A plea for intra-laboratory reference limits. Part 2. A bimodal retrospective concept for determining reference limits from intra-laboratory databases demonstrated by catalytic activity concentrations of enzymes

The theory of reference values: an unfinished symphony

The history of the theory of reference values can be written as an unfinished symphony. The first movement, allegro con fuoco, played from 1960 to 1980: a mix of themes devoted to the study of biological variability (intra-, inter-individual, short- and long-term), preanalytical conditions, standardization of analytical methods, quality control, statistical tools for deriving reference limits, all of them complex variations developed on a central melody: the new concept of reference values that would replace the notion of normality whose definition was unclear. Additional contributions (multivariate reference values, use of reference limits from broad sets of patient data, drug interferences) conclude the movement on the variability of laboratory tests. The second movement, adagio, from 1980 to 2000, slowly develops and implements initial works. International and national recommendations were published by the IFCC-LM (International Federation of Clinical Chemistry and Laboratory Medicine) and scientific societies [French (SFBC), Spanish (SEQC), Scandinavian societies…]. Reference values are now topics of many textbooks and of several congresses, workshops, and round tables that are organized all over the world. Nowadays, reference values are part of current practice in all clinical laboratories, but not without difficulties, particularly for some laboratories to produce their own reference values and the unsuitability of the concept with respect to new technologies such as HPLC, GCMS, and PCR assays. Clinicians through consensus groups and practice guidelines have introduced their own tools, the decision limits, likelihood ratios and Reference Change Value (RCV), creating confusion among laboratorians and clinicians in substituting reference values and decision limits in laboratory reports. The rapid development of personalized medicine will eventually call for the use of individual reference values. The beginning of the second millennium is played allegro ma non-troppo from 2000 to 2012: the theory of reference values is back into fashion. The need to revise the concept is emerging. The manufacturers make a friendly pressure to facilitate the integration of Reference Intervals (RIs) in their technical documentation. Laboratorians are anxiously awaiting the solutions for what to do. The IFCC-LM creates Reference Intervals and Decision Limits Committee (C-RIDL) in 2005. Simultaneously, a joint working group IFCC-CLSI is created on the same topic. In 2008 the initial recommendations of IFCC-LM are revised and new guidelines are published by the Clinical and Laboratory Standards Institute (CLSI C28-A3). Fundamentals of the theory of reference values are not changed, but new avenues are explored: RIs transference, multicenter reference intervals, and a robust method for deriving RIs from small number of subjects. Concomitantly, other statistical methods are published such as bootstraps calculation and partitioning procedures. An alternative to recruiting healthy subjects proposes the use of biobanks conditional to the availability of controlled preanalytical conditions and of bioclinical data. The scope is also widening to include veterinary biology! During the early 2000s, several groups proposed the concept of 'Universal RIs' or 'Global RIs'. Still controversial, their applications await further investigations. The fourth movement, finale: beyond the methodological issues (statistical and analytical essentially), important questions remain unanswered. Do RIs intervene appropriately in medical decision-making? Are RIs really useful to the clinicians? Are evidence-based decision limits more appropriate? It should be appreciated that many laboratory tests represent a continuum that weakens the relevance of RIs. In addition, the boundaries between healthy and pathological states are shady areas influenced by many biological factors. In such a case the use of a single threshold is questionable. Wherever it will apply, individual reference values and reference change values have their place. A variation on an old theme! It is strange that in the period of personalized medicine (that is more stratified medicine), the concept of reference values which is based on stratification of homogeneous subgroups of healthy people could not be discussed and developed in conjunction with the stratification of sick patients. That is our message for the celebration of the 50th anniversary of Clinical Chemistry and Laboratory Medicine. Prospects are broad, enthusiasm is not lacking: much remains to be done, good luck for the new generations!

The Heritability of HbA1c and Fasting Blood Glucose in Different Measurement Settings

In an extended twin study we estimated the heritability of fasting HbA1c and blood glucose levels. Blood glucose was assessed in different settings (at home and in the clinic). We tested whether the genetic factors influencing fasting blood glucose levels overlapped with those influencing HbA1c and whether the same genetic factors were expressed across different settings. Fasting blood glucose was measured at home and during two visits to the clinic in 77 healthy families with same-sex twins and siblings, aged 20 to 45 years. HbA1c was measured during the first clinic visit. A 4-variate genetic structural equation model was used that estimated the heritability of each trait and the genetic correlations among traits. Heritability explained 75% of the variance in HbA1c. The heritability of fasting blood glucose was estimated at 66% at home and lower in the clinic (57% and 38%). Fasting blood glucose levels were significantly correlated across settings (0.34 <r< 0.54), mostly due to a common set of genes that explained between 53% and 95% of these correlations. Correlations between HbA1c and fasting blood glucoses were low (0.11 <r< 0.23) and genetic factors influencing HbA1c and fasting glucose were uncorrelated. These results suggest that in healthy adults the genes influencing HbA1c and fasting blood glucose reflect different aspects of the glucose metabolism. As a consequence these two glycemic parameters can not be used interchangeably in diagnostic procedures or in studies attempting to find genes for diabetes. Both contribute unique (genetic) information.

