Estimating Reference Intervals

Gary L. Horowitz
2010 American Journal of Clinical Pathology  
As indicated in the thought-provoking article in this issue of the Journal by Katayev and colleagues, 1 there are few things more important than the reference intervals we report along with our laboratory measurements. Unfortunately, we laboratory professionals give them far too little attention, adopting manufacturers' recommended intervals, often without even verifying them ourselves and, rarely, if ever, establishing our own values. Thus, the article "Establishing Reference Intervals for
more » ... e Intervals for Clinical Laboratory Test Results: Is There a Better Way?" is certain to attract much attention. Katayev and colleagues 1 make several assertions that bear comment. They claim that there is no clear guideline as to which technique to use, but the recommendations of the International Federation of Clinical Chemistry and Laboratory Medicine 2 and the CLSI 3 are quite clear. If one collects samples carefully from 120 vetted healthy people, then the technique of choice is nonparametric analysis. The reason for this is that the nonparametric technique requires no knowledge of, and makes no assumptions about, the nature of the data distribution. In other words, the reference interval values obtained are valid no matter what the underlying distribution is. If one has fewer samples, again from carefully screened, apparently healthy people, one can use a parametric technique with as few as 40 points, so long as the original data (or some transformed version of the data) exhibit a gaussian distribution. And with even fewer than 40 data points, one can use robust techniques to get an estimate of the reference interval. 3,4 Notwithstanding the assertions by Katayev and colleagues, 1 the reference intervals obtained from properly collected and analyzed data do not vary depending on the technique used. 3 Katayev and colleagues 1 also make the point that it becomes prohibitively difficult to collect sufficient data for all the potential partitions for which one might want reference intervals. They mention specifically sex and age (eg, deciles), but one might also include others (eg, fasting and race or ancestry). In this regard, it is particularly interesting that Katayev and colleagues 1 did not specifically mention differences (or lack thereof) for any partitions, with the exception of sex for hemoglobin and creatinine. In his original article, Hoffman 5 demonstrated the use of his technique with "just" 500 points. Clearly, Katayev and colleagues 1 had more than enough data to look at every analyte by sex and by age. One wonders, for example, whether there was any effect of sex and age on calcium or on thyroid-stimulating hormone (TSH). The fact that something is difficult to do does not negate the importance, or usefulness, of doing it. As a particularly good example, a group in the Netherlands recently did a superb reference interval study. 6 By collecting data for 1,444 people and using the recommended nonparametric method of analysis, they determined that creatine kinase reference intervals varied tremendously not only by sex but also by race/ancestry as well. Specifically, the 97.5th percentile for women varied from 201 to 313 to 414 IU/L for "white Europeans, South Asians, and blacks," respectively; for men, the corresponding values were 322, 641, and 801 IU/L. By using the manufacturer's reference intervals (defined as a single partition), the authors showed that the proportion of healthy women whose values were "abnormal" was 8% for white Europeans, 16% for South Asians, and 42% for blacks; for men, the corresponding values were 17%, 32%, and 62%.
doi:10.1309/ajcpq4n7brzqvhal pmid:20093225 fatcat:5l2fequt3jd5dp2xsyalvqzrey