Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-12-03T00:13:57.586Z Has data issue: false hasContentIssue false
  • English
  • Français

Impact of Severity of Illness Bias and Control Group Misclassification Bias in Case-Control Studies of Antimicrobial-Resistant Organisms

Published online by Cambridge University Press:  21 June 2016

Anthony D. Harris ,
Yehuda Carmeli ,
Matthew H. Samore ,
Keith S. Kaye  and
Eli Perencevich
Anthony D. Harris*
Affiliation:
Department of Epidemiology and Preventive Medicine, University of Maryland, College Park, and the Veterans Affairs Maryland Health Care System, Baltimore, Maryland
Yehuda Carmeli
Affiliation:
Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
Matthew H. Samore
Affiliation:
University of Utah, Salt Lake City, Utah
Keith S. Kaye
Affiliation:
Duke University Medical Center, Durham, North Carolina
Eli Perencevich
Affiliation:
Department of Epidemiology and Preventive Medicine, University of Maryland, College Park, and the Veterans Affairs Maryland Health Care System, Baltimore, Maryland
*
Division of Healthcare Outcomes Research, Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, 100 Greene Street, Lower Level, Baltimore, MD 21201[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

Case-control studies often analyze risk factors for antibiotic resistance. Recently published articles have illustrated that randomly selected control-patients may be preferable to those with the susceptible phenotype of the organism. A possible methodologic problem with randomly selected control-patients is potential bias due to control group misclassification. This occurs if some control-patients did not have clinical cultures performed and thus might have been unidentified case-patients. If this bias exists, these studies might be expected to report lower odds ratios (ORs) because control-patients would be more like case-patients.

Objective:

To analyze potential biases that might arise due to control group misclassification and potentially larger selection biases that may be introduced if control-patients are required to have at least one clinical culture.

Patients:

One hundred twenty case-patients, 770 control-patients in group 1, and 510 control-patients in group 2.

Methods:

Two case-control studies. Case-patients had clinical cultures positive for imipenem-resistant Pseudomonas aeruginosa. The first group of control-patients were random. The second group of control-patients were identical to those in group 1 except being required to have at least one clinical culture.

Results:

Univariate analyses showed higher ORs for case-patients versus control-patients in group 1 (imipenem [OR, 12.5], piperacillin-tazobactam [OR, 3.7], and vancomycin [OR, 4.7]) as compared with case-patients versus control-patients in group 2 (imipenem [OR, 8.0], piperacillin-tazobactam [OR, 2.5], and vancomycin [OR, 3.0]).

Conclusion:

Requiring control-patients to have at least one clinical culture introduces a selection bias likely because it eliminates patients with less severe illness.

Type
Orginal Articles
Information
Infection Control & Hospital Epidemiology , Volume 26 , Issue 4 , April 2005 , pp. 342 - 345
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Carmeli, Y, Samore, MH, Huskins, C. The association between antecedent vancomycin treatment and hospital-acquired vancomycin-resistant enterococci: a meta-analysis. Arch Intern Med 1999;159:2461–2468.CrossRefGoogle ScholarPubMed
2.Harris, AD, Samore, MH, Carmeli, Y. Control group selection is an important but neglected issue in studies of antibiotic resistance. Ann Intern Med 2000;132:925.Google Scholar
3.Harris, AD, Karchmer, TB, Carmeli, Y, Samore, MH. Methodological principles of case-control studies that analyzed risk factors for antibiotic resistance: a systematic review. Clin Infect Dis 2001;32:1055–1061.Google Scholar
4.Harris, AD, Samore, MH, Lipsitch, M, Kaye, KS, Perencevich, E, Carmeli, Y. Control-group selection importance in studies of antimicrobial resistance: examples applied to Pseudomonas aeruginosa, enterococci, and Escherichia coli. Clin Infect Dis 2002;34:1558–1563.Google Scholar
5.Harris, AD, Smith, D, Johnson, JABradham, DD, Roghmann, MC. Risk factors for imipenem-resistant Pseudomonas aeruginosa among hospitalized patients. Clin Infect Dis 2002;34:340–345.Google Scholar
6.Deyo, RA, Cherkin, DC, Ciol, MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45:613–619.Google Scholar
7.Harris, AD, Perencevich, E, Roghmann, MC, Morris, G, Kaye, KS, Johnson, JA. Risk factors for piperacillin-tazobactam-resistant Pseudomonas aeruginosa among hospitalized patients. Antimicrob Agents Chemother 2002;46:854–858.Google Scholar
8.Kaye, KS, Harris, AD, Gold, H, Carmeli, Y. Risk factors for recovery of ampicillin-sulbactam-resistant Escherichia coli in hospitalized patients. Antimicrob Agents Chemother 2000;44:1004–1009.Google Scholar