Second Edition (NCCLS document CA2) is written for users of diagnostic laboratory tests. It offers a .. CLSI Laboratories (PA) HA3. Procedures for the Collection of Arterial Blood Specimens; Approved Standard—. CLSI CA3. November Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory; Approved Guideline, Third. For guidance on establishing or validating reference intervals, Dr. Horowitz recommends that a laboratory obtain a copy of CA3, which was.
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Reliable and accurate reference intervals RIs for dlsi analyses are an integral part of the process of correct interpretation of clinical laboratory test results. RIs given in laboratory reports have an important role in aiding the clinician in interpreting test results in reference to values for healthy populations. Multicentric RIs studies are the most important development in the area of RIs.
Confusion of RIs and clinical decision limits CDLs remains an issue and pediatric and geriatric age groups are a significant problem. For future studies of RIs, the genetic effect would seem to be the most challenging area.
The aim of the review is to present the current theory and practice of RIs, with special emphasis given to multicenter RIs studies, RIs studies for pediatric and geriatric age groups, clinical decision limits and partitioning by genetic effects on RIs. From tothe International Federation of Clinical Chemistry IFCC published a series of 6 papers, in which it was recommended that each laboratory follow defined procedures to produce its own reference values 3 – 8.
Although there were very important developments and implementations between the s and 9 – 12the CA3 guideline, published in by CLSI and IFCC constituted the most significant step in the development of RIs and is still in current use In the CA3 guideline, in order to perform a multicenter RI study, criteria need to be cclsi described with the topics i.
Interest has been renewed in the topic as a result of the following regulatory initiatives in the last two decades In the present-day era of evidence-based medicine, there is still a big gap between theory and practice with respect to the application of RIs as decision-making tools, despite the mandatory c28a-3 The C-RIDL recently published two papers including a protocol and comprehensive standard operating procedures SOPs for multicenter RI studies 18with indication of the utility of a panel of sera for the alignment of test results among laboratories in multicenter studies This problem can be overcome by gathering large populations of reference individuals Another point of discussion is cldi confusion which arises from RIs and clinical decision limits CDLs.
Transference and Validation of Reference Intervals | Clinical Chemistry
Reference values are calculated specific to health whereas CDLs indicate sensitivity to disease The aim of the review is to present the current theory and practice of RIs together with a detailed evaluation of the most recent multicenter studies, an assessment c28-x3 the RIs of c28a3 pediatric and geriatric age groups, which is still regarded as a problem in this area, a clarification of the confusion which arises from the use of CDLs and future possibilities based on partitioning by genetic information to generate RIs.
The classical cascade is defined from reference individuals, a reference sample group, reference values, reference distribution, reference limits and RIs. The reference individuals form f28-a3 reference sample group for measurement of the values from the reference population.
Through statistical analysis of the distribution of the obtained values, the reference limits are calculated. These limits then define the RI 3. Health is a relative condition lacking a universal definition.
The exclusion and partitioning criteria can be implemented appropriately through a well-designed questionnaire.
Exclusion criteria are features which prevent the individual from being included in the reference sample. clis
Transference and Validation of Reference Intervals
Although some criteria, such as alcohol, tobacco and some environmental factors, may be potential exclusion criteria, amounts of consumption of alcohol and tobacco can be recorded in detail on the sample questionnaire and the effects are evaluated statistically, primarily using multiple regression analysis MRA 18 c28-3, Cli informed consent from participants is needed from each reference individual who agrees to participate in the study.
The consent form should state clearly that laboratory personnel are allowed to obtain specimens, and to use the associated laboratory values and questionnaire information for the determination of RIs In the a priori sampling approach, exclusion criteria are applied before sampling collection and it is the more appropriate approach when the biology of an analyte is known.
In a posteriori sampling, the exclusion criteria are applied after the sampling. Both of these methods are known as direct sampling, which c28-q3 the primary recommendation of the IFCC. Ideally, RIs are determined on the basis of a healthy population using direct methods 4. However, indirect methods, which are also known as data mining, based on previous laboratory data can also be useful Various methods may be used for the selection of a group of healthy individuals from a general hospital population and reference values are calculated from hospital data using statistical methods, such as Bhattacharya analysis 24 and some modifications of the method 25 There is opposition to this approach from some, as there is insufficient knowledge of the subjects and reliance on statistical methods to exclude the unhealthy subjects as explained in CA3.
