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Misclassification Adjustment of Family History of Breast Cancer in a Case-Control Study: a Bayesian Approach
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 Title & Authors
Misclassification Adjustment of Family History of Breast Cancer in a Case-Control Study: a Bayesian Approach
Moradzadeh, Rahmatollah; Mansournia, Mohammad Ali; Baghfalaki, Taban; Ghiasvand, Reza; Noori-Daloii, Mohammad Reza; Holakouie-Naieni, Kourosh;
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Background: Misreporting self-reported family history may lead to biased estimations. We used Bayesian methods to adjust for exposure misclassification. Materials and Methods: A hospital-based case-control study was used to identify breast cancer risk factors among Iranian women. Three models were jointly considered; an outcome, an exposure and a measurement model. All models were fitted using Bayesian methods, run to achieve convergence. Results: Bayesian analysis in the model without misclassification showed that the odds ratios for the relationship between breast cancer and a family history in different prior distributions were 2.98 (95% CRI: 2.41, 3.71), 2.57 (95% CRI: 1.95, 3.41) and 2.53 (95% CRI: 1.93, 3.31). In the misclassified model, adjusted odds ratios for misclassification in the different situations were 2.64 (95% CRI: 2.02, 3.47), 2.64 (95% CRI: 2.02, 3.46), 1.60 (95% CRI: 1.07, 2.38), 1.61 (95% CRI: 1.07, 2.40), 1.57 (95% CRI: 1.05, 2.35), 1.58 (95% CRI: 1.06, 2.34) and 1.57 (95% CRI: 1.06, 2.33). Conclusions: It was concluded that self-reported family history may be misclassified in different scenarios. Due to the lack of validation studies in Iran, more attention to this matter in future research is suggested, especially while obtaining results in accordance with sensitivity and specificity values.
Misclassification;bias;Bayesian assessment;self-report;
 Cited by
Akbari A, Razzaghi Z, Homaee F, et al (2011). Parity and breastfeeding are preventive measures against breast cancer in Iranian women. Breast Cancer, 18, 51-5. crossref(new window)

Chu H, Wang Z, Cole S, et al (2006). Sensitivity analysis of misclassification: A graphical and a Bayesian approach. Ann Epidemiol, 16, 834-41. crossref(new window)

Ebrahimi M, Vahdaninia M, Montazeri A (2002). Risk factors for breast cancer in Iran: a case-control study. Breast Cancer Res, 4, R10. crossref(new window)

Fox M, Lash T, Greenland S (2005). A method to automate probabilistic sensitivity analyses of misclassified binary variables. International J Epidemiol, 36, 1370-6.

Gelman A, Carlin JB, Stern HS, et al 2003. Bayesian Data Analysis, London, CRC Press.

Gelman A, Rubin DB ( 1992). Inference from iterative simulation using multiple sequences. Statistical Science, 7, 457-511. crossref(new window)

Ghiasvand R, Bahmanyar S, Zendehdel K, et al (2012). Postmenopausal breast cancer in Iran; risk factors and their population attributable fractions. BMC Cancer, 12, 414. crossref(new window)

Ghiasvand R, Maram ES, Tahmasebi S, et al (2011). Risk factors for breast cancer among young women in southern Iran. International J Cancer, 129, 1443-9. crossref(new window)

Greenland S (2005). Multiple-bias modelling for analysis of observational data. J Royal Statistical Society, A, 168, 1-25. crossref(new window)

Greenland S (2008). Invited commentary: variable selection versus shrinkage in the control of multiple confounders. Am J Epidemiology, 167, 523-9.

Greenland S (2009). Bayesian perspectives for epidemiologic research: III. Bias analysis via missing-data methods. International J Epidemiol, 38, 1662-73. crossref(new window)

Greenland S, Lash T (2008). Bias analysis. In 'Modern Epidemiology', Eds Lippincott-Williams-Wilkins, Philadelphia, 345-80

Greenland S, Mansournia MA (2015). Penalization, bias reduction, and default priors in logistic and related categorical and survival regressions. Statistics in Medicine, 34, 3133-43. crossref(new window)

Hamra G, MacLehose R, Richardson D (2013a). Marcov Chain Monte Carlo: an introduction for epidemiologists. International J Epidemiol, 42, 627-34. crossref(new window)

Hamra GB, MacLehose RF, Cole SR (2013b). Sensitivity analyses for sparse-data problems-using weakly informative bayesian priors. Epidemiology (Cambridge, Mass.), 24, 233-9. crossref(new window)

Hassanzadeh J, Moradzadeh R, Rajaee fard A, et al (2012). A comparison of case-control and case-only designs to investigate gene-environment interactions using breast cancer data. Iranian Journal of Medical Sciences, 37, 112-8.

