When you run testing for a patient, you get results or numbers. How do you interpret those numbers? You use reference ranges to help define normal versus abnormal results. This is why reference ranges are so important. The way reference ranges are established is even more important.
Have you ever wondered where these numbers actually come from? Why might the same test have different reference ranges at different laboratories? Does a result outside the reference range automatically mean something is wrong with the patient?
Reference ranges are more than just numbers printed beside a patient’s results. They are an important part of laboratory testing, helping healthcare providers interpret results and make informed decisions about patient care.
What Are Reference Ranges?
A reference range, also known as a reference interval, is a set of values used to help determine whether a patient’s laboratory result falls within an expected range. Reference intervals are typically established by collecting and analyzing samples from a group of individuals considered to be healthy. The results are then evaluated statistically to determine the range of values expected for that population. Most conventional reference intervals represent the central 95% of values from a selected reference population (ASCLS, 2019; Centra Diagnostics, n.d.).
What does that actually mean? It means that approximately 95% of healthy individuals in that population are expected to have results within the reference interval. The remaining 5% may have results outside the interval, even though they are healthy. Reference intervals only provide a starting point for interpreting results. They should always be considered alongside the patient’s clinical history, symptoms, and other laboratory findings (Centra Diagnostics, n.d.).
How Are Reference Ranges Established?
Reference intervals are not randomly selected. Establishing them involves several steps, including selecting an appropriate reference population, collecting and analyzing specimens, and using statistical methods to determine the expected distribution of results (Higgins, 2009).
Step 1: Selecting a Reference Population
The first step is selecting individuals who represent the population for which the reference interval will be used. These individuals are generally considered healthy based on predetermined inclusion and exclusion criteria (NIH/PMC, n.d.).
Age, sex, pregnancy status, and other physiological characteristics may influence the results. Depending on the analyte, separate reference intervals may be necessary for different patient populations. For example, think about hemoglobin. The expected values for a newborn differ from those for an adult. Using the same reference interval for both populations could lead to incorrect interpretation (Centra Diagnostics, n.d.). This is why selecting the appropriate reference population is such an important part of the process.
Step 2: Collecting and Testing Samples
Once the reference population has been selected, specimens are collected and analyzed. For the traditional nonparametric method, guidelines generally recommend collecting samples from at least 120 reference individuals to establish a reference interval. This sample size allows laboratories to estimate the central 95% of results and calculate confidence limits around the upper and lower reference limits (Higgins, 2009; NIH/PMC, n.d.).
Preanalytical variables must also be controlled. These include:
- Patient preparation, such as fasting, medications, and physical activity.
- Specimen collection conditions, including time of day, tube type, and tourniquet application.
- Specimen handling, such as centrifugation, storage, and transportation.
For example, cortisol concentrations naturally fluctuate throughout the day. If specimens are collected at inconsistent times, those differences could influence the distribution of results. Standardizing collection and testing conditions helps ensure that the resulting reference interval reflects the intended population rather than avoidable variations in specimen collection or handling.
Step 3: Using Statistics to Establish the Reference Interval
After the specimens have been analyzed, the laboratory uses statistical methods to determine the reference interval. One commonly recommended approach is the nonparametric method. With this approach, the laboratory arranges the results from lowest to highest and identifies the values corresponding to the 2.5th and 97.5th percentiles. These two values become the lower and upper reference limits (Higgins, 2009; NIH/PMC, n.d.).
Imagine you have laboratory results from 120 healthy individuals. After arranging the results from lowest to highest, you identify the values that represent the central 95% of the population. Approximately 2.5% of the values fall below the lower limit, and another 2.5% fall above the upper limit. The values between those limits form the reference interval. It is important to remember that this statistical process identifies what is typical for the selected population, not necessarily what is ideal for every patient’s health.
Establishing vs. Verifying Reference Intervals: What’s the Difference?
Not every laboratory establishes its own reference intervals. Establishing reference intervals requires considerable time, resources, and access to an appropriate reference population. Many laboratories adopt reference intervals provided by manufacturers or established through published studies. This does not mean laboratories should automatically accept those intervals without proper evaluation. This is where reference interval verification comes in.
Establishing a reference interval means generating the data needed to determine the limits. Verifying a reference interval means evaluating whether an existing interval is appropriate for the laboratory’s method and patient population.
According to the CLSI approach discussed by NIH, a laboratory can use a verification procedure involving 20 appropriately selected reference individuals. If no more than two of the 20 results fall outside the proposed reference interval, the interval may be considered acceptable under that procedure. If three or more results fall outside the interval, further investigation and additional data may be necessary. This is a more practical way to evaluate existing reference intervals without conducting a new study.
Why Do Reference Ranges Differ Between Laboratories?
Have you ever noticed that two laboratories may report slightly different reference intervals for the same test? This does not mean one laboratory is wrong. Reference intervals can vary for several reasons.
