR=0.93, 95% CI=0.84–1.03, P=0.15). In conclusion, the extent of implementation of the Calman–Hine report has been variable and its recommendations are associated with improvements in processes and outcomes of care for colorectal cancer patients

    Cardiovascular disease in a cohort exposed to the 1940-45 Channel Islands occupation

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    BACKGROUND To clarify the nature of the relationship between food deprivation/undernutrition during pre- and postnatal development and cardiovascular disease (CVD) in later life, this study examined the relationship between birth weight (as a marker of prenatal nutrition) and the incidence of hospital admissions for CVD from 1997–2005 amongst 873 Guernsey islanders (born in 1923–1937), 225 of whom had been exposed to food deprivation as children, adolescents or young adults (i.e. postnatal undernutrition) during the 1940–45 German occupation of the Channel Islands, and 648 of whom had left or been evacuated from the islands before the occupation began. METHODS Three sets of Cox regression models were used to investigate (A) the relationship between birth weight and CVD, (B) the relationship between postnatal exposure to the occupation and CVD and (C) any interaction between birth weight, postnatal exposure to the occupation and CVD. These models also tested for any interactions between birth weight and sex, and postnatal exposure to the occupation and parish of residence at birth (as a marker of parish residence during the occupation and related variation in the severity of food deprivation). RESULTS The first set of models (A) found no relationship between birth weight and CVD even after adjustment for potential confounders (hazard ratio (HR) per kg increase in birth weight: 1.12; 95% confidence intervals (CI): 0.70 – 1.78), and there was no significant interaction between birth weight and sex (p = 0.60). The second set of models (B) found a significant relationship between postnatal exposure to the occupation and CVD after adjustment for potential confounders (HR for exposed vs. unexposed group: 2.52; 95% CI: 1.54 – 4.13), as well as a significant interaction between postnatal exposure to the occupation and parish of residence at birth (p = 0.01), such that those born in urban parishes (where food deprivation was worst) had a greater HR for CVD than those born in rural parishes. The third model (C) found no interaction between birth weight and exposure to the occupation (p = 0.43). CONCLUSION These findings suggest that the levels of postnatal undernutrition experienced by children, adolescents and young adults exposed to food deprivation during the 1940–45 occupation of the Channel Islands were a more important determinant of CVD in later life than the levels of prenatal undernutrition experienced in utero prior to the occupatio

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

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    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

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

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    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.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74791/1/j.1600-051X.2007.01058.x.pd

    Age-period-cohort analysis of trends in amyotrophic lateral sclerosis incidence

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    Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease with an unknown cause. Studies have reported that the incidence rate of ALS might be changing. As ALS is an age related disease, crude incidence could increase as population structure changes and overall life expectancy improves. Age-period-cohort (APC) models are frequently used to investigate trends in demographic rates such as incidence. Age-specific incidence rate for ALS from 1996 to 2014 were taken from a population-based ALS register in Ireland. To circumvent the well-known identifiability issue in APC models, we apply the method of Partial Least Squares Regression to separate the effects of Age, Period and Cohort on ALS incidence over time. This APC analysis shows no cohort effect and the initial signs of a period effect; increasing incidence of ALS in the most recently diagnosed group. As further years of data accrue to the Irish register it will become clear if this effect emerges as a strong trend in the incidence of ALS in Ireland and replication of these analyses in other populations will show if our findings on temporal patterns in ALS incidence are shared elsewhere

    Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox

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    This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results

    Translating HbA1c measurements into estimated average glucose values in pregnant women with diabetes

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    Aims/hypothesis This study aimed to examine the relationship between average glucose levels, assessed by continuous glucose monitoring (CGM), and HbA1c levels in pregnant women with diabetes to determine whether calculations of standard estimated average glucose (eAG) levels from HbA1c measurements are applicable to pregnant women with diabetes. Methods CGM data from 117 pregnant women (89 women with type 1 diabetes; 28 women with type 2 diabetes) were analysed. Average glucose levels were calculated from 5–7 day CGM profiles (mean 1275 glucose values per profile) and paired with a corresponding (±1 week) HbA1c measure. In total, 688 average glucose–HbA1c pairs were obtained across pregnancy (mean six pairs per participant). Average glucose level was used as the dependent variable in a regression model. Covariates were gestational week, study centre and HbA1c. Results There was a strong association between HbA1c and average glucose values in pregnancy (coefficient 0.67 [95% CI 0.57, 0.78]), i.e. a 1% (11 mmol/mol) difference in HbA1c corresponded to a 0.67 mmol/l difference in average glucose. The random effects model that included gestational week as a curvilinear (quadratic) covariate fitted best, allowing calculation of a pregnancy-specific eAG (PeAG). This showed that an HbA1c of 8.0% (64 mmol/mol) gave a PeAG of 7.4–7.7 mmol/l (depending on gestational week), compared with a standard eAG of 10.2 mmol/l. The PeAG associated with maintaining an HbA1c level of 6.0% (42 mmol/mol) during pregnancy was between 6.4 and 6.7 mmol/l, depending on gestational week. Conclusions/interpretation The HbA1c–average glucose relationship is altered by pregnancy. Routinely generated standard eAG values do not account for this difference between pregnant and non-pregnant individuals and, thus, should not be used during pregnancy. Instead, the PeAG values deduced in the current study are recommended for antenatal clinical care
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