Real-world data in the molecular era-finding the reality in the real world

Challenges and opportunities in building a health economic framework for personalized medicine in oncology

Personalized medicine has allowed for knowledge at an individual level for several diseases and this has led to improvements in prevention and treatment of various types of neoplasms. Despite the greater availability of tests, the costs of genomic testing and targeted therapies are still high for most patients, especially in low- and middle-income countries. Although value frameworks and health technology assessment are fundamental to allow decision-making by policymakers, there are several concerns in terms of personalized medicine pharmacoeconomics. A global effort may improve these tools in order to allow access to personalized medicine for an increasing number of patients with cancer.

Precision Medicine and the future of Cardiovascular Diseases: A Clinically Oriented Comprehensive Review

Cardiac diseases form the lion's share of the global disease burden, owing to the paradigm shift to non-infectious diseases from infectious ones. The prevalence of CVDs has nearly doubled, increasing from 271 million in 1990 to 523 million in 2019. Additionally, the global trend for the years lived with disability has doubled, increasing from 17.7 million to 34.4 million over the same period. The advent of precision medicine in cardiology has ignited new possibilities for individually personalized, integrative, and patient-centric approaches to disease prevention and treatment, incorporating the standard clinical data with advanced "omics". These data help with the phenotypically adjudicated individualization of treatment. The major objective of this review was to compile the evolving clinically relevant tools of precision medicine that can help with the evidence-based precise individualized management of cardiac diseases with the highest DALY. The field of cardiology is evolving to provide targeted therapy, which is crafted as per the "omics", involving genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics, for deep phenotyping. Research for individualizing therapy in heart diseases with the highest DALY has helped identify novel genes, biomarkers, proteins, and technologies to aid early diagnosis and treatment. Precision medicine has helped in targeted management, allowing early diagnosis, timely precise intervention, and exposure to minimal side effects. Despite these great impacts, overcoming the barriers to implementing precision medicine requires addressing the economic, cultural, technical, and socio-political issues. Precision medicine is proposed to be the future of cardiovascular medicine and holds the potential for a more efficient and personalized approach to the management of cardiovascular diseases, contrary to the standardized blanket approach.

Use of Real-World Evidence in US Payer Coverage Decision-Making for Next-Generation Sequencing-Based Tests: Challenges, Opportunities, and Potential Solutions

OBJECTIVES

Given the potential of real-world evidence (RWE) to inform understanding of the risk-benefit profile of next-generation sequencing (NGS)-based testing, we undertook a study to describe the current landscape of whether and how payers use RWE as part of their coverage decision making and potential solutions for overcoming barriers.

METHODS

We performed a scoping literature review of existing RWE evidentiary frameworks for evaluating new technologies and identified barriers to clinical integration and evidence gaps for NGS. We synthesized findings as potential solutions for improving the relevance and utility of RWE for payer decision-making.

RESULTS

Payers require evidence of clinical utility to inform coverage decisions, yet we found a relatively small number of published RWE studies, and these are predominately focused on oncology, pharmacogenomics, and perinatal/pediatric testing. We identified 3 categories of innovation that may help address the current undersupply of RWE studies for NGS: (1) increasing use of RWE to inform outcomes-based contracting for new technologies, (2) precision medicine initiatives that integrate clinical and genomic data and enable data sharing, and (3) Food and Drug Administration reforms to encourage the use of RWE. Potential solutions include development of data and evidence review standards, payer engagement in RWE study design, use of incentives and partnerships to lower the barriers to RWE generation, education of payers and providers concerning the use of RWE and NGS, and frameworks for conducting outcomes-based contracting for NGS.

CONCLUSIONS

We provide numerous suggestions to overcome the data, methodologic, infrastructure, and policy challenges constraining greater integration of RWE in assessments of NGS.

The Missing Reality of Real Life in Real-World Evidence

Reality is defined as a real event, a real thing, or state of affairs. Reality exists in the places where we live our daily lives, in the relationships we have with others, and in our experiences, circumstances, and situations that occur across the lifespan. As the everydayness of our lives becomes increasingly digitized, data generated from the reality that exists outside of our healthcare encounters holds much promise to fill recognized gaps in real‐world evidence (RWE). In the past decade, many factors have converged to uniquely position person‐generated data for use in health care delivery, payment reform, product development, and regulatory decision making. Yet, real‐world data will fall short of its promise to fill gaps in RWE if what we learn does not reflect the real lives of real people from across the spectrum of social, economic, and cultural experiences.

