scholarly journals Application of the TML method to big data analytics and reference interval harmonization

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mary Kathryn Bohn ◽  
Khosrow Adeli
Keyword(s):  
Clinical Chemistry ◽  
A Priori ◽  
Big Data Analytics ◽  
Reference Interval ◽  
German Society ◽  
Reference Intervals ◽  
Indirect Methods ◽  
Advantages And Disadvantages ◽  
Result Interpretation ◽  
Indirect Reference

Abstract Significant variation in reported reference intervals across healthcare centers and networks for many well-standardized laboratory tests continues to exist, negatively impacting patient outcomes by increasing the risk of inappropriate and inconsistent test result interpretation. Reference interval harmonization has been limited by challenges associated with direct reference interval establishment as well as hesitancies to apply currently available indirect methodologies. The Truncated Maximum Likelihood (TML) method for indirect reference interval establishment developed by the German Society of Clinical Chemistry and Laboratory Medicine (DGKL) presents unique clinical and statistical advantages compared to traditional indirect methods (Hoffmann and Bhattacharya), increasing the feasibility of developing indirect reference intervals that are comparable to those determined using a direct a priori approach based on healthy reference populations. Here, we review the application of indirect methods, particularly the TML method, to reference interval harmonization and discuss their associated advantages and disadvantages. We also describe the CSCC Reference Interval Harmonization Working Group’s experience with the application of the TML method in harmonization of adult reference intervals in Canada.

scholarly journals Indirect methods for reference interval determination – review and recommendations

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Graham R.D. Jones ◽  
Rainer Haeckel ◽  
Tze Ping Loh ◽  
Ken Sikaris ◽  
Thomas Streichert ◽  
...  
Keyword(s):  
Clinical Chemistry ◽  
Direct Methods ◽  
Analytical Techniques ◽  
Reference Interval ◽  
Reference Population ◽  
Reference Intervals ◽  
Statistical Techniques ◽  
Indirect Methods ◽  
Indirect Approach ◽  
Patient Health

Abstract Reference intervals are a vital part of the information supplied by clinical laboratories to support interpretation of numerical pathology results such as are produced in clinical chemistry and hematology laboratories. The traditional method for establishing reference intervals, known as the direct approach, is based on collecting samples from members of a preselected reference population, making the measurements and then determining the intervals. An alternative approach is to perform analysis of results generated as part of routine pathology testing and using appropriate statistical techniques to determine reference intervals. This is known as the indirect approach. This paper from a working group of the International Federation of Clinical Chemistry (IFCC) Committee on Reference Intervals and Decision Limits (C-RIDL) aims to summarize current thinking on indirect approaches to reference intervals. The indirect approach has some major potential advantages compared with direct methods. The processes are faster, cheaper and do not involve patient inconvenience, discomfort or the risks associated with generating new patient health information. Indirect methods also use the same preanalytical and analytical techniques used for patient management and can provide very large numbers for assessment. Limitations to the indirect methods include possible effects of diseased subpopulations on the derived interval. The IFCC C-RIDL aims to encourage the use of indirect methods to establish and verify reference intervals, to promote publication of such intervals with clear explanation of the process used and also to support the development of improved statistical techniques for these studies.

scholarly journals Separating disease and health for indirect reference intervals

2021 ◽  
Vol 45 (2) ◽  
pp. 55-68 ◽  
Author(s):  
Kenneth A. Sikaris
Keyword(s):  
A Priori ◽  
Laboratory Data ◽  
Reference Interval ◽  
Statistical Technique ◽  
Reference Intervals ◽  
Large Databases ◽  
Statistical Issues ◽  
Physiological Variations ◽  
Indirect Reference ◽  
Apparently Healthy

Abstract The indirect approach to defining reference intervals operates ‘a posteriori’, on stored laboratory data. It relies on being able to separate healthy and diseased populations using one or both of clinical techniques or statistical techniques. These techniques are also fundamental in a priori, direct reference interval approaches. The clinical techniques rely on using clinical data that is stored either in the electronic health record or within the laboratory database, to exclude patients with possible disease. It depends on the investigators understanding of the data and the pathological impacts on tests. The statistical technique relies on identifying a dominant, apparently healthy, typically Gaussian distribution, which is unaffected by the overlapping populations with higher (or lower) results. It depends on having large databases to give confidence in the extrapolation of the narrow portion of overall distribution representing unaffected individuals. The statistical issues involved can be complex, and can result in unintended bias, particularly when the impacts of disease and the physiological variations in the data are under appreciated.

scholarly journals Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation

2020 ◽  
Author(s):  
Abdurrahman Coşkun ◽  
Sverre Sandberg ◽  
Ibrahim Unsal ◽  
Coskun Cavusoglu ◽  
Mustafa Serteser ◽  
...  
Keyword(s):  
Steady State ◽  
Personalized Medicine ◽  
Clinical Chemistry ◽  
Reference Interval ◽  
Reference Intervals ◽  
Biological Variation ◽  
Test Results ◽  
Steady State Condition ◽  
Laboratory Test Results ◽  
Measurement Results

