The European Organisation of External Quality Assurance Providers in Laboratory Medicine (EQALM) Statement: guidelines for publishing about interlaboratory comparison studies (PubILC).

Data and results from interlaboratory comparison (ILC) studies, external quality assessment (EQA) and proficiency testing (PT) activities are important and valuable contributions both to the further development of all disciplines of medical laboratory diagnostics, and to the evaluation and comparison of in vitro diagnostic assays. So far, however, there are no recommendations as to which essential items should be addressed in publications on interlaboratory comparisons. The European Organization of External Quality Assurance Providers in Laboratory Medicine (EQALM) recognized the need for such recommendations, and these were developed by a group of experts. The result of this endeavor is the EQALM Statement on items recommended to be addressed in publications on interlaboratory comparison activities (PubILC), in conjunction with a user-friendly checklist. Once adopted by authors and journals, the EQALM Statement will ensure essential information and/or study-related facts are included within publications on EQA/PT activities.

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.

Six Sigma - is it time to re-evaluate its value in laboratory medicine?

The Sigma metric is widely used in laboratory medicine.

A model for managing quality control for a network of clinical chemistry instruments measuring the same analyte.

OBJECTIVES: Monitoring quality control for a laboratory or network with multiple instruments measuring the same analyte is challenging. We present a retrospective assessment of a method to detect medically significant out-of-control error conditions across a group of instruments measuring the same analyte. The purpose of the model was to ensure that results from any of several instruments measuring the same analytes in a laboratory or a network of laboratories provide comparable results and reduce patient risk. Limited literature has described how to manage QC in these very common situations. METHODS: Single Levey-Jennings control charts were designed using peer group target mean and control limits for five common clinical chemistry analytes in a network of eight analyzers in two different geographical sites. The QC rules used were 13s/22s/R4s, with the mean being a peer group mean derived from a large population of the same instrument and the same QC batch mean and a group CV. The peer group data used to set the target means and limits were from a quality assurance program supplied by the instrument supplier. Both statistical and clinical assessments of significance were used to evaluate QC failure. Instrument bias was continually monitored. RESULTS: It was demonstrated that the biases of each instrument were not statistically or clinically different compared to the peer group's average over six months from February 2023 until July 2023. Over this period, the error rate determined by the QC model was consistent with statistical expectations for the 13s/22s/R4s rule. There were no external quality assurance failures, and no detected error exceeded the TEa (medical impact). Thus, the combined statistical/clinical assessment reduced unnecessary recalibrations and the need to amend results. CONCLUSIONS: This paper describes the successful implementation of a quality control model for monitoring a network of instruments, measuring the same analytes and using externally provided quality control targets. The model continually assesses individual instrument bias and imprecision while ensuring all instruments in the network meet clinical goals for quality. The focus of this approach is on detecting medically significant out-of-control error conditions.

Sharing reference intervals and monitoring patients across laboratories - findings from a likely commutable external quality assurance program.

OBJECTIVES: Laboratory results are increasingly interpreted against common reference intervals (CRIs), published clinical decision limits, or previous results for the same patient performed at different laboratories. However, there are no established systems to determine whether current analytical performance justifies these interpretations. We analysed data from a likely commutable external quality assurance program (EQA) to assess these interpretations. METHODS: The use of CRIs was assessed by evaluating instrument group medians against minimum specifications for bias. The use of clinical decision limits was assessed using specifications from professional bodies, and the monitoring of patients by testing at different laboratories was assessed by comparing all-laboratory imprecision to within-subject biological variation. RESULTS: Five of the 18 analytes with Australasian CRIs did not meet specification for all instrument groups. Among these, calcium and magnesium failed for one instrument group out of seven, while bicarbonate, chloride, and lipase failed for two instrument groups. Of the 18 analytes reviewed currently without CRIs in Australasia, 10 candidates were identified. Among analytes with clinical decision limits, i.e. lipids, glucose, and vitamin D, only triglycerides met both bias and imprecision specifications, while vitamin D met the imprecision specification. Monitoring patients by testing at different laboratories was supported for 15 of the 46 (33 %) analyte-method principles groups that met minimum imprecision specifications. CONCLUSIONS: Analysis of data from commutable EQA programs can provide a mechanism for monitoring whether analytical performance justifies the interpretations made in contemporary laboratory practice. EQA providers should establish systems for routinely providing this information to the laboratory community.

Enhanced patient-based real-time quality control using the graph-based anomaly detection.