1. Testing methods and instrumentation
Different analyzers, reagents, and analytical methods may produce slightly different results. Therefore, a reference interval established using one method may not always be appropriate for another.
2. Patient populations
The population used to establish a reference interval matters. Age, sex, pregnancy, and other physiological characteristics may influence expected laboratory values.
3. Specimen type
Serum, plasma, and whole blood are not always interchangeable. Depending on the analyte, the specimen type can influence the measured result and the reference interval.
4. Preanalytical variables
Fasting status, physical activity, collection timing, and specimen handling can all influence laboratory results. A change in a patient’s laboratory result may reflect a true physiological change, but differences in testing methodology or specimen conditions should also be considered.
What Happens When Reference Intervals Are Not Appropriate?
Using an inappropriate reference interval can have significant consequences for patient care. A patient may have a result flagged as abnormal even though it is expected for their population. On the other hand, an inappropriate interval could potentially cause a clinically important result to go unrecognized.
Reference Intervals vs. Clinical Decision Limits
Another important distinction is that not every laboratory result should be interpreted using a conventional reference interval. Some tests rely on clinical decision limits instead. A reference interval is typically based on the distribution of values in a selected reference population, whereas a clinical decision limit is based on evidence connecting a particular result with disease risk, diagnosis, or clinical management (NIH/PMC, n.d.).
Cholesterol is a good example. The NIH explains that an older reference interval for total cholesterol in apparently healthy adult men extended to approximately 273 mg/dL. Research has demonstrated that cholesterol concentrations associated with increased cardiovascular risk can fall within the statistically established interval. As a result, clinical guidelines adopted decision thresholds based on cardiovascular risk rather than relying solely on the distribution of cholesterol values in healthy individuals (NIH/PMC, n.d.).
Just because a laboratory value is common within a population does not mean it represents optimal health. Other analytes for which clinical decision limits or guideline-based thresholds are particularly important include glucose, hemoglobin A1c, and neonatal bilirubin. For these tests, analytical accuracy becomes especially important because even relatively small measurement errors can affect how results are classified or interpreted.
Why Analytical Accuracy Matters
Laboratory professionals normally evaluate analytical performance through quality control and proficiency testing. There is an important difference between obtaining results that agree with those of other laboratories and obtaining accurate results. A laboratory may produce results that are consistent with other laboratories using the same method, yet all those results could share a similar bias. This is mainly concerning when results are interpreted using established clinical decision limits. Quality control, method validation, proficiency testing, and appropriate accuracy assessments all contribute to reliable patient results.
What Is the Laboratory Professional’s Role?
Laboratory professionals play an important role in ensuring that reference intervals are appropriate and that results are reported accurately. It is important that they do not simply accept the reference intervals supplied with an instrument or reagent package insert. Laboratories should evaluate the suitability of reference intervals during method implementation and when changes occur that could affect analytical results (ASCLS, 2019; NIH/PMC, n.d.).
Laboratory professionals can help support this process by:
- Verifying reference intervals when adopting new testing methods.
- Evaluating the effects of instrument or reagent changes on existing intervals.
- Recognizing preanalytical and analytical factors that may affect patient results.
- Ensuring appropriate intervals are assigned to relevant patient populations.
- Maintaining reliable quality control and analytical performance.
- Communicating with healthcare providers when laboratory results require additional clarification.
Even a properly established reference interval has limited value if the testing method does not produce reliable results.
Reference ranges play a major role in how results are interpreted. Understanding how reference intervals are established helps laboratory professionals recognize why ranges differ, why manufacturer-provided intervals should be evaluated, and why results must be interpreted within the appropriate clinical context.
A statistically normal result is not always clinically normal, and an abnormal result does not automatically indicate disease. The next time you review a laboratory result, take a moment to consider the reference interval beside it. Where did it come from? Is it appropriate for the patient and the testing method? And does it provide the right context for interpreting the result? In the clinical laboratory, producing an accurate number is important, but ensuring that number can be interpreted appropriately is just as important.
References
- American Society for Clinical Laboratory Science (ASCLS). Laboratory Reference Intervals: Information for Providers.
https://ascls.org/wp-content/uploads/2012/11/Brochure_Laboratory_Reference_Intervals_Providers_2019.pdf - Centra Diagnostics. Reference Ranges in Lab Results and Patient Care.
https://centradiagnostics.com/reference-ranges-lab-results-care/ - Higgins, C. Reference Intervals (2): Some Practical Considerations. Acute Care Testing.
https://acutecaretesting.org/en/articles/reference-intervals-2–some-practical-considerations - Reference Intervals and Clinical Decision Limits. National Institutes of Health, PubMed Central.
https://pmc.ncbi.nlm.nih.gov/articles/PMC4975204/