Investigating the Current Harmonization Status of Tumor Markers Using Global External Quality Assessment Programs: A Feasibility Study.

BACKGROUND: The harmonization status of most tumor markers (TMs) is unknown. We report a feasibility study performed to determine whether external quality assessment (EQA) programs can be used to obtain insights into the current harmonization status of the tumor markers α-fetoprotein (AFP), prostate specific antigen (PSA), carcinoembryonic antigen (CEA), cancer antigen (CA)125, CA15-3 and CA19-9. METHODS: EQA sample results provided by 6 EQA providers (INSTAND [Germany], Korean Association of External Quality Assessment Service [KEQAS, South Korea], National Center for Clinical Laboratories [NCCL, China], United Kingdom National External Quality Assessment Service [UK NEQAS, United Kingdom], Stichting Kwaliteitsbewaking Medische Laboratoriumdiagnostiek [SKML, the Netherlands], and the Royal College of Pathologists of Australasia Quality Assurance Programs [RCPAQAP, Australia]) between 2020 and 2021 were used. The consensus means, calculated from the measurement procedures present in all EQA programs (Abbott Alinity, Beckman Coulter DxI, Roche Cobas, and Siemens Atellica), was used as reference values. Per measurement procedure, the relative difference between consensus mean for each EQA sample and the mean of all patient-pool-based EQA samples were calculated and compared to minimum, desirable, and optimal allowable bias criteria based on biological variation. RESULTS: Between 19040 (CA15-3) and 25398 (PSA) individual results and 56 (PSA) to 76 (AFP) unique EQA samples were included in the final analysis. The mean differences with the consensus mean of patient-pool-based EQA samples for all measurement procedures were within the optimum bias criterion for AFP, the desirable bias for PSA, and the minimum bias criterion for CEA. However, CEA results <8 µg/L exceeded the minimum bias criterion. For CA125, CA15-3, and CA19-9, the harmonization status was outside the minimum bias criterion, with systematic differences identified. CONCLUSIONS: This study provides relevant information about the current harmonization status of 6 tumor markers. A pilot harmonization investigation for CEA, CA125, CA15-3, and CA19-9 would be desirable.

Lung cancer tumor marker analysis: A clinical laboratory perspective.

 Clinical laboratories are responsible for performing lung cancer tumor marker testing as part of routine clinical care. It is their responsibility to guarantee that the reported tumor marker results are reliable and meet the necessary quality standards for proper clinical use. During the different laboratory phases, pre-analytical, analytical and post-analytical, specific steps and processes can introduce errors and generate incorrect clinical interpretation. This editorial briefly outlines critical laboratory issues related to lung cancer tumor markers, specific for each of these three laboratory phases.

Lung cancer biomarkers: Raising the clinical value of the classical and the new ones.

Blood-based diagnostics for lung cancer support the diagnosis, estimation of prognosis, prediction, and monitoring of therapy response in lung cancer patients. The clinical utility of serum tumor markers has considerably increased due to developments in serum protein tumor markers analytics and clinical biomarker studies, the exploration of preanalytical and influencing conditions, the interpretation of biomarker combinations and individual biomarker kinetics, as well as the implementation of biostatistical models. In addition, circulating tumor DNA (ctDNA) and other liquid biopsy markers are playing an increasingly prominent role in the molecular tumor characterization and the monitoring of tumor evolution over time. Thus, modern lung cancer biomarkers may considerably contribute to an individualized companion diagnostics and provide a sensitive guidance for patients throughout the course of their disease. In this special edition on Tumor Markers in Lung Cancer, experts summarize recent developments in clinical laboratory diagnostics of lung cancer and give an outlook on future challenges and opportunities.

Clinical perspectives on serum tumor marker use in predicting prognosis and treatment response in advanced non-small cell lung cancer.

The optimal positioning and usage of serum tumor markers (STMs) in advanced non-small cell lung cancer (NSCLC) care is still unclear. This review aimed to provide an overview of the potential use and value of STMs in routine advanced NSCLC care for the prediction of prognosis and treatment response. Radiological imaging and clinical symptoms have shown not to capture a patient's entire disease status in daily clinical practice. Since STM measurements allow for a rapid, minimally invasive, and safe evaluation of the patient's tumor status in real time, STMs can be used as companion decision-making support tools before start and during treatment. To overcome the limited sensitivity and specificity associated with the use of STMs, tests should only be applied in specific subgroups of patients and different test characteristics should be defined per clinical context in order to answer different clinical questions. The same approach can similarly be relevant when developing clinical applications for other (circulating) biomarkers. Future research should focus on the approaches described in this review to achieve STM test implementation in advanced NSCLC care.