OBJECTIVES: Patient-based real-time quality control (PBRTQC) is an alternative tool for laboratories that has gained increasing attention. Despite the progress made by using various algorithms, the problems of data volume imbalance between in-control and out-of-control results, as well as the issue of variation remain challenges. We propose a novel integrated framework using anomaly detection and graph neural network, combining clinical variables and statistical algorithms, to improve the error detection performance of patient-based quality control. METHODS: The testing results of three representative analytes (sodium, potassium, and calcium) and eight independent variables of patients (test date, time, gender, age, department, patient type, and reference interval limits) were collected. Graph-based anomaly detection network was modeled and used to generate control limits. Proportional and random errors were simulated for performance evaluation. Five mainstream PBRTQC statistical algorithms were chosen for comparison. RESULTS: The framework of a patient-based graph anomaly detection network for real-time quality control (PGADQC) was established and proven feasible for error detection. Compared with classic PBRTQC, the PGADQC showed a more balanced performance for both positive and negative biases. For different analytes, the average number of patient samples until error detection (ANPed) of PGADQC decreased variably, and reductions could reach up to approximately 95 % at a small bias of 0.02 taking calcium as an example. CONCLUSIONS: The PGADQC is an effective framework for patient-based quality control, integrating statistical and artificial intelligence algorithms. It improves error detection in a data-driven fashion and provides a new approach for PBRTQC from the data science perspective.

Machine Learning in Laboratory Medicine: Recommendations of the IFCC Working Group.

BACKGROUND: Machine learning (ML) has been applied to an increasing number of predictive problems in laboratory medicine, and published work to date suggests that it has tremendous potential for clinical applications. However, a number of groups have noted the potential pitfalls associated with this work, particularly if certain details of the development and validation pipelines are not carefully controlled. METHODS: To address these pitfalls and other specific challenges when applying machine learning in a laboratory medicine setting, a working group of the International Federation for Clinical Chemistry and Laboratory Medicine was convened to provide a guidance document for this domain. RESULTS: This manuscript represents consensus recommendations for best practices from that committee, with the goal of improving the quality of developed and published ML models designed for use in clinical laboratories. CONCLUSIONS: The committee believes that implementation of these best practices will improve the quality and reproducibility of machine learning utilized in laboratory medicine. SUMMARY: We have provided our consensus assessment of a number of important practices that are required to ensure that valid, reproducible machine learning (ML) models can be applied to address operational and diagnostic questions in the clinical laboratory. These practices span all phases of model development, from problem formulation through predictive implementation. Although it is not possible to exhaustively discuss every potential pitfall in ML workflows, we believe that our current guidelines capture best practices for avoiding the most common and potentially dangerous errors in this important emerging field.

The next wave of innovation in laboratory automation: systems for auto-verification, quality control and specimen quality assurance.

Laboratory automation in clinical laboratories has made enormous differences in patient outcomes, with a wide range of tests now available that are accurate and have a rapid turnaround. Total laboratory automation (TLA) has mechanised tube handling, sample preparation and storage in general chemistry, immunoassay, haematology, and microbiology and removed most of the tedious tasks involved in those processes. However, there are still many tasks that must be performed by humans who monitor the automation lines. We are seeing an increase in the complexity of the automated laboratory through further platform consolidation and expansion of the reach of molecular genetics into the core laboratory space. This will likely require rapid implementation of enhanced real time quality control measures and these solutions will generate a significantly greater number of failure flags. To capitalise on the benefits that an improved quality control process can deliver, it will be important to ensure that an automation process is implemented simultaneously with enhanced, real time quality control measures and auto-verification of patient samples in middleware. Therefore, it appears that the best solution may be to automate those critical decisions that still require human intervention and therefore include quality control as an integral part of total laboratory automation.

The effect of the immunoassay curve fitting routine on bias in troponin.

