Comparison of survival by allocation to medical therapy, surgery, or heart transplantation for ischemic advanced heart failure.

BACKGROUND: To ascertain survival of ischemic advanced heart failure patients by treatment allocation, we examined the outcome of transplant assessment patients allocated to medical therapy, high-risk conventional surgery, or transplantation. METHODS: Patients were identified from the Papworth transplant database and excluded if primary etiology was not ischemic. Grouping was undertaken according to treatment allocation at initial assessment, and analysis was performed by intention to treat. Survival was computed from the time of assessment and Cox regression used to stratify patients according risk with the Heart Failure Survival Score. RESULTS: From May 1993 to September 2001, a total of 755 patients were admitted for transplant assessment, with 348 (46.1%) identified as having heart failure of ischemic origin. Variables required for calculation of the Heart Failure Survival Score was available in 273 patients (78.4%), and 20 patients (7.3%) were lost to follow-up. Of the remaining 253 patients, 89 (35.2%) were allocated to medical therapy, 32 (12.6%) to surgery, and 132 (52.2%) to transplantation. The relative risk (95% confidence limit) of death compared with medical therapy was 0.62 (0.28, 1.40) for surgery and 0.38 (0.24, 0.61) for transplantation in medium- to high-risk patients. For low-risk patients, the relative risks for death compared with medical therapy were 1.87 (0.63, 5.60) for surgery and 1.97 (0.79, 4.96) for transplantation. CONCLUSIONS: Transplantation improved survival of medium- and high-risk patients compared with medical therapy. In the low-risk group, this was not evident. However, repeated assessment of risk is required because the hazard for death rises steadily after the third year in these patients.     

Working conditions and health behavior as causes of educational inequalities in self-rated health: an inverse odds weighting approach

Objective:Using a novel mediation method that presents unbiased results even in the presence of exposure–mediator interactions, this study estimated the extent to which working conditions and health behaviors contribute to educational inequalities in self-rated health in the workforce.Methods:Respondents of the longitudinal Survey of Health, Ageing, and Retirement in Europe (SHARE) in 16 countries were selected, aged 50–64 years, in paid employment at baseline and with information on education and self-rated health (N=15 028). Education, health behaviors [including body mass index (BMI)] and working conditions were measured at baseline and self-rated health at baseline and two-year follow-up. Causal mediation analysis with inverse odds weighting was used to estimate the total effect of education on self-rated health, decomposed into a natural direct effect (NDE) and natural indirect effect (NIE).Results:Lower educated workers were more likely to perceive their health as poor than higher educated workers [relative risk (RR) 1.48, 95% confidence interval (CI) 1.37–1.60]. They were also more likely to have unfavorable working conditions and unhealthy behaviors, except for alcohol consumption. When all working conditions were included, the remaining NDE was RR 1.30 (95% CI 1.15–1.44). When BMI and health behaviors were included, the remaining NDE was RR 1.40 (95% CI 1.27–1.54). Working conditions explained 38% and health behaviors and BMI explained 16% of educational inequalities in health. Including all mediators explained 64% of educational inequalities in self-rated health.Conclusions:Working conditions and health behaviors explain over half of the educational inequalities in self-rated health. To reduce health inequalities, improving working conditions seems to be more important than introducing health promotion programs in the workforce.     

An assessment of spatial clustering of leukaemias and lymphomas among young people in New Zealand

STUDY OBJECTIVE: To assess spatial clustering of childhood leukaemias and lymphomas in New Zealand, using a national dataset from a country with no nuclear installations. DESIGN: New Zealand Map Grid coordinates, derived from the birth addresses of cases and controls were used in clustering analyses that applied Cuzick and Edwards' method. SETTING: The whole of New Zealand. PARTICIPANTS: The cases were ascertained from the New Zealand Cancer Registry. They were diagnosed with leukaemia or lymphoma at ages 0-14 years during the period 1976 to 1987. For Hodgkin's disease, the age range was extended to include those aged from 0-24 years. The cancer registrations were linked with national birth records, to obtain the birth addresses of the cases. The controls were selected at random from birth records, with matching to cases (1:1) on age and sex. The analyses included 600 cases and 600 controls. MAIN RESULTS: There was no statistically significant spatial clustering for any tumour group overall, including acute lymphoblastic leukaemia, acute nonlymphoblastic leukaemia, other leukaemias, non-Hodgkin's lymphomas, Hodgkin's disease, and all these combined. Significant clustering was found in a sub-analysis for one of three age specific subgroups of acute lymphoblastic leukaemia (ages 10-14 years, p = 0.003). CONCLUSION: The subgroup finding may have been real or a chance association, as several comparisons were made. This study found little evidence for spatial clustering of leukaemias or lymphomas in a population with no nuclear installations.     