Verifying reference intervals for coagulation tests by using stored data

OBJECTIVE

The purpose of the study was to verify the reference intervals for prothrombin time (PT) and activated partial thromboplastin time (APTT), using stored data of ambulatory pre-op subjects with exclusion of certain clinics, according to age and sex.

MATERIALS AND METHODS

Results of test requests (13,600 PT and 14,083 APTT) of subjects aged 15?80 made from outpatient clinics of surgical departments before surgical interventions in 2008 were retrieved from the electronic medical record. Thromborel S and Actin (Dade Behring, Germany) were used on the Sysmex® CA-1500 coagulation analyzer. Extreme values were determined by using Horn's algorithm after Box-Cox transformation, and the upper and lower reference limits were determined as the 2.5th and 97.5th percentiles of the cleaned data.

RESULTS

The values outside the interval of PT data 10.5-17.0 seconds and the interval of APTT data 20.6-35.8 seconds were excluded from the analysis. There were significant differences among age subsets of PT measurements ( p < 0.0001) and of APTT measurements ( p < 0.0001). Accordingly, the data were tested for gender differences and a significant difference was found in PT ( p = 0.002). APPT results did not differ statistically between men and women.

CONCLUSION

Although we found values different from the limits stated in the kit insert, it would be better to confirm our findings with the direct method, especially in APTT for patients under the age of 40 and over the age of 59, and also for sex differences in PT.

Indirect reference intervals of plasma and serum thyrotropin (TSH) concentrations from intra-laboratory data bases from several German and Italian medical centres

BACKGROUND

The dogma of establishing intra-laboratory reference limits (RLs) and their periodic review cannot be fulfilled by most laboratories due to the expenses involved. Thus, most laboratories adopt external sources for their RLs, often neglecting the problems of transferability. This is particularly problematic for analytes with a large diversity of existing RLs, as for example thyrotropin (TSH). Several attempts were taken to derive RLs from the large data pools stored in modern laboratory information systems. These attempts were further developed to a more sophisticated indirect procedure. The new approach can be considered a combined concept because it pre-excludes some subjects by direct criteria a-posterior. In the current study, the applicability of the new concept for modern protein bindings assays was examined for estimating RLs of serum and plasma TSH with data sets from several German and Italian laboratories.

METHODS

A smoothed kernel density function was estimated for the distribution of the total mixed data of the sample group (combined data of non-diseased and diseased subjects). It was assumed that the "central" part of the distribution of all data represents the non-diseased ("healthy") population. The central part was defined by truncation points using an optimisation method, and was used to estimate a Gaussian distribution of the values of presumably non-diseased subjects after Box-Cox transformation of the empirical data. This distribution was now considered as the distribution of the non-diseased subgroup. The percentiles of this parametrical distribution were calculated to obtain RLs.

RESULTS

RLs determined by the indirect combined decomposition technique led to similar RLs as found by several recent study reports using a direct method according to international recommendations. Furthermore, the RLs obtained from 13 laboratories in two different European regions reflected the well-known differences of various analytical procedures. Stratification for gender and age was necessary in contrast to earlier reports. With increasing age, an increase of the upper RL and the reference range was observed. Hospitalisation also affected the RLs. Common RLs appeared acceptable only within the same analytical systems. Some laboratories used RLs which were not appropriate for the population served.

CONCLUSIONS

The proposed strategy of combining exclusion criteria with a resolution technique led to retrospective RLs from intra-laboratory data pools for TSH which were comparable with directly determined RLs. Differences between laboratories were due primarily to the well-known bias of the different analytical procedures and to the status of the population.

Reference limits of plasma and serum creatinine concentrations from intra-laboratory data bases of several German and Italian medical centres: Comparison between direct and indirect procedures

BACKGROUND

The current dogma of establishing intra-laboratory reference limits (RLs) and their periodical reviewing cannot be fulfilled by most laboratories due to the expenses involved. Thus, most laboratories adopt external sources for their RLs often neglecting the problems of transferability. Therefore, several attempts were undertaken to derive RLs from the large data pools stored in modern laboratory information systems. These attempts were further developed to a more sophisticated indirect procedure. The new model can be considered a combined approach because it pre-excludes some subjects by direct criteria. In the current study, the new concept was applied to estimate RLs for serum and plasma creatinine from several German and Italian laboratories.

METHODS

A smoothed kernel density function was estimated for the distribution of the total mixed data of the sample group (combined data of non-diseased and diseased subjects). It was assumed that the "central" part of the distribution of all data represents the non-diseased ("healthy") population. The central part was defined by truncation points using an optimisation method, and was used to estimate a Gaussian distribution of the values of presumably non-diseased subjects after Box-Cox transformation of the empirical data. This distribution was now considered as the distribution of the non-diseased subgroup. The percentiles of this parametrical distribution were calculated to obtain RLs.

