Perspectives on Clinical Adoption Barriers to Blood-Based Multi-Cancer Early Detection Tests across Stakeholders.

Current United States Preventive Services Task Force (USPSTF) recommendations include routine screening for breast, cervical, colorectal, and lung cancer; however, two out of every three cancer cases occur in other indications, leading to diagnoses in advanced stages of the disease and a higher likelihood of mortality. Blood-based multi-cancer early detection (MCED) tests can impact cancer screening and early detection by monitoring for multiple different cancer types at once, including indications where screening is not performed routinely today. We conducted a survey amongst healthcare providers (HCPs), payers, and patients within the U.S. health system to understand the current utilization of cancer screening tests and the anticipated barriers to widespread adoption of blood-based MCED tests. The results indicated that the community favors the adoption of blood-based MCED tests and that there is broad agreement on the value proposition. Despite this recognition, the survey highlighted that there is limited use today due to the perceived lack of clinical accuracy and utility data, high out-of-pocket patient costs, and lack of payer coverage. To overcome the hurdles for future widespread adoption of blood-based MCED tests, increased investment in data generation, education, and implementation of logistical support for HCPs will be critical.

Impact of Clinical Practice Gaps on the Implementation of Personalized Medicine in Advanced Non-Small-Cell Lung Cancer.

PURPOSE: Personalized medicine presents new opportunities for patients with cancer. However, many patients do not receive the most effective personalized treatments because of challenges associated with integrating predictive biomarker testing into clinical care. Patients are lost at various steps along the precision oncology pathway because of operational inefficiencies, limited understanding of biomarker strategies, inappropriate testing result usage, and access barriers. We examine the impact of various clinical practice gaps associated with diagnostic testing-informed personalized medicine strategies on the treatment of advanced non-small-cell lung cancer (aNSCLC). METHODS: Using Diaceutics' Data Repository, a multisource database including commercial and Medicare claims and laboratory data from over 500,000 patients with non-small-cell lung cancer in the United States, we analyzed the number of patients with newly diagnosed aNSCLC who could have, but did not, benefit from a personalized treatment. The analysis focuses on the independent and cumulative impacts of gaps occurring during seven steps of the precision oncology pathway, from diagnosis to treatment. RESULTS: For every 1,000 patients in the study cohort, 497 (49.7%) are lost to precision oncology because of factors associated with getting biomarker test results. Among the 503 of 1,000 patients who did receive results from a biomarker test, 147 (29.2%) did not receive appropriate targeted treatments. Thus, approximately 64% of potentially eligible patients with aNSCLC are not benefiting from precision oncology therapies appropriate for their disease. CONCLUSION: Most patients with aNSCLC eligible for precision oncology treatments do not benefit from them because of clinical practice gaps. This finding is likely reflective of similar gaps in other cancer types. An increased understanding of the impact of each practice gap can inform strategies to improve the delivery of precision oncology, helping to fully realize the promise of personalized medicine.

Stakeholders Perceptions of Barriers to Precision Medicine Adoption in the United States.

Despite evidence that precision medicine (PM) results in improved patient care, the broad adoption and implementation has been challenging across the United States (US). To better understand the perceived barriers associated with PM adoption, a quantitative survey was conducted across five stakeholders including medical oncologists, surgeons, lab directors, payers, and patients. The results of the survey reveal that stakeholders are often not aligned on the perceived challenges with PM awareness, education and reimbursement, with there being stark contrast in viewpoints particularly between clinicians, payers, and patients. The output of this study aims to help raise the awareness that misalignment on the challenges to PM adoption is contributing to broader lack of implementation that ultimately impacts patients. With better understanding of stakeholder viewpoints, we can help alleviate the challenges by focusing on multi-disciplinary education and awareness to ultimately improve patient outcomes.

Comparison of FDA Table of Pharmacogenetic Associations and Clinical Pharmacogenetics Implementation Consortium guidelines.

