ESMO 2020, the annual meeting of the European Society for Medical Oncology, is taking place in unprecedented times and the event’s motto, “bringing innovation to cancer patients” is more relevant than ever. The COVID-19 pandemic has caused massive disruption to cancer care, with routine screening falling by 60 to 80 percent in the US, and an estimated 2,000 fewer cancers diagnosed each week in the UK. Delays in diagnosis and treatment will inevitably impact patient outcomes and highlight the importance of establishing a personalized healthcare approach that provides tailored care, integrates innovation, and supports equal access to cancer care. The shift to personalized healthcare is accelerated by expanding knowledge of cancer biology, advanced technologies and analytics, and innovation in the collection and handling of information.
With greater knowledge, diagnosis and treatment of cancer has changed and expanded, leading to huge volumes of data from electronic health records, imaging, pathology, genomics, and apps. Clinical decision-making is therefore increasing in complexity, but human cognitive capacity cannot integrate and interpret data from so many sources to formulate an accurate diagnosis and individual care plan. Time is also a major factor, with the average physician needing to spend 29 hours a week to keep up to date with new medical research. Intelligent tools are beginning to support clinical decision-making, e.g. imaging classification and diagnosis, and as machine-learning algorithms advance, implementation of artificial intelligence-driven clinical decision support systems (CDSS) will further optimize individual care plans.
Delivering personalized care in oncology
Advances in technology such as next-generation sequencing (NGS) have improved the understanding of cancer biology and changed the diagnosis and treatment of individual cancer patients. Through comprehensive genomic profiling (CGP) using NGS, it is possible to analyze hundreds of cancer-related genes and genomic signatures to inform the best care plan for each patient. Through repeat analysis, early detection of relapse is also possible, allowing timely adaptation of treatment. NGS was recently recommended by the ESMO Precision Medicine Working Group for patients with metastatic non-small-cell lung cancer, cholangiocarcinoma, prostate, and ovarian cancer.
Although both solid tissue and liquid biopsies can be used for CGP, liquid biopsy is becoming increasingly important to inform personalized treatment decisions for patients with advanced cancer and offers a more complete analysis of tumor heterogeneity. The simple, minimally invasive procedure — a single blood draw — can offer a quick and convenient option for use in the outpatient setting and can potentially reduce the burden on healthcare resources. Liquid biopsy also offers a means for longitudinal assessment, with wide-ranging clinical applications from screening through diagnosis, to assessment of residual disease, recurrence, and resistance. The transition to liquid biopsy is expected to gain momentum following recent approvals of two liquid biopsy assays by the U.S. Food and Drug Administration (FDA).
Learning from patients in real time
Based on insights gained from advances in technology, clinicians can characterize cancer more precisely. Large-scale genomic profiling has enabled a systematic molecular-based taxonomy of cancer, resulting in molecular subtypes with low prevalence. Interpretation of complex molecular data, to inform treatment decisions, is facilitated by molecular tumor boards comprising geneticists, molecular biologists, pathologists, bioinformaticians, and oncologists. However, the field now faces a dilemma regarding standards of evidence, as small patient populations are difficult to investigate within classical clinical trial settings.
To overcome this challenge, innovative biomarker-driven trial designs that enroll patients based on molecular/genomic profiles across numerous histologies — tumor-agnostic, basket and umbrella trials — are being used to generate clinical evidence for molecularly guided therapies. Evidence generated from these trials is complemented by real-world data (RWD), which can help address any remaining knowledge gaps and validate evidence from clinical trials in real-life clinical practice. Insights from RWD can facilitate better understanding of the impact and long-term outcomes of treatment and ensure patient access to the most appropriate treatment. Both the FDA and European Medicines Agency (EMA) recognize the utility of evidence derived from RWD (real-world evidence; RWE) in supporting marketed products, product development, and regulatory decision-making. To harness the full potential of RWE, questions around the quality must be addressed through complete, standardized and prospective RWD collection, and access improved through open collaboration and sharing of local/global datasets.
Linking information from multiple sources to build a comprehensive picture of each patient is imperative in precision cancer medicine. NGS data is now being linked to treatment decisions and patient outcomes, and information is being shared between multiple stakeholders using large clinico-genomic databases, such as the AACR Project GENIE (American Association for Cancer Research’s Genomics Evidence Neoplasia Information Exchange).
Making personalized healthcare a reality everywhere
As the pandemic places unprecedented strain on healthcare systems globally, exposing their limitations, there is a need to find more sustainable solutions to continue providing high-quality care for every patient. Integration of research and clinical care into learning healthcare systems (LHS) allows clinicians to understand, learn from, and improve healthcare activities. Key features of LHS are enhanced capacity to collect and use data from advanced technology, care improvement targets to encourage use of CDSS, and a supportive policy environment to reward performance and increase transparency. A number of LHS have been created, such as CancerLinQ and EUROCAT, but for wider implementation in healthcare practice barriers need to be overcome, including securing sufficient resources to support learning activities, limited quality of stored clinical data, and regulatory barriers to data sharing.
Conclusions
For many countries, putting the vision of personalized healthcare into practice will require a fundamental change in the way patient care is delivered and managed. Transformation of healthcare systems is reliant on strong collaboration between physicians, patient advocacy groups, researchers, payers, and policy makers to create a comprehensive solution incorporating genomic testing, CDSS, and access to molecularly guided therapies. Croatia is among a number of countries where efforts are already being made, with a government commitment to offer CGP for all patients with advanced cancer and collaboration with partners to ensure access and funding for innovative treatments within a year of EMA approval. A program to build personalized healthcare capabilities, establish data repositories, and train oncologists is also underway. Healthcare systems across the globe are diverse, but through partnership it will be possible to achieve the common goal of faster access to better care for patients.
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