Implementation and Clinical Adoption of Precision Oncology Workflows Across a Healthcare Network

A vision to the future: value-based laboratory medicine

The ultimate goal of value-based laboratory medicine is maximizing the effectiveness of laboratory tests in improving patient outcomes, optimizing resources and minimizing unnecessary costs. This approach abandons the oversimplified notion of test volume and cost, in favor of emphasizing the clinical utility and quality of diagnostic tests in the clinical decision-making. Several key elements characterize value-based laboratory medicine, which can be summarized in some basic concepts, such as organization of in vitro diagnostics (including appropriateness, integrated diagnostics, networking, remote patient monitoring, disruptive innovations), translation of laboratory data into clinical information and measurable outcomes, sustainability, reimbursement, ethics (e.g., patient empowerment and safety, data protection, analysis of big data, scientific publishing). Education and training are also crucial, along with considerations for the future of the profession, which will be largely influenced by advances in automation, information technology, artificial intelligence, and regulations concerning in vitro diagnostics. This collective opinion paper, composed of summaries from presentations given at the two-day European Federation of Laboratory Medicine (EFLM) Strategic Conference "A vision to the future: value-based laboratory medicine" (Padova, Italy; September 23-24, 2024), aims to provide a comprehensive overview of value-based laboratory medicine, projecting the profession into a more clinically effective and sustainable future.

Key considerations when implementing new diagnostic technologies in routine practice

BACKGROUND

The field of pathology is evolving with the integration of advanced and artificial-intelligence-powered diagnostic technologies. However, there remains a significant gap in clearly outlining the key considerations for the effective implementation of these innovations into clinical care.

OBJECTIVES

The aim of this review was to identify and address the essential aspects required to bridge the implementation gap of new diagnostic technologies in pathology.

MATERIAL AND METHODS

This review synthesizes key elements from relevant scientific journals, organizational websites, and practical examples from pathology practice. The findings are presented as a structured framework of six key elements, supported by an infographic and illustrative cases from clinical settings.

RESULTS

The key elements are: (1) Innovation depends more on the people driving it than on the work it demands, highlighting the importance of team collaboration and communication; (2) in-depth knowledge of the delivery system emphasizing the importance of care, IT, and administrative layers is crucial; (3) data-driven decision-making in healthcare transformation is central, with an emphasis on the process of converting real-world data (RWD) into actionable real-world evidence (RWE); (4) a proven approach for practice transformation uses a structured (utilization management strategy, UMS) framework; (5) a balanced approach toward financial sustainability, including local and systemic financial strategies, is important; and (6)  ensuring safe and effective progress requires a new, collaborative definition of regulatory science, aligning innovation with regulatory oversight to support technological advancements.

CONCLUSION

These key aspects offer a foundational framework for integrating new technologies into healthcare. Although not exhaustive, overlooking them would miss a significant opportunity to enhance patient care.

Bridging the divide: addressing discrepancies between clinical guidelines, policy guidelines, and biomarker utilization

OBJECTIVES

This paper aims to identify and address gaps in cancer treatment and diagnosis within European health services, focusing specifically on discrepancies between clinical guidelines and policy guidelines. It seeks to highlight how the underutilization of advanced diagnostic techniques recommended by medical societies contributes to missed opportunities for improving patient outcomes.

METHODS

A comprehensive analysis was conducted across multiple European countries to assess the compliance and integration of clinical guidelines with the availability of advanced diagnostic technologies. Secondary data related to clinical and policy guidelines in cancer care were collected and analyzed. Key indicators of adoption and utilization of next-generation sequencing and liquid biopsy were examined to evaluate their impact on health service efficiency and patient care.

RESULTS

The analysis revealed significant discrepancies between the recommendations of medical societies regarding advanced diagnostic techniques and their adoption in health policy decisions across Europe. Country-specific assessments indicated varying levels of alignment between clinical guidelines and the availability of advanced diagnostics. These findings underscored missed opportunities for optimizing patient care and health service efficiency through better alignment and integration of clinical guidelines with policy decisions.