Holakouie-Naieni K, Ardalan A, Mahmoodi M, et al (2007). Risk factors of breast cancer in North of Iran: A Case-Control in Mazandaran Province. Asian Pac J Cancer Prev, 8, 395-8.

Hosseinzadeh M, Eivazi Ziaei J, Mahdavi N, et al (2014). Risk factors for breast cancer in Iranian women: a hospitalbased case-control study in tabriz, Iran. J Breast Cancer, 17, 236-43. crossref(new window)

Jurek AM, Lash TL, Maldonado G (2009). Specifying exposure classification parameters for sensitivity analysis: family breast cancer history. Clinical Epidemiology, 1, 109-17.

Keil AP, Daniels JL, Hertz-Picciotto I (2014). Autism spectrum disorder, flea and tick medication, and adjustments for exposure misclassification: the CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study. Environmental Health, 13, 3. crossref(new window)

Lash T, Fink A (2003). Semi-automated sensitivity analysis to assess systematic errors in observational data. Epidemiology, 14, 451-8.

Lash TL, Fox MP, Fink AK 2009. Applying quantitative bias analysis to epidemiologic data, berlin, Germany, Springer.

Lash TL, Fox MP, MacLehose RF, et al (2014). Good practices for quantitative bias analysis. International Journal of Epidemiology, 43, 1969-85. crossref(new window)

MacLehose RF, Gustafson P (2012 January). Is probabilistic bias analysis approximately Bayesian? Epidemiology, 23, 151-8. crossref(new window)

MacLehose RF, Olshan AF, Herring AH, et al (2009). Bayesian Methods for Correcting Misclassification: An Example from Birth Defects Epidemiology. Epidemiology, 20, 27-35. crossref(new window)

Mahouri K, Dehghani-Zahedani M, Zare S (2007 Nov-Dec). Breast cancer risk factors in south of Islamic Republic of Iran: a case-control study. East Mediterr Health J, 13, 1265-73. crossref(new window)

Marrie RA, Cutter G, Tyry T, et al (2008). Smoking status over two years in patients with multiple sclerosis. Neuroepidemiology, 32, 72-9.

Prescott GJ, Garthwaite PH (2005). Bayesian analysis of misclassified binary data from a matched case-control study with a validation sub-study. Statistics in Medicine, 24, 379-401. crossref(new window)

Rothman KJ, Greenland S, Lash TL (2008). Validity in epidemiologic studies. in 'modern epidemiology', eds lippincott williams and wilkins, Philadelphia, 128-47

Sepandi M, Akrami M, Tabatabaee H, et al (2014). Breast Cancer Risk Factors in Women Participating in a Breast Screening Program: a Study on 11,850 Iranian Females. Asian Pac J Cancer Prev, 15, 8499-502. crossref(new window)

Szatmari P, Jones MB (1999). Effects of misclassification on estimates of relative risk in family history studies. Genetic Epidemiology, 16, 368-81. crossref(new window)

Tehranifar P, Wu H-C, Shriver T, et al (2015). Validation of family cancer history data in high-risk families: the influence of cancer site, ethnicity, kinship degree, and multiple family reporters. American Journal of Epidemiology.

van Gelder MMHJ, Donders ART, Devine O, et al (2014a). Using bayesian models to assess the effects of under-reporting of cannabis use on the association with birth defects, national birth defects prevention study, 1997-2005. Paediatric and Perinatal Epidemiology, 28, 424-33. crossref(new window)

van Gelder MMHJ, Donders ART, Devine O, et al (2014b). Using bayesian models to assess the effects of under-reporting of cannabis use on the association with birth defects, national birth defects prevention study, 1997-2005. Paediatric and Perinatal Epidemiology, n/a-n/a.

Veisy A, Lotfinejad S, Salehi K, et al (2015). Risk of breast cancer in relation to reproductive factors in north-west of Iran, 2013-2014. Asian Pac J Cancer Prev, 16, 451-5. crossref(new window)

Zare N, Haem E, Lankarani KB, et al (2013). Breast cancer risk factors in a defined population: weighted logistic regression approach for rare events. J Breast Cancer, 16, 214-9. crossref(new window)