Skip to content
Publicly Available Published by De Gruyter July 26, 2019

A protocol for testing the stability of biochemical analytes. Technical document

  • Rubén Gómez-Rioja EMAIL logo , Marta Segovia Amaro , Jorge Diaz-Garzón , Josep Miquel Bauçà , Débora Martínez Espartosa , Pilar Fernández-Calle , on behalf of Extra-Analytical Quality Commission of the Spanish Society of Laboratory Medicine (SEQCML) and on behalf of Analytical Quality Commission of the Spanish Society of Laboratory Medicine (SEQCML)


Stability of a measurand in a specimen is a function of the property variation over time in specific storage conditions, which can be expressed as a stability equation, and is usually simplified to stability limits (SLs). Stability studies show differences or even inconsistent results due to the lack of standardized experimental designs and heterogeneity of the chosen specifications. Although guidelines for the validation of sample collection tubes have been published recently, the measurand stability evaluation is not addressed. This document provides an easy guideline for the development of a stability test protocol based on a two-step process. A preliminary test is proposed to evaluate the stability under laboratory habitual conditions. The loss of stability is assessed by comparing measurement values of two samples obtained from the same patient and analyzed at different time points. One of them is analyzed under optimal conditions (basal sample). The other is stored under specific stability conditions for a time set by the laboratory (test sample). Differences are expressed using percentage deviation (PD%) to facilitate comparison with specifications. When the preliminary test demonstrates instability, a comprehensive test is proposed in order to define the stability equation and to specify SLs. Several samples are collected from a set of patients. The basal sample is analyzed under optimal conditions, whereas analysis of test samples is delayed at time intervals. For each patient PD% is calculated as the difference between measurements for every test sample and its basal one and represented in a coordinate graph versus time.


The stability of a biochemical analyte is defined as the capability of a sample/specimen material to retain its properties over time. Hence, loss of stability is calculated as a function of property variation and time in specific storage conditions (type of container, temperature and light exposure, among other factors). A stability limit (SL) is defined as the period of time in which a property variation does not exceed a maximum permissible instability (MPI) [1]. MPI is established a priori in the laboratory on the basis of regulations and clinical use. SLs will depend on the MPI established and local laboratory practice.

A myriad of experimental stability tests have been performed for the analytes most frequently measured in clinical laboratories. Yet, differing or even inconsistent results have been obtained due to the lack of standard experimental designs and wide variability in MPI specifications, as shown in the systematic literature reviews published [1], [2], [3]. In addition, the Clinical and Laboratory Standards Institute (CLSI) guidelines for the management of laboratory specimens only provide general SLs based on specific studies [4], [5], [6].

The stability of an analyte depends, among other factors, on the characteristics of the container. SLs are a basic aspect of routine laboratory practice, as defined in ISO 15189 [7]. Yet, assessing SLs is not mandatory for manufacturers of in vitro diagnostic products. In relation to sample containers, the EU 98/79/CE directive [8] requires manufacturers to test the stability of container components, but not of container contents. Although guidelines for the validation of sample collection tubes have been published recently [9], [10], they do not address the issue of loss of analyte stability in specimens.

In 2006, the Board of Laboratory Quality of the Spanish Society of Laboratory Medicine approached this problem and developed a stability testing protocol [11]. This new version of the protocol is aimed at providing a simplified formula based on a preliminary stability test and a comprehensive stability test that help define stability test formulas.

Purpose and scope

The purpose of this document is to provide guidelines for the development of a stability test protocol. This protocol is focused on the specimens most frequently used in clinical laboratories (blood and urine), which are generally collected using vacuum collection tubes. This protocol may be applicable to other types of specimens, provided that the characteristics of each type of specimen are considered.

This document can serve as a guide to manufacturers of diagnostic in vitro products, helping them evaluate the characteristics of their sample collection devices. At the same time, this protocol may be useful for medical laboratories interested in verifying manufacturer’s data.


Stability: Capability of an analyte to retain its properties over time.

Loss of stability: Significant change in the properties of a biological analyte over time.

Maximum permissible instability (MPI): Maximum permissible deviation of a value obtained after a specific storage time under given conditions from a reference value obtained under optimal storage conditions. It is expressed as a percentage of baseline value.