CONCLUSIONS

This study concludes that there is a critical need for health policy decision-makers to prioritize the adoption of clinical guidelines in resource allocation and health service organization. Greater attention to the recommendations of medical societies regarding advanced diagnostic techniques could significantly enhance diagnostic accuracy, treatment efficacy, and overall patient outcomes in cancer care. The paper advocates for policy reforms that acknowledge and leverage the potential benefits of advanced diagnostics in improving health service performance and patient-centered care across Europe.

The WERA cancer center matrix: Strategic management of patient access to precision oncology in a large and mostly rural area of Germany

PURPOSE

Providing patient access to precision oncology (PO) is a major challenge of clinical oncologists. Here, we provide an easily transferable model from strategic management science to assess the outreach of a cancer center.

METHODS

As members of the German WERA alliance, the cancer centers in Würzburg, Erlangen, Regensburg and Augsburg merged care data regarding their geographical impact. Specifically, we examined the provenance of patients from WERA´s molecular tumor boards (MTBs) between 2020 and 2022 (n = 2243). As second dimension, we added the provenance of patients receiving general cancer care by WERA. Clustering our catchment area along these two dimensions set up a four-quadrant matrix consisting of postal code areas with referrals towards WERA. These areas were re-identified on a map of the Federal State of Bavaria.

RESULTS

The WERA matrix overlooked an active screening area of 821 postal code areas - representing about 50 % of Bavaria´s spatial expansion and more than six million inhabitants. The WERA matrix identified regions successfully connected to our outreach structures in terms of subsidiarity - with general cancer care mainly performed locally but PO performed in collaboration with WERA. We also detected postal code areas with a potential PO backlog - characterized by high levels of cancer care performed by WERA and low levels or no MTB representation.

CONCLUSIONS

The WERA matrix provided a transparent portfolio of postal code areas, which helped assessing the geographical impact of our PO program. We believe that its intuitive principle can easily be transferred to other cancer centers.

Diagnostic Test Utilization Management Strategies as an Opportunity for Equitable Access to Molecularly Informed Clinical Care

BACKGROUND

Companion diagnostics are an essential component of oncology. Timing, cost, and adaptability to new drug/biomarker approvals represent challenges in assuring value-based care. Overcoming these challenges requires strategies for equitable access and efficient integration.

METHODS

Based on prior laboratory improvements and payor policy implementations, we define equitable access in laboratory testing and conceptualized a framework for initiatives that optimize diagnostic performance.

RESULTS

We define equitable access as an imperative goal seeking to remove disparities that may arise due to financial hardships, geographical isolation, cultural differences, or other social determinants of health. We distinguish (a) utilization, as the practice pattern of ordered tests, (b) utilization management, as the evidence-based guidance of the utilization decisions, and (c) utilization management strategies, defined as the tools and techniques used to influence decision-making. These 3 dimensions establish a standardized vocabulary to clarify equitable alignment of strategies in specific care pathways. Alignment of logistic, administrative, and financial incentive structures is paramount when creating sustainable personalized care pathway programs.

CONCLUSIONS

Strategies to accomplish equitable and meaningful use of diagnostic tests can help enhance access to timely and accurate diagnoses, ultimately leading to improved patient outcomes.