It has also been emphasised that as there is little control of the pre-analytical and analytical conditions, the indirect approach could be used for local situations or difficult groups of subjects such csli neonates, children or the elderly, or as a means to confirm the goodness of the selected RI Other researchers favour the indirect method as the results are clinically relevant and much simpler for an individual laboratory to implement than the time-consuming direct a priori method, which requires considerable data and c28-3a input 28 Pre-analytical and analytical aspects must be taken into consideration in the implementation of a RI study.
Generally, the pre-analytical considerations involve biological i. For reproducibility and standardization, it is essential that the pre-analytical aspects are accurately defined and described as the preanalytical c28-x3 is known to have the highest errors in the total test process Because of the importance of harmonizing pre-analytical phase of the total testing process, an effort has been made by the European Federation for Clinical Chemistry and Laboratory Medicine EFLM Working Group for Preanalytical Phase WG-PRE to support the worldwide harmonization of color coding for blood collection tube closures 31 Different commercial methods may be used in a trueness-based approach to the reference measurement system providing results traceable to the system and thus, comparable results can be produced in clinical laboratories.
When performing a RI study, the reference measurement systems and standard reference materials are of great importance to ensure traceability c28-a the test results in comparisons Calculation of RIs includes parametric and nonparametric calculation methods, detection of outliers, partitioning, and confidence intervals.
The lower reference limits are estimated as the 2. The reference values of many analytes do not display Gaussian distribution, so the parametric method can be applied after data transformation. The most suitable transformation method must be selected e. The nonparametric clxi of estimation does not assume the probability distribution of the observed reference values 7. Although the CA3 recommends the nonparametric calculation method, the RIs calculated by the parametric and nonparametric methods were compared in the recent IFCC, C-RIDL study which concluded that the results of the two methods are very close and parametric methods can also be used as a first choice Whichever method is used in the calculation of the RIs, detection and exclusion of the outliers are very important to obtain reliable RIs.
A simple but effective method for the detection of outliers is visual inspection of the data. However, this method is not very sensitive when there is more than one outlier.
The Horn using Tukey method is a more sophisticated method, which includes Box-Cox transformation of the data to obtain Gaussian distribution followed by identification of the outliers in interquartile ranges IQR: This method is an iterative approach for the derivation of multiple reference RIs simultaneously, when no exclusion of values has been made in the initial computation of the RIs.
Several statistical methodologies have been proposed to be able to make the extremely important decision cldi whether or not to separate different groups. The most widely-used partitioning method is that of Harris and Boyd, in which the means and standard deviations of the subgroups are considered as a separate different standard deviation that may produce different limits However, this method is only appropriate for analytes with a Gaussian distribution with subclasses, where the values are of similar size and standard deviation.
A similar method was proposed by Lahti et al.
Reference intervals: current status, recent developments and future considerations
More recently, Ichihara and Boyd recommended a partioning method on the basis of the magnitude of the standard deviations of test results named standard deviation ratio SDR An SDR greater than 0. Sensitivity of the population based-RIs can be increased and thereby, the usefulness of RIs is improved by stratification of age, gender, race, ethnicity and lifestyle. Stratification by age and gender is the minimum pre-requisite and other means include race, ethnicity, body mass index or nutritional habits The CI is a range of values including the true percentile e.
In the CA3 guideline, non-parametric CIs are given from the observed values corresponding to certain rank numbers from Reed et al. This method can provide the reference limits from a limited number of observations using only 20 subjects However, a robust method with such a small number of reference subjects e.
A small number of subjects can lead to uncertainty of calculated reference limits revealed by the width of its CIs. The RI is derived from each pseudosample and the process is repeated many times – yielding a distribution of lower and upper RIs If a clinical laboratory changes the method used or wishes to apply RIs established by another laboratory which has used a different method, transference of the RIs can be implemented, rather than collecting samples from reference individuals to establish a RI for the new method.
