Exposure Measurement Errors, Risk Estimate and Statistical Power in Case-Control Studies Using Dichotomous Analysis of a Continuous Exposure Variable

1995 ◽  
Vol 24 (4) ◽  
pp. 851-862 ◽  
Author(s):  
VINCENT DELPIZZO ◽  
JOANNA L BORGHESI
Keyword(s):  
Measurement Errors ◽  
Statistical Power ◽  
Case Control ◽  
Risk Estimate ◽  
Continuous Exposure ◽  
Case Control Studies ◽  
Exposure Measurement ◽  
Exposure Variable

scholarly journals Bayesian Variable Selection Methods for Matched Case-Control Studies

2017 ◽  
Vol 13 (1) ◽  
Author(s):  
Josephine Asafu-Adjei ◽  
Mahlet G. Tadesse ◽  
Brent Coull ◽  
Raji Balasubramanian ◽  
Michael Lev ◽  
...  
Keyword(s):  
Variable Selection ◽  
Statistical Power ◽  
High Efficiency ◽  
Massachusetts General Hospital ◽  
Imaging Study ◽  
Bayesian Variable Selection ◽  
Case Control ◽  
Selection Methods ◽  
Case Control Studies ◽  
Matched Case

AbstractMatched case-control designs are currently used in many biomedical applications. To ensure high efficiency and statistical power in identifying features that best discriminate cases from controls, it is important to account for the use of matched designs. However, in the setting of high dimensional data, few variable selection methods account for matching. Bayesian approaches to variable selection have several advantages, including the fact that such approaches visit a wider range of model subsets. In this paper, we propose a variable selection method to account for case-control matching in a Bayesian context and apply it using simulation studies, a matched brain imaging study conducted at Massachusetts General Hospital, and a matched cardiovascular biomarker study conducted by the High Risk Plaque Initiative.

The influence of radon measurement errors on the uncertainties of epidemiological case-control studies

2011 ◽  
Vol 145 (2-3) ◽  
pp. 243-247 ◽  
Author(s):  
M. Zhukovsky ◽  
A. Onishchenko ◽  
A. Varaksin ◽  
A. Vasilyev
Keyword(s):  
Measurement Errors ◽  
Case Control ◽  
Case Control Studies ◽  
Radon Measurement

scholarly journals 1304Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the EPIC study

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Marie Breeur ◽  
Pietro Ferrari ◽  
Julie Schmidt ◽  
Ruth Travis ◽  
Tim Key ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cancer Risk ◽  
Statistical Power ◽  
Conditional Logistic Regression ◽  
Total Sample ◽  
Case Control ◽  
Cancer Site ◽  
Case Control Studies ◽  
Cancer Types ◽  
Pan Cancer

Abstract Background Metabolomics studies in cancer epidemiology have mostly focused on single metabolite-cancer site associations. Pan-cancer analyses may have larger statistical power when identifying metabolites showing consistent associations across cancer sites, while allowing the identification of site-specific associations. Methods Data from seven cancer-specific case-control studies nested within the European Prospective Investigation into Cancer and Nutrition Cohort (EPIC) were pooled, resulting in a total sample of 7,957 case-control pairs from eight cancer types (breast, colorectal, endometrial, gallbladder, kidney, localized prostate and advanced prostate cancer, and hepatocellular carcinoma). A total of 117 pre-diagnostic blood metabolites were measured. After clustering the most highly correlated ones together, we studied the association between 50 features (metabolites or clusters of metabolites) and cancer risk in multivariate penalized conditional logistic regression models controlled for body mass index using the data shared lasso. Results We identified: (i) 8 features with consistent associations across cancer sites: e.g., glutamine and C4-acylcarnitine, one cluster of lysophosphatidylcholines and one of phosphatidylcholines were inversely associated with cancer, while C10-acylcarnitine, valine and proline showed positive associations; (ii) 11 features with heterogeneous associations across cancer sites: e.g., arginine was positively associated with colorectal cancer only, while one cluster of sphingomyelins was associated inversely with hepatocellular carcinoma and positively with endometrial cancer. Conclusions Our pan-cancer analysis notably identified metabolites showing consistent associations with cancer risk across different cancer-types. Key messages Our results could lead to the identification of common pathways shared across different cancer types.

scholarly journals Association of FcεRIβ polymorphisms with risk of asthma and allergic rhinitis: evidence based on 29 case–control studies

2018 ◽  
Vol 38 (4) ◽  
Author(s):  
Huanhuan Guo ◽  
Tao Peng ◽  
Ping Luo ◽  
Huabin Li ◽  
Shuo Huang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Statistical Power ◽  
Meta Analysis ◽  
Allergic Diseases ◽  
Case Control ◽  
Nucleotide Polymorphisms ◽  
Case Control Studies ◽  
Potential Risk Factors ◽  
Genetic And Environmental Factors ◽  
The Stability

