The gaps between the new EU legislation on in vitro diagnostics and the on-the-ground reality

Assessing post-analytical phase harmonization in European laboratories: a survey promoted by the EFLM Working Group on Harmonization

OBJECTIVES

Harmonization of the laboratory total testing process (TTP) is critical to improving patient outcome. In 2016, an EFLM survey on the harmonization of TTP underlined the serious shortcomings pertaining to the post-analytical phase. In 2023, the WG-H conducted a new survey aiming to update information in the 2016 harmonization report in order to ascertain whether countries that had declared they were keen to adopt SI units had continued with this program, the aim being to verify the state-of art in harmonization units in areas of laboratory medicine not included in the previous survey.

METHODS

Questionnaires were distributed to the Presidents and National Representatives of EFLM Full Member Societies and EFLM affiliate Members. The survey questions were grouped into three categories: measurement units, reference intervals, and nomenclature/terminology, and results were evaluated using Survey Monkey software and Excel.

RESULTS

A total of 123 questionnaires from 31 countries were analyzed. A trend (+19.3 %) was observed toward a wider use of SI units for general clinical biochemistry parameters. The results for tests not included in the 2016 survey (i.e., endocrinology diagnostics and coagulation panels), demonstrated that for reports on hormones, responses were satisfactory, 70-90 % of the responders adopting the recommended units, whereas for coagulation test panels, a serious lack of harmonization was found, "seconds", which are inaccurate and not recommended, being widely used units (91 %).

CONCLUSIONS

The findings made in the 2023 survey demonstrated a progressive, albeit slow, improvement in harmonization reports. However, further efforts at improvement are mandatory.

Current challenges and practical aspects of molecular pathology for non-small cell lung cancers

The continuing evolution of treatment options in thoracic oncology requires the pathologist to regularly update diagnostic algorithms for management of tumor samples. It is essential to decide on the best way to use tissue biopsies, cytological samples, as well as liquid biopsies to identify the different mandatory predictive biomarkers of lung cancers in a short turnaround time. However, biological resources and laboratory member workforce are limited and may be not sufficient for the increased complexity of molecular pathological analyses and for complementary translational research development. In this context, the surgical pathologist is the only one who makes the decisions whether or not to send specimens to immunohistochemical and molecular pathology platforms. Moreover, the pathologist can rapidly contact the oncologist to obtain a new tissue biopsy and/or a liquid biopsy if he/she considers that the biological material is not sufficient in quantity or quality for assessment of predictive biomarkers. Inadequate control of algorithms and sampling workflow may lead to false negative, inconclusive, and incomplete findings, resulting in inappropriate choice of therapeutic strategy and potentially poor outcome for patients. International guidelines for lung cancer treatment are based on the results of the expression of different proteins and on genomic alterations. These guidelines have been established taking into consideration the best practices to be set up in clinical and molecular pathology laboratories. This review addresses the current predictive biomarkers and algorithms for use in thoracic oncology molecular pathology as well as the central role of the pathologist, notably in the molecular tumor board and her/his participation in the treatment decision-making. The perspectives in this setting will be discussed.

Clouds across the new dawn for clinical, diagnostic and biological data: accelerating the development, delivery and uptake of personalized medicine

Growing awareness of the genetic basis of disease is transforming the opportunities for improving patient care by accelerating the development, delivery and uptake of personalised medicine and diseases diagnostics. This can mean more precise treatments reaching the right patients at the right time at the right cost. But it will be possible only with a coherent European Union (EU) approach to regulation. For clinical and biological data, on which the EU is now legislating with its planned European Health Data Space (EHDS), it is crucial that the design of this new system respects the constraints also implicit in the testing which generates data. The current EHDS proposal may fail to meet this requirement. It risks being over-ambitious, while taking insufficient account of the demanding realities of data access in daily practice and current economics/business models. It is marred by imprecision and ambiguity, by overlaps with other EU legislation, and by lack of clarity on funding. This paper identifies key issues where legislators should ensure that the opportunities are not squandered by the adoption of over-hasty or ill-considered provisions that jeopardise the gains that could be made in improved healthcare.

Results from an IFCC Global Survey on Laboratory Practices for the Analysis of Circulating Tumor DNA

BACKGROUND

The clinical validity of ctDNA analysis as a diagnostic, prognostic and predictive biomarker has been demonstrated in many studies. The rapid spread of tests for the analysis of ctDNA raises questions regarding their standardization and quality assurance. The aim of this study was to provide a global overview of the test methods, laboratory procedures and quality assessment practices using ctDNA diagnostics.

