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Unmeasured Confounders (unmeasured + confounder)

Distribution by Scientific Domains

Medical Sciences	50%

Selected Abstracts

Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics,

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 5 2006
Sebastian Schneeweiss MD
Abstract Background Large health care utilization databases are frequently used to analyze unintended effects of prescription drugs and biologics. Confounders that require detailed information on clinical parameters, lifestyle, or over-the-counter medications are often not measured in such datasets, causing residual confounding bias. Objective This paper provides a systematic approach to sensitivity analyses to investigate the impact of residual confounding in pharmacoepidemiologic studies that use health care utilization databases. Methods Four basic approaches to sensitivity analysis were identified: (1) sensitivity analyses based on an array of informed assumptions; (2) analyses to identify the strength of residual confounding that would be necessary to explain an observed drug-outcome association; (3) external adjustment of a drug-outcome association given additional information on single binary confounders from survey data using algebraic solutions; (4) external adjustment considering the joint distribution of multiple confounders of any distribution from external sources of information using propensity score calibration. Conclusion Sensitivity analyses and external adjustments can improve our understanding of the effects of drugs and biologics in epidemiologic database studies. With the availability of easy-to-apply techniques, sensitivity analyses should be used more frequently, substituting qualitative discussions of residual confounding. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Real-life impact of early interferon, therapy in relapsing multiple sclerosis,

ANNALS OF NEUROLOGY, Issue 4 2009
M. Trojano MD
Objective Recent findings support greater efficacy of early vs. delayed interferon beta (IFN,) treatment in patients with a first clinical event suggestive of multiple sclerosis (MS). We aimed to evaluate the effectiveness of early IFN, treatment in definite relapsing-remitting MS (RRMS) and to assess the optimal time to initiate IFN, treatment with regard to the greatest benefits on disability progression. Methods A cohort of 2,570 IFN,-treated RRMS patients was prospectively followed for up to 7 years in 15 Italian MS Centers. A Cox proportional hazards regression model adjusted for propensity score (PS) quintiles was used to assess differences between groups of patients with early vs. delayed IFN, treatment on risk of reaching a 1-point progression in the Expanded Disability Status Scale (EDSS) score, and the EDSS 4.0 and 6.0 milestones. A set of PS-adjusted Cox hazards regression models were calculated according to different times of treatment initiation (within 1 year up to within 5 years from disease onset). A sensitivity analysis was performed to assess the robustness of findings. Results The lowest hazard ratios (HRs) for the three PS quintiles,adjusted models were obtained by a cutoff of treatment initiation within 1 year from disease onset. Early treatment significantly reduced the risk of reaching a 1-point progression in EDSS score (HR = 0.63; 95% CI = 0.48,0.85; p < 0.002), and the EDSS 4.0 milestone (HR = 0.56; 95% CI = 0.36,0.90; p = 0.015). Sensitivity analysis showed the bound of significance for unmeasured confounders. Interpretation Greater benefits on disability progression may be obtained by an early IFN, treatment in RRMS. Ann Neurol 2009;66:513,520 [source]

Estimation of the Causal Effects on Survival of Two-Stage Nonrandomized Treatment Sequences for Recurrent Diseases

BIOMETRICS, Issue 3 2006
Xuelin Huang
Summary In the treatment of cancer, patients commonly receive a variety of sequential treatments. The initial treatments administered following diagnosis can vary, as well as subsequent salvage regimens given after disease recurrence. This article considers the situation where neither initial treatments nor salvage treatments are randomized. Assuming there are no unmeasured confounders, we estimate the joint causal effects on survival of initial and salvage treatments, that is, the effects of two-stage treatment sequences. For each individual treatment sequence, we estimate the survival distribution function and the mean restricted survival time. Different treatment sequences are then compared using these estimates and their corresponding covariances. Simulation studies were conducted to evaluate the performance of the methods, including their sensitivity to the violation of the assumption of no unmeasured confounders. The methods are illustrated by a retrospective study of patients with soft tissue sarcoma, which motivated this research. [source]

Sensitivity Analyses for Ecological Regression

BIOMETRICS, Issue 1 2003
Jon Wakefield
Summary. In many ecological regression studies investigating associations between environmental exposures and health outcomes, the observed relative risks are in the range 1.0,2.0. The interpretation of such small relative risks is difficult due to a variety of biases,some of which are unique to ecological data, since they arise from within-area variability in exposures/confounders. The potential for residual spatial dependence, due to unmeasured confounders and/or data anomalies with spatial structure, must also be considered, though it often will be of secondary importance when compared to the likely effects of unmeasured confounding and within-area variability in exposures/confounders. Methods for addressing sensitivity to these issues are described, along with an approach for assessing the implications of spatial dependence. An ecological study of the association between myocardial infarction and magnesium is critically reevaluated to determine potential sources of bias. It is argued that the sophistication of the statistical analysis should not outweigh the quality of the data, and that finessing models for spatial dependence will often not be merited in the context of ecological regression. [source]