Abstract Background The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. Methods A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. Results Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. Conclusions Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

A new indirect estimation of reference intervals: truncated minimum chi-square (TMC) approach

2019 ◽  
Vol 57 (12) ◽  
pp. 1933-1947 ◽  
Author(s):  
Werner Wosniok ◽  
Rainer Haeckel
Keyword(s):  
Detection Limit ◽  
Simulated Data ◽  
Reference Interval ◽  
Reference Intervals ◽  
Skewed Data ◽  
Chi Square ◽  
Indirect Methods ◽  
Indirect Estimation ◽  
Estimated Parameters ◽  
Data Files

Abstract All known direct and indirect approaches for the estimation of reference intervals (RIs) have difficulties in processing very skewed data with a high percentage of values at or below the detection limit. A new model for the indirect estimation of RIs is proposed, which can be applied even to extremely skewed data distributions with a relatively high percentage of data at or below the detection limit. Furthermore, it fits better to some simulated data files than other indirect methods. The approach starts with a quantile-quantile plot providing preliminary estimates for the parameters (λ, μ, σ) of the assumed power normal distribution. These are iteratively refined by a truncated minimum chi-square (TMC) estimation. The finally estimated parameters are used to calculate the 95% reference interval. Confidence intervals for the interval limits are calculated by the asymptotic formula for quantiles, and tolerance limits are determined via bootstrapping. If age intervals are given, the procedure is applied per age interval and a spline function describes the age dependency of the reference limits by a continuous function. The approach can be performed in the statistical package R and on the Excel platform.

Reference intervals for 21 clinical chemistry analytes in arterial and venous umbilical cord blood

1993 ◽  
Vol 39 (6) ◽  
pp. 1041-1044 ◽  
Author(s):  
S L Perkins ◽  
J F Livesey ◽  
J Belcher
Keyword(s):  
Alkaline Phosphatase ◽  
Umbilical Cord ◽  
Clinical Chemistry ◽  
Venous Blood ◽  
Reference Interval ◽  
Reference Intervals ◽  
Nonparametric Analysis ◽  
Term Infants ◽  
Male And Female ◽  
Gamma Glutamyltransferase

Abstract Reference intervals were determined for 21 clinical chemistry analytes in umbilical cord arterial and venous blood from healthy term infants. Nonparametric analysis (rank number) was used to determine the central 95% reference interval. No significant differences were observed between male and female infants. Reference intervals for glucose, urea, creatinine, urate, phosphate, calcium, albumin, total protein, cholesterol, triglycerides, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, lactate dehydrogenase, gamma-glutamyltransferase, and magnesium all were significantly different from adult values.

Optimizing the use of the “state-of-the-art” performance criteria

2015 ◽  
Vol 53 (6) ◽  
Author(s):  
Rainer Haeckel ◽  
Werner Wosniok ◽  
Thomas Streichert
Keyword(s):  
State Of The Art ◽  
Clinical Chemistry ◽  
Reference Interval ◽  
German Society ◽  
Laboratory Medicine ◽  
Biological Variation ◽  
The State ◽  
Analytical Performance ◽  
Performance Criteria ◽  
Performance Goals

AbstractThe organizers of the first EFLM Strategic Conference “Defining analytical performance goals” identified three models for defining analytical performance goals in laboratory medicine. Whereas the highest level of model 1 (outcome studies) is difficult to implement, the other levels are more or less based on subjective opinions of experts, with models 2 (based on biological variation) and 3 (defined by the state-of-the-art) being more objective. A working group of the German Society of Clinical Chemistry and Laboratory Medicine (DGKL) proposes a combination of models 2 and 3 to overcome some disadvantages inherent to both models. In the new model, the permissible imprecision is not defined as a constant proportion of biological variation but by a non-linear relationship between permissible analytical and biological variation. Furthermore, the permissible imprecision is referred to the target quantity value. The biological variation is derived from the reference interval, if appropriate, after logarithmic transformation of the reference limits.

scholarly journals The zlog value as a basis for the standardization of laboratory results

2017 ◽  
Vol 41 (1) ◽  
Author(s):  
Georg Hoffmann ◽  
Frank Klawonn ◽  
Ralf Lichtinghagen ◽  
Matthias Orth
Keyword(s):  
Clinical Chemistry ◽  
Standard Procedure ◽  
Inverse Function ◽  
Real Data ◽  
Reference Interval ◽  
Reference Population ◽  
German Society ◽  
Health Law ◽  
Original Result ◽  
Laboratory Results

