Screening for Colorectal Cancer: The Role of Clinical Laboratories

BACKGROUND

Colorectal cancer (CRC) is a leading cause of cancer incidence and mortality. Screening can result in reductions in incidence and mortality, but there are many challenges to uptake and follow-up.

CONTENT

Here, we will review the changing epidemiology of CRC, including increasing trends for early and later onset CRC; evidence to support current and emerging screening strategies, including noninvasive stool and blood-based tests; key challenges to ensuring uptake and high-quality screening; and the critical role that clinical laboratories can have in supporting health system and public health efforts to reduce the burden of CRC on the population.

SUMMARY

Clinical laboratories have the opportunity to play a seminal role in optimizing early detection and prevention of CRC.

Technical Note: Comparison of Alinity c Hemoglobin A1c Immunoassay with Premier Hb9210 Automated HPLC Assay: A Preliminary Report

OBJECTIVE

We utilized Premier Hb9210 analyzer (HPLC method; Trinity Biotech, Jamestown, NY) for measuring HBA1c in whole blood. As our laboratory is transitioning to Abbott system, we compared HbA1c values obtained by Alinity c and Premier Hb9210.

METHODS

The Premier Hb9210 analyzer is based on boronate affinity high performance liquid chromatography with analytical measurement range of 3.8 to 18.5%. The Alinity c Hemoglobin A1c assay measured both total hemoglobin and HbA1c (enzymatic assay) in whole blood and then calculated %HbA1c. The analytical measurement range of this assay is 4 to 14% of HbA1c. We evaluated the analytical performance of Alinity c HbA1c by evaluating precision and also comparing 77 clinical samples with our reference HPLC method.

RESULTS

Both Alinity c HbA1c and Premier HB9210 have excellent total precision. Plotting HbA1c results obtained by the Premier Hb9210 analyzer in the x-axis (currently used reference method) and the corresponding values obtained by the Alinity c assay, we observed the following regression equation: y=0.9473x+0.1548 ( n=77, r=0.99).

DISCUSSION

Our result indicates that HbA1c enzymatic assay on the Alinity c analyzer showed values comparable to HPLC method. However, at the decision points (2.8% average negative bias at >6.4% and 3.3% average negative bias at 7%), HbA1c values obtained by the Alinity c analyzer were lower than the reference method.

CONCLUSIONS

We conclude that HbA1c assay on the Alinity c analyzer is a viable alternative to HPLC for measuring HbA1c in clinical laboratories but values at the decision points must be interpreted with caution and if necessary should be repeated by a reference HPLC method.

The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.

Contrastive Transfer Learning for Prediction of Adverse Events in Hospitalized Patients

OBJECTIVE

Deterioration index (DI) is a computer-generated score at a specific frequency that represents the overall condition of hospitalized patients using a variety of clinical, laboratory and physiologic data. In this paper, a contrastive transfer learning method is proposed and validated for early prediction of adverse events in hospitalized patients using DI scores.

METHODS AND PROCEDURES

An unsupervised contrastive learning (CL) model with a classifier is proposed to predict adverse outcome using a single temporal variable (DI scores). The model is pretrained on an unsupervised fashion with large-scale time series data and fine-tuned with retrospective DI score data.

RESULTS

The performance of this model is compared with supervised deep learning models for time series classification. Results show that unsupervised contrastive transfer learning with a classifier outperforms supervised deep learning solutions. Pretraining of the proposed CL model with large-scale time series data and fine-tuning that with DI scores can enhance prediction accuracy.

CONCLUSION

A relationship exists between longitudinal DI scores of a patient and the corresponding outcome. DI scores and contrastive transfer learning can be used to predict and prevent adverse outcomes in hospitalized patients.

CLINICAL IMPACT

This paper successfully developed an unsupervised contrastive transfer learning algorithm for prediction of adverse events in hospitalized patients. The proposed model can be deployed in hospitals as an early warning system for preemptive intervention in hospitalized patients, which can mitigate the likelihood of adverse outcomes.