Pre-analytical stability of the CEA, CYFRA 21.1, NSE, CA125 and HE4 tumor markers.

BACKGROUND: For lung cancer, circulating tumor markers (TM) are available to guide clinical treatment decisions. To ensure adequate accuracy, pre-analytical instabilities need to be known and addressed in the pre-analytical laboratory protocols. OBJECTIVE: This study investigates the pre-analytical stability of CA125, CEA, CYFRA 21.1, HE4 and NSE for the following pre-analytical variables and procedures; i) whole blood stability, ii) serum freeze-thaw cycles, iii) electric vibration mixing and iv) serum storage at different temperatures. METHODS: Left-over patient samples were used and for every investigated variable six patient samples were used and analysed in duplicate. Acceptance criteria were based on analytical performance specifications based on biological variation and significant differences with baseline. RESULTS: Whole blood was stable for at least 6 hours for all TM except for NSE. Two freeze-thaw cycles were acceptable for all TM except CYFRA 21.1. Electric vibration mixing was allowed for all TM except for CYFRA 21.1. Serum stability at 4°C was 7 days for CEA, CA125, CYFRA 21.1 and HE4 and 4 hours for NSE. CONCLUSIONS: Critical pre-analytical processing step conditions were identified that, if not taken into account, will result in reporting of erroneous TM results.

Comparing modeling strategies combining changes in multiple serum tumor biomarkers for early prediction of immunotherapy non-response in non-small cell lung cancer.

BACKGROUND: Patients treated with immune checkpoint inhibitors (ICI) are at risk of adverse events (AEs) even though not all patients will benefit. Serum tumor markers (STMs) are known to reflect tumor activity and might therefore be useful to predict response, guide treatment decisions and thereby prevent AEs. OBJECTIVE: This study aims to compare a range of prediction methods to predict non-response using multiple sequentially measured STMs. METHODS: Nine prediction models were compared to predict treatment non-response at 6-months (n = 412) using bi-weekly CYFRA, CEA, CA-125, NSE, and SCC measurements determined in the first 6-weeks of therapy. All methods were applied to six different biomarker combinations including two to five STMs. Model performance was assessed based on sensitivity, while model training aimed at 95% specificity to ensure a low false-positive rate. RESULTS: In the validation cohort, boosting provided the highest sensitivity at a fixed specificity across most STM combinations (12.9% -59.4%). Boosting applied to CYFRA and CEA achieved the highest sensitivity on the validation data while maintaining a specificity >95%. CONCLUSIONS: Non-response in NSCLC patients treated with ICIs can be predicted with a specificity >95% by combining multiple sequentially measured STMs in a prediction model. Clinical use is subject to further external validation.

An LC-MS/MS-based method for the simultaneous quantification of melatonin, cortisol and cortisone in saliva.

Disturbances in the diurnal pattern are associated with several clinical and psychological conditions, including depression and fatigue. Salivary sampling for melatonin, cortisol and cortisone provides a non-invasive method for frequent sampling and obtaining biochemical insight into the diurnal pattern of individuals. Therefore, a new liquid chromatography-tandem mass spectrometry-based method for the measurement of salivary melatonin, cortisol and cortisone was developed and validated. The method required 250 µl saliva, used isotope dilution methodology and was based on a liquid-liquid extraction for sample preparation, reversed-phase chromatography and multiple reaction monitoring on a mass spectrometer for quantitation. The lower limits of quantification obtained were 0.010 nmol/L for melatonin, 0.5 nmol/L for cortisol and 1.00 nmol/L for cortisone and the limits of detection were 0.003 nmol/L, 0.15 nmol/L and 0.1 nmol/L respectively. The method imprecision was ≤14% for all measurands, and the method comparison showed highly comparable results with high correlation coefficients (all ≥0.964). Potential interference of cortisol and cortisone by prednisolone was observed and could be detected by chromatogram review. Typical diurnal patterns for melatonin, cortisol and cortisone were observed in the saliva of 20 cancer survivors who collected saliva throughout the day.

Quality control in the Netherlands; todays practices and starting points for guidance and future research.

