Breakfast Roundtables will be held on Monday, June 19:
Monday June 19 – 0730-0830
- R190730-A Cases in pediatric clinical chemistry
- R190730-B Approaches to ensure the equivalence of patient results within one healthcare system
- R190730-C Implementation of dihydropyrimidine dehydrogenase genotype test to guide fluoropyrimidine therapy
- R190730-D Artificial Intelligence: Ethical Issues and Challenges
- R190730-E A novel tool that makes clinical chemistry CliCK
- R190730-F The pre-examination phase for stool samples – challenges and opportunities for success
- R190730-G Using artificial intelligence to produce an analytical definition of minor distortions in the gamma region of SPEP by capillary electrophoresis
- R190730-H Proposed harmonized pediatric lipid reporting for Canadian clinical laboratories
R190730-Cases in pediatric clinical chemistry Monday June 19, 0730-0830
Lawrence de Koning, University of Calgary
Learning Objectives:
At the end of the session, the participants will be able to:
- Explain the benefits of a QA program that periodically assesses the appropriateness of critical values.
- Describe pediatric-related issues in stages of the testing process that can cause unusual results.
- Describe unique physiologic aspects of children, rare pediatric conditions, and errors in the testing process and clinical care that can cause unusual results.
Pediatric clinical chemistry is an extremely stimulating area of laboratory medicine. Rare congenital conditions combined with dynamic physiology can lead to surprising results that can challenge the comfort levels of clinical chemists. This ongoing series will review several pediatric cases which presented with highly unusual or unexpected test results. Significant errors in the testing process and clinical care will be reviewed as well as important congenital and metabolic conditions.
R190730-B Approaches to ensure the equivalence of patient results within one healthcare system Monday June 19, 0730-0830
Jieli Shirley Li, The Ohio State University Wexner Medical Center
Learning Objectives:
At the end of the session, the participants will be able to:
- Describe the advantages of standardization in clinical laboratory services, including but not limited to instrumentation, quality management and workflows.
- Identify common challenges encountered in the process of implementing laboratory standardization.
- Implement practical approaches to assess the comparability of patient results within one healthcare system.
The trend for multi-hospital networks has been growing over the last two decades, with an ever-increasing number of hospitals and health systems looking to consolidate. As health systems grow, standardization of laboratory service across all sites is a vital part to ensure consistent fully-integrated care can be delivered to patients. Standardization offers many benefits including better efficiency and lower cost, equivalence of patient results, as well as cross-training of staff members, to name just a few. These gains carry over to improved quality of care and patient satisfaction. While the benefits significantly outweigh the negatives, we should also bear in mind that standardization comes with challenges and can be a long process. For example, standardizing laboratory instruments to the same vendor will undoubtedly contribute to better comparability of test results, lower per test cost and allow laboratories to share best practices and procedures. However, at the same time, the system becomes more vulnerable to issues with the contracted vendor. These include limitations in test menu, patient-specific assay interferences, reagent recalls and/or backorders. This session will use an interactive format and a case-based approach to share the path to laboratory standardization, the benefits achieved, and how they used creative ways to mitigate challenges. Various aspects of laboratory standardization will be highlighted, including instrumentation, quality management, operations, and workflows.
R190730-C Implementation of dihydropyrimidine dehydrogenase genotype test to guide fluoropyrimidine therapy Monday June 19, 0730-0830
Lei Fu, Sunnybrook Health Sciences Centre and University of Toronto
Learning Objectives:
At the end of the session, the participants will be able to:
- Explain the importance of DPYD genotype test in patients receiving fluoropyrimidine chemotherapy.
- Describe the analytical and clinical considerations in the process of clinical implementation of DPYD genotype test.
- Discuss the limitations of pharmacogenetic test and future development.
Fluoropyrimidines, such as 5-fluorouracil (5-FU) and capecitabine, are widely used for patients with solid tumors, and are the chemotherapy backbone in colorectal and other gastrointestinal chemotherapy regimens. It has been reported that as many as 10-30% patients treated with fluoropyrimidine drugs experience severe toxicity. The DPYD gene encodes the rate-limiting enzyme dihydropyrimidine dehydrogenase (DPD) responsible for fluoropyrimidine catabolism. The US Food and Drug Administration (FDA) added warning statements to the drug labels for 5-FU to against its use in patients with DPD deficiency. Since 2017, the Clinical Pharmacogenetics Implementation Consortium (CPIC) has updated its practice guideline for DPYD genotype and fluoropyrimidine dosing. Recently, Cancer Care Ontario has announced its funding for DPYD genotype test in patients receiving fluoropyrimidine chemotherapy.