RESULTS

RLs determined by the indirect combined decomposition technique led to similar RLs as the classical direct method. Furthermore, the RLs obtained from 14 laboratories in 2 different European regions reflected the well-known differences of various analytical procedures. Stratification for gender and age was necessary. With rising age, an increase of the upper RL and of the reference range was observed. Hospitalization appeared also to affect the RLs. The new approach led to RLs in an artificially mixed population of diseased and non-diseased subjects (selected by clinical criteria) which were identical to RLs determined by a direct method applied to the non-diseased subgroup.

CONCLUSIONS

The proposed strategy of combining exclusion criteria with a resolution technique led to plausible retrospective RLs from intra-laboratory data pools for creatinine. Differences between laboratories were mainly due to the well-known bias of the different analytical procedures.

An improved indirect approach for determining reference limits from intra-laboratory data bases exemplified by concentrations of electrolytes / Ein verbesserter indirekter Ansatz zur Bestimmung von Referenzgrenzen mittels intra-laboratorieller Datensätze am Beispiel von Elektrolyt-Konzentrationen

Background: The current dogma of establishing intra-laboratory reference limits (RLs) and their periodical reviewing cannot be fulfilled by most laboratories due to the expenses involved. Thus, most laboratories adopt RLs from external sources often neglecting the problems of transferability. Presently accepted validation concepts still require experimental expenses. Several attempts were undertaken to derive RLs from the large data pools stored in modern laboratory information systems. Former indirect procedures were not generally accepted, but were recently further developed and combined with direct exclusion criteria and applied to estimate RLs of the catalytic activity concentrations of enzymes. This approach was now applied to several electrolytes in serum and plasma most commonly applied in clinical chemistry.

Methods: A smoothed kernel density function was estimated for the distribution of the mixed data of the sample group (combined data of non-diseased and diseased subjects). It was assumed that the “central” part of the distribution of all data represents the non-diseased (“healthy”) population (non-pathological values) with high probability. The central part was defined by truncation points using an optimisation method, and was used to estimate a Gaussian distribution of the values of non-diseased subjects. This distribution was now considered as the distribution of the non-diseased subgroup. The percentiles of this parametrical distribution were calculated to obtain unimodal reference intervals.

Results: The RLs obtained from different laboratories were similar to recently published values established by direct procedures. Stratification for gender was not necessary, but in some cases for age. With rising age, an increase of the upper RL and of the reference range was observed for potassium. Hospitalisation affected the RLs of sodium, potassium, calcium and magnesium, but not of phosphate. In the case of sodium, the data of at least five regional laboratories could be combined to common RLs. The presented indirect procedure was further validated with a large dataset of potassium concentrations from the NHANES III study with five groups of different health status.

Conclusions: The proposed strategy of combining exclusion criteria with an indirect method led to RLs from intra-laboratory data pools for electrolytes which were plausible in comparison to published data obtained by the generally accepted direct approach. The combined concept, however, still requires further investigations. Therefore, it is presently only recommended for checking and reviewing already existing RLs.

Reference intervals: the way forward

New facts have recently enhanced interest in the topic of reference intervals. In particular, the International Organization for Standardization standard 15189, requesting that 'biological reference intervals shall be periodically reviewed', and the directive of the European Union on in vitro diagnostic medical devices asking manufacturers to provide detailed information on reference intervals, have renewed interest in the subject. This review presents an update on the topic, discussing the theoretical aspects and the most critical issues. The basic approach to the definition of reference intervals proposed in the original International Federation of Clinical Chemistry documents still remain valid. The use of data mining to obtain reference data from existing databases has severe limitations. New statistical approaches to discard outliers and to compute reference limits have been recommended. On the other hand, perspectives opened by the improvement in standardization through the implementation of the concept of traceability suggest new models to define 'common' reference intervals that can be transferred and adopted by different clinical laboratories in order to decrease the proliferation of different reference intervals not always justified by differences in population characteristics or in analytical methodology.

A plea for intra-laboratory reference limits. Part 1. General considerations and concepts for determination

Accurate results for quantitative procedures can be useless if the reference limits for the interpretation of laboratory results are unreliable. Recent concepts for quality management systems require that laboratories pay more attention to identification and verification of reference limits. Scientific recommendations often claim that each laboratory should determine intra-laboratory reference limits, which should be reviewed periodically. This recommendation is currently neglected by most laboratories; instead they use reference limits from external sources, despite various problems of transference. Prospective and retrospective methods either using or neglecting disease prevalences (polymodal or unimodal concepts, respectively) and applying different statistical approaches for determining reference limits have been described. The various procedures are reviewed with regard to their diagnostic sensitivity, specificity and (non-)efficiency. The present gold standard is the reference limit concept according to IFCC recommendations (a unimodal prospective approach). This concept, together with trueness-based standardization, is the most useful basis for harmonization of the decision-making process with laboratory results, despite complex problems of traceability and transference. This harmonization is at present only achieved for a limited number of analytes for which SI units and traceability can be technically realized. For the majority of measurands in laboratory medicine, much research is still required and results cannot be expected in the near future. For these measurands, a need remains for internal, efficient and simple identification of population-based reference limits. Therefore, newer retrospective concepts were developed that use large data sets from laboratory information systems to derive intra-laboratory reference limits. These approaches appear promising and should be further developed.