Recommendations for Setting a Criterion and Assessing Commutability of Sample Materials Used in External Quality Assessment/Proficiency Testing Schemes

It is important for external quality assessment materials (EQAMs) to be commutable with clinical samples; i.e., they should behave like clinical samples when measured using end-user clinical laboratory in vitro diagnostic medical devices (IVD-MDs). Using commutable EQAMs makes it possible to evaluate metrological traceability and/or equivalence of results between IVD-MDs. The criterion for assessing commutability of an EQAM between 2 IVD-MDs is that its result should be within the prediction interval limits based on the statistical distribution of the clinical sample results from the 2 IVD-MDs being compared. The width of the prediction interval is, among other things, dependent on the analytical performance characteristics of the IVD-MDs. A presupposition for using this criterion is that the differences in nonselectivity between the 2 IVD-MDs being compared are acceptable. An acceptable difference in nonselectivity should be small relative to the analytical performance specifications used in the external quality assessment scheme. The acceptable difference in nonselectivity is used to modify the prediction interval criterion for commutability assessment. The present report provides recommendations on how to establish a criterion for acceptable commutability for EQAMS, establish the difference in nonselectivity that can be accepted between IVD-MDs, and perform a commutability assessment. The report also contains examples for performing a commutability assessment of EQAMs.

High prevalence group testing in epidemiology with geometrically inspired algorithms

Demand for mass surveillance during peak times of the SARS-CoV-2 pandemic caused high workload for clinical laboratories. Efficient and cost conserving testing designs by means of group testing can substantially reduce resources during possible future emergency situations. The novel hypercube algorithm proposed by Mutesa et al. 2021 published in Nature provides methodological proof of concept and points out the applicability to epidemiological testing. In this work, the algorithm is explored and expanded for settings with high group prevalence. Numerical studies investigate the limits of the adapted hypercube methodology, allowing to optimize pooling designs for specific requirements (i.e. number of samples and group prevalence). Hyperparameter optimization is performed to maximize test-reduction. Standard deviation is examined to investigate resilience and precision. Moreover, empirical validation was performed by elaborately pooling SARS-CoV-2 virus samples according to numerically optimized pooling designs. Laboratory experiments with SARS-CoV-2 sample groups, ranging from 50 to 200 items, characterized by group prevalence up to 10%, are successfully processed and analysed. Test-reductions from 50 to 72.5% were achieved in the experimental setups when compared to individual testing. Higher theoretical test-reduction is possible, depending on the number of samples and the group prevalence, indicated by simulation results.

AI Chatbots in Clinical Laboratory Medicine: Foundations and Trends

BACKGROUND

Artificial intelligence (AI) conversational agents, or chatbots, are computer programs designed to simulate human conversations using natural language processing. They offer diverse functions and applications across an expanding range of healthcare domains. However, their roles in laboratory medicine remain unclear, as their accuracy, repeatability, and ability to interpret complex laboratory data have yet to be rigorously evaluated.

CONTENT

This review provides an overview of the history of chatbots, two major chatbot development approaches, and their respective advantages and limitations. We discuss the capabilities and potential applications of chatbots in healthcare, focusing on the laboratory medicine field. Recent evaluations of chatbot performance are presented, with a special emphasis on large language models such as the Chat Generative Pre-trained Transformer in response to laboratory medicine questions across different categories, such as medical knowledge, laboratory operations, regulations, and interpretation of laboratory results as related to clinical context. We analyze the causes of chatbots' limitations and suggest research directions for developing more accurate, reliable, and manageable chatbots for applications in laboratory medicine.

SUMMARY

Chatbots, which are rapidly evolving AI applications, hold tremendous potential to improve medical education, provide timely responses to clinical inquiries concerning laboratory tests, assist in interpreting laboratory results, and facilitate communication among patients, physicians, and laboratorians. Nevertheless, users should be vigilant of existing chatbots' limitations, such as misinformation, inconsistencies, and lack of human-like reasoning abilities. To be effectively used in laboratory medicine, chatbots must undergo extensive training on rigorously validated medical knowledge and be thoroughly evaluated against standard clinical practice.

The LEAP checklist for Laboratory Evaluation and Analytical Performance characteristics reporting of clinical measurement procedures

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.

The LEAP checklist for Laboratory Evaluation and Analytical Performance Characteristics reporting of clinical measurement procedures

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript.The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.

Design of an algorithm for the detection of intravenous fluid contamination in clinical laboratory samples

OBJECTIVES

Contamination of blood samples from patients receiving intravenous fluids is a common error with potential risk to the patient. Algorithms based on the presence of aberrant results have been described but have the limitation that not all infusion fluids have the same composition. Our objective is to develop an algorithm based on the detection of the dilution observed on the analytes not usually included in infusion fluids.