Stability limit (SL): The storage time in which the loss of stability of an analyte exceeds the MPI.

Factors affecting stability

Apart from time – which modifies all properties–, there are other variables that affect the stability of analyte properties, as follows:

  1. Cellular metabolism. Contact with cells causes an exchange of materials that does not necessarily involve cell destruction [12], [13], [14]. Contact with cells primarily affects electrolytes and substrates of intermediary metabolism and, to a lesser extent, complex molecules. The presence of cellular material after centrifugation and separation from cells is more frequent in plasma than in serum, and it depends on the separation and centrifugation method employed.

    Cells of blood origin and microorganism can be found in urine samples [15], [16].

  2. Contact with air, diffusion and evaporation. When a tube is opened during an assay, the solvent evaporates partially. As a result, concentrations of most analytes increase [17] and diffusion of dissolved gases augments. This causes a rise of carbon dioxide levels and an increase in pH [5], [18], [19]. Even when the tube is capped, gas diffusion occurs across the walls of the container, as it occurs with oxygen in plastic tubes [20], [21].

    Urine is collected in contact with air (except when collected by puncture), even although it is rapidly stored in vacuum containers.

  3. Exposure to light. Tubes are generally transparent. Therefore, specimens are exposed to light throughout the whole assay. The loss of stability of some analytes depends on the intensity and type of light they are exposed to [22].

  4. Tube storage position and spinning. Spinning affects the velocity of chemical reactions. It is an important aspect in long-distance transportation of specimens. Serum tubes are placed in an upright position to allow the specimen to fully clot, reduce constituent spinning, and prevent fibrin adherence when the tube is capped [4].

  5. Adsorption. A transfer of constituents from the specimen to tube components or vice versa may occur when plastic tubes or tubes containing a separating gel are used. This phenomenon is more frequent in trace elements, medications and hormones [23], [24], [25].

  6. Temperature. Temperature is an important catalyst of the chemical reactions causing loss of stability [26], [27], [28], [29], [30].

Many of these factors are subject to significant inter-individual variability. This variability is explained by cellular concentration variations in a specimen or genetic variability in degradation mechanisms [31].

The factors interfering with analyte stability are affected by the characteristics of the container, such as tube composition, separator, lid and sample handling method (timing and duration of centrifugation). European laws and regulations require manufacturers of sample collection devices to assess the limitations of their products. Therefore, manufacturers should provide information about the stability of the analytes commonly measured in each type of container.

Experimental design


The stability of an analyte under standard laboratory conditions can be determined experimentally by a preliminary test. In a preliminary test, the values obtained under optimal conditions (shortest time between sampling and analysis) are compared with those obtained after the maximum time considered acceptable in the standard laboratory practice. If bias does not exceed the MPI, there is no loss of stability at the storage time studied. A comprehensive test will be performed if deviation exceeds the MPI or a stability equation is to be developed. A comprehensive test involves testing different storage times.

The conditions and purposes of a stability test will be set by each manufacturer or laboratory according to their needs. It is recommended that the manufacturer always performs a comprehensive test to provide users with a stability equation. This formula will allow users to determine an SL that meets the quality specifications of each laboratory.

The following general aspects should be considered in the design of comprehensive tests.

Stability conditions

The factors and conditions affecting the stability of each analyte should be explored. In all cases, laboratories should investigate the effects of contact with cells, storage time and temperature, among others. The storage time to be studied will be set by each laboratory, based on routine practice and applicable laws and guidelines.

In routine laboratory practice, there are “three basic conditions” affecting the stability of analytes in blood samples (Figure 1), namely:

  1. From collection to centrifugation. Stability of the analyte in whole blood stored in sealed tubes at room temperature exposed to light.

  2. Stability in serum/plasma generally stored in the primary container at room temperature, temporarily uncapped and exposed to light.

  3. Storage conditions. Stability in serum/plasma generally stored in a sealed refrigerated primary container in the dark. In the case of prolonged storage in a serum bank, generally frozen and separated in a secondary tube.

Figure 1: Standard blood handling conditions in laboratories with regard to the main factors affecting stability.
Figure 1:

Standard blood handling conditions in laboratories with regard to the main factors affecting stability.

