| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Letters |
1 Sullivan Nicolaides Pathology 134 Whitmore St. Taringa Qld 4068, Australia
aAuthor for correspondence.
To the Editor:
Last year, Ockene et al. (1) published a report in this journal that made the claim that high-sensitivity C-reactive protein (hs-CRP) has a degree of measurement stability that is similar to that of total cholesterol and that this provides further evidence of the potential clinical utility of hs-CRP screening as a novel tool for vascular risk prediction.
The key evidence that Ockene et al. (1) present to justify their claim is a histogram showing an almost identical agreement in terms of group classification between first and second measurements for hs-CRP and total cholesterol. This apparent agreement is spurious and is attributable to the way in which Ockene et al. partitioned the hs-CRP data. Although the total cholesterol data in the histogram are divided into quartiles, the hs-CRP data are partitioned into arbitrary intervals that contain 
15%, 20%, 30%, and 35%, respectively, of the sample.
Ockene et al. (1) provide two graphs showing the data for all 113 patients for serial cholesterol and CRP values ranked by mean concentration. These values are different for the two analytes. For cholesterol, the average intraindividual variation is 18.2%, and the intraindividual variation is roughly constant across all the range of data. For CRP, the average intraindividual variation is higher, at 44.2%. It is lowest at low CRP concentrations and then increases as the mean CRP concentration increases.
Ockene et al. (1) also provide graphs showing the distributions of the total cholesterol and hs-CRP results. As expected, the total cholesterol distribution is approximately gaussian and the hs-CRP distribution is skewed. A result of the skewed distribution of CRP concentrations is that even if true quartiles had been used, the interquartile spacing would increase markedly as the mean CRP concentration increased. The arbitrary intergroup spacings used by Ockene et al. amplify this effect. The third group concentration range is twice as wide, and the fourth group concentration range is 16 times as wide as each of the first two groups. The group cutoffs used by Ockene et al. also allow the upper 65% of the study participants, who among them encompass the majority of the intraindividual variation in hs-CRP, to fall within these two wider intervals. It is readily apparent that the probability that a second or subsequent CRP value will fall outside the original group is lower if the original value was in the wide third or fourth group. The net result is a bias toward reducing misclassification in the hs-CRP data.
It might be argued that it is reasonable to use these particular CRP intergroup cutoffs because they are based on risk. However, inspection of the reference provided by the authors shows that the cutoffs used are apparently based on cutoffs that divided the all-male control group of a previous case-control study into quartiles (2). Because the selection criteria for the control group in that study (2) and the experimental group in the study by Ockene et al. (1) are clearly different, use of these cutoff values cannot be justified.
Even if the hs-CRP data and the total cholesterol data had been divided into true quartiles before comparison, it could be argued that such a comparison is inappropriate because of the differences in both the sample distributions of values and the distributions of the intraindividual variation between the two analytes. Basing the comparison on arbitrary division of the hs-CRP data into unequal groups further invalidates the conclusions drawn from the study.
Total cholesterol and hs-CRP are not equivalent in terms of clinical utility for predicting cardiovascular risk in individual patients. A recent study (3) has demonstrated that hs-CRP assays have limited clinical utility in this situation because of the unacceptably large intraindividual variation in values.
References
R1 Department of Medicine Divisions of Cardiovascular Medicine and
R2
Preventive and Behavioral Medicine University of Massachusetts Medical School 55 Lake Ave. North Worcester, MA 01655
R3
Department of Epidemiology and Biostatistics University of South Carolina School of Public Health Columbia, SC 29208
R4
Department of Laboratory Medicine Children’s Hospital Harvard Medical School 300 Longwood Ave. Boston, MA 02115
R5
Division of Preventive Medicine Harvard Medical School Brigham and Women’s Hospital 900 Commonwealth Ave. East Boston, MA 02215
R6
Department of Biostatistics and Epidemiology School of Public Health and Health Sciences University of Massachusetts Arnold House Box 30430 Amherst, MA 01003
aAuthor for correspondence.
To the Editor:
Campbell et al. argue that our report (1) describing a degree of measurement stability for high-sensitivity C-reactive protein (hs-CRP) that is similar to that of total cholesterol draws an unjustifiable conclusion. They argue that our histogram showing agreements of group classification between first and second measurements for hs-CRP and total cholesterol is spurious because the cholesterol data were divided into quartiles whereas the hs-CRP data were divided into arbitrary intervals based on clinical utility. We did this because it seemed appropriate to us to use clinical utility as the driving factor for a clinically useful test, but we appreciate the opportunity to describe additional analyses that space constraints prevented us from presenting in the original report. We repeated the analysis, dividing CRP into four equal quartiles. This produced an overall agreement of 59.3% compared with 62.8% in our original analysis, with a 
statistic of 0.452 (95% confidence interval, 0.34–0.56) compared with 0.479 (0.39–0.60) for the original.
Campbell et al. also note that the skewed distribution of CRP concentrations leads to the higher quartiles being much wider than the lower quartiles, and from this they conclude that a second or subsequent CRP value is less likely to fall outside of the original group if its first value was in the third or fourth quartile, as these quartiles encompass a greater range. This argument, however, is not logical, for as Campbell et al. themselves note, the average intraindividual variation for cholesterol is 18.2% and is relatively constant over the range of values, whereas intraindividual variation is 44.2% for CRP with variation much higher at higher concentrations. Thus the wider range of values in the higher quartiles is proportional to the greater variation at these concentrations and thus would not produce a lower probability that a subsequent CRP value would fall outside of the original group. As noted in Table 2 of our original report, the use of log hs-CRP reduces variance to 21.7%, a value very comparable to the 18.2% for total cholesterol, but the quartile ranking is the same for the log-transformed value as for the untransformed variable because the log is a monotonic transformation.
CRP may reflect and respond strongly to acute inflammatory insult, including common viral infections, whereas cholesterol will not; to the extent that CRP concentrations are measured after such insults, repeatability will be reduced, and the clinician needs to take care to avoid such sources of variation.
Highly skewed analytes are not uncommon in clinical practice. Plasma concentrations of triglycerides are metabolically and pathophysiologically important, and their measurement is of value, despite a nongaussian distribution and considerable intraindividual biological variability. We believe that the use of cutpoints related to clinical utility is justifiable and produces levels of classification agreement that are little different from other possible choices.
Acknowledgments
Paul Ridker is listed as an inventor on patents, filed by Brigham and Womens Hospital, that relate to inflammatory biomarkers and cardiovascular disease.
References
The following articles in journals at HighWire Press have cited this article:
|
|
 |
|
  L. W. Cho, V. Jayagopal, E. S. Kilpatrick, and S. L. Atkin The Biological Variation of C-Reactive Protein in Polycystic Ovarian Syndrome Clin. Chem., October 1, 2005; 51(10): 1905 - 1907. [Full Text] [PDF]
|
|
|
|
|
|
T. B. Ledue and N. Rifai Preanalytic and Analytic Sources of Variations in C-reactive Protein Measurement: Implications for Cardiovascular Disease Risk Assessment Clin. Chem., August 1, 2003; 49(8): 1258 - 1271. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
