Biomedical subjects

Samuel O M Manda

Publications and source records attributed to Samuel O M Manda.

6 recordsLinked to original sources

PubMed2005

Detecting small-area similarities in the epidemiology of childhood acute lymphoblastic leukemia and diabetes mellitus, type 1: a Bayesian approach.

Childhood acute lymphoblastic leukemia and diabetes mellitus, type 1, have common epidemiologic and etiologic features, including correlated international incidence and associations with infections. The authors examined whether the diseases' similar large-scale distributions are reflected in small geographic areas while also examining the influence of sociodemographic characteristics. Details of 299 children (0-14 years) with acute lymphoblastic leukemia and 1,551 children with diabetes diagnosed between 1986 and 1998 were extracted from two registers in Yorkshire, United Kingdom. Standardized incidence ratios across 532 electoral wards were compared using Poisson regression, confirming significant associations between population mixing and the geographic heterogeneity of both conditions. Bayesian methods analysis of spatial correlation between diseases by modeling a bivariate outcome based on their standardized incidence ratios was applied; spatial and heterogeneity components were included within a hierarchical random effects model. A positive correlation between diseases of 0.33 (95% credible interval: -0.20, 0.74) was observed, and this was reduced after control for population mixing (r = 0.18), population density (r = 0.14), and deprivation (r = 0.06). The Bayesian approach showed a modest but nonsignificant joint spatial correlation between diseases, only partially suggesting that the risk of both was associated within some electoral wards. With Bayesian methodology, population mixing remained significantly associated with both diseases. The links between diabetes and acute lymphoblastic leukemia observed for large regions are weaker for small areas. More powerful replications are needed for confirmation of these findings.

Adolescent↗

PubMed2005

Bayesian inference for recurrent events data using time-dependent frailty.

In medical studies, we commonly encounter multiple events data such as recurrent infection or attack times in patients suffering from a given disease. A number of statistical procedures for the analysis of such data use the Cox proportional hazards model, modified to include a random effect term called frailty which summarizes the dependence of recurrent times within a subject. These unobserved random frailty effects capture subject effects that are not explained by the known covariates. They are typically modelled constant over time and are assumed to be independently and identically distributed across subjects. However, in some situations, the subject-specific random frailty may change over time in the same manner as time-dependent covariate effects. This paper presents a time-dependent frailty model for recurrent failure time data in the Bayesian context and estimates it using a Markov chain Monte Carlo method. Our approach is illustrated by a data set relating to patients with chronic granulomatous disease and it is compared to the constant frailty model using the deviance information criterion.

Bayes Theorem↗

PubMed2005

A Bayesian analysis of amalgam restorations in the Royal Air Force using the counting process approach with nested frailty effects.

Survival analysis methods are increasingly used in dental research to measure risk of tooth eruption and caries as well as life spans of amalgam restorations. Analyses have been extended to account for lack of independence in the data, which arises from the clustering of observations within units such as tooth-surfaces, teeth and subjects. There are various analytical strategies and modelling approaches now available to us in dealing with clustered dental data. In this article, the modelling strategy of Cox's proportional hazards regression is formulated using the counting process approach, which can easily be extended to include time-variant covariates as well as nested random frailty effects. A semi-parametric Bayesian method is presented for the analysis of the proposed model. The methodology is applied to an analysis of nested clustered data on life-span of amalgam restorations in the UK Royal Air Force. These data have previously been analysed using a non-Bayesian approach. The Gibbs sampler, a Markov chain Monte Carlo method, is used to generate samples from the marginal posterior distribution of the parameters of this Bayesian model.

Bayes Theorem↗

PubMed2004

Relation of left ventricular sphericity to 10-year survival after acute myocardial infarction.

After ST-elevation myocardial infarction, the association between left ventricular sphericity (measured by biplane ventriculography) and survival rate at a median of 6.5 years was determined in 825 patients. The highest tertile of sphericity (vs the lowest and middle tertiles) was associated with a decreased 10-year survival rate in patients who had anterior myocardial infarction (p = 0.002), inferior myocardial infarction (p = 0.011), Thrombolysis In Myocardial Infarction (TIMI) grade 3 flow (p = 0.005), or TIMI grade 0 to 2 flow (p = 0.001) in the infarct artery. The independent multivariate predictors of a 10-year survival rate were ejection fraction (p = 0.002), treadmill exercise duration (p = 0.004), biplane left ventricular sphericity index (p = 0.032), age (p = 0.043), and end-systolic volume index (p = 0.047), but not TIMI flow grade.

Cineangiography↗

PubMed2002

A Bayesian ordinal model for heterogeneity in a multi-centre myocardial infarction clinical trial.

A Bayesian methodology is developed to investigate the homogeneity of the treatment effects in a multi-centre clinical trial with an ordinal response. A hierarchical model is formulated for the ordinal response, and the marginal posterior distributions of the covariates, overall treatment and the centre effects are calculated using the Gibbs sampler. The methodology is applied to data arising from a multi-centre clinical trial of therapies for acute myocardial infarction. In this trial, the overall results show that the treatment is effective. However, there appears to be substantial differences in both the baseline risk and treatment effect across centres. Thus, the observed treatment effects may not be generalized to a broader patient population, and exploratory analyses to ascertain reasons for the treatment-by-centre interaction and its possible effect on the study conclusions would be useful.

Anti-Inflammatory Agents, Non-Steroidal↗

PubMed2002

Early ST-segment recovery, infarct artery blood flow, and long-term outcome after acute myocardial infarction.

BACKGROUND: Early resolution of ST-segment deviation (ST recovery) on the postthrombolytic electrocardiograms and restoration of "normal" blood flow in the infarct-related artery are associated with improved outcomes after myocardial infarction (MI). METHODS AND RESULTS: To evaluate the relationships between ST recovery, infarct-related artery flow, and late survival we studied 766 patients with electrocardiograms recorded at a median of 167 minutes after thrombolytic therapy. Angiography was performed at 3 weeks, and follow-up was done at a median of 6.3 years (interquartile range [IQR] 5.0-8.4). At 10 years, the survival rates were 55% (95% CI 43-70) in patients with <30% ST recovery in the single lead with maximum ST elevation, 71% (95% CI 64-79) in those with 30% to 70% ST recovery, and 74% (95% CI 68-82) in those with >70% ST recovery (P =.0005), whereas ST recovery measured as the sum of voltage changes of either ST deviation (elevation or depression) or ST elevation was not associated with 10-year survival (log-rank test, P =.06 and P =.34, respectively). In patients with Thrombolysis In Myocardial Infarction (TIMI) grade 3 flow, ST recovery of >70% (vs <30% and 30% to 70%) in the lead with maximum ST elevation was associated with increased late survival (P =.04). On multivariate analysis, the predictors, at admission, of 5-year survival were age (P <.001), ST recovery (measured as a continuous variable, P =.001), diabetes (P =.003) and female gender (P =.02). When the ejection fraction (P =.003) and TIMI flow grade (P =.02) at 3 weeks were included in the analysis, the P value for ST recovery was.08. CONCLUSIONS: ST recovery measured in the single lead with maximum ST elevation was a predictor of late survival, even in patients with TIMI grade 3 flow but ST recovery measured as the sum of voltage changes in all leads with ST deviation was not. This simple electrocardiographic parameter can identify patients with a reduced chance of survival who might benefit from additional therapies.

Aged↗