Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Effect of Alcohol Consumption on Breast Cancer: Probabilistic Bias Analysis for Adjustment of Exposure Misclassification Bias and Confounders Publisher Pubmed



Pakzad R1, 2 ; Nedjat S3 ; Salehiniya H4 ; Mansournia N5 ; Etminan M6 ; Nazemipour M3 ; Pakzad I7 ; Mansournia MA3
Authors
Show Affiliations
Authors Affiliations
  1. 1. Department of Epidemiology, Faculty of Health, Ilam University of Medical Sciences, Ilam, Iran
  2. 2. Student Research Committee, Ilam University of Medical Sciences, Ilam, Iran
  3. 3. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, PO Box: 14155-6446, Tehran, Iran
  4. 4. Department of Epidemiology and Biostatistics, School of Health, Birjand University of Medical Sciences, South Khorasan, Iran
  5. 5. Department of Endocrinology, School of Medicine, AJA University of Medical Sciences, Tehran, Iran
  6. 6. Departments of Ophthalmology and Visual Sciences, Medicine and Pharmacology, University of British Columbia, Vancouver, Canada
  7. 7. Department of Microbiology, School of Medicine, Ilam University of Medical Sciences, Ilam, Iran

Source: BMC Medical Research Methodology Published:2023


Abstract

Purpose: This study was conducted to evaluate the effect of alcohol consumption on breast cancer, adjusting for alcohol consumption misclassification bias and confounders. Methods: This was a case-control study of 932 women with breast cancer and 1000 healthy control. Using probabilistic bias analysis method, the association between alcohol consumption and breast cancer was adjusted for the misclassification bias of alcohol consumption as well as a minimally sufficient set of adjustment of confounders derived from a causal directed acyclic graph. Population attributable fraction was estimated using the Miettinen’s Formula. Results: Based on the conventional logistic regression model, the odds ratio estimate between alcohol consumption and breast cancer was 1.05 (95% CI: 0.57, 1.91). However, the adjusted estimates of odds ratio based on the probabilistic bias analysis ranged from 1.82 to 2.29 for non-differential and from 1.93 to 5.67 for differential misclassification. Population attributable fraction ranged from 1.51 to 2.57% using non-differential bias analysis and 1.54–3.56% based on differential bias analysis. Conclusion: A marked measurement error was in self-reported alcohol consumption so after correcting misclassification bias, no evidence against independence between alcohol consumption and breast cancer changed to a substantial positive association. © 2023, The Author(s).
Other Related Docs
12. Interaction Contrasts and Collider Bias, American Journal of Epidemiology (2022)
17. Time-Fixed Vs Time-Varying Causal Diagrams for Immortal Time Bias, International Journal of Epidemiology (2022)
19. P-Value, Compatibility, and S-Value, Global Epidemiology (2022)
26. Causal Diagrams for Immortal Time Bias, International Journal of Epidemiology (2021)
27. Case–Control Matching on Confounders Revisited, European Journal of Epidemiology (2023)
29. Using Causal Diagrams for Biomedical Research, Annals of Emergency Medicine (2023)
32. Causal Methods for Observational Research: A Primer, Archives of Iranian Medicine (2018)