In this session, we will use cases to explain why DPYD genotype test is important for patients receiving fluoropyrimidine chemotherapy. We will describe the analytical and clinical considerations in clinical implementation of DPYD genotype test. Lastly, we will discuss the limitations of pharmacogenetic test and the future development.
R190730-D Artificial Intelligence: Ethical Issues and Challenges Monday June 19, 0730-0830
Jay Kalra, University of Saskatchewan and Saskatchewan Health Authority
Learning Objectives:
At the end of the session, the participants will be able to:
- Analyze concepts and emerging ethics of Artificial Intelligence.
- Discuss strengths and weaknesses of dried blood spots (DBS) as a sampling technique for testing.
- Discuss why ethics is important and recognize risk of ignoring ethics in machine learning.
- Explore the integration of SHERPA project and the Delphi study to identify ethical issues.
- Assess the accuracy of Artificial Intelligence in different medical disciplines.
- Discuss biomedical ethical issues and challenges in healthcare, research and regulation.
- Appraise guidelines to address AI.
Artificial intelligence (AI) is a relatively new medical resource with the potential to revolutionize current practices in the prevention and treatment of disease. AI has been defined as computer programs simulating processes typically performed by humans to accomplish a task without needing to be specifically programmed to do so. As the ethical benefits of increased efficiency and productivity of AI systems are being realized, the consequences of implementing such transformative technology have raised ethical questions across the globe. The Delphi technique, a well-established international protocol used to find consensus among experts and solutions to complex multidisciplinary challenges has identified key ethical issues pertaining to AI. Systemic Human Error Reduction and Prediction Approach (SHERPA), a consortium of eleven partners from six countries has analysed how AI affects ethics and human rights. Ethical challenges of AI such as risk management, data security, and a lack of transparency span all sectors working to implement these new technologies. All medical disciplines working to leverage the potential applications of AI struggle with the ethical challenges of informed consent, autonomy, accountability, biases, and equitable healthcare delivery. The field of laboratory medicine and pathology was a pioneer in the implementation of AI technology. Advancing the technologies that this work relies on carries with it ethical challenges to ensure the validity and accuracy of results. Laboratory medicine and pathology face additional hurdles when ensuring accurate interpretation such as unequal contexts, opportunity costs, and low levels of acceptable risk and uncertainty. Rather than an all-or-nothing approach, we suggest a stepwise, transparent, and patient-centred approach with clear boundaries to the incorporation of new tools. The AI-assisted era of medical care will be transformative but will never be void of all risk or ethical challenges. This work represents the first of many steps in using AI technology to optimize healthcare delivery in a way that protects and strengthens the ethical values of medical care.
R190730-E A novel tool that makes clinical chemistry CliCK Monday June 19, 0730-0830
Jennifer Taher, Mount Sinai Hospital and University of Toronto
Learning Objectives:
At the end of the session, the participants will be able to:
- Describe information available on the CliCK study tool.
- Explain how to effectively navigate and use the CliCK study tool.
- Identify how to be involved in development of CliCK educational content.
- Discuss the benefits of using CliCK to retain relevant information.
Clinical biochemists are required to retain and recall a significant amount of clinical and analytical information. To aid in these efforts, a clinical chemistry knowledge (CliCK) tool was developed by Canadian biochemists and vetted by experts in the field. CliCK allows end-users to review and learn up-to-date information for topics in the current CACB syllabus. The ANKI software selected for CliCK incorporates an evidence-based educational approach to recall information and has been endorsed by education experts due to its effectiveness. The CliCK tool is relevant for clinical chemistry educators, fellows/learners or clinical biochemists who simply need to refresh their memory and will be launched on the CSCC website in 2023. This roundtable will be interactive and allow attendees to obtain hands on experience with CliCK.
R190730-F The pre-examination phase for stool samples – challenges and opportunities for success Monday June 19, 0730-0830
Basma Ahmed, McMaster University
Learning Objectives:
At the end of the session, the participants will be able to:
- Describe the modifiable barriers to providing or successfully collecting stool samples by patients and the role of the clinical laboratory in addressing them.
