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Antimicrobial Agents and Chemotherapy, January 2006, p. 62-67, Vol. 50, No. 1
0066-4804/06/$08.00+0     doi:10.1128/AAC.50.1.62-67.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.

Comparison of Censored Regression and Standard Regression Analyses for Modeling Relationships between Antimicrobial Susceptibility and Patient- and Institution-Specific Variables

Jeffrey P. Hammel,^1, Sujata M. Bhavnani,^1,2* Ronald N. Jones,^3,4 Alan Forrest,² and Paul G. Ambrose^1,2,

Cognigen Corporation, Buffalo, New York,¹ School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York,² The JONES Group/JMI Laboratories, North Liberty, Iowa,³ Tuft's University School of Medicine, Boston, Massachusetts⁴

Received 28 July 2004/ Returned for modification 2 January 2005/ Accepted 26 September 2005

In order to identify patients likely to be infected with resistant bacterial pathogens, analytic methods such as standard regression (SR) may be applied to surveillance data to determine patient- and institution-specific factors predictive of an increased MIC. However, the censored nature of MIC data (e.g., MIC 0.5 mg/liter or MIC > 8 mg/liter) imposes certain limitations on the use of SR. In order to investigate the nature of these limitations, simulations were performed to compare a regression tailored for censored data (censored regression [CR]) and one tailored for an SR. By using a model relating piperacillin-tazobactam MICs against Enterobacter spp. to patient age and hospital bed capacity, 200 simulations of 500 isolates were performed. Various MIC censoring patterns were imposed by using 26 left- or right-censored (L,R) pairs (i.e., MICs 2 mg/liter^L [2^L] or MICs > 2 mg/liter^R [2^R], respectively). Data were fit by CR and SR for which censored MICs were either (i) excluded, (ii) replaced by 2^L or 2^R, or (iii) replaced by 2^{L – 1} or 2^{R + 1}. Total censoring for the 26 pairs ranged from 7 to 86%. By CR, deviations of average parameter estimates from the true parameter values were <0.10 log₂ (mg/liter) for all parameters for each of the 26 pairs. By SR, these deviations were >0.10 log₂ (mg/liter) for at least 18 of the 26 pairs for all but one parameter. Two-standard-error confidence intervals for individual parameters contained as little as 0% of cases for all SR approaches but 91.5% of cases for the CR approach. When censored MIC data are modeled, CR may reduce or eliminate biased parameter estimates obtained by SR.

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* Corresponding author. Present address: Institute for Clinical Pharmacodynamics, Ordway Research Institute, 150 New Scotland Avenue, Albany, NY 12208 Phone: (518) 641-6473. Fax: (518) 641-6304. E-mail: SBhavnani-ICPD{at}OrdwayResearch.org.

Present address: Collaborative Biostatistics Center, Cleveland Clinic Foundation, Cleveland, OH 44195.

Present address: Institute for Clinical Pharmacodynamics, Ordway Research Institute, Albany, NY 12208.

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Antimicrobial Agents and Chemotherapy, January 2006, p. 62-67, Vol. 50, No. 1
0066-4804/06/$08.00+0     doi:10.1128/AAC.50.1.62-67.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.