OBJECTIVES: Adequate analytical quality of reported results is primarily ensured by performing internal quality control (iQC). Currently, several different iQC practices are in use. As a prelude to the revision of a Dutch guidance document on analytical QC, a questionnaire was sent out to gain insights in the applied practices and the need for guidance. METHODS: A questionnaire, containing 20 multiple-choice questions with possibilities for explanation and comment on iQC practices and aspects was distributed to all clinical chemistry laboratories within the Netherlands. Results were reported descriptively. RESULTS: Responses were received from 27 clinical laboratories (response 43 %). In 30 % the iQC was based on the analytical characteristics only, while 30 % used a 6-Sigma method, 19 % risk-based beyond 6-Sigma and 22 % used an alternative approach. 89 % of laboratories used a virtual analyzer model for iQC setup within one or more laboratory sites. Practices for determining standard deviation (SD) values included determining SD for each new iQC material (35 %), using historical SD values for new materials (35 %), and incorporating clinical tolerances into the SD value (31 %). Furthermore, 44 % of laboratories used patient moving averages for one or more tests. Daily iQC management was based on either "traffic lights" indicating in or out of control status, and review of all QC charts, often using multiple software systems. CONCLUSIONS: A large heterogeneity of iQC practices in clinical laboratories was observed in the Netherlands. Several starting points for further research and/or guidance were identified, particularly in relation to the determination of SD values, the virtual analyzer model and methods to ensure analyzer equivalence.

Self-sampling of blood using a topper and pediatric tubes; a prospective feasibility study for PSA analysis using 120 prostate cancer patients.

OBJECTIVES: Self-collection of blood for diagnostic purposes by blood collection assist devices (BCAD) has gained a lot of momentum. Nonetheless, there are a lack of studies demonstrating the feasibility and reliability of self-collecting capillary blood for routine (immuno)chemistry testing. In this study we describe the topper technology together with pediatric tubes to enable self-collection of blood and investigated its feasibility for PSA testing by prostate cancer patients. METHODS: A total of 120 prostate cancer patients for which a routine follow-up PSA test was requested, were included in this study. Patients received instruction materials and the blood-collection device consisting of a topper, pediatric tube and base-part, and performed the blood collection procedure themselves. Afterwards a questionnaire was filled-in. Finally, PSA was measured on a Roche Cobas Pro. RESULTS: The overall self-sampling success rate was 86.7 %. Furthermore, when specified per age category, a 94.7 % success rate for patients under 70 years and a 25 % success rate for patients of 80 years and older was observed. Venous and self-collected PSA were highly comparable when analyzed by Passing-Bablok regression with a slope of 0.99 and intercept of 0.00011, Spearmans correlation coefficient (0.998) and average self-collected PSA recovery of 99.8 %. CONCLUSIONS: Evidence is presented that self-collected capillary blood by topper and pediatric tube from the finger is feasible, particularly for patients under 70 years. Furthermore, capillary blood self-sampling did not compromise any of the PSA test results. Future validation in a real-world setting, without supervision and including sample stability and logistics, is required.

Technical quality assurance and quality control for medical laboratories: a review and proposal of a new concept to obtain integrated and validated QA/QC plans.

Technical quality assurance (QA) and quality control (QA/QC) are important activities within medical laboratories to ensure the adequate quality of obtained test results. QA/QC tools available at medical laboratories include external QC and internal QC, patient-based real-time quality control (PBRTQC) tools such as moving average quality control (MAQC), limit checks, delta checks, and multivariate checks, and finally, analyzer flagging. Recently, for PBRTQC tools, new optimization and validation methods based on error detection simulation have been developed to obtain laboratory-specific insights into PBRTQC error detection. These developments have enabled implementation and application of these individual tools in routine clinical practice. As a next step, they also enable performance comparison of the individual QA/QC tools and integration of all the individual QA/QC tools in order to obtain the most powerful and efficient QA/QC plans. In this review, a brief overview of the individual QA/QC tools and their characteristics is provided and the error detection simulation approaches are explained. Finally, a new concept entitled integrated quality assurance and control (IQAC) is presented. To enable IQAC, a conceptual framework is suggested and demonstrated for sodium, based on available published data. The proposed IQAC framework provides ways and tools by which the performance of different QA/QC tools can be compared in a so-called QA/QC error detection table to enable optimization and validation of the overall QA/QC plan in terms of alarm rate as well as pre-analytical, analytical, and post-analytical error detection performance.

Testosterone analysis in castrated prostate cancer patients: suitability of the castration cut-off and analytical accuracy of the present-day clinical immunoassays.