Ethics and Epistemology in Big Data Research

Biomedical innovation and translation are increasingly emphasizing research using "big data." The hope is that big data methods will both speed up research and make its results more applicable to "real-world" patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals.

Use of Real-World Data for the Research, Development, and Evaluation of Oncology Precision Medicines

Although randomized controlled trials remain the scientific ideal for determining the efficacy and safety of new treatments, they are sometimes insufficient to address the evidentiary requirements of regulators and payers. This is particularly the case when it comes to precision medicines because trials are often small, deliver incomplete insights into outcomes of most interest to policymakers (eg, overall survival), and may fail to address other complex diagnostic and treatment-related questions. Additional methods, both experimental and observational, are increasingly being used to fill critical evidentiary gaps. A number of modified early- and late-phase trial designs have been proposed to better support earlier biomarker validation, patient identification, and selection for regulatory studies, but there is still a need for confirmatory evidence from real-world data sources. These data are usually provided through observational, postapproval, phase IIIB and IV studies, which rely heavily on registries and other electronic data sets—most notably data from electronic health records. It is, therefore, crucial to understand what ethical, practical, and scientific challenges are raised by the use of electronic health records to generate evidence about precision medicines.

Twelve-week ribavirin-free direct-acting antivirals for treatment-experienced Chinese with HCV genotype 1b infection including cirrhotic patients

BACKGROUND

Treatment-experienced chronic hepatitis C (CHC) genotype (GT) 1b represents a major medical burden in China. We evaluate the efficacy, safety and cost-effectiveness of ribavirin (RBV)-free pan-oral direct-acting antivirals (DAAs) in treatment-experienced Chinese with GT1b CHC, including patients with cirrhosis.

METHODS

One hundred forty treatment-experienced GT1b CHC Chinese with and without cirrhosis were included in this study. Ninety-four patients were treated with either daclatasvir (DCV, 60 mg)-sofosbuvir (SOF, 400 mg) (group 1, n = 46) or ledipasvir (LDV, 90 mg)-SOF (400 mg) (group 2, n = 48) for 12 weeks. Forty-six patients treated with pegylated interferon and RBV therapy for 72 weeks were enrolled as the control group (group 3). Patients were followed at 4-weekly intervals till 24 weeks after the end of treatment.

RESULTS

All patients in group 1 (46/46, 100 %) and 2 (48/48, 100 %) had achieved sustained virologic response at 24 weeks after the end of treatment (SVR 24), which was significantly higher than that of group 3 (13/46, 28.3 %) (p < 0.001). The SVR 24 rates of cirrhotic patients in group 1 (27/27, 100 %) and 2 (27/27, 100 %) were also significantly higher than that of group 3 (3/25, 12 %) (p < 0.001). Twelve weeks of RBV-free LDV-SOF and DCV-SOF was either cost-saving or cost-effective. Adverse events were significantly lower in group 1 and 2 compared with group 3 (p < 0.001).

CONCLUSION

Compared with standard therapies, 12 weeks of RBV-free DAA therapies is highly effective, well tolerated and cost-effective in treatment-experienced Chinese with GT1b CHC including patients with cirrhosis.

Precision medicine in cardiology

The cardiovascular research and clinical communities are ideally positioned to address the epidemic of noncommunicable causes of death, as well as advance our understanding of human health and disease, through the development and implementation of precision medicine. New tools will be needed for describing the cardiovascular health status of individuals and populations, including 'omic' data, exposome and social determinants of health, the microbiome, behaviours and motivations, patient-generated data, and the array of data in electronic medical records. Cardiovascular specialists can build on their experience and use precision medicine to facilitate discovery science and improve the efficiency of clinical research, with the goal of providing more precise information to improve the health of individuals and populations. Overcoming the barriers to implementing precision medicine will require addressing a range of technical and sociopolitical issues. Health care under precision medicine will become a more integrated, dynamic system, in which patients are no longer a passive entity on whom measurements are made, but instead are central stakeholders who contribute data and participate actively in shared decision-making. Many traditionally defined diseases have common mechanisms; therefore, elimination of a siloed approach to medicine will ultimately pave the path to the creation of a universal precision medicine environment.