OBJECTIVES: Unlike many dose-response curves used in clinical chemistry, the immunoassay curve used to quantitate measurands is often sigmoidal rather than linear. Consequently, a more complex curve fitting model is required. Various models are available, but they can introduce bias, and there can be little awareness of why this error can be introduced. CONTENT: These curve-fitting models include those based on the law of mass-action, empirical models such as splines or linearization models such as the log/logit function. All these models involve assumptions, which can introduce bias as the dose-response curve is 'forced' to fit or minimize the distance between the standard concentration points to the theoretical curve. The most common curve fitting model is the four or five parameter model, which uses four or five parameters to fit a sigmoidal curve to a set of standard points. SUMMARY AND OUTLOOK: Measurement of cardiac troponin is an important element in establishing a diagnosis of acute myocardial infarction. We use troponin, a cardiac biomarker, to demonstrate the potential effect of the bias that the curve fit could introduce. Troponin is used for both rule-in and rule-out decisions at different concentrations and at either end of the dose-response curve. The curve fitting process can cause lot-to-lot reagent (and calibrator) variation in immunoassay. However, laboratory staff need to be aware of this potential source of error and why it occurs. Understanding how the error occurs leads to a greater awareness of the importance of validating new reagent/calibrator assessment using patient samples with concentrations at crucial decision points.

Challenges in antibody titration for ABO-incompatible renal transplantation.

BACKGROUND AND OBJECTIVES: Accurate and regular monitoring of anti-A and anti-B titres pre- and post-transplantation plays a crucial role in the clinical management of patients receiving ABO-incompatible renal transplants. There is no standardized protocol or an external quality assurance program (EQA) currently available for this testing in Australia. The aim of this study was to investigate the diversity of techniques, test platforms and reagents that were currently in use in various laboratories with the aim of developing an EQA. MATERIALS AND METHODS: An online survey was sent to the participants enrolled with the Royal College of Pathologists of Australasia Quality Assurance Program (RCPAQAP) to assess their interest in participation in the pilot study. A total of 24 participants who expressed interest were sent the group O plasma, A1 , A2 and B cells to perform ABO titration using their own methods. RESULTS: Participants reported a wide range of titre results, from 8 to 1024 for the anti-A titre using A1 cells, from 2 to 128 for anti-A titre using A2 cells and from neat to 32 for anti-B titre using B cells. CONCLUSION: There was a wide variation in titre results between and within different technologies. These findings demonstrate the need for an ABO titration EQA. Development of a standard technique and participation in an EQA program should, over time, reduce variation and enable transferrable results across testing centres, which will assist in consistent clinical interpretation and better outcomes for patients.

Metrological traceability and clinical traceability of laboratory results - the role of commutability in External Quality Assurance.

The role of an External Quality Assurance (EQA) program is generally seen as providing a service to routine laboratories that their analytical performance is satisfactory and stimulating corrective action in the event of poor results. It is recognised that an ideal EQA program uses materials that are commutable with patient samples and have values assigned by higher-order reference methods. Despite this, most routine EQA programs use materials without verified commutability and use consensus means (based on either peer group or all laboratories) as target values. We propose an ongoing role for EQA programs using non-commutable materials and consensus targets to support the measurement services of routine laboratories. This is provided the relevant comparators supplied by the laboratory, e.g. reference intervals and clinical decision points, are based on the same or equivalent measurement system as is used by the laboratory. Materials without verified commutability often have certain practical advantages, which may include the range of analyte concentrations, verified stability, replicate samples and, significantly, lower costs. Laboratories using such programs need to be aware of the limitations, especially comparing results from different measurement systems. However, we also recognise that as well as individual laboratories, data from EQA programs informs manufacturers, professional organisations, clinical guideline writers and other medical bodies For consideration beyond an individual laboratory, proper assessment of differences between measurement systems (results harmonization) and demonstration of correct implementation of metrological traceability (methods trueness) become vital, and for that purpose, commutability of EQA materials and traceability of target values are required.

External quality assessment providers' services appear to more impact the immunohaematology performance of laboratories than national regulatory and economic conditions.

OBJECTIVES: Medical laboratories may, at their own discretion, exceed but not undercut regulatory quality requirements. Available economic resources, however, may drive or hinder eagerness to exceed minimum requirements. Depending on the respective scopes of regulatory and economic framework conditions, differing levels of quality efforts to safeguard laboratory performance can be anticipated. However, this has not yet been investigated. METHODS: Immunohaematology external quality assessment (EQA) results collected by 26 EQA providers from their participant laboratories in 73 countries from 2004 to 2019 were evaluated. Error rates were aggregated in groups according to the respective national regulatory and economic framework conditions, to whether or not expert advice was provided in case of incorrect results, and the frequency of EQA samples. RESULTS: These representative data indicate no association between national regulatory (mandatory participation in EQA, monitoring of performance of individual laboratories by authorities, financial consequences of incorrect results) and economic (level of national income, share of national health expenditure) conditions to the quality performance of medical laboratories in immunohaematology. However, EQA providers' support for laboratories in the event of incorrect results appear to be associated with lower error rates, but a high EQA sample frequency with higher error rates. CONCLUSIONS: Further research into the impact of introducing or changing services of EQA providers is needed to confirm the results found in this first of its kind study.