If the new method has similar imprecision and known interferences, uses the same or comparable standards or calibrators, and provides values that are acceptably comparable, the RIs can be transferred by method comparison based on linear regression analysis.
In addition, the question of transference becomes one of comparability of the reference population The CA3 guideline allows for subjective validation of a RI by laboratory assessment of population demographics and pre-analytical and analytical parameters.
Reference intervals: current status, recent developments and future considerations
This guideline recommends that each laboratory adopts existing RI values by performing an analysis to validate the transference of a RI reported by a manufacturer or other donor laboratory. If more than 2 of the 20 samples fall outside these limits, a second 20 reference specimens 20 clzi be obtained. If no more than 2 of the 20 samples fall out of the clwi of the existing RI, it may be adopted for use.
If three or more again fall outside these limits, the user should re-examine the analytical procedures used and consider possible differences cldi the biological characteristics of the two populations sampled Intra- and inter-individual biological variability of the subjects within the reference population may influence the determination of that RI.
Thus, the RI will not be sensitive to changes for that individual and, on average, for any individual and in this case, subject-based RIs are considered. This approach is quite simple and requires the collection of several samples from the same individual However, clis for statistical analysis are very different: In addition, they may be collected in a defined order and may not be mutually independent.
The results of measurements on these samples for a given analyte will produce a temporal cc28-a3, forming a baseline against which future results will be judged. A fundamental issue is the number of samples needed to define the baseline value. This depends upon the biological variability of the analyte, its analytical reproducibility and the applied mathematical procedures The requirement that each clinical laboratory produce its own RIs is practically impossible for most clinical laboratories.
The selection and recruitment of a sufficient number of reference subjects is difficult, time-consuming, and costly. Although some laboratories have performed local studies for their own use, there have also been multicenter studies performed with considerable numbers of subjects to establish useful RIs by laboratories in the Nordic countries 5051Spain 52Australia 5354Asia 5556 and Turkey As common standardization and traceability are crucial during production of reference values, each step of pre-analytical, analytical and statistical application follows a well-defined protocol.
A study was made of the measurement of three enzymes aspartate aminotransferase – AST, alanine aminotransferase – ALT and gamma-glutamyltransferase – GGT measured with commercial analytical systems according to the standard methods recommended by the IFCC With the implementation of a common protocol and SOPs, the utility of a panel of sera was indicated for the alignment of test results among laboratories in multicenter studies clso The two most recent papers published by the C-RIDL include this strategy for the alignment of test results for the derivation of RIs 18 The requirements for conducting the multicenter study, phase by phase, are described in a new protocol which recommends that a practically attainable target sample size from each country is set at a minimum ofwhich is more than double the previously recommended minimum in the CA3 ; male and female.
The other prerequsites of multicenter studies can be summarized as a priori selection of reference subjects i. This should ensure that country-specific RIs are obtained in a more reproducible manner. In addition to ethnic origins, other items were included in the questionnaire to obtain more quantitative information regarding alcohol consumption, physical activities, menstrual cycle, and medications to ascertain how these factors influence test values.
Overall, the procedure for standardization of test results is of the utmost importance, and all centers need to comply when dealing with standardized analytes.
The requirements of the central laboratory are also described in detail, including the method of cross-check testing between the central laboratory of each country and the local laboratories before the RIs can be applied In the protocol for multicenter studies 18cross-check testing is recommended to convert the RIs obtained from the multicenter study by the centralized assay to the values of each participating laboratory.
The linear structural relationship reduced major axis regression is used to convert the RIs. A cross comparison study with another laboratory is an approach to compare the laboratories participating in the multicenter study, using a panel of sera from healthy individuals, and recalibrating the results based on regression analysis, especially in cases where there are no standardized materials for harmonization of test results 1819 The steps for the scheme of a multicenter study when all the samples from healthy individuals are collected in the participating laboratories and sent to the central laboratory for analysis are summarised in Table 1.