Realizing the Dream of Precision Oncology: A Solution for All Patients

MICRO-ABSTRACT

As molecularly informed oncology care has increasingly become standard practice for patients with cancer, society must prioritize equitable access to genetic testing that guides subsequent care. Despite the availability of genomic testing laboratories, published guidelines, US Food and Drug Administration-approved targeted therapies, financial assistance programs, and clinical decision tools, precision medicine remains out of reach for many patients. While there has been modest improvement in testing rates in recent years, molecular testing and targeted therapy for cancer patients continue to vary by practice setting and patient insurance status, and racial and socioeconomic disparities persist. National standards and centralized solutions are needed to promote the equitable distribution of patient benefit from precision medicine technology. Although various online resources are currently available, no single all-encompassing precision oncology tool currently exists. A one-stop shop to address all aspects of precision oncology-tissue selection and test ordering, interpretation of results, prescribing targeted therapies, and enrolling patients in clinical trials-would disrupt cancer care. Recent advances in artificial intelligence, digital pathology, and data science provide an opportunity for stakeholders to partner together to leverage these technologies to develop this unified, freely accessible, national solution. Whether locoregionally, nationally, or internationally, only collaborative efforts can fully realize the potential of technological advancements in molecular pathology and oncology therapeutics for all cancer patients.

Investigation and benchmarking of U-Nets on prostate segmentation tasks

In healthcare, a growing number of physicians and support staff are striving to facilitate personalized radiotherapy regimens for patients with prostate cancer. This is because individual patient biology is unique, and employing a single approach for all is inefficient. A crucial step for customizing radiotherapy planning and gaining fundamental information about the disease, is the identification and delineation of targeted structures. However, accurate biomedical image segmentation is time-consuming, requires considerable experience and is prone to observer variability. In the past decade, the use of deep learning models has significantly increased in the field of medical image segmentation. At present, a vast number of anatomical structures can be demarcated on a clinician's level with deep learning models. These models would not only unload work, but they can offer unbiased characterization of the disease. The main architectures used in segmentation are the U-Net and its variants, that exhibit outstanding performances. However, reproducing results or directly comparing methods is often limited by closed source of data and the large heterogeneity among medical images. With this in mind, our intention is to provide a reliable source for assessing deep learning models. As an example, we chose the challenging task of delineating the prostate gland in multi-modal images. First, this paper provides a comprehensive review of current state-of-the-art convolutional neural networks for 3D prostate segmentation. Second, utilizing public and in-house CT and MR datasets of varying properties, we created a framework for an objective comparison of automatic prostate segmentation algorithms. The framework was used for rigorous evaluations of the models, highlighting their strengths and weaknesses.

Slide-to-Slide Tissue Transfer and Array Assembly From Limited Samples for Comprehensive Molecular Profiling

Tissue microarrays (TMA) have become an important tool in high-throughput molecular profiling of tissue samples in the translational research setting. Unfortunately, high-throughput profiling in small biopsy specimens or rare tumor samples (eg, orphan diseases or unusual tumors) is often precluded owing to limited amounts of tissue. To overcome these challenges, we devised a method that allows tissue transfer and construction of TMAs from individual 2- to 5-μm sections for subsequent molecular profiling. We named the technique slide-to-slide (STS) transfer, and it requires a series of chemical exposures (so-called xylene-methacrylate exchange) in combination with rehydrated lifting, microdissection of donor tissues into multiple small tissue fragments (methacrylate-tissue tiles), and subsequent remounting on separate recipient slides (STS array slide). We developed the STS technique by assessing the efficacy and analytical performance using the following key metrics: (a) dropout rate, (b) transfer efficacy, (c) success rates using different antigen-retrieval methods, (d) success rates of immunohistochemical stains, (e) fluorescent in situ hybridization success rates, and (f) DNA and (g) RNA extraction yields from single slides, which all functioned appropriately. The dropout rate ranged from 0.7% to 6.2%; however, we applied the same STS technique successfully to fill these dropouts ("rescue" transfer). Hematoxylin and eosin assessment of donor slides confirmed a transfer efficacy of >93%, depending on the size of the tissue (range, 76%-100%). Fluorescent in situ hybridization success rates and nucleic acid yields were comparable with those of traditional workflows. In this study, we present a quick, reliable, and cost-effective method that offers the key advantages of TMAs and other molecular techniques-even when tissue is sparse. The perspectives of this technology in biomedical sciences and clinical practice are promising, given that it allows laboratories to create more data with less tissue.