In routine laboratory practice, a maximum storage time is set for each of these conditions affecting stability. Maximum storage time limits are determined for pre-analytical processes prior to delivery to the laboratory, intra-laboratory pre-analytical processes+analytical processes and post-analytical processes.

Types of specimens/samples

It is recommended to use samples from patients rather than healthy subjects. This way, researchers will ensure that concentrations are near clinical decision limits. Use recent samples and avoid the presence of hemolysis, icterus or lipemia.

For the results obtained to be applicable to regular laboratory practice, the type of specimen and container used in a stability test should be the same as those used in routine measurements.

Significant differences have been obtained in measurements made in the same sample stored in different tubes. To ensure the validity of all tubes, phlebotomy should be performed in accordance with standard guidelines [32].

Analyte concentrations

The stability of an analyte may depend on its baseline concentration [21]. In general, stability tests should be performed using samples which concentrations are near clinical decision limits, in accordance with the type of laboratory and reference population. Yet, recruiting patients whose concentrations are near clinical decision limits is challenging, as it is difficult to predict concentrations, except in very controlled cases. Therefore, most specimens will contain concentrations within normal limits.

Experimental design

Ideally, samples should be analyzed in a single run to avoid analytical bias. To analyze all samples in a single run, storage at −70 °C could be an alternative. However, not all analytes can be frozen, as freezing can cause deterioration. Use of quality control samples of the same batch on each analytical run could be useful to determine between-run systematic error. Between-run systematic error is defined as the difference between measurement values for quality control samples in each analytical run.

Quality performance specifications

The MPI set by each laboratory for each analyte will be based on the quality standards of the laboratory.

In the 1st Strategic Conference of the European Federation of Laboratory Medicine (EFLM), three models were defined for the selection of quality specifications [33], namely: impact on clinical outcomes, biological variation of the analyte and state-of-the-art. Guidelines were provided for the selection of one of these formulas according to the analyte to be assayed. Although a hierarchy was not established, there was a general agreement that the two first models are better suited for certain analytes than others, as these formulas are based on the clinical use of analytes. Laboratories should use quality performance specifications based on robust studies which population was similar to that of the laboratory. As to biological variation, a tool has been developed to review the studies published so far. In addition, the Task Force on Biological Variation DataBase of the European Federation of Laboratory Medicine and Clinical Chemistry is building an updated international database based on methodologically-robust studies [34].

Preliminary stability test

Experiment design

Loss of stability is assessed by comparing measurement values for two samples simultaneously obtained from the same patient and analyzed at different time points. One of them is analyzed under optimal stability conditions (basal sample). The other sample is stored under specific stability conditions for a time set by the laboratory (test sample).


  1. Determine the analytes and stability conditions to be tested. Each test involves a specific combination of type of container, specimen and temperature (or other conditions). It is recommended to assess stability in at least three separate tests, namely: analyte stability in the specimen (whole blood) at room temperature, in the sample (serum/plasma) at room temperature, and in the refrigerated sample (see Section “Stability conditions”). Each laboratory should consider whether it is necessary to consider other factors based on the analyte to be tested and specific conditions of the laboratory.

  2. Establish an MPI for each analyte under study.

  3. Define the duration of each test. The duration of each test will be determined by the maximum time the sample can be stored in this stability conditions in standard laboratory practice. This method will make it possible to assess the stability of an analyte in the worst conditions.

  4. Determine the number of study subjects. It is recommended to include at least three patients to assess inter-individual variations of stability.

  5. Determine the number of replicates needed. The study must reach a statistical power and level of statistical significance that guarantees that the bias observed involves a significant loss of stability. The number of replicates needed will be estimated based on the ratio of MPI to the analytical imprecision of the method, as determined by the coefficient of variation (CVa). Table 1 shows the number of replicates needed to reach a 90% statistical power and a 95% confidence interval (adapted from CLSI EP7 A3) [35]. The minimum number of replicates to be performed will be five in all cases.

  6. Determine the number of tubes required for the whole assay according to steps 1–5. We recommend using a primary tube for each stability condition instead of using aliquots. The reason is that the transfer of aliquots may alter the results with respect to standard laboratory practice.

  7. Consider the possibility of deep freezing the sample to perform the assay in a single run. Otherwise, avoid between-run bias by analyzing the same batch of control material in each run.

