Health Economics Tools and Precision Medicine: Opportunities and Challenges

Advances in Addressing Patient Heterogeneity in Economic Evaluation: A Review of the Methods Literature

Cost-effectiveness analyses commonly use population or sample averages, which can mask key differences across subgroups and may lead to suboptimal resource allocation. Despite there being several new methods developed over the last decade, there is no recent summary of what methods are available to researchers. This review sought to identify advances in methods for addressing patient heterogeneity in economic evaluations and to provide an overview of these methods. A literature search was conducted using the Econlit, Embase and MEDLINE databases to identify studies published after 2011 (date of a previous review on this topic). Eligible studies needed to have an explicit methodological focus, related to how patient heterogeneity can be accounted for within a full economic evaluation. Sixteen studies were included in the review. Methodologies were varied and included regression techniques, model design and value of information analysis. Recent publications have applied methodologies more commonly used in other fields, such as machine learning and causal forests. Commonly noted challenges associated with considering patient heterogeneity included data availability (e.g., sample size), statistical issues (e.g., risk of false positives) and practical factors (e.g., computation time). A range of methods are available to address patient heterogeneity in economic evaluation, with relevant methods differing according to research question, scope of the economic evaluation and data availability. Researchers need to be aware of the challenges associated with addressing patient heterogeneity (e.g., data availability) to ensure findings are meaningful and robust. Future research is needed to assess whether and how methods are being applied in practice.

Clinical Value of Molecular Targets and FDA-Approved Genome-Targeted Cancer Therapies

Importance

The number of new genome-targeted cancer drugs has increased, offering the possibility of personalized therapy, often at a very high cost.

Objective

To assess the validity of molecular targets and therapeutic benefits of US Food and Drug Administration-approved genome-targeted cancer drugs based on the outcomes of their corresponding pivotal clinical trials.

Design and Settings

In this cohort study, all genome-targeted cancer drugs that were FDA-approved between January 1, 2015, and December 31, 2022, were analyzed. From FDA drug labels and trial reports, key characteristics of pivotal trials were extracted, including the outcomes assessed.

Main Outcomes and Measures

The strength of evidence supporting molecular targetability was assessed using the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of Molecular Targets (ESCAT). Clinical benefit for their approved indications was evaluated using the ESMO-Magnitude of Clinical Benefit Scale (ESMO-MCBS). Substantial clinical benefit was defined as a grade of A or B for curative intent and 4 or 5 for noncurative intent. Molecular targets qualifying for ESCAT category level I-A and I-B associated with substantial clinical benefit by ESMO-MCBS were rated as high-benefit genomic-based cancer treatments.

Results

A total of 50 molecular-targeted drugs covering 84 indications were analyzed. Forty-five indications (54%) were approved based on phase 1 or phase 2 pivotal trials, 45 (54%) were supported by single-arm pivotal trials, and 48 (57%) were approved on the basis of subgroup analyses. By each indication, 46 of 84 primary end points (55%) were overall response rate (median [IQR] overall response rate, 57% [40%-69%]; median [IQR] duration of response, 11.1 [9.2-19.8] months). Among the 84 pivotal trials supporting these 84 indications, 38 trials (45%) had I-A ESCAT targetability, and 32 (38%) had I-B targetability. Overall, 24 of 84 trials (29%) demonstrated substantial clinical benefit via ESMO-MCBS. Combining these ratings, 24 of 84 indications (29%) were associated with high-benefit genomic-based cancer treatments.

Conclusions and Relevance

The results of this cohort study demonstrate that among recently approved molecular-targeted cancer therapies, fewer than one-third demonstrated substantial patient benefits at approval. Benefit frameworks such as ESMO-MCBS and ESCAT can help physicians, patients, and payers identify therapies with the greatest clinical potential.

Reimbursement in the Context of Precision Oncology Approaches in Metastatic Breast Cancer: Challenges and Experiences

Background

Precision oncology programs using next-generation sequencing to detect predictive biomarkers are extending therapeutic options for patients with metastatic breast cancer (mBC). Regularly, based on the recommendations of the interdisciplinary molecular tumor board (iMTB), an inclusion in a clinical trial is not possible. In this case, the German health insurance system allows for the application of reimbursement for an off-label drug use. Here, we describe the current challenges and our experience with reimbursement of molecular therapies in mBC.

Methods

A total of 100 applications for reimbursement of off-label therapies recommended by an iMTB were filed for patients with mBC, of which 89 were evaluable for this analysis. The approval rate was correlated with the molecular level of evidence of the respective therapy according to the National Center for Tumor Diseases (NCT) and European Society for Medical Oncology Scale for Clinical Actionability of molecular Targets (ESCAT) classification as well as with pretreatment therapy lines.