PURPOSE: Healthcare professionals need a clear understanding of information about gene-drug interactions in order to make optimal use of pharmacogenetic (PGx) testing. In this report, we compare PGx information in the US Food and Drug Administration (FDA) Table of Pharmacogenetic Associations with information presented in Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. SUMMARY: Information from CPIC guidelines and the FDA Table of Pharmacogenetic Associations do not have a high level of concordance. Many drugs mentioned in CPIC guidelines are not listed in the FDA table and vice versa, and the same gene-drug association and dosing recommendation was reported for only 5 of the 126 drugs included in either source. Furthermore, classification of drugs in specific sections of the FDA table does not correlate well with CPIC-assigned or provisionally assigned clinical actionability levels. The Pharmacogenomics Knowledge Base (PharmGKB) clinical annotation levels are generally high for drugs mentioned in CPIC guidelines. PharmGKB clinical annotation levels are often unassigned or are lower level for drugs listed on the FDA table but not in CPIC guidelines. These differences may be due in part to FDA having access to PGx information that is unavailable in published literature and/or because PGx classifications are based on criteria other than clinical actionability. CONCLUSION: There are important differences between the PGx information presented in the FDA Table of Pharmacogenetic Associations and in CPIC guidelines. FDA and CPIC have different perspectives when evaluating PGx associations and use different approaches and information resources when considering clinical validity related to specific medicines. Understanding how information sources developed by each group differ and can be used together to form a holistic view of PGx may be helpful in increasing adoption of these information sources in practice.

Clinical Utility of Genomic Testing in Cancer Care.

PURPOSE: In the era of personalized medicine, physicians rely on their understanding of clinical utility to assess the value of rapidly evolving genetic and genomic tests. Current definitions of the clinical utility of genetic testing sufficiently capture a range of benefits and risks that derive from positive and negative results of tests that assess one gene or a few genes. However, these definitions of clinical utility are inadequate to recognize the wider scope of benefits that accrue from more comprehensive genomic tests, which can develop data sets that inform clinical decision making as well as population health and scientific advancement in novel ways. METHODS: An expert roundtable discussion with leaders from multiple sectors of the health care ecosystem was convened to develop a contemporary, fuller definition of the clinical utility of genomic testing in cancer care. RESULTS: We present an updated definition and offer recommendations for successful implementation. CONCLUSION: Applying this expanded definition will encourage evidence-based use of genomic testing in cancer care by helping physicians and other health care decision makers account for the broader range of benefits and risks of testing for individual patients, health systems, population health, and scientific advancement.

The integration of personalized medicine into health systems: progress and a path forward.

Tweetable abstract Fueled by technological advancements and the integration efforts of many pioneer health systems, personalized medicine is now being clinically implemented at measurable but incomplete levels system-wide.

A Quantitative Framework for Measuring Personalized Medicine Integration into US Healthcare Delivery Organizations.

Personalized medicine (PM) approaches have revolutionized healthcare delivery by offering new insights that enable healthcare providers to select the optimal treatment approach for their patients. However, despite the consensus that these approaches have significant value, implementation across the US is highly variable. In order to address barriers to widespread PM adoption, a comprehensive and methodical approach to assessing the current level of PM integration within a given organization and the broader healthcare system is needed. A quantitative framework encompassing a multifactorial approach to assessing PM adoption has been developed and used to generate a rating of PM integration in 153 organizations across the US. The results suggest significant heterogeneity in adoption levels but also some consistent themes in what defines a high-performing organization, including the sophistication of data collected, data sharing practices, and the level of internal funding committed to supporting PM initiatives. A longitudinal approach to data collection will be valuable to track continued progress and adapt to new challenges and barriers to PM adoption as they arise.

Clinical and Economic Value of Genetic Sequencing for Personalized Therapy in Non-small-cell Lung Cancer.

Two recent studies examining the clinical and economic value of next-generation sequencing (NGS)-based diagnostic testing (multi-gene panel examining ≥ 30 genes) for non-small-cell lung cancer therapy compared with single gene ALK, EGFR testing to select therapy demonstrated statistically insignificant improvement in population-level overall survival and only a moderate incremental cost-effectiveness ratio associated with the NGS testing approach. The data, however, revealed a key practice gap: many patients with actionable mutations did not receive targeted therapies. This gap is attributed, in part, to limitations in the availability and interpretation of NGS results, sample processing constraints, limited access to targeted therapies, and lagging awareness of the rapidly evolving field of personalized medicine, all of which result in "clinical inertia," (ie, suboptimal use of targeted therapy against an actionable driver alteration identified by NGS testing). Additional analysis estimated that cost-effectiveness would improve significantly if a higher percentage of patients received testing and if all patients who were eligible for targeted therapies received them. Strategies to address implementation barriers will help to realize the full value of NGS testing in cancer care.

One size does not always fit all in value assessment.

Laying a clear path for incorporating reliable evidence on heterogeneity in value assessments could improve their applicability for healthcare decision making.

