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Exposure Definitions (exposure + definition)

Distribution by Scientific Domains
Medical Sciences100%

Selected Abstracts

Using prescription registries to define continuous drug use: how to fill gaps between prescriptions,

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 4 2008
Lars Hougaard Nielsen MSc
Abstract Pharmacoepidemiological studies often use prescription registries to assess patients' drug episodes. The databases usually provide information on the date of the redemption of the prescription as well as on the dispensed amount, and this allows us to define episodes of drug use. However, when patients take less medication than prescribed, apparent gaps between prescriptions occur, and most studies handle this issue by allowing for small gaps when defining continuous drug use. This paper argues that it becomes crucial whether gaps are ,filled' prospectively or retrospectively. In the latter case the inferred exposure status depends on the patient's future dispensing behaviour and this can lead to severe bias in the findings of the study. In this paper we investigate this potential bias in a study of the risk of acute myocardial infarction (AMI) for women using hormone therapy (HT), and we show that the retrospective exposure definition introduces an artificially protective effect of HT. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Application of lag-time into exposure definitions to control for protopathic bias,

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 3 2007
H. Tamim
Abstract Purpose To control for protopathic bias, some studies have incorporated the concept of lag-time into their exposure definition (time period before the index date that was not considered in assessing exposure). The objective of this study was to introduce a procedure to identify the best lag-time to be applied in studies where control for protopathic bias is required. Methods We used data from a case-control study carried out to assess the association between exposure to proton pump inhibitors (PPIs) and risk of gastric cancer, using RAMQ databases. Exposure was defined as the number of defined daily doses of PPIs dispensed during the 5-year period prior to the index date (divided into four quartiles). Thirty-one different lag-times were applied (0,30 months) based on 1-month intervals. Logistic regression was used to estimate the matched odds ratio (OR) for each lag-time. The change point in the ln(ORs) was identified by applying a two-compartmental model and a segmented regression model. Results A trend of decreasing ORs was found with the application of an increasing lag-time. As an illustration, the ORs for the 1st quartile of defined daily doses, when applying the 31 different lag-times, ranged between 3.52 when applying a 0 lag-time and 0.97 when applying a 30 months lag-time. Applying the two methods for the different lag-times showed that the ORs stabilized at around 6 months. Conclusion For the purpose of controlling for protopathic bias in pharmacoepidemiological studies, we have provided a method to assess the most appropriate lag-time that should be applied for the assessment of drug exposure. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Defining hormone replacement therapy in longitudinal studies: impact on measures of effect

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 4 2004
Ilona Csizmadi PhD
Abstract Data from a nested case-control study, designed to examine the effect of hormone replacement therapy (HRT) on colorectal cancer risk, were analyzed to determine the effect of exposure definition on the estimation of risk ratios (RR). A prescription drug plan database was used to ascertain HRT prescriptions dispensed prior to index dates to cases (n,=,3059) and age-matched controls (n,=,12,116). HRT exposure was defined as ,prescription' and ,tablet' counts, ,conjugated estrogen only' and a method based on proportions of minimum exposure to a number of estrogens (SUM-P3 and SUM-P12). The effect of HRT was described with reference to ,ever', <,5 and ,,5 years of HRT use. Conditional logistic regression was used to estimate ORs and 95% confidence intervals (CI). Adjusted ORs for ,ever use' of HRT ranged from 0.72 (95%CI: 0.60,0.88) to 0.86 (95%CI: 0.76,0.99); for <5 years use, from 0.70 (95%CI: 0.56,0.88) to 0.89 (95%CI: 0.78,1.01) and for ,5 year of HRT use, from 0.74 (95%CI: 0.59,0.92) to 0.98 (95%CI: 0.42,2.26). Various methods used to define HRT exposure produce a range of estimated ORs that vary in magnitude similar to results reported in the literature from observational studies investigating the association between HRT and colorectal cancer. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Have studies of urinary tract infection and preterm delivery used the most appropriate methods?