- Describe the pre-analytical challenges related to stool samples.
- Discuss the role of clinical laboratory experts in guiding researchers who collect stool samples.
Asking patients to provide stool samples for screening or diagnostic purposes may sound easy, but several barriers prevent patients from providing or successfully collecting stool samples. Additionally, the pre-analytical variability for stool sample collection can be challenging. There is an increased interest in using stool samples for research purposes that may evolve into diagnostic tools i.e., gut microbiota for its proven role in human health and diseases. With the increased stool testing, discussing the challenges and opportunities for a successful pre-examination phase is key.
In this roundtable, we will discuss the barriers that limit patients from providing stool samples and the clinical laboratory’s role in preventing and addressing the modifiable barriers. We will also discuss the pre-analytical variables that need to be considered during stool sample specimen collection to avoid erroneous results.
R190730-G Using artificial intelligence to produce an analytical definition of minor distortions in the gamma region of SPEP by capillary electrophoresis Monday June 19, 0730-0830
Tracy Morrison, LifeLabs
Learning Objectives:
At the end of the session, the participants will be able to:
- Use AI terminology in a practical setting.
- Discuss current AI performance for detecting monoclonal peaks in the gamma region.
- Debate the use of AI to define analytical sensitivity for minor distortions in the gamma region.
Artificial intelligence (AI) is becoming a more prominent tool in laboratory medicine. There is potential for its application in curve interpretation of serum protein electrophoresis (SPEP) by capillary electrophoresis (CE) for the investigation of monoclonal gammopathies. In this roundtable we will discuss ongoing efforts to produce a machine learning model to detect monoclonal peaks in the gamma region. Current achievements include sensitivity of 0.978, specificity of 0.977, and precision of 0.732 on the test dataset. The focus of the discussion will be on the properties of the model and whether it sufficiently detects minor distortions. In addition, we will debate whether the model’s analytical sensitivity is clinically appropriate. This will be discussed in the context of a variety of scenarios along the clinical pathway of monoclonal gammopathies, including diagnosis, remission, and relapse.
R190730-H Proposed harmonized pediatric lipid reporting for Canadian clinical laboratories Monday June 19, 0730-0830
Nicole White-Al Habeeb, Canadian Society of Clinical Chemists (CSCC) Working Group on Reference Interval Harmonization
Learning Objectives:
At the end of the session, the participants will be able to:
- Discuss the 2022 CCS/CPCA pediatric lipid clinical practice update.
- List the five recommendations for harmonized pediatric lipid reporting proposed by the CSCC hRI-WG.
- Create a plan to locally implement harmonized pediatric lipid reporting complete with decision thresholds and interpretative comments.
This session will discuss the Canadian Society of Clinical Chemists (CSCC) Harmonized Reference Interval Working Group (hRI-WG) recommendations for harmonized pediatric lipid reporting primarily based on CALIPER data and the 2022 Canadian Cardiovascular Society (CCS)/Canadian Pediatric Cardiology Association (CPCA) clinical practice update. A 2018 nation-wide survey distributed by the CSCC hRI-WG identified significant variation in lipid reporting across Canada. Harmonization of pediatric lipid reporting will facilitate standardized lipid assessment and clinical decision making, ultimately optimizing patient care, and reducing risk.
A subcommittee of the CSCC hRI-WG developed pediatric lipid reporting recommendations including: 1) availability of non-fasting and fasting testing; 2) a complete lipid panel including total cholesterol, LDL-C, HDL-C, non-HDL-C and triglycerides, with ApoB and Lp(a) available as individually orderable tests; 3) a lipid reporting format that includes lipid decision thresholds based on the age- and sex-specific 95th percentile for total cholesterol, triglycerides, LDL-C, non-HDL-C and ApoB, and the 10th percentile for HDL-C; 4) interpretative comments to include decision thresholds for desired, borderline and increased risk; and 5) the use of the new NIH LDL-C equation in place of Friedewald LDL-C equation.
In this session, we will provide an overview of the 2022 CCS/CPCA recommendations, review other relevant literature and retrospective data analysis to support the recommendations, describe the development of the CSCC hRI-WG proposed pediatric lipid report, outline five recommendations, and the proposed formatting and interpretive comments.