OBJECTIVES: Testosterone testing is relevant for evaluating castration adequacy and diagnosis of castration-resistant prostate cancer (PCa). However, the recommended testosterone cut-off of 1.7 nmol/L (50 ng/dL) to define adequate castration is based on consensus and not validated for the automated immunoassays (AIA) used in today's medical laboratories. Furthermore, appropriate population intervals have not been determined by a state-of-the-art assay. We investigated the analytical suitability of this cut-off and the accuracy of the present-day AIAs for testosterone analysis in castrated PCa patients. METHODS: Leftover serum from 120 PCa patients castrated with luteinizing hormone-releasing hormone agonists was analysed for testosterone by five methods: Architect i2000 (Abbott), Access (Beckman), Cobas 6000 (Roche), Atellica (Siemens), LC-MS/MS. For all assays, the castration 95th, 97.5th and 99th percentile upper limits were determined. Furthermore, Passing-Bablok regression, mean bias and Spearman's correlation coefficients were compared to the LC-MS/MS method and total error based on biological variation. RESULTS: All castration upper limits, ranging from 0.472 nmol/L (LC-MS/MS) to 1.25 nmol/L (Access) (95% percentile), were significantly lower than the current castration cut-off (1.7 nmol/L). Slopes of Passing-Bablok regressions comparing the AIA with the LC-MS/MS method ranged from 1.4 (Cobas and Atellica) to 3.8 (Access). The Architect showed the highest correlation with LC-MS/MS (ρ=0.58). All AIA failed to meet the desirable total error criterion. CONCLUSIONS: These results suggest that a lower general testosterone castration cut-off may be more appropriate in evaluating the adequacy of castration in PCa and that present-day AIA lack analytical accuracy to quantify testosterone levels in castrated PCa.

Moving average quality control of routine chemistry and hematology parameters - a toolbox for implementation.

OBJECTIVES: Moving average quality control (MA QC) is a patient-based real-time quality control system. Advantages compared to conventional periodic internal quality control (IQC) include absence of commutability problems and continuous monitoring of performance. We implemented MA QC for multiple routine hematology and chemistry parameters. We describe the evaluation process and provide practical tools to aid MA QC implementation. METHODS: Nine parameters (serum sodium, calcium, bicarbonate and free thyroxine, hemoglobin [Hb], mean corpuscular volume, mean corpuscular hemoglobin concentration [MCHC], reticulocyte count and erythrocyte sedimentation rate [ESR]) were chosen for initial consideration. Using data extractions from the laboratory information system (LIS; General Laboratory Information Management System), evaluation of usefulness and optimization of MA QC settings was performed using bias detection curves. After this, MA QC settings were incorporated in our LIS for further evaluation and implementation in routine care. RESULTS: Three out of nine parameters (Hb, ESR, and sodium) were excluded from MA QC implementation due to high variation and technical issues in the LIS. For the six remaining parameters, MA QC showed added value to IQC and was therefore implemented in the LIS. For three parameters a direct MA alarm work-up method was set up, including newly developed built-in features in the LIS. For the other parameters, we identified MA utilization beyond real-time monitoring. CONCLUSIONS: Implementation of MA QC has added value for our laboratory setting. Additional utilization beyond real-time QC monitoring was identified. We find MA QC especially useful for trend monitoring, detection of small shifts after maintenance and inter-analyzer comparisons.

Validation of a clinical blood-based decision aid to guide immunotherapy treatment in patients with non-small cell lung cancer.