Proposals from the 2018 PhRMA Challenge Award Program.

DISCLOSURES: This introduction was written under the sponsorship of the PhRMA Foundation Award Program. The authors have nothing to disclose.

Cost Effectiveness of Multigene Panel Sequencing for Patients With Advanced Non-Small-Cell Lung Cancer.

PURPOSE: Compared with single-marker genetic testing (SMGT), multigene panel sequencing (MGPS) has the potential to identify more patients with cancer who could benefit from targeted therapies, but the effects on outcome and total cost of care are uncertain. Our goal was to estimate the clinical and cost effectiveness of MGPS versus SMGT among patients with advanced non-small-cell lung cancer (aNSCLC). METHODS: Patients with aNSCLC-stage IIIB or metastatic-who were diagnosed between 2011 and 2016 were identified from the Flatiron Health database. After stratifying patients into MGPS or SMGT cohorts, we analyzed the percentage of patients who received targeted treatment, survival, and total costs of care. SMGT included epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase testing. MGPS also allowed for the detection of BRAF, RET, ROS1, HER2, and MET mutations. Cost data sources were the Centers for Medicare & Medicaid Services Fee Schedule and 2017 average sales price drug cost. We estimated the incremental cost-effectiveness ratio from a US payer perspective over a lifetime horizon using a decision model. RESULTS: We identified 5,688 patients with aNSCLC who received MGPS (n = 875) or SMGT (n = 4,813), of which 22% tested positive for epidermal growth factor receptor (18.5% MGPS; 17.3% SMGT) or anaplastic lymphoma kinase (3.59% MGPS; 3.78% SMGT). Among MGPS-tested patients, an additional 8% were found to have BRAF, RET, ROS1, HER2, or MET mutations. Of MGPS-tested patients, 21% received treatments that were targeted to the specific mutations versus 19% with SMGT. Expected survival was 1.14 life years (LYs) in SMGT versus 1.20 LYs in MGPS. Lifetime total costs were $8,814 higher per patient for MGPS. The incremental cost-effectiveness ratio of MGPS versus SMGT was $148,478 per LY gained. CONCLUSION: On the basis of data from a nationwide oncology patient database, MGPS is shown to have moderate cost effectiveness compared with SMGT in patients with aNSCLC.

Strategies For Clinical Implementation: Precision Oncology At Three Distinct Institutions.

Despite rapid advances in molecular diagnostics and targeted therapeutics, the adoption of precision medicine into clinical oncology workflows has been slow. Questions about clinical utility, inconsistent reimbursement for molecular diagnostics, and limited access to targeted therapies are some of the major hurdles that have hampered clinical adoption. Despite these challenges, providers have invested in precision medicine programs in an ongoing search for innovative care models to deliver improved patient outcomes and achieve economic gains. We describe the precision oncology medicine programs implemented by an integrated delivery system, a community care center, and an academic medical center, to demonstrate the approaches and challenges associated with clinical implementation efforts designed to advance this treatment paradigm. Payer policies that include coverage for broad genomic testing panels would support the broader application of precision medicine, deepen research benefits, and bring targeted therapies to more patients with advanced cancer.

Strategies for integrating personalized medicine into healthcare practice.

AIM: Research and innovation in personalized medicine are surging, however, its adoption into clinical practice is comparatively slow. We identify common challenges to the clinical adoption of personalized medicine and provide strategies for addressing these challenges. METHODS: Our team developed a list of common challenges through a series of group discussions, surveys and interviews, and convened a national summit to discuss solutions for overcoming these challenges. We used a framework approach for thematic analysis. RESULTS: We categorized challenges into five areas of need: education and awareness; patient empowerment; value recognition; infrastructure and information management; and ensuring access to care. We then developed strategies to address these challenges. CONCLUSION: In order for healthcare to transition into personalized medicine, it is necessary for stakeholders to build momentum by implementing a progression of strategies.

What Contributes Most to High Health Care Costs? Health Care Spending in High Resource Patients.