METHODS

The Molecular Diagnostics Committee of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC C-MD) conducted a survey among international laboratories performing ctDNA analysis. Questions on analytical techniques, test parameters, quality assurance and the reporting of findings were included.

RESULTS

A total of 58 laboratories participated in the survey. The majority of the participating laboratories (87.7%) performed testing for patient care. Most laboratories conducted their assays for lung cancer (71.9%), followed by colorectal (52.6%) and breast (40.4%) cancer, and 55.4% of the labs used ctDNA analysis for follow-up/monitoring of treatment-resistant alterations. The most frequent gene analysed was EGFR (75.8%), followed by KRAS (65.5%) and BRAF (56.9%). Participation in external quality assessment programs was reported by only 45.6% of laboratories.

CONCLUSIONS

The survey indicates that molecular diagnostic methods for the analysis of ctDNA are not standardized across countries and laboratories. Furthermore, it reveals a number of differences regarding sample preparation, processing and reporting test results. Our findings indicate that ctDNA testing is being conducted without sufficient attention to analytical performance between laboratories and highlights the need for standarisation of ctDNA analysis and reporting in patient care.

Diagnostic quality model (DQM): an integrated framework for the assessment of diagnostic quality when using AI/ML

BACKGROUND

Laboratory medicine has reached the era where promises of artificial intelligence and machine learning (AI/ML) seem palpable. Currently, the primary responsibility for risk-benefit assessment in clinical practice resides with the medical director. Unfortunately, there is no tool or concept that enables diagnostic quality assessment for the various potential AI/ML applications. Specifically, we noted that an operational definition of laboratory diagnostic quality - for the specific purpose of assessing AI/ML improvements - is currently missing.

METHODS

A session at the 3rd Strategic Conference of the European Federation of Laboratory Medicine in 2022 on "AI in the Laboratory of the Future" prompted an expert roundtable discussion. Here we present a conceptual diagnostic quality framework for the specific purpose of assessing AI/ML implementations.

RESULTS

The presented framework is termed diagnostic quality model (DQM) and distinguishes AI/ML improvements at the test, procedure, laboratory, or healthcare ecosystem level. The operational definition illustrates the nested relationship among these levels. The model can help to define relevant objectives for implementation and how levels come together to form coherent diagnostics. The affected levels are referred to as scope and we provide a rubric to quantify AI/ML improvements while complying with existing, mandated regulatory standards. We present 4 relevant clinical scenarios including multi-modal diagnostics and compare the model to existing quality management systems.

CONCLUSIONS

A diagnostic quality model is essential to navigate the complexities of clinical AI/ML implementations. The presented diagnostic quality framework can help to specify and communicate the key implications of AI/ML solutions in laboratory diagnostics.

ISO 15189 is a sufficient instrument to guarantee high-quality manufacture of laboratory developed tests for in-house-use conform requirements of the European In-Vitro-Diagnostics Regulation

The EU In-Vitro Diagnostic Device Regulation (IVDR) aims for transparent risk-and purpose-based validation of diagnostic devices, traceability of results to uniquely identified devices, and post-market surveillance. The IVDR regulates design, manufacture and putting into use of devices, but not medical services using these devices. In the absence of suitable commercial devices, the laboratory can resort to laboratory-developed tests (LDT) for in-house use. Documentary obligations (IVDR Art 5.5), the performance and safety specifications of ANNEX I, and development and manufacture under an ISO 15189-equivalent quality system apply. LDTs serve specific clinical needs, often for low volume niche applications, or correspond to the translational phase of new tests and treatments, often extremely relevant for patient care. As some commercial tests may disappear with the IVDR roll-out, many will require urgent LDT replacement. The workload will also depend on which modifications to commercial tests turns them into an LDT, and on how national legislators and competent authorities (CA) will handle new competences and responsibilities. We discuss appropriate interpretation of ISO 15189 to cover IVDR requirements. Selected cases illustrate LDT implementation covering medical needs with commensurate management of risk emanating from intended use and/or design of devices. Unintended collateral damage of the IVDR comprises loss of non-profitable niche applications, increases of costs and wasted resources, and migration of innovative research to more cost-efficient environments. Taking into account local specifics, the legislative framework should reduce the burden on and associated opportunity costs for the health care system, by making diligent use of existing frameworks.