METHODS

A group of 89 cases was selected from samples flagged as contaminated. Contamination was confirmed by reviewing the clinical history and comparing the results with previous and subsequent samples. A control group with similar characteristics was selected. Eleven common biochemical parameters not usually included in infusion fluids and with low intraindividual variability were selected. The dilution in relation to the immediate previous results was calculated for each analyte and a global indicator, defined as the percentage of analytes with significant dilution, was calculated. ROC curves were used to define the cut-off points.

RESULTS

A cut-off point of 20 % of dilutional effect requiring also a 60 % dilutional ratio achieved a high specificity (95 % CI 91-98 %) with an adequate sensitivity (64 % CI 54-74 %). The Area Under Curve obtained was 0.867 (95 % CI 0.819-0.915).

CONCLUSIONS

Our algorithm based on the global dilutional effect presents a similar sensitivity but greater specificity than the systems based on alarming results. The implementation of this algorithm in the laboratory information systems may facilitate the automated detection of contaminated samples.

A head-to-head comparison of three MALDI-TOF mass spectrometry systems with 16S rRNA gene sequencing

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized diagnostics in culture-based microbiology. Commonly used MALDI-TOF MS systems in clinical microbiology laboratories are MALDI Biotyper (Bruker Daltonics) and Vitek MS (bioMérieux), but recently the new EXS2600 (Zybio) has been launched. This study aimed to evaluate the performance of the three devices by comparing the results to 16S rRNA gene sequencing. A set of 356 previously collected difficult-to-identify bacteria was tested in parallel with the three systems. Only the direct smear method and simple formic acid extraction were applied. Valid results were achieved for 98.6%, 94.4%, and 93.3% of all isolates by MALDI Biotyper, EXS2600, and Vitek MS, respectively. Of all valid results, agreement with sequencing data was achieved in 98.9%, 98.5%, and 99.7% by MALDI Biotyper, EXS2600, and Vitek MS, respectively. Considering only the isolates with valid measurements at the single-species level, misidentification rates were 0%, 2.6%, and 1.1% for MALDI Biotyper, EXS2600, and Vitek MS, respectively. Apart from minor performance differences, our data demonstrate that the three systems provide comparable results and are suitable for use in medical diagnostic laboratories.

Reference intervals of biochemical analytes in healthy adults from northern China: A population-based cross-sectional study

Reference intervals (RIs) of laboratory testing play a fundamental role in medical activities. RIs vary greatly for populations in different areas This study aimed to evaluate the age- and sex-specific reference intervals for a healthy population in a typical city of northern China. A cross-sectional study was performed in 4 tertiary care centers of Shijiazhuang of China, biochemical analytes were analyzed using a Beckman Coulter AU5800 (Beckman Coulter Inc., Brea, CA). A total of 42,979 healthy individuals were involved in this study. Grouped by age- and sex-specific, reference intervals of all the measures have been established. We found that different age groups of males and females have significant differences (all P < .001) in levels of various biochemical analytes. We provided a comprehensive age- and sex-specific RIs for biochemical analytes, which showed dynamic changes with both age and sex. For the local population, the reference intervals established here can be adopted in other clinical laboratories after appropriate validation.

The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the Laboratory Evaluation and Analytical Performance Characteristics (LEAP) checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.

veRification: an R Shiny application for laboratory method verification and validation

OBJECTIVES

According to international standards, clinical laboratories are required to verify the performance of assays prior to their implementation in routine practice. This typically involves the assessment of the assay's imprecision and trueness vs. appropriate targets. The analysis of these data is typically performed using frequentist statistical methods and often requires the use of closed source, proprietary software. The motivation for this paper was therefore to develop an open-source, freely available software capable of performing Bayesian analysis of verification data.

METHODS

The veRification application presented here was developed with the freely available R statistical computing environment, using the Shiny application framework. The codebase is fully open-source and is available as an R package on GitHub.

RESULTS

The developed application allows the user to analyze imprecision, trueness against external quality assurance, trueness against reference material, method comparison, and diagnostic performance data within a fully Bayesian framework (with frequentist methods also being available for some analyses).

CONCLUSIONS

Bayesian methods can have a steep learning curve and thus the work presented here aims to make Bayesian analyses of clinical laboratory data more accessible. Moreover, the development of the application and seeks to encourage the dissemination of open-source software within the community and provides a framework through which Shiny applications can be developed, shared, and iterated upon.