AbstractBackground:With regard to the German E-Health Law of 2016, the German Society for Clinical Chemistry and Laboratory Medicine (DGKL) has been invited to develop a standard procedure for the storage and transmission of laboratory results. We suggest the commonly used z-transformation.Methods:This method evaluates by how many standard deviations (SDs) a given result deviates from the mean of the respective reference population. We confirm with real data that laboratory results of healthy individuals can be adjusted to a normal distribution by logarithmic transformation.Results:Thus, knowing the lower and upper reference limits LL and UL, one can transform any result x into a zlog value using the following equation:$\eqalign{ {\rm{zlog}} = & {\rm{(log(x)}}-{\rm{(log(LL)}} + {\rm{log(UL))/2)\cdot3}}{\rm{.92/(log(UL)}} \cr -{\bf{ }}{\rm{log(LL))}} \cr} $The result can easily be interpreted, as its reference interval (RI) is –1.96 to +1.96 by default, and very low or high results yield zlog values around –5 and +5, respectively. For intuitive data presentation, the zlog values may be transformed into a continuous color scale, e.g. from blue via white to orange.Using the inverse function, any zlog value can then be translated into the theoretical result of an analytical method with another RI:(1)$${\rm{x}} = {\rm{L}}{{\rm{L}}^{0.5 - {\rm{zlog}}/3.92}} \cdot {\rm{U}}{{\rm{L}}^{0.5 + {\rm{zlog}}/3.92}}$$Conclusions:Our standardization proposal can easily be put into practice and may effectively contribute to data quality and patient safety in the frame of the German E-health law. We suggest for the future that laboratories should provide the zlog value in addition to the original result, and that the data transmission protocols (e.g. HL7, LDT) should contain a special field for this additional value.

Canadian Laboratory Initiative on Pediatric Reference Interval Database (CALIPER): Pediatric reference intervals for an integrated clinical chemistry and immunoassay analyzer, Abbott ARCHITECT ci8200

2009 ◽  
Vol 42 (9) ◽  
pp. 885-891 ◽  
Author(s):  
Man Khun Chan ◽  
Isolde Seiden-Long ◽  
Mujdat Aytekin ◽  
Frank Quinn ◽  
Tricia Ravalico ◽  
...  
Keyword(s):  
Clinical Chemistry ◽  
Reference Interval ◽  
Reference Intervals ◽  
Abbott Architect

scholarly journals A robust approach to reference interval estimation and evaluation

1998 ◽  
Vol 44 (3) ◽  
pp. 622-631 ◽  
Author(s):  
Paul S Horn ◽  
Amadeo J Pesce ◽  
Bradley E Copeland
Keyword(s):  
Prediction Interval ◽  
Clinical Chemistry ◽  
Real Data ◽  
Reference Interval ◽  
Reference Intervals ◽  
Small Sample ◽  
The Other ◽  
Robust Estimator ◽  
Sample Sizes ◽  
Robust Approach

Abstract We propose a new methodology for the estimation of reference intervals for data sets with small numbers of observations or for those with substantial numbers of outliers. We propose a prediction interval that uses robust estimates of location and scale. The SAS software can be readily modified to do these calculations. We compared four reference interval procedures (nonparametric, transformed, robust with a nonparametric lower limit, and transformed robust) for sample sizes of 20, 40, 60, 80, 100, and 120 from χ2 distributions of 1, 4, 7, and 10 df. χ2 distributions were chosen because they simulate the skewness of distributions often found in clinical chemistry populations. We used the root mean square error as the measure of performance and used computer simulation to calculate this measure. The robust estimator showed the best performance for small sample sizes. As the sample size increased, the performance values converged. The robust method for calculating upper reference interval values yields reasonable results. In two examples using real data for haptoglobin and glucose, the robust estimator provides slightly smaller upper reference limits than the other procedures. Lastly, the robust estimator was compared with the other procedures in a population where 5% of the values were multiplied by a factor of 5. The reference intervals were calculated with and without outlier detection. In this case, the robust approach consistently yielded upper reference interval values that were closer to those of the true underlying distributions. We propose that robust statistical analysis can be of great use for determinations of reference intervals from limited or possibly unreliable data.

Establishment of Reference Intervals for Alkaline Phosphatase in Pakistani Children Using a Data Mining Approach

2019 ◽  
Vol 51 (5) ◽  
pp. 484-490 ◽  
Author(s):  
Sibtain Ahmed ◽  
Jakob Zierk ◽  
Aysha Habib Khan
Keyword(s):  
Data Mining ◽  
Alkaline Phosphatase ◽  
Clinical Decision Making ◽  
Clinical Chemistry ◽  
Age Groups ◽  
Clinical Decision ◽  
German Society ◽  
Reference Intervals ◽  
Photometric Method ◽  
Data Mining Approach

Abstract Objective To establish reference intervals (RIs) for alkaline phosphatase (ALP) levels in Pakistani children using an indirect data mining approach. Methods ALP levels analyzed on a Siemens Advia 1800 analyzer using the International Federation of Clinical Chemistry’s photometric method for both inpatients and outpatients aged 1 to 17 years between January 2013 and December 2017, including patients from intensive care units and specialty units, were retrieved. RIs were calculated using a previously validated indirect algorithm developed by the German Society of Clinical Chemistry and Laboratory Medicine’s Working Group on Guide Limits. Results From a total of 108,845 results, after the exclusion of patients with multiple specimens, RIs were calculated for 24,628 males and 18,083 females with stratification into fine-grained age groups. These RIs demonstrate the complex age- and sex-related ALP dynamics occurring during physiological development. Conclusion The population-specific RIs serve to allow an accurate understanding of the fluctuations in analyte activity with increasing age and to support clinical decision making.

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