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.

Harmonization status of procalcitonin measurements: what do comparison studies and EQA schemes tell us?

Sepsis represents a global health priority because of its high mortality and morbidity. The key to improving prognosis remains an early diagnosis to initiate appropriate antibiotic treatment. Procalcitonin (PCT) is a recognized biomarker for the early indication of bacterial infections and a valuable tool to guide and individualize antibiotic treatment. To meet the increasing demand for PCT testing, numerous PCT immunoassays have been developed and commercialized, but results have been questioned. Many comparison studies have been carried out to evaluate analytical performance and comparability of results provided by the different commercially available immunoassays for PCT, but results are conflicting. External Quality Assessment Schemes (EQAS) for PCT constitute another way to evaluate results comparability. However, when making this comparison, it must be taken into account that the variety of EQA materials consist of different matrices, the commutability of which has not yet been investigated. The present study gathers results from all published comparison studies and results from 137 EQAS surveys to describe the current state-of-the-art harmonization of PCT results. Comparison studies globally highlight a significant variability of measurement results that nonetheless seem to have a moderate impact on medical decision-making. For their part, EQAS for PCT provides highly discrepant estimates of the interlaboratory CV. Due to differences in commutability of the EQA materials, the results from different peer groups could not be compared. To improve the informative value of the EQA data, the existing limitations such as non-harmonized conditions and suboptimal and/or unknown commutability of the EQA materials have to be overcome. The study highlights the need for commutable reference materials that could be used to properly evaluate result comparability and possibly standardize calibration, if necessary. Such an initiative would further improve the safe use of PCT in clinical routine.

Comparison of potential pharmacokinetic drug interactions in patients with atrial fibrillation and changing from warfarin to non-vitamin K oral anticoagulant therapy.

There are now anticoagulant choices with proposed advantages of non-vitamin K oral anticoagulants (NOACs) over warfarin being less routine monitoring and less drug interactions. Interacting medication can impact the efficacy and safety of anticoagulant therapy with management remaining clinically challenging. There have been limited studies comparing the potential for pharmacokinetic (PK) drug interactions between different anticoagulants. Therefore, the aim of this study was to compare potential PK interactions in patients with atrial fibrillation (AF) changing from warfarin to NOAC therapy. A retrospective analysis was conducted of patients with AF enrolled in a dedicated warfarin program but exiting this program to commence a NOAC. Patient data was collected, and concurrent medications were utilised to identify potential PK drug interactions with both warfarin and the chosen NOAC therapy. Patients were grouped according to the number of medications with potential PK interactions and comparisons made between groups. Of the 712 eligible patients who ceased warfarin to commence a NOAC, most commenced either apixaban (45.9%) or rivaroxaban (41.9%). When comparing warfarin to NOACs, there were significant differences in the proportion of patients taking no medication with potential PK drug interactions (46.9% vs 62.8%, p < 0.0001), and taking one (35.2% vs 28.5%, p = 0.0067) and two (14.5% vs 7.3%, p < 0.0001) potentially PK interacting medications. This study found when patients with AF were switched from warfarin to a NOAC, the potential for PK drug interactions significantly reduced but remained around 40%. Identifying and managing potential PK drug interactions with NOACs remains a priority to optimise clinical benefit of these anticoagulants.

COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy-a design thinking approach.

BACKGROUND: Health systems around the world have been forced to make choices about how to prioritize care, manage infection control and maintain reserve capacity for future disease outbreaks. Primary healthcare has moved into the front line as COVID-19 testing transitions from hospitals to multiple providers, where tracking testing behaviours can be fragmented and delayed. Pooled general practice data are a valuable resource which can be used to inform population and individual care decision-making. This project aims to examine the feasibility of using near real-time electronic general practice data to promote effective care and best-practice policy. METHODS: The project will utilize a design thinking approach involving all collaborators (primary health networks [PHNs], general practices, consumer groups, researchers, and digital health developers, pathology professionals) to enhance the development of meaningful and translational project outcomes. The project will be based on a series of observational studies utilizing near real-time electronic general practice data from a secure and comprehensive digital health platform [POpulation Level Analysis and Reporting (POLAR) general practice data warehouse]. The study will be carried out over 1.5 years (July 2020-December 2021) using data from over 450 general practices within three Victorian PHNs and Gippsland PHN, Eastern Melbourne PHN and South Eastern Melbourne PHN, supplemented by data from consenting general practices from two PHNs in New South Wales, Central and Eastern Sydney PHN and South Western Sydney PHN. DISCUSSION: The project will be developed using a design thinking approach, leading to the building of a meaningful near real-time COVID-19 geospatial reporting framework and dashboard for decision-makers at community, state and nationwide levels, to identify and monitor emerging trends and the impact of interventions/policy decisions. This will integrate timely evidence about the impact of the COVID-19 pandemic related to its diagnosis and treatment, and its impact across clinical, population and general practice levels.