BACKGROUND: The widespread introduction of immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) has led to durable responses but still many patients fail and are treated beyond progression. OBJECTIVE: This study investigated whether readily available blood-based tumor biomarkers allow accurate detection of early non-responsiveness, allowing a timely switch of therapy and cost reduction. METHODS: In a prospective, observational study in patients with NSCLC treated with nivolumab or pembrolizumab, five serum tumor markers were measured at baseline and every other week. Six months disease control as determined by RECIST was used as a measure of clinical response. Patients with a disease control <  6 months were deemed non-responsive. For every separate tumor marker a criterion for predicting of non-response was developed. Each marker test was defined as positive (predictive of non-response) if the value of that tumor marker increased at least 50% from the value at baseline and above a marker dependent minimum value to be determined. Also, tests based on combination of multiple markers were designed. Specificity and sensitivity for predicting non-response was calculated and results were validated in an independent cohort. The target specificity of the test for detecting non-response was set at >  95%, in order to allow its safe use for treatment decisions. RESULTS: A total of 376 patients (training cohort: 180, validation cohort: 196) were included in our analysis. Results for the specificity of the single marker tests in the validation set were CEA: 98·3% (95% CI: 90·9-100%), NSE: 96·5% (95% CI: 87·9-99·6%), SCC: 96·5% (95% CI: 88·1-99·6%), Cyfra21·1 : 91.8% (95% CI: 81·9-97·3%), and CA125 : 86·0% (95% CI: 74·2-93·7%). A test based on the combination of Cyfra21.1, CEA and NSE accurately predicted non-response in 32.3% (95% CI 22.6-43.1%) of patients 6 weeks after start of immunotherapy. Survival analysis showed a significant difference between predicted responders (Median PFS: 237 days (95% CI 184-289 days)) and non-responders (Median PFS: 58 days (95% CI 46-70 days)) (p <  0.001). CONCLUSIONS: Serum tumor marker based tests can be used for accurate detection of non-response in NSCLC, thereby allowing early and safe discontinuation of immunotherapy in a significant subset of patients.

Benefits, limitations, and controversies on patient-based real-time quality control (PBRTQC) and the evidence behind the practice.

BACKGROUND: In recent years, there has been renewed interest in the "old" average of normals concept, now generally referred to as moving average quality control (MA QC) or patient-based real-time quality control (PBRTQC). However, there are some controversies regarding PBRTQC which this review aims to address while also indicating the current status of PBRTQC. CONTENT: This review gives the background of certain newly described optimization and validation methods. It also indicates how QC plans incorporating PBRTQC can be designed for greater effectiveness and/or (cost) efficiency. Furthermore, it discusses controversies regarding the complexity of obtaining PBRTQC settings, the replacement of iQC, and software functionality requirements. Finally, it presents evidence of the added value and practicability of PBRTQC. OUTLOOK: Recent developments in, and availability of, simulation methods to optimize and validate laboratory-specific PBRTQC procedures have enabled medical laboratories to implement PBRTQC in their daily practice. Furthermore, these methods have made it possible to demonstrate the practicability and added value of PBRTQC by means of two prospective "clinical" studies and other investigations. Although internal QC will remain an essential part of any QC plan, applying PBRTQC can now significantly improve its performance and (cost) efficiency.

Implementation of patient-based real-time quality control.

The quest to use patient results as quality control for routine clinical chemistry testing has long been driven by issues of the unavailability and cost of suitable quality control material and the matrix effects of synthetic material. Hematology laboratories were early adopters of average of normals techniques, primarily because of the difficulty in acquiring appropriate, stable quality control material, while in the chemistry laboratories, the perceived advantages and availability of synthetic material outweighed the disadvantages. However, the increasing volume of testing in clinical chemistry plus the capability of computer systems to deal with large and complex calculations has now made the use of patient-based quality control algorithms feasible. The desire to use patient-based quality control is also driven by increasing awareness that common quality control rules and frequency of analysis may fail to detect clinically significant assay biases. The non-commutability of quality control material has also become a problem as laboratories seek to harmonize results across regions and indeed globally. This review describes the history of patient-based quality control in clinical chemistry, summarizes the various approaches that can be implemented by laboratory professionals, and discusses how patient-based quality control can be integrated with traditional quality control techniques.

Understanding Patient-Based Real-Time Quality Control Using Simulation Modeling.

BACKGROUND: Patient-based real-time quality control (PBRTQC) avoids limitations of traditional quality control methods based on the measurement of stabilized control samples. However, PBRTQC needs to be adapted to the individual laboratories with parameters such as algorithm, truncation, block size, and control limit. METHODS: In a computer simulation, biases were added to real patient results of 10 analytes with diverse properties. Different PBRTQC methods were assessed on their ability to detect these biases early. RESULTS: The simulation based on 460 000 historical patient measurements for each analyte revealed several recommendations for PBRTQC. Control limit calculation with "percentiles of daily extremes" led to effective limits and allowed specification of the percentage of days with false alarms. However, changes in measurement distribution easily increased false alarms. Box-Cox but not logarithmic transformation improved error detection. Winsorization of outlying values often led to a better performance than simple outlier removal. For medians and Harrell-Davis 50 percentile estimators (HD50s), no truncation was necessary. Block size influenced medians substantially and HD50s to a lesser extent. Conversely, a change of truncation limits affected means and exponentially moving averages more than a change of block sizes. A large spread of patient measurements impeded error detection. PBRTQC methods were not always able to detect an allowable bias within the simulated 1000 erroneous measurements. A web application was developed to estimate PBRTQC performance. CONCLUSIONS: Computer simulations can optimize PBRTQC but some parameters are generally superior and can be taken as default.