Role of computed tomographic scanning of the thorax prior to bronchoscopy in the investigation of suspected lung cancer

BACKGROUND: Fibreoptic bronchoscopy (FOB) is the usual initial investigation of choice in patients with suspected endobronchial carcinoma, but it is often non-diagnostic. Once a positive diagnosis has been made, many patients undergo staging by computed tomographic (CT) scanning to assess the extent of the disease and its suitability for radical treatment. To determine whether initial CT scanning before FOB is a cost effective way of reducing subsequent unnecessary or unhelpful invasive diagnostic procedures, a study was undertaken in 171 patients with suspected endobronchial carcinoma. METHODS: A randomised two group study was performed with all patients undergoing an initial CT staging scan. In group A the CT scans were reviewed before FOB, allowing cancellation or a change to an alternative invasive procedure if considered appropriate. In group B all patients proceeded to FOB with the bronchoscopist blinded to the result of the CT scan until after the procedure. RESULTS: In group A six of 90 patients (7%) required no further investigations as the CT scan was either normal, consistent with benign disease, or consistent with widespread metastatic disease. Of the remainder, bronchoscopy was diagnostic in 50 of 68 (73%) in group A compared with 44 of 81 (54%) in group B (p = 0.015). Overall, a positive diagnosis was made after a single invasive investigation in 64 of 84 patients (76%) in group A compared with only 45 of 81 patients (55%) in group B (p = 0.005). Only seven of 90 patients (8%) in group A required more than one invasive investigation compared with 15 of 81 patients (18.5%) in group B. In patients with malignancy, bronchoscopy was more likely to be diagnostic in group A (50 of 56 patients (89%)) than in group B (44 of 62 (71%); p = 0. 012), and the diagnosis was more frequently made on the initial invasive investigation (group A, 63 of 70 (90%); group B, 44 of 62 (71%); p = 0.004). Because of the lower number of invasive procedures performed in group A than in group B, the cost of performing CT scans before FOB in all patients in group A would have equated to a projected cost of performing CT scans in 60% of patients after FOB in group B. CONCLUSIONS: Performing initial CT thoracic scans before bronchoscopy in patients with suspected endobronchial malignancy is a cost effective way of improving diagnostic yield from invasive diagnostic procedures and occasionally may obviate the need for any further investigation.     

Characterization of xenobiotic-metabolizing enzymes and nitrosamine metabolism in the human esophagus

Esophageal cancer has been associated with tobacco smoking, and nitrosamines are possible causative agents for this cancer. The present study investigated the metabolism of the tobacco carcinogens N'- nitrosonornicotine (NNN), 4-(methylnitrosamino)-1-(3-pyridyl)-1- butanone (NNK), and N-nitrosodimethylamine (NDMA), as well as the presence of xenobiotic-metabolizing enzymes in human esophageal tissues from individuals in the United States and Huixian, Henan Province, China (a high-risk area for esophageal cancer). All esophageal microsomal samples activated NNN and the metabolic rate was 2-fold higher in the esophageal samples from China than the USA. All microsomal samples activated NDMA. However, most of the microsomal samples did not activate NNK. Troleandomycin (an inhibitor of cytochrome P450 3A) decreased the formation of NNN-derived keto acid by 20-26% in the esophageal microsomes. The activities for NADPH: cytochrome c reductase, ethoxycoumarin O-deethylase, NAD(P)H: quinone oxidoreductase and glutathione S-transferase were present in the esophageal samples. Coumarin 7-hydroxylase (a representative activity for P450 2A6) activity was not detected in the esophageal microsomal samples. The activities for nitrosamine metabolism and xenobiotic- metabolizing enzymes were decreased (by 30-50%) in the squamous cell carcinomas compared with their corresponding non-cancerous mucosa. The presence of activation and detoxification enzymes in the esophagus may play an important role in determining the susceptibility of the esophagus to the carcinogenic effect of nitrosamines. Our results suggest that P450s 3A4 and 2E1 are involved in the activation of NNN and NDMA, respectively, in the human esophagus.      

State selection in Markov models for panel data with application to psoriatic arthritis

Markov multistate models in continuous‐time are commonly used to understand the progression over time of disease or the effect of treatments and covariates on patient outcomes. The states in multistate models are related to categorisations of the disease status, but there is often uncertainty about the number of categories to use and how to define them. Many categorisations, and therefore multistate models with different states, may be possible. Different multistate models can show differences in the effects of covariates or in the time to events, such as death, hospitalisation, or disease progression. Furthermore, different categorisations contain different quantities of information, so that the corresponding likelihoods are on different scales, and standard, likelihood‐based model comparison is not applicable. We adapt a recently developed modification of Akaike's criterion, and a cross‐validatory criterion, to compare the predictive ability of multistate models on the information which they share. All the models we consider are fitted to data consisting of observations of the process at arbitrary times, often called ‘panel’ data. We develop an implementation of these criteria through Hidden Markov models and apply them to the comparison of multistate models for the Health Assessment Questionnaire score in psoriatic arthritis. This procedure is straightforward to implement in the R package ‘msm’. Copyright © 2015 John Wiley & Sons, Ltd.