Time to Stable Therapeutic Range on Initiation of Warfarin as an Indicator of Control.

OBJECTIVES: Warfarin remains widely used with a time in therapeutic range (TiTR) above 65% recommended for best outcomes. Patients not achieving or maintaining this warfarin control may be better suited to alternate anticoagulants. Despite this, there is limited data defining a suitable trial time in patients initiating warfarin therapy, therefore the aim of this study was to determine the mean time to stable therapeutic range (TtSTR). MATERIALS AND METHODS: Retrospective data was collected for patients with atrial fibrillation enrolled in a dedicated warfarin program at a private pathology practice within 7 days of warfarin initiation. TiTR at specified timepoints was calculated and median TtSTR determined as defined by TiTR ≥ 65% over three months. Comparisons were made of populations with TtSTR above or below the median. RESULTS: The 566 patients included in the study had a mean TiTR of 64.9±16.5% at month three and median TtSTR of six months. Patients with TtSTR≤6 months achieved a mean TiTR of 68.9±12.8% at month two and maintained a TiTR over 75% from month 3 to 24. Patients with a TtSTR>6 months obtained a TiTR of 66.4±10.6% at month nine and continued to achieve lower TiTR throughout the 24 months study period. CONCLUSIONS: A majority of patients can achieve a stable TiTR above 65% within six months so review at six to nine months is likely to be a good indicator of warfarin control and to determine if patients should continue warfarin or switch to alternate anticoagulant therapy.

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.

From Somatic Variants Toward Precision Oncology: An Investigation of Reporting Practice for Next-Generation Sequencing-Based Circulating Tumor DNA Analysis.

BACKGROUND: With the accelerated development of next-generation sequencing (NGS), identified variants, and targeted therapies, clinicians who confront the complicated and multifarious genetic information may not effectively incorporate NGS-based circulating tumor DNA (ctDNA) analysis into routine patient care. Consequently, standardized ctDNA testing reports are of vital importance. In an effort to guarantee high-quality reporting performance, we conducted an investigation of the current detection and reporting practices for NGS-based ctDNA analysis. MATERIALS AND METHODS: A set of simulated ctDNA samples with known variants at known allelic frequencies and a corresponding case scenario were distributed to 66 genetic testing laboratories for ctDNA analysis. Written reports were collected to evaluate the detection accuracy, reporting integrity, and information sufficiency using 21 predefined criteria. RESULTS: Current reporting practices for NGS-based ctDNA analysis were found to be far from satisfactory, especially regarding testing interpretation and methodological details. Only 42.4% of laboratories reported the results in complete concordance with the expected results. Moreover, 74.2% of reports only listed aberrations with direct and well-known treatment consequences for the tumor type in question. Genetic aberrations for which experimental agents and/or drug access programs are available may thus be overlooked. Furthermore, methodological details for the interpretation of results were missing from the majority of reports (87.9%). CONCLUSION: This proof-of-principle study suggests that the capacity for accurate identification of variants, rational interpretation of genotypes, comprehensive recommendation of potential medications, and detailed description of methodologies need to be further improved before ctDNA analysis can be formally implemented in the clinic. IMPLICATIONS FOR PRACTICE: Accurate, comprehensive, and standardized clinical sequencing reports can help to translate complex genetic information into patient-centered clinical decisions, thereby shepherding precision oncology into daily practice. However, standards, guidelines, and quality requirements for clinical reports of next-generation sequencing (NGS)-based circulating tumor DNA (ctDNA) analysis are currently absent. By using a set of simulated clinical ctDNA samples and a corresponding case scenario, current practices were evaluated to identify deficiencies in clinical sequencing reports of ctDNA analysis. The recommendations provided here may serve as a roadmap for the improved implementation of NGS-based ctDNA analysis in the clinic.

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.