  8. Test performance. Once all the specimens have been obtained, separate the baseline specimen from the test specimens. Centrifuge the baseline specimen rapidly after collection and analyze it or store it at −70 °C. In stability tests in whole blood, centrifugation of test specimens is delayed for a specific time. In stability tests in serum/plasma, test samples are centrifuged together with the baseline sample, and analysis or deep freezing are performed after a fixed storage time.

Table 1:

Number of replicates required to reach a 90% statistical power and a 95% confidence interval (adapted from CLSI EP7 A3) [35].

MPI (%)/CV (%) ratioNumber of replicates
  1. MPI (%), maximum permissible instability; CV (%), coefficient of variation.

Analytical design

The data obtained are compared to assess whether a significant loss of stability occurred.

  1. Detection of atypical values (outliers). Revise the results obtained to identify the presence of atypical values (the test to be applied will depend on the number of replicates performed, and its use must be duly justified).

  2. Estimation of percentage deviation (PD%). PD% is the difference between measurand concentrations in optimal conditions (baseline sample; t0, average of replicate measurements) and its concentrations when stored for the maximum permissible storage time (test sample; tx average of replicate measurements). The difference is converted into a %PD from the baseline value.


    tx: average concentration in the test sample.

    t0: average concentration in the baseline sample.

  3. Interpretation of results. A PD% <MPI for all study subjects indicates that there was not a significant loss of stability within the storage time studied. A PD% ≥MPI in some of the subjects indicates that there was a significant loss of stability within the storage time studied. To define the SL for an analyte, a comprehensive assay must be performed to refine the stability equation.

  4. Bias test. When an assay is performed in different runs, the occurrence of bias must be controlled using quality control results. To such purpose, calculate the PD% between the controls used in each run. If the PD% for controls is >1/3 of intraindividual biological variation, repeat the assay [36], [37].

Supplementary material shows how to perform a preliminary stability test.

Comprehensive test

The comprehensive test is used to develop the equation of PD% change vs. time and SL under given conditions in accordance with particular MPI specifications (Figure 2).

Figure 2: Comprehensive stability equation.
Figure 2:

Comprehensive stability equation.

Experiment design

Loss of stability under given conditions is assessed by collecting simultaneously several samples from a patient. The control sample is analyzed under optimal stability conditions, whereas analysis of test samples is delayed at fixed time intervals. Loss of stability is measured as the difference between measurement values for the baseline sample and the values obtained for each test sample. The results drawn are shown in a coordinate graph with PD% in the Y-axis and time in the X-axis.


  1. Determine the analytes and stability conditions to be tested.

  2. Establish an MPI for each analyte.

  3. Define the timing of sampling. In case a preliminary test has been performed, sampling times should include a point above and below the test time. Otherwise, if a comprehensive test is performed without a preliminary test, sampling times will include standard laboratory processing and storage times. We recommend that sampling is performed in all subjects at the same time point to facilitate statistical analysis.

  4. Determine the number of study subjects. We recommend that at least 10 patients are included.

  5. Determine the number of replicates needed. In general, analysis in duplicate is adequate.

  6. Consider the possibility of storing the sample at −70 °C to perform the assay in a single run. Otherwise, to avoid bias, quality control measurements will be performed.

  7. Based on steps 1−6, determine the total number of tubes needed. Considering the volume and number of tubes to be filled, consider the possibility of testing stability conditions and measurands in samples collected in a single sampling session. To ensure the validity of all tubes, perform phlebotomy in accordance with standard guidelines and avoid prolonged extractions [32].

  8. Test performance. Once all specimens have been obtained, handle the baseline specimen under optimal conditions. Perform centrifugation or deep freezing/analysis of test samples at fixed storage times.

Analytical design

Once all data have been obtained the stability equation can be defined. Apply MPI to the y-axis, which will yield an SL for the analyte under study on the x-axis.

  1. Detection of atypical values (outliers). Revise duplicate measurements to ensure that variance with respect to common analytical imprecision is not significant.

  2. Estimation of PD%. Estimate the PD% between each storage time and the baseline sample.


    tx: average concentration in the test sample at storage time x.

    t0: average concentration in the baseline sample.

  3. Graphic representation. Design a coordinate graph displaying PD% values (abscissa) for each storage time (ordinates) for each patient. Each patient will be labeled to identify potential cases of inter-individual variation (when the loss of stability formula for a patient differs significantly from the formulas for other patients).