Recommendation for performance verification of patient-based real-time quality control.

Patient-based real-time quality control (PBRTQC) is a laboratory tool for monitoring the performance of the testing process. It includes well-established procedures like Bull's algorithm, average of nomals, moving median, moving average (MA) and exponentially (weighted) MAs. Following the setup and optimization processes, a key step prior to the routine implementation of PBRTQC is the verification and documentation of the performance of the PBRTQC as part of the laboratory quality system. This verification process should provide a realistic representation of the performance of the PBRTQC in the environment it is being implemented in, to allow proper risk assessment by laboratory practitioners. This document focuses on the recommendation on performance verification of PBRTQC prior to implementation.

Patient-Based Real-Time Quality Control: Review and Recommendations.

For many years the concept of patient-based quality control (QC) has been discussed and implemented in hematology laboratories; however, the techniques have not been widely implemented in clinical chemistry. This is mainly because of the complexity of this form of QC, as it needs to be optimized for each population and often for each analyte. However, the clear advantages of this form of QC, together with the ongoing realization of the shortcomings of "conventional" QC, have driven a need to provide guidance to laboratories to assist in deploying patient-based QC. This overview describes the components of a patient-based QC system (calculation algorithm, block size, truncation limits, control limits) and the relationship of these to the analyte being controlled. We also discuss the need for patient-based QC system optimization using patient data from the individual testing laboratory to reliably detect systematic errors while ensuring that there are few false alarms. The term patient-based real-time quality control covers many activities that use data from patient samples to detect analytical errors. These activities include the monitoring of patient population parameters such as the mean or median analyte value or using single within-patient changes such as the delta check. In this report, we will restrict the discussion to population-based parameters. This overview is intended to serve as a guide for the implementation of a patient-based QC system. The report does not cover the clinical evaluation of the population.

Moving average quality control: principles, practical application and future perspectives.

Moving average quality control (MA QC) was described decades ago as an analytical quality control instrument. Although a potentially valuable tool, it is struggling to meet expectations due to its complexity and need for evidence-based guidance. For this review, relevant literature and the world wide web were examined in order to (i) explain the basic concepts and current understanding of MA QC, (ii) discuss moving average (MA) optimization methods, (iii) gain insight into practical aspects related to applying MA in daily practice and (iv) describe future prospects to enable more widespread acceptance and application of MA QC. Each of the MA QC optimization methods currently available has their own advantages and disadvantages. Recently developed simulation methods provide realistic error detecting properties for MA QC and are available for laboratories. Operational MA management issues have been identified that allow developers of MA software to upgrade their packages to support optimal MA QC application and guide laboratories on MA management issues, such as MA alarm workup. The new insights into MA QC characteristics and operational issues, together with supporting online tools, may promote more widespread acceptance and application of MA QC.

Design and implementation of quality control plans that integrate moving average and internal quality control: incorporating the best of both worlds.

Background New moving average quality control (MA QC) optimization methods have been developed and are available for laboratories. Having these methods will require a strategy to integrate MA QC and routine internal QC. Methods MA QC was considered only when the performance of the internal QC was limited. A flowchart was applied to determine, per test, whether MA QC should be considered. Next, MA QC was examined using the MA Generator (www.huvaros.com), and optimized MA QC procedures and corresponding MA validation charts were obtained. When a relevant systematic error was detectable within an average daily run, the MA QC was added to the QC plan. For further implementation of MA QC for continuous QC, MA QC management software was configured based on earlier proposed requirements. Also, protocols for the MA QC alarm work-up were designed to allow the detection of temporary assay failure based on previously described experiences. Results Based on the flowchart, 10 chemistry, two immunochemistry and six hematological tests were considered for MA QC. After obtaining optimal MA QC settings and the corresponding MA validation charts, the MA QC of albumin, bicarbonate, calcium, chloride, creatinine, glucose, magnesium, potassium, sodium, total protein, hematocrit, hemoglobin, MCH, MCHC, MCV and platelets were added to the QC plans. Conclusions The presented method allows the design and implementation of QC plans integrating MA QC for continuous QC when internal QC has limited performance.