TOIB Study. Are topical or oral ibuprofen equally effective for the treatment of chronic knee pain presenting in primary care: a randomised controlled trial with patient preference study. [ISRCTN79353052]

BACKGROUND: Many older people have chronic knee pain. Both topical and oral non- steroidal anti-inflammatory drugs (NSAIDs) are commonly used to treat this. Oral NSAIDS are effective, at least in the short term, but can have severe adverse effects. Topical NSAIDs also appear to be effective, at least in the short term. One might expect topical NSAIDs both to be less effective and to have fewer adverse effects than oral NSAIDs. If topical NSAIDs have fewer adverse effects this may outweigh both the reduction in effectiveness and the higher cost of topical compared to oral treatment. Patient preferences may influence the comparative effectiveness of drugs delivered via different routes. METHODS: TOIB is a randomised trial comparing topical and oral ibuprofen, with a parallel patient preference study. We are recruiting people aged 50 or over with chronic knee pain, from 27 MRC General Practice Research Framework practices across the UK. We are seeking to recruit 283 participants to the RCT and 379 to the PPS. Participants will be followed up for up to two years (with the majority reaching one year). Outcomes will be assessed by postal questionnaire, nurse examination, laboratory tests and medical record searches at one and two years or the end of the study. DISCUSSION: This study will provide new evidence on the overall costs and benefits of treating chronic knee pain with either oral or topical ibuprofen. The use of a patient preference design is unusual, but will allow us to explore how preference influences response to a medication. In addition, it will provide more information on adverse events. This study will provide evidence to inform primary care practitioners, and possibly influence practice

Confounding and exposure measurement error in air pollution epidemiology

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution. The association between long-term exposure to ambient air pollution and mortality has been investigated using cohort studies in which subjects are followed over time with respect to their vital status. In such studies, control for individual-level confounders such as smoking is important, as is control for area-level confounders such as neighborhood socio-economic status. In addition, there may be spatial dependencies in the survival data that need to be addressed. These issues are illustrated using the American Cancer Society Cancer Prevention II cohort. Exposure measurement error is a challenge in epidemiology because inference about health effects can be incorrect when the measured or predicted exposure used in the analysis is different from the underlying true exposure. Air pollution epidemiology rarely if ever uses personal measurements of exposure for reasons of cost and feasibility. Exposure measurement error in air pollution epidemiology comes in various dominant forms, which are different for time-series and cohort studies. The challenges are reviewed and a number of suggested solutions are discussed for both study domains

Myocardial ischemia and reperfusion: The role of oxygen radicals in tissue injury

Thrombolytic therapy has gained widespread acceplance as a means of treating coronary artery thrombosis in patients with acute myocardial infarction. Although experimental data have demonstrated that timely reperfusion limits the extent of infarction caused by regional ischemia, there is growing evidence that reperfusion is associated with an inflammatory response to ischemia that exacerbates the tissue injury. Ischemic myocardium releases archidonate and complement-derived chemotactic factors, e.g., leukotriene B 4 and C 5a , which attract and activate neutrophils. Reperfusion of ischemic myocardium accelerates the influx of neutrophils, which release reactive oxygen products, such as superoxide anion and hydrogen peroxide, resulting in the formation of a hydroxyl radical and hypochlorous acid. The latter two species may damage viable endothelial cells and myocytes via the peroxidation of lipids and oxidation of protein sulfhydryl groups, leading to perturbations of membrane permeability and enzyme function. Neutrophil depletion by antiserum and inhibition of neutrophil function by drugs, e.g., ibuprofen, prostaglandins (prostacyclin and PGE 1 ), or a monoclonal antibody, to the adherence-promoting glycoprotein Mo-1 receptor, have been shown to limit the extent of canine myocardial injury due to coronary artery occlusion/reperfusion. Recent studies have challenged the hypothesis that xanthine-oxidase-derived oxygen radicals are a cause of reperfusion injury. Treatment with allopurinol or oxypurinol may exert beneficial effects on ischemic myocardium that are unrelated to the inhibition of xanthine oxidase. Furthermore, the human heart may lack xanthine oxidase activity. Further basic research is needed, therefore, to clarify the importance of xanthine oxidase in the pathophysiology of reperfusion injury. Current data are highly suggestive of a deleterious role of the neutrophil in organ reperfusion and justify consideration of the clinical investigation of neutrophil inhibitors in patients receiving thrombolytic agents during the evolution of an acute myocardial infarction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44595/1/10557_2004_Article_BF00133206.pd

