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Median differences or actual differences?
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Clinica Chimica Acta 391 (2008) 126 www.elsevier.com/locate/clinchim
Letter to the Editor
Median differences or actual differences?
Kost GJ et al. advocate the use of locally smoothed median absolute differences to evaluate glucose method comparison data [1]. Although we share their goal regarding the need for methodological accuracy during tight glycemic control (TGC) protocols, we would like to point out a potential drawback of this statistical method. The authors state that the smoothed curves in Fig. 2 were generated using split-sample results of 613 arterial blood gas samples from critical care patients. It is highly probable that these 613 residual samples were not homogeneous — and that, in addition to glucose, they represent a wide range of hematocrit, oxygen tension, pH, and perhaps even sample temperature. If this was the case, the smoothed curves are influenced by sample artifact as well as by the methods. For example, a rising trend line might be indicative of several low hematocrit samples (high biased results resulting from low hematocrit are indicated by Table 3). Therefore, the smoothed curves may not be representative of method performance but rather a compilation of several confounding variables. The authors also fail to support the stringent 5-mg/dL-(0.28 mmol/L)-error tolerance limit with any medical evidence. We prefer Fig. 1 (bias plots) for illustrating actual differences between glucose methods. International standard organizations agree — and advocate bias plots because they are simple to understand, the calculations are straightforward, and because
0009-8981/$ - see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.cca.2008.02.007
the statistical assumptions are minimal [2]. Bias plots can be easily adapted to TGC protocols by magnifying the x-axis range [e.g. from 80 to 110 mg/dL (4.4 to 6.1 mmol/L)] to better visualize the actual bias and imprecision of the method over a clinically relevant range. References [1] Kost GJ, Tran NK, Abad VJ, Louie RF. Evaluation of point-of-care testing accuracy using locally-smoothed median absolute difference curves. Clin Chim Acta 2008;389:31–9. [2] ISO 15197 In vitro diagnostic test systems — Requirements for bloodglucose monitoring systems for self-testing in managing diabetes mellitus. First edition dated 2003-05-01. ISO 15197:2003(E) International Standards Organization, Geneva, Switzerland.
John J. Mahoney Department of Clinical Affairs, LifeScan, Inc., United States E-mail address: [email protected]. Corresponding author. LifeScan, Inc. 1000 Gibraltar Drive, M/S 3I, Milpitas, 95035-6312 CA, United States. Tel.: +1 408 956 4348. John M. Ellison Department of Clinical Research, LifeScan, Inc., United States
23 January 2008
Clinica Chimica Acta 391 (2008) 126 www.elsevier.com/locate/clinchim
Letter to the Editor
Median differences or actual differences?
Kost GJ et al. advocate the use of locally smoothed median absolute differences to evaluate glucose method comparison data [1]. Although we share their goal regarding the need for methodological accuracy during tight glycemic control (TGC) protocols, we would like to point out a potential drawback of this statistical method. The authors state that the smoothed curves in Fig. 2 were generated using split-sample results of 613 arterial blood gas samples from critical care patients. It is highly probable that these 613 residual samples were not homogeneous — and that, in addition to glucose, they represent a wide range of hematocrit, oxygen tension, pH, and perhaps even sample temperature. If this was the case, the smoothed curves are influenced by sample artifact as well as by the methods. For example, a rising trend line might be indicative of several low hematocrit samples (high biased results resulting from low hematocrit are indicated by Table 3). Therefore, the smoothed curves may not be representative of method performance but rather a compilation of several confounding variables. The authors also fail to support the stringent 5-mg/dL-(0.28 mmol/L)-error tolerance limit with any medical evidence. We prefer Fig. 1 (bias plots) for illustrating actual differences between glucose methods. International standard organizations agree — and advocate bias plots because they are simple to understand, the calculations are straightforward, and because
0009-8981/$ - see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.cca.2008.02.007
the statistical assumptions are minimal [2]. Bias plots can be easily adapted to TGC protocols by magnifying the x-axis range [e.g. from 80 to 110 mg/dL (4.4 to 6.1 mmol/L)] to better visualize the actual bias and imprecision of the method over a clinically relevant range. References [1] Kost GJ, Tran NK, Abad VJ, Louie RF. Evaluation of point-of-care testing accuracy using locally-smoothed median absolute difference curves. Clin Chim Acta 2008;389:31–9. [2] ISO 15197 In vitro diagnostic test systems — Requirements for bloodglucose monitoring systems for self-testing in managing diabetes mellitus. First edition dated 2003-05-01. ISO 15197:2003(E) International Standards Organization, Geneva, Switzerland.
John J. Mahoney Department of Clinical Affairs, LifeScan, Inc., United States E-mail address: [email protected]. Corresponding author. LifeScan, Inc. 1000 Gibraltar Drive, M/S 3I, Milpitas, 95035-6312 CA, United States. Tel.: +1 408 956 4348. John M. Ellison Department of Clinical Research, LifeScan, Inc., United States
23 January 2008