Adeli K: Special Issue on Laboratory Reference Intervals. eJIFCC. September 2008. http://www.ifcc.org/PDF/190201200801.pdf.
C28A3: Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory: Approved Guideline, 3rd ed. http://www.clsi.org/source/orders.
GUIDELINES FOR USE OF DATA IN A REFERENCE RANGE STUDY
The College of American Pathologists provides guidelines for the adoption of reference ranges used in hospitals and commercial clinical laboratories. It recognizes the enormous task of establishing a laboratory’s own reference ranges, and recommends alternatives to the process. A laboratory may acquire reference ranges by:
1. Conducting its own study to evaluate a statistically significant number of “healthy” volunteers. It is a monumental task for a laboratory to develop its own pediatric reference ranges, because parental consent and procedural approval by review boards need to be addressed. The numerous age categories to be evaluated also add to the complexity and size of the study.
2. Adopting ranges established by the manufacturer of a particular analytical instrument. The laboratory must validate the data by analyzing a sample of 20 “reference” subjects (patients representing that specific population) to confirm that the adopted range is truly representative of that group.
3. Using reference data in the general medical literature and conferring with physicians to make sure the data agree with their clinical experience. A validation study is also recommended.
4. Analyzing hospital patient data. Laboratory test results from hospital patients have been used to compute reference ranges provided they fulfill stated clinical criteria. Patient records need to indicate that the patient’s specific medical condition does not influence the analyte whose reference range is being determined. For example, a child undergoing surgery for bone fracture repair is expected to have normal electrolytes and thyroid function, whereas a child examined for precocious puberty should not be included in a reference range study for luteinizing hormone. In the REALAB Project, Grossi et al chose the “inclusion criterion,” whereby tests that have a single laboratory measurement were used; justification was based on the fact that persons with repeated testing had a higher probability of being diseased and their results should be excluded from the study.
Statistically, the sample size of a hospital patient study should be considerably larger than that of a healthy group. A study from a healthy population may require 20 subjects to be statistically significant, whereas a hospital population should evaluate a minimum of 120 patients. At Children’s Hospital, Colorado, the free thyroxine reference range was recently established using 1480 clinic and hospital patient results in this manner.
Biological Variation Database Reference List: http://www.westgard.com/biological-variation-database-reference-list.htm.
College of American Pathologists publication: http://www.cap.org/apps/docs/laboratory_accreditation/sample_checklist.pdf.
Grossi E et al: The REALAB Project: a new method for the formulation of reference intervals based on current data. Clin Chem 2005;51:1232 [PMID: 15919879].
Schnabl K, Chan MK, Gong Y, Adeli K: Closing the gap on paediatric reference intervals: the CALIPER initiative. Clin Biochem Rev 2008 Aug;29(3):89–96 [PMID: 19107221].
STATISTICAL COMPUTATION OF REFERENCE INTERVALS
The establishment of reference intervals is based on a statistical distribution of test results obtained from a representative population. The CLSI recommendation for data collection and statistical analysis provides guidelines for managing the data. For clinicians, it is not important that they can reproduce the calculation. It is far more critical to understand the benefits and restrictions provided by the described statistical approaches and to evaluate patient results with these limitations in mind.
In reviewing the statistics, 95% of all results will be inherently included in the reference range. Note that 5% of that population will have “abnormal” results, when in fact they are “healthy” and an integral part of the reference group study. Similarly, an equivalent 5% of the “ill” population will have laboratory results within the reference range. These are inherent features of the statistical computation. Taking that analysis one step further, the probability of a healthy patient having a test result within a calculated reference range is
P = .95
When multiple tests or panels of tests are used, the combined probability of all the test results falling in their respective reference ranges drops dramatically. For example, the probability of all results from 10 tests in the complete metabolic panel being in the reference range is
P = (.95)10 = .60
Therefore, about one-third of healthy patients will have one test result in the panel that is outside the reference range.
A. Parametric Method of Computation
The parametric method of establishing reference intervals is simple, though not always representative, since it is based on the assumption that the data have a Gaussian distribution. A mean (x) and standard deviation (s) are calculated; test results of 95% of that specific population will fall within the mean ±1.96s, as shown in Figure 46–1.
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