PAEDIATRIC & PERINATAL EPIDEMIOLOGY, Issue 3 2003
Marie S. O'Neill
Summary Published investigations of the association between urinary tract infection (UTI) and preterm delivery used logistic regression or chi-squared tests. Because both exposure and outcome are time dependent, these methods were not optimal and did not account for person,time under observation, potentially an important feature given the variability of women's entry to prenatal care as well as of gestational lengths. Previous researchers probably classified as exposed some women whose UTI occurred after their pregnancies exceeded 37 weeks. We applied the previous analytical methods to 1990,93 births from two Durham, NC, USA, hospitals (n = 4053) and demonstrate survival methods as an alternative. Two logistic regression models were fitted with differing exposure definitions: model 1 in which exposed = UTI diagnosed after 20 weeks' gestation; and model 2 in which exposed = UTI diagnosed between 20 weeks' and 37 weeks' gestation. Model 3 used proportional hazards regression with person,time after 20 weeks and before UTI diagnosis as unexposed, and person,time after diagnosis as exposed. Models were fit with and without five time-constant potential confounders. Model 1 yielded an adjusted odds ratio (OR) of 0.8 [95% confidence interval (CI) 0.5, 1.2], and model 2, which did not include UTI diagnoses after 37 weeks, an adjusted OR of 0.9 [95% CI 0.6, 1.4]. The Cox model hazard ratio (HR) for preterm delivery was 1.1 (adjusted) [95% CI 0.7, 1.7]. As these results indicated some bias, but not remarkable differences, we conducted a sensitivity analysis using 100 samples of 80% of the original data set, with replacement to determine how large the differences might be in other, similar data sets. The Cox method consistently produced higher effect estimates than either logistic model. The two samples with the greatest differences between the Cox and logistic model estimates yielded an OR of 1.47 [95% CI 0.95, 2.29] for model 1 vs. HR of 2.06 [95% CI 1.39, 3.06] for model 3, and an OR of 1.41 [95% CI 0.88, 2.25] for model 2 vs. HR of 1.79 [95% CI 1.17, 2.71] for model 3 respectively. Previous published results on UTI and preterm delivery require cautious interpretation. Data on UTI timing should be gathered to allow appropriate analyses; survival methods account for person,time under observation and ensure that studied exposures precede effects. [source]

Application of lag-time into exposure definitions to control for protopathic bias,

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 3 2007
H. Tamim
Abstract Purpose To control for protopathic bias, some studies have incorporated the concept of lag-time into their exposure definition (time period before the index date that was not considered in assessing exposure). The objective of this study was to introduce a procedure to identify the best lag-time to be applied in studies where control for protopathic bias is required. Methods We used data from a case-control study carried out to assess the association between exposure to proton pump inhibitors (PPIs) and risk of gastric cancer, using RAMQ databases. Exposure was defined as the number of defined daily doses of PPIs dispensed during the 5-year period prior to the index date (divided into four quartiles). Thirty-one different lag-times were applied (0,30 months) based on 1-month intervals. Logistic regression was used to estimate the matched odds ratio (OR) for each lag-time. The change point in the ln(ORs) was identified by applying a two-compartmental model and a segmented regression model. Results A trend of decreasing ORs was found with the application of an increasing lag-time. As an illustration, the ORs for the 1st quartile of defined daily doses, when applying the 31 different lag-times, ranged between 3.52 when applying a 0 lag-time and 0.97 when applying a 30 months lag-time. Applying the two methods for the different lag-times showed that the ORs stabilized at around 6 months. Conclusion For the purpose of controlling for protopathic bias in pharmacoepidemiological studies, we have provided a method to assess the most appropriate lag-time that should be applied for the assessment of drug exposure. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Refining exposure definitions for studies of periodontal disease and systemic disease associations

COMMUNITY DENTISTRY AND ORAL EPIDEMIOLOGY, Issue 6 2008
Ryan T. Demmer
Abstract,,, Background:, Substantial variation exists in reported associations between periodontal infections and cardiovascular disease. Imprecise periodontal exposure definitions are possible contributors to this variability. We studied appropriate exposure definitions for studying associations between clinical periodontal disease (PD) and systemic disease. Methods:, Data originate from men and women aged 20,79 enrolled in the Study of Health in Pomerania (SHIP) from 1997,2001. Age and sex-adjusted correlation analysis identified PD definitions with the highest cross-sectional associations with three subclinical markers of systemic disease: plasma fibrinogen (n = 3481), serum hemoglobin A1c (HbA1c) (n = 3480), and common carotid artery intima-media thickness (c-IMT) (n = 1745, age , 45). Results:, In men and women, percent of sites with attachment loss (AL) ,6 mm and tooth loss both revealed the highest correlation with HbA1c (, = 0.11; several other definitions related similarly), while the strongest fibrinogen correlation was observed with percent of sites with pocket depth ,3 mm (, = 0.19). Findings for c-IMT among men were strongest for percent of sites with AL ,6 mm (, = 0.14; several other definitions related similarly) while among women, percent of sites with pocket depth ,5 or 6 mm had the highest observed correlation (, = 0.13). Conclusions:, A range of near optimal definitions varied according to gender and whether the systemic disease marker reflected an acute or chronic situation. Pocket depth was more strongly correlated with the acute marker fibrinogen while attachment and tooth loss tended to be more strongly correlated with the chronic markers, HbA1c, and c-IMT. These findings can be useful in designing future studies investigating the association between PD and systemic disease. [source]