  4. Adjustment of the stability equation. The formula for testing stability can be adjusted manually on the stability chart or by the least squares method (preferred method). The regression curve must always be forced to cross the intersection of coordinates, as at time 0, loss of stability must be 0. The best adjustment may not be lineal. Adjustment of the stability equation must have enough statistical power (Pearson’s coefficient >0.7). The established slope must always be significantly different from 0.

  5. Definition of SLs. Based on the MPI set for each analyte, the SLs for a set of specific storage conditions can be obtained from the stability equation (Figure 3). Consider the confidence interval for each storage time. Calculate and represent graphically the average PD% and confidence interval for each storage time. A high specificity (“a loss of stability cannot be discarded”) or high sensitivity (“it is certain” that the MPI is exceeded) can be defined.

  6. Bias test. If an assay has been performed in different runs, calculate the PD% between the quality control samples used in each run. If the PD% for control samples is >1/3 of intraindividual biological variation, consider repeating the assay [36], [37].

Figure 3: Comprehensive stability test. Confidence intervals for each storage time.MPI, maximum permissible instability.
Figure 3:

Comprehensive stability test. Confidence intervals for each storage time.

MPI, maximum permissible instability.

Supplementary material shows how to perform a comprehensive assay.


The SL of an analyte depends on the conditions under which a sample is collected and handled and on the sample collection device used. Other factors include the MPI set by the laboratory.

A myriad of experimental assays have been performed to assess the stability of most clinically relevant analytes. However, conflicting results have been obtained and extrapolation of results from experimental assays to other laboratories is challenging. These difficulties are partially due to the lack of standard guidelines for the performance of stability tests. The purpose of this paper is to propose a standard protocol for the performance of experimental stability tests. This protocol can be useful for clinical laboratories and manufacturers for the evaluation of sample collection devices.

Corresponding author: Rubén Gómez-Rioja, PhD, Laboratory Medicine Department, La Paz-Cantoblanco-Carlos III University Hospital, Paseo de la Castellana 261, 28046 Madrid, Spain
aComposition of the Extra-Analytical Quality Commission: Andrea Caballero Garralda, Mercedes Ibarz, María Antonia Llopis, Itziar Marzana, Monserrat Ventura, Isabel García del Pino, Carolina Gómez, Juan José Puente, Debora Martínez Espartosa, Josep Miquel Bauçà, Marta Segovia Amaro, Rubén Gómez-Rioja.bComposition of the Analytical Quality Commission: Carmen Ricos Aguilá, Carmen Perich Alsina, Joana Minchinela, Margarita Simón, Jose Vicente García Lario, Beatriz Boned Juliani, Pilar Fernández Fernández, Elisabet González Lao, Zoraida Cortés, Fernando Marqués García, Xavier Tejedor Ganduxé, Jorge Díaz-Garzón Marco, Pilar Fernández-Calle.
  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


1. Guder WG, Fiedler M, daFonseca Wollheim F, Schmitt Y, Töpfer G, Wisser H, et al. The quality of diagnostic samples. 4th completely revised ed. 2005. Oxford: BD Diagnostics.Search in Google Scholar

2. Effects of Disease on Clinical Laboratory Tests, 4th Edition, Vol. 1 and 2. D.S. Young and R.B. Friedman, eds. Washington, DC: AACC Press, 2001.Search in Google Scholar

3. Gómez-Rioja R, Martínez Espartosa D, Segovia M, Ibarz M, LlopisMA, Bauça JM, et al. Laboratory sample stability. Is it possible to define a consensus stability function? An example of five blood magnitudes. Clin Chem Lab Med 2018;56:1806–18.10.1515/cclm-2017-1189Search in Google Scholar

4. CLSI. Procedures for the Handling and Processing of Blood Specimens for Common Laboratory Tests; Approved Guideline 4th Edition. CLSI document GP44-A4. Wayne, PA: Clinical and Laboratory Standards Institute; 2010.Search in Google Scholar

5. CLSI. Procedures for de Collection of Arterial Blood Specimens; Approved Standard-4th Edition. CLSI document GP43-A4. Wayne, PA: Clinical and Laboratory Standards Institute; 2004.Search in Google Scholar