A Review of Current Practices and Future Trends in Body Fluid Testing

BACKGROUND

Body fluid testing in the clinical chemistry laboratory is a cornerstone in the diagnostic workup of pathological effusions. Laboratorians may not be aware of the preanalytical workflows used in the collection of body fluids though the value is evident whenever processes change or issues arise. The analytical validation requirements can vary depending on the regulations dictated by the laboratories' jurisdiction and accreditor requirements. Much of analytical validation hinges on how useful testing is to clinical care. Usefulness of testing varies with how well established and incorporated the tests and interpretation are in practice guidelines.

CONTENT

Body fluid collections are depicted and described so clinical laboratorians have a basic appreciation of what specimens are submitted to the laboratory for testing. A review of validation requirements by major laboratory accreditation entities is presented. A review of the usefulness and proposed decision limits for common body fluid chemistry analytes is presented. Body fluid tests that show promise and those that are losing (or lost long ago) value are also reviewed.

SUMMARY

The total testing process from collection to result interpretation can be complicated and easily overlooked by the clinical laboratory. This review aims to improve the understanding and awareness of collections, validation, result interpretation, and provide an update on recent trends.

The Future of Laboratory-Developed Tests in Hemostasis Laboratories

Laboratory-developed tests (LDTs) are widely used in clinical hemostasis laboratories. The extent to which LDTs are regulated varies greatly around the world, and proposed changes to regulations have raised concerns about the future of LDTs in clinical laboratories. It is increasingly difficult to justify the use of an LDT where a commercially available method with regulatory approval is available. Conversely, where there is no suitable test with regulatory approval and there is a compelling clinical need, using an LDT outweighs the risk associated with not performing the test. We argue that LDTs are still required in specialist clinical laboratories to fulfill unmet clinical needs, and in lower middle-income countries where they are a vital resource.

Current status and challenges in establishing reference intervals based on real-world data

Reference intervals (RIs) are the cornerstone for evaluation of test results in clinical practice and are invaluable in judging patient health and making clinical decisions. Establishing RIs based on clinical laboratory data is a branch of real-world data mining research. Compared to the traditional direct method, this indirect approach is highly practical, widely applicable, and low-cost. Improving the accuracy of RIs requires not only the collection of sufficient data and the use of correct statistical methods, but also proper stratification of heterogeneous subpopulations. This includes the establishment of age-specific RIs and taking into account other characteristics of reference individuals. Although there are many studies on establishing RIs by indirect methods, it is still very difficult for laboratories to select appropriate statistical methods due to the lack of formal guidelines. This review describes the application of real-world data and an approach for establishing indirect reference intervals (iRIs). We summarize the processes for establishing iRIs using real-world data and analyze the principle and applicable scope of the indirect method model in detail. Moreover, we compare different methods for constructing growth curves to establish age-specific RIs, in hopes of providing laboratories with a reference for establishing specific iRIs and giving new insight into clinical laboratory RI research. (201 words).

Patient-based pre-classified real-time quality control (PCRTQC)

BACKGROUND

Patient-based real-time quality control (PBRTQC) has gained increasing attention in clinical laboratory management. Although its valuable characteristics complement traditional quality control measures, its performance and practical application have faced scrutiny. In this study, patient-based pre-classified real-time quality control (PCRTQC), an extended approach was devised to enhance real-time quality control protocols.

METHODS

PCRTQC distinguishes itself by incorporating an additional patient pre-classification step utilising the OPTICS algorithm, thus addressing interference from diverse patient types. The complete set of patient test results obtained from a clinical chemistry analyser at The First Hospital of China Medical University in 2021 was utilised. Constant error (CE) and proportional error (PE) were introduced as analytical errors. Four analytes were selected to evaluate the PCRTQC, measuring probability for false rejection (Pfr) and the average number of patient samples until error detection (ANPed). Relevant error detection charts were generated.

RESULTS

The PCRTQC outperformed regression-adjusted real-time quality control (RARTQC) based on the ANPed by approximately 50% for both the CE and PE, compared to the RARTQC, particularly for the total allowable error threshold.

CONCLUSION

The pre-classification step effectively reduced inter-individual variation and improved data preprocessing, filtering, and modelling. The PCRTQC is a robust framework for real-time quality control research.