Left truncation, susceptibility, and bias in occupational cohort studies

Epidemiology

Volumn 22, Issue 4, 2011, Pages 599-606

  Applebaum, Katie M ^a,b   Malloy, Elizabeth J ^c   Eisen, Ellen A ^b,d  

^a BOSTON UNIVERSITY SCHOOL OF PUBLIC HEALTH   (United States)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^c AMERICAN UNIVERSITY   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; COHORT ANALYSIS; DISEASE ASSOCIATION; DISEASE PREDISPOSITION; EMPLOYMENT STATUS; EPIDEMIOLOGICAL DATA; FOLLOW UP; HUMAN; INCIDENCE; MAJOR CLINICAL STUDY; MONTE CARLO METHOD; MORTALITY; OCCUPATIONAL EXPOSURE; PREVALENCE; PRIORITY JOURNAL; PROBABILITY; PROPORTIONAL HAZARDS MODEL; REPRODUCIBILITY;

BIAS (EPIDEMIOLOGY); COHORT STUDIES; EPIDEMIOLOGIC RESEARCH DESIGN; FOLLOW-UP STUDIES; HUMANS; MONTE CARLO METHOD; OCCUPATIONAL DISEASES; OCCUPATIONAL EXPOSURE; PROPORTIONAL HAZARDS MODELS;

EID: 80051545702     PISSN: 10443983     EISSN: 15315487     Source Type: Journal    
DOI: 10.1097/EDE.0b013e31821d0879     Document Type: Article

References (28)

1. Szklo M. Design and conduct of epidemiologic studies. Prev Med. 1987;16:142-149. (Pubitemid 17067791)
2. Brookmeyer R, Gail MH, Polk BF. The prevalent cohort study and the acquired immunodeficiency syndrome. Am J Epidemiol. 1987; 126:14-24. (Pubitemid 17117685)
3. Brookmeyer R, Gail MH. Biases in prevalent cohorts. Biometrics. 1987;43:739-749. (Pubitemid 18016761)
4. Cole SR, Li R, Anastos K, et al. Accounting for leadtime in cohort studies: evaluating when to initiate HIV therapies. Stat Med. 2004;23: 3351-3363. (Pubitemid 39462092)
5. Howards PP, Hertz-Picciotto I, Poole C. Conditions for bias from differential left truncation. Am J Epidemiol. 2007;165:444-452.
6. Hernàn MA, Hernandez-Diaz S, Werler MM, Mitchell AA. Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology. Am J Epidemiol. 2002;155:176-184. (Pubitemid 34072741)
7. Azzato EM, Greenberg D, Shah M, et al. Prevalent cases in observational studies of cancer survival: do they bias hazard ratio estimates? Br J Cancer. 2009;100:1806-1811.
8. Koskela RS, Jarvinen E, Kolari PJ. Effect of cohort definition and follow-up length on occupational mortality rates. Scand J Work Environ Health. 1984;10:311-316. (Pubitemid 15180799)
9. Weiss W. Heterogeneity in historical cohort studies: a source of bias in assessing lung cancer risk. J Occup Med. 1983;25:290-294. (Pubitemid 13097850)
10. Checkoway H, Pearce N, Kriebel D. Research Methods in Occupational Epidemiology. Monographs in Epidemiology and Biostatistics. 2nd ed. New York: Oxford University Press; 2004.
11. Applebaum KM, Malloy EJ, Eisen EA. Reducing healthy worker survivor bias by restricting date of hire in a cohort study of Vermont granite workers. Occup Environ Med. 2007;64:681-687. (Pubitemid 47488095)
12. Richardson D, Wing S, Steenland K, McKelvey W. Time-related aspects of the healthy worker survivor effect. Ann Epidemiol. 2004;14:633-639. (Pubitemid 39233623)
13. Steenland K, Stayner L. The importance of employment status in occupational cohort mortality studies. Epidemiology. 1991;2:418-421.
14. Delzell E, Monson RR. Mortality among rubber workers. Part IV: General mortality patterns. J Occup Med. 1981;23:850-856. (Pubitemid 12249264)
15. Gilbert ES. Some confounding factors in the study of mortality and occupational exposures. Am J Epidemiol. 1982;116:177-188. (Pubitemid 12087734)
16. Weiss W. Lung cancer due to chloromethyl ethers: bias in cohort definition. J Occup Med. 1989;31:102-105. (Pubitemid 19066847)
17. Stayner L, Smith R, Schnorr T, Lemen R, Thun M. Lung cancer. Ann Epidemiol. 1993;3:114-116.
18. Greenland S, Robins JM. Identifiability, exchangeability, and epidemiological confounding. Int J Epidemiol. 1986;15:413-419. (Pubitemid 17171893)
19. D'Agostino RB, Lee ML, Belanger AJ, Cupples LA, Anderson K, Kannel WB. Relation of pooled logistic regression to time dependent Cox regression analysis: the Framingham Heart Study. Stat Med. 1990; 9:1501-1515.
20. Khoury MJ, Adams MJ Jr, Flanders WD. An epidemiologic approach to ecogenetics. Am J Hum Genet. 1988;42:89-95. (Pubitemid 18081285)
21. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 3rd ed. Philadelphia: Wolters Kluwer Health/Lippincott Williams & Wilkins; 2008.
22. Kleinbaum DG, Klein M. Survival Analysis: a Self-Learning Text. Statistics for Biology and Health. 2nd ed. New York: Springer; 2005.
23. Keiding N. Survival and event history analysis. In: Andersen PK, Keiding N, eds. Wiley Reference Series in Biostatistics. Chichester, West Sussex, England, Hoboken, NJ: Wiley; 2006:173-178.
24. Klein JP, Moeschberger ML. Survival Analysis: Techniques for Censored and Truncated Data. Statistics for Biology and Health. 2nd ed. New York: Springer; 2003.
25. Brookmeyer R. Biased sampling of cohorts. In: Armitage P, Colton T, eds. Encyclopedia of Biostatistics. 2nd ed. Chichester, West Sussex, England;Hoboken, NJ: John Wiley; 2005:427-439.
26. Hernán MA. The hazards of hazard ratios. Epidemiology. 2010;21: 13-15.
27. Stayner L, Steenland K, Dosemeci M, Hertz-Picciotto I. Attenuation of exposure-response curves in occupational cohort studies at high exposure levels. Scand J Work Environ Health. 2003;29:317-324. (Pubitemid 37009863)
28. Robins J. A new approach to causal inference in mortality studies with a sustained exposure period -application to control of the healthy worker survivor effect. Math Mod. 1986;7:1393-1512.