6. CLSI. Urinalysis; Approved Guideline-Third Edition CLSI document GP16-A3. Wayne, PA: Clinical and Laboratory Standards Institute; Clinical and Laboratory Standards Institute; 2009.Search in Google Scholar

7. UNE-EN ISO 15189:2012. Medical laboratories – articular requirements for quality and competence. in Google Scholar

8. Directive 98/79/EC of the European Parliament and of the Council of 27 October 1998 on in vitro diagnostic medical devices. OJ L 331, 7.12.1998, p. 1–37. in Google Scholar

9. CLSI. Validation and Verification of Tubes for Venous and Capillary Blood Specimen Collection; Approved Guideline. CLSI document GP34-A. Wayne, PA: Clinical and Laboratory Standards Institute; 2010.Search in Google Scholar

10. Lippi G, Cornes MP, Grankvist K, Nybo M, Simundic AM. EFLM WG-Preanalytical phase opinion paper: local validation of blood collection tubes in clinical laboratories. Clin Chem Lab Med 2016;54:755–60.10.1515/cclm-2015-1274Search in Google Scholar

11. Alsina MJ, Álvarez V, Bueno M, Cortés M, García Lario JV, Jiménez CV, et al. Protocolo para el estudio de la estabilidad de las magnitudes biológicas. Documento A, Fase 3, Versión 1. Química Clínica 2006;25:86–9.Search in Google Scholar

12. Monneret D, Godmer A, Le Guen R, Bravetti C, Emeraud C, Marteau A, et al. Stability of routine biochemical analytes in whole blood and plasma from lithium heparin gel tubes during 6-hr storage. J Clin Lab Anal 2016;30:602–9.10.1002/jcla.21909Search in Google Scholar

13. Dupuy AM, Cristol JP, Vincent B, Bargnoux AS, Mendes M, Philibert P, et al. Stability of routine biochemical analytes in whole blood and plasma/serum: focus on potassium stability from lithium heparin. Clin Chem Lab Med 2018;56:413–21.10.1515/cclm-2017-0292Search in Google Scholar

14. Zhang DJ, Elswick RK, Miller WG, Bailey JL. Effect of serum-clot contact time on clinical chemistry laboratory results. Clin Chem 1998;44:1325–33.10.1093/clinchem/44.6.1325Search in Google Scholar

15. Sureda-Vives M, Morell-Garcia D, Rubio-Alaejos A, Valiña L, Robles J, Bauça JM. Stability of serum, plasma and urine osmolality in different storage conditions: relevance of temperature and centrifugation. Clin Biochem 2017;50:772–6.10.1016/j.clinbiochem.2017.03.019Search in Google Scholar

16. Remer T, Montenegro-Bethancourt G, Shi L. Long-term urine biobanking: storage stability of clinical chemical parameters under moderate freezing conditions without use of preservatives. Clin Biochem 2014;47:307–11.10.1016/j.clinbiochem.2014.09.009Search in Google Scholar

17. Sibilia R, Lohff M. Analyte stability in closed containers after 6 days storage. Clin Chem 1989;35:1158.Search in Google Scholar

18. Smeenk FW, Janssen JD, Arends BJ, Harff GA, van den Bosch JA, Schönberger JP, et al. Effects of four different methods of sampling arterial blood and storage time on gas tensions and shunt calculations in the 100% oxygen test. Eur Respir J 1997;10:910–3.10.1183/09031936.97.10040910Search in Google Scholar

19. Harsten A, Berg IS, Muth L. Importance of correct handling of samples for the result of blood gas analysis. Acta Anaesthesiol Scand 1988;32:365.10.1111/j.1399-6576.1988.tb02746.xSearch in Google Scholar

20. Muller-Plathe O, Heyduck S. Stability of blood gases, electrolytes, and hemoglobin in heparinized whole blood samples: influence of the type of syringe. Eur J Clin Chem Clin Biochem 1992;30:349–55.Search in Google Scholar

21. Baulieu M, Lapointe Y, Vinet B. Stability of PO2, PCO2, and pH in fresh blood samples stored in a plastic syringe with low heparin in relation to various blood-gas and hematological parameters. Clin Biochem 1999;32:101–7.10.1016/S0009-9120(98)00098-8Search in Google Scholar