Spatial modeling of PM<inf>10</inf> and NO<inf>2</inf> in the continental United States, 1985-2000

BACKGROUND: Epidemiologic studies of air pollution have demonstrated a link between long-term air pollution exposures and mortality. However, many have been limited to city-specific average pollution measures or spatial or land-use regression exposure models in small geographic areas. OBJECTIVES: Our objective was to develop nationwide models of annual exposure to particulate matter < 10 μm in diameter (PM10) and nitrogen dioxide during 1985-2000. METHODS: We used generalized additive models (GAMs) to predict annual levels of the pollutants using smooth spatial surfaces of available monitoring data and geographic information system-derived covariates. Model performance was determined using a cross-validation (CV) procedure with 10% of the data. We also compared the results of these models with a commonly used spatial interpolation, inverse distance weighting. RESULTS: For PM10, distance to road, elevation, proportion of low-intensity residential, high-intensity residential, and industrial, commercial, or transportation land use within 1 km were all statistically significant predictors of measured PM10 (model R2 = 0.49, CV R2 = 0.55). Distance to road, population density, elevation, land use, and distance to and emissions of the nearest nitrogen oxides-emitting power plant were all statistically significant predictors of measured NO2 (model R2 = 0.88, CV R2 = 0.90). The GAMs performed better overall than the inverse distance models, with higher CV R2 and higher precision. CONCLUSIONS: These models provide reasonably accurate and unbiased estimates of annual exposures for PM10 and NO2. This approach provides the spatial and temporal variability necessary to describe exposure in studies assessing the health effects of chronic air pollution

Temporal aspects of air pollutant measures in epidemiologic analysis: a simulation study

Numerous observational studies have assessed the association between ambient air pollution and chronic disease incidence, but there is no uniform approach to create an exposure metric that captures the variability in air pollution through time and determines the most relevant exposure window. The purpose of the present study was to assess ways of modeling exposure to air pollution in relation to incident hypertension. We simulated data on incident hypertension to assess the performance of six air pollution exposure metrics, using characteristics from the Black Women’s Health Study. Each metric made different assumptions about how to incorporate time trends in pollutant data, and the most relevant window of exposure. We use observed values for particulate matter ≤2.5 microns (PM(2.5)) for this cohort to create the six exposure metrics and fit Cox proportional hazards models to the simulated data using the six metrics. The optimal exposure metric depends on the underlying association between PM(2.5) and disease, which is unknown. Metrics that incorporate exposure information from multiple years tend to be more robust and suffer from less bias. This study provides insight into factors that influence the metric used to quantifying exposure to PM(2.5) and suggests the need for careful sensitivity analyses

Factors influencing time-location patterns and their impact on estimates of exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

We assessed time-location patterns and the role of individual- and residential-level characteristics on these patterns within the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) cohort and also investigated the impact of individual-level time-location patterns on individual-level estimates of exposure to outdoor air pollution. Reported time-location patterns varied significantly by demographic factors such as age, gender, race/ethnicity, income, education, and employment status. On average Chinese participants reported spending significantly more time indoors and less time outdoors and in transit than white, black, or Hispanic participants. Using a tiered linear regression approach, we predicted time indoors at home and total time indoors. Our model, developed using forward selection procedures, explained 43 percent of the variability in time spent indoors at home, and incorporated demographic, health, lifestyle, and built environment factors. Time-weighted air pollution predictions calculated using recommended time indoors from USEPA(1) overestimated exposures as compared to predictions made with MESA Air participant-specific information. These data fill an important gap in the literature by describing the impact of individual and residential characteristics on time-location patterns and by demonstrating the impact of population-specific data on exposure estimates