Purpose: Accumulating evidence has shown that allergic diseases are caused by a complex interaction of genetic and environmental factors, some single nucleotide polymorphisms (SNPs) existing in high-affinity IgE receptor β chain (FcεRIβ) are potential risk factors for allergic diseases. However, the results have been inconsistent and inconclusive due to the limited statistical power in individual study. Thus, we conducted a meta-analysis to systematically evaluate the association between FcεRIβ SNPs and allergic diseases risk. Methods: Eligible studies were collected from PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure, and WanFang databases. Pooled odd ratios (ORs) and corresponding 95% confidence intervals (95% CIs) were calculated to assess the strength of the relationships between five polymorphisms (E237G, -109 C/T, RsaI_in2, RsaI_ex7, and I181L) and the risk of allergic diseases by using five genetic models. In addition, the stability of our analysis was evaluated by publication bias, sensitivity, and heterogeneity analysis. Results: Overall, a total of 29 case–control studies were included in this meta-analysis. We found that E237G (B vs. A: OR = 1.28, 95% CI = 1.06–1.53, P<0.001, I2 = 63.1%) and -109 C/T (BB vs. AA + AB: OR = 1.58, 95%CI = 1.26–1.98, P<0.001, I2 = 66.4%) were risk factors for allergic diseases. Conclusion: Our meta-analysis suggests that polymorphisms in FcεRIβ may be associated with the development of allergic diseases.

Reducing Bias Due to Exposure Measurement Error Using Disease Risk Scores

2020 ◽  
Author(s):  
David B Richardson ◽  
Alexander P Keil ◽  
Stephen R Cole ◽  
Jessie K Edwards
Keyword(s):  
Measurement Error ◽  
Disease Risk ◽  
Risk Scores ◽  
Continuous Exposure ◽  
Disease Score ◽  
Exposure Measurement ◽  
Classical Measurement ◽  
Exposure Measurement Error ◽  
Exposure Variable ◽  
Using Data

Abstract Suppose that an investigator wants to estimate an association between a continuous exposure variable and an outcome, adjusting for a set of confounders. If the exposure variable suffers classical measurement error, in which the measured exposures are distributed with independent error around the true exposure, then an estimate of the covariate-adjusted exposure-outcome association may be biased. We propose an approach to estimate a marginal exposure-outcome association in the setting of classical exposure measurement error using a disease score-based approach to standardization to the exposed sample. First, we show that the proposed marginal estimate of the exposure-outcome association will suffer less bias due to classical measurement error than the covariate-conditional estimate of association when the covariates are predictors of exposure. Second, we show that if an exposure validation study is available with which to assess exposure measurement error then the proposed marginal estimate of the exposure-outcome association can be corrected for measurement error more efficiently than the covariate-conditional estimate of association. We illustrate both of these points using simulations and an empirical example using data from the Orinda Longitudinal Study of Myopia (1989-2001).

scholarly journals Selection bias and misclassification in case–control studies conducted using the National Violent Death Reporting System

2020 ◽  
Vol 26 (6) ◽  
pp. 566-568
Author(s):  
Vivian H Lyons ◽  
Ali Rowhani-Rahbar ◽  
Avanti Adhia ◽  
Noel S Weiss
Keyword(s):  
Selection Bias ◽  
Reporting System ◽  
Case Control ◽  
Violent Death ◽  
Methodological Issues ◽  
Case Control Studies ◽  
Exposure Measurement ◽  
Control Selection ◽  
Introduce Selection Bias ◽  
Selection Of

Conducting case–control studies using the National Violent Death Reporting System (NVDRS) has the potential to introduce selection bias and misclassification through control selection. Some studies that use NVDRS compare groups of individuals who died by one mechanism, intent or circumstance, to individuals who died by another mechanism, intent or circumstance. For aetiological studies within NVDRS, the use of controls who had a different type of violent death has the potential to introduce selection bias, while relying on narrative summaries for exposure measurement may result in misclassification. We discuss these two methodological issues, and identify an unusual circumstance in which selection of live controls within NVDRS can be employed.

scholarly journals Garlic consumption and colorectal cancer risk in man: a systematic review and meta-analysis

2015 ◽  
Vol 19 (2) ◽  
pp. 308-317 ◽  
Author(s):  
Manuela Chiavarini ◽  
Liliana Minelli ◽  
Roberto Fabiani
Keyword(s):  
Colorectal Cancer ◽  
Cancer Risk ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Pooled Analysis ◽  
Case Control ◽  
Dietary Factors ◽  
Colorectal Cancer Risk ◽  
Risk Estimate ◽  
Case Control Studies

AbstractObjectiveColorectal cancer shows large incidence variations worldwide that have been attributed to different dietary factors. We conducted a meta-analysis on the relationship between garlic consumption and colorectal cancer risk.DesignWe systematically reviewed publications obtained by searching ISI Web of Knowledge, MEDLINE and EMBASE literature databases. We extracted the risk estimate of the highest and the lowest reported categories of intake from each study and conducted meta-analysis using a random-effects model.ResultsThe pooled analysis of all fourteen studies, seven cohort and seven case–control, indicated that garlic consumption was not associated with colorectal cancer risk (OR=0·93; 95 % CI 0·82, 1·06, P=0·281; I2=83·6 %, P≤0·001). Separate analyses on the basis of cancer sites and sex also revealed no statistically significant effects on cancer risk. However, when separately analysed on the basis of study type, we found that garlic was associated with an approximately 37 % reduction in colorectal cancer risk in the case–control studies (combined risk estimate=0·63, 95 % CI 0·48, 0·82, P=0·001; I2=75·6 %, P≤0·001).ConclusionsOur results suggest that consumption of garlic is not associated with a reduced colorectal cancer risk. Further investigations are necessary to clarify the discrepancy between results obtained from different types of epidemiological studies.

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