Findings

Overall, 53.9% (48/89) of reimbursement applications were approved. Applications for therapies based on level of evidence m1 (NCT classification), tier I and II (ESCAT classification) had a significantly and clinically relevant increased chance of reimbursement, while a greater number of previous treatment lines had no significantly increased chance of approval, though a trend of approval toward higher treatment lines was detectable.

Interpretation

Currently, the German jurisdiction seems to aggravate the clinical implementation of clinically urgently needed molecular therapies.

The Utility of Next-Generation Sequencing in the Treatment Decision-Making for Metastatic Non-Small-Cell Lung Cancer

Next-generation sequencing (NGS) is a fast and relatively inexpensive method to sequence a large number of genes with crucial importance in cancer medicine. Nowadays, NGS is frequently used in diagnostic and therapeutic decisions in oncology; however, recently, it was demonstrated that only a few cancer sites actually benefit from this assessment. Moreover, the association of a mutant gene with a targeted drug is not always as predicted during in-vitro trials and is often not associated with tumor response. To predict the efficacy of such an association several classification systems have been developed. The present review aims to analyze the most important tumor agnostic treatment trials and assess how they shape selecting cancer patients for NGS. Moreover, it aims to determine how mutation-drug associations can be classified by their targetability and level of evidence of efficacy in non-small-cell lung cancer.

Early technology assessment of using whole genome sequencing in personalized oncology

Introduction: Personalized medicine-based treatments in advanced cancer hold the promise to offer substantial health benefits to genetic subgroups, but require efficient biomarker-based patient stratification to match the right treatment and may be expensive. Standard molecular diagnostics are currently very heterogeneous, and tests are often performed sequentially. The alternative to whole genome sequencing (WGS) i.e. simultaneously testing for all relevant DNA-based biomarkers thereby allowing immediate selection of the most optimal therapy, is more costly than current techniques. In the current implementation stage, it is important to explore the added value and cost-effectiveness of using WGS on a patient level and to assess optimal introduction of WGS on the level of the healthcare system.Areas covered: First, an overview of current worldwide initiatives concerning the use of WGS in clinical practice for cancer diagnostics is given. Second, a comprehensive, early health technology assessment (HTA) approach of evaluating WGS in the Netherlands is described, relating to the following aspects: diagnostic value, WGS-based treatment decisions, assessment of long-term health benefits and harms, early cost-effectiveness modeling, nation-wide organization, and Ethical, Legal and Societal Implications.Expert opinion: This study provides evidence to guide further development and implementation of WGS in clinical practice and the healthcare system.

Practical considerations in screening for genetic alterations in cholangiocarcinoma

Cholangiocarcinoma (CCA) encompasses diverse epithelial tumors historically associated with poor outcomes due to an aggressive disease course, late diagnosis, and limited benefit of standard chemotherapy for advanced disease. Comprehensive molecular profiling has revealed a diverse landscape of genomic alterations as oncogenic drivers in CCA. TP53 mutations, CDKN2A/B loss, and KRAS mutations are the most common genetic alterations in CCA. However, intrahepatic CCA (iCCA) and extrahepatic CCA (eCCA) differ substantially in the frequency of many alterations. This includes actionable alterations, such as isocitrate dehydrogenase 1 (IDH1) mutations and a large variety of FGFR2 rearrangements, which are found in up to 29% and ∼10% of patients with iCCA, respectively, but are rare in eCCA. FGFR2 rearrangements are currently the only genetic alteration in CCA for which a targeted therapy, the fibroblast growth factor receptor 1-3 inhibitor pemigatinib, has been approved. However, favorable phase III results for IDH1-targeted therapy with ivosidenib in iCCA have been published, and numerous other alterations are actionable by targeted therapies approved in other indications. Recent advances in next-generation sequencing (NGS) have led to the development of assays that allow comprehensive genomic profiling of large gene panels within 2-3 weeks, including in vitro diagnostic tests approved in the United States. These assays vary regarding acceptable source material (tumor tissue or peripheral whole blood), genetic source for library construction (DNA or RNA), target selection technology, gene panel size, and type of detectable genomic alterations. While some large commercial laboratories offer rapid and comprehensive genomic profiling services based on proprietary assay platforms, clinical centers may use commercial genomic profiling kits designed for clinical research to develop their own customized laboratory-developed tests. Large-scale genomic profiling based on NGS allows for a detailed and precise molecular diagnosis of CCA and provides an important opportunity for improved targeted treatment plans tailored to the individual patient's genetic signature.

THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar

In 2016, the World Innovation Summit for Health (WISH) published its Forum Report on precision medicine "PRECISION MEDICINE - A GLOBAL ACTION PLAN FOR IMPACT". Healthcare is undergoing a transformation, and it is imperative to leverage new technologies to generate new data and support the advent of precision medicine (PM). Recent scientific breakthroughs and technological advancements have improved our disease knowledge and altered diagnosis and treatment approaches resulting in a more precise, predictive, preventative and personalized health care that is customized for the individual patient. Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. Additionally, personalized medicine promises to revolutionize healthcare, with its key goal of providing the right treatment to the right patient at the right time and dose, and thus the potential of improving quality of life and helping to bring down healthcare costs.This policy briefing will look in detail at the issues surrounding continued development, sustained investment, risk factors, testing and approval of innovations for better strategy and faster process. The paper will serve as a policy bridge that is required to enhance a conscious decision among the powers-that-be in Qatar in order to find a way to harmonize multiple strands of activity and responsibility in the health arena. The end goal will be for Qatar to enhance public awareness and engagement and to integrate effectively the incredible advances in research into healthcare systems, for the benefit of all patients.The PM policy briefing provides concrete recommendations on moving forward with PM initiatives in Qatar and internationally. Equally important, integration of PM within a primary care setting, building a coalition of community champions through awareness and advocacy, finally, communicating PM value, patient engagement/empowerment and education/continued professional development programs of the healthcare workforce.Key recommendations for implementation of precision medicine inside and outside Qatar: 1. Create Community Awareness and PM Education Programs 2. Engage and Empower Patients 3. Communicate PM Value 4. Develop appropriate Infrastructure and Information Management Systems 5. Integrate PM into standard Healthcare System and Ensure Access to Care PM is no longer futuristic. It is here. Implementing PM in routine clinical care does require some investment and infrastructure development. Invariably, cost and lack of expertise are cited as barriers to PM implementation. Equally consequential, are the curriculum and professional development of medical care experts.Policymakers need to lead and coordinate effort among stakeholders and consider cultural and faith perspectives to ensure success. It is essential that policymakers integrate PM approaches into national strategies to improve health and health care for all, and to drive towards the future of medicine precision health.

Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: a report from the ESMO Precision Medicine Working Group

Next-generation sequencing (NGS) allows sequencing of a high number of nucleotides in a short time frame at an affordable cost. While this technology has been widely implemented, there are no recommendations from scientific societies about its use in oncology practice. The European Society for Medical Oncology (ESMO) is proposing three levels of recommendations for the use of NGS. Based on the current evidence, ESMO recommends routine use of NGS on tumour samples in advanced non-squamous non-small-cell lung cancer (NSCLC), prostate cancers, ovarian cancers and cholangiocarcinoma. In these tumours, large multigene panels could be used if they add acceptable extra cost compared with small panels. In colon cancers, NGS could be an alternative to PCR. In addition, based on the KN158 trial and considering that patients with endometrial and small-cell lung cancers should have broad access to anti-programmed cell death 1 (anti-PD1) antibodies, it is recommended to test tumour mutational burden (TMB) in cervical cancers, well- and moderately-differentiated neuroendocrine tumours, salivary cancers, thyroid cancers and vulvar cancers, as TMB-high predicted response to pembrolizumab in these cancers. Outside the indications of multigene panels, and considering that the use of large panels of genes could lead to few clinically meaningful responders, ESMO acknowledges that a patient and a doctor could decide together to order a large panel of genes, pending no extra cost for the public health care system and if the patient is informed about the low likelihood of benefit. ESMO recommends that the use of off-label drugs matched to genomics is done only if an access programme and a procedure of decision has been developed at the national or regional level. Finally, ESMO recommends that clinical research centres develop multigene sequencing as a tool to screen patients eligible for clinical trials and to accelerate drug development, and prospectively capture the data that could further inform how to optimise the use of this technology.

Machine Learning for Precision Health Economics and Outcomes Research (P-HEOR): Conceptual Review of Applications and Next Steps

Precision health economics and outcomes research (P-HEOR) integrates economic and clinical value assessment by explicitly discovering distinct clinical and health care utilization phenotypes among patients. Through a conceptualized example, the objective of this review is to highlight the capabilities and limitations of machine learning (ML) applications to P-HEOR and to contextualize the potential opportunities and challenges for the wide adoption of ML for health economics. We outline a P-HEOR conceptual framework extending the ML methodology to comparatively assess the economic value of treatment regimens. Latest methodology developments on bias and confounding control in ML applications to precision medicine are also summarized.