22. Sofronescu AG, Loebs T, Zhu Y. Effects of temperature and light on the stability of bilirubin in plasma samples. Clin Chim Acta 2012;413:463–6.10.1016/j.cca.2011.10.036Search in Google Scholar PubMed

23. Calam RR. Specimen processing separator gels: an update. J Clin Immunoassay 1988;11:86–90.Search in Google Scholar

24. Hepburn S, Wright MJ, Boyder C, Sahertian RC, Lu B, Zhang R, et al. Sex steroid hormone stability in serum tubes with and without separator gels. Clin Chem Lab Med 2016;54:1451–9.10.1515/cclm-2015-1133Search in Google Scholar

25. Shah VP, Knapp G, Skully JP, Cabana BE. Interference with measurements of certain drugs in plasma by a plasticizer in vacutainer tubes. Clin Chem 1982;28:2327–8.10.1093/clinchem/28.11.2327Search in Google Scholar

26. Haller MJ, Schuster JJ, Schatz D, Melker RJ. Adverse impact of temperature and humidity on blood glucose monitoring reliability: a pilot study. Diabetes Technol Ther 2007;9:1–9.10.1089/dia.2006.0051Search in Google Scholar

27. Briscoe CJ, Hage DS. Factors affecting the stability of drugs and drug metabolites in biological matrices. Bioanalysis 2009;1:205–20.10.4155/bio.09.20Search in Google Scholar

28. Ellis JM, Livesey JH, Evans MJ. Hormone stability in human whole blood. Clin Biochem 2003;36:109–12.10.1016/S0009-9120(02)00440-XSearch in Google Scholar

29. Diver MJ, Hughes JG, Hutton JL, West CR, Hipkin LJ. The long-term stability in whole blood of 14 commonly-requested hormone analytes. Ann Clin Biochem 1994;31:561–5.10.1177/000456329403100606Search in Google Scholar

30. Livesey JH, Hodgkinson SC, Roud HR, Donald RA. Effect of time, temperature and freezing on the stability of immunoreactive LH, FSH, TSH, growth hormone, prolactin and insulin in plasma. Clin Biochem 1980;13:151–5.10.1016/S0009-9120(80)91040-1Search in Google Scholar

31. Thummel KE, Lin YS. Sources of interindividual variability. Methods Mol Biol 2014;1113:363–415.10.1007/978-1-62703-758-7_17Search in Google Scholar PubMed

32. Simundic AM, Bölenius K, Cadamuro J, Church S, Cornes MP, van Dongen-Lases EC, et al. Joint EFLM-COLABIOCLI Recommendation for venous blood sampling.,%20June%202018.Search in Google Scholar

33. Sandberg S, Fraser CG, Horvath AR, Jansen R, Jones G, Oosterhuis W, et al. Defining analytical performance specifications: Consensus Statement from the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem Lab Med 2015;53:833–5.10.1515/cclm-2015-0067Search in Google Scholar PubMed

34. Aarsand AK, Røraas T, Fernandez-Calle P, Ricos C, Díaz Garzón J, Jonker N, et al. The biological variation data critical appraisal checklist: a standard for evaluating studies on biological variation. Clin Chem 2018;64:501–14.10.1373/clinchem.2017.281808Search in Google Scholar PubMed

35. CLSI. Interference testing in Clinical Chemistry. 3rd ed. CLSI document EP07. Wayne, PA: Clinical and Laboratory Standards Institute, 2018.Search in Google Scholar

36. Petersen PH, Fraser CG, Westgard JO, Larsen ML. Analytical goal-setting for monitoring patients when two analytical methods are used. Clin Chem 1992;38:2256–60.10.1093/clinchem/38.11.2256Search in Google Scholar

37. Minchinela J, Ricós C, Perich C, Fernández-Calle P, Alvarez V, Doménech MV, et al. Base de datos de los componentes de Variación Biológica, con las especificaciones de la calidad analítica (deseable, mínima y óptima). Actualización del año 2014. in Google Scholar

Supplementary Material

The online version of this article offers supplementary material (

Received: 2019-06-11
Accepted: 2019-06-17
Published Online: 2019-07-26
Published in Print: 2019-11-26

©2019 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 25.2.2024 from
Scroll to top button