BACKGROUND: U.S. health care spending nearly doubled in the decade from 2000-2010. Although the pace of increase has moderated recently, the rate of growth of health care costs is expected to be higher than the growth in the economy for the near future. Previous studies have estimated that 5% of patients account for half of all health care costs, while the top 1% of spenders account for over 27% of costs. The distribution of health care expenditures by type of service and the prevalence of particular health conditions for these patients is not clear, and is likely to differ from the overall population. OBJECTIVE: To examine health care spending patterns and what contributes to costs for the top 5% of managed health care users based on total expenditures. METHODS: This retrospective observational study employed a large administrative claims database analysis of health care claims of managed care enrollees across the full age and care spectrum. Direct health care expenditures were compared during calendar year 2011 by place of service (outpatient, inpatient, and pharmacy), payer type (commercially insured, Medicare Advantage, and Medicaid managed care), and therapy area between the full population and high resource patients (HRP). RESULTS: The mean total expenditure per HRP during calendar year 2011 was $43,104 versus $3,955 per patient for the full population. Treatment of back disorders and osteoarthritis contributed the largest share of expenditures in both HRP and the full study population, while chronic renal failure, heart disease, and some oncology treatments accounted for disproportionately higher expenditures in HRP. The share of overall expenditures attributed to inpatient services was significantly higher for HRP (40.0%) compared with the full population (24.6%), while the share of expenditures attributed to pharmacy (HRP = 18.1%, full = 21.4%) and outpatient services (HRP = 41.9%, full = 54.1%) was reduced. This pattern was observed across payer type. While the use of physician-administered pharmaceuticals was slightly higher in HRP, their use did not alter this spending pattern. CONCLUSIONS: Overall, expenditures in the HRP population are more than 10-fold higher compared with the full population. Managed care pharmacy can benefit from understanding what contributes to these higher costs, and managed care directors should consider an appropriately balanced assessment of the share of total spend by service and therapeutic category in HRP when devising drug usage and related cost-management strategies.

Improving the Efficiency and Quality of the Value Assessment Process for Companion Diagnostic Tests: The Companion test Assessment Tool (CAT).

BACKGROUND: Companion diagnostic tests (CDTs) have emerged as a vital technology in the effective use of an increasing number of targeted drug therapies. Although CDTs can offer a multitude of potential benefits, assessing their value within a health technology appraisal process can be challenging because of a complex array of factors that influence clinical and economic outcomes. OBJECTIVE: To develop a user-friendly tool to assist managed care and other health care decision makers in screening companion tests and determining whether an intensive technology review is necessary and, if so, where the review should be focused to improve efficiency. METHODS: First, we conducted a systematic literature review of CDT cost-effectiveness studies to identify value drivers. Second, we conducted key informant interviews with a diverse group of stakeholders to elicit feedback and solicit any additional value drivers and identify desirable attributes for an evidence review tool. A draft tool was developed based on this information that captured value drivers, usability features, and had a particular focus on practical use by nonexperts. Finally, the tool was pilot tested with test developers and managed care evidence evaluators to assess face-validity and usability. The tool was also evaluated using several diverse examples of existing companion diagnostics and refined accordingly. RESULTS: We identified 65 cost-effectiveness studies of companion diagnostic technologies. The following factors were most commonly identified as value drivers from our literature review: clinical validity of testing; efficacy, safety, and cost of baseline and alternative treatments; cost and mortality of health states; and biomarker prevalence and testing cost. Stakeholders identified the following additional factors that they believed influenced the overall value of a companion test: regulatory status, actionability, utility, and market penetration. These factors were used to maximize the efficiency of the evidence review process. Stakeholders also stated that a tool should be easy to use and time efficient. Cognitive interviews with stakeholders led to minor changes in the draft tool to improve usability and relevance. The final tool consisted of 4 sections: (1) eligibility for review (2 questions), (2) prioritization of review (3 questions), (3) clinical review (3 questions), and (4) economic review (5 questions). CONCLUSIONS: Although the evaluation of CDTs can be challenging because of limited evidence and the added complexity of incorporating a diagnostic test into drug treatment decisions, using a pragmatic tool to identify tests that do not need extensive evaluation may improve the efficiency and effectiveness of CDT value assessments.

Clinical evidence inputs to comparative effectiveness research could impact the development of novel treatments.

AIM: This study aims to analyze the impacts of a range of clinical evidence generation scenarios associated with comparative effectiveness research (CER) on pharmaceutical innovation. MATERIALS & METHODS: We used the Global Pharmaceutical Policy Model to project the effect of changes in pharmaceutical producer costs, revenues and timings on drug innovation and health for the age 55+ populations in the USA and Europe through year 2060 using three clinical scenarios. RESULTS: Changes in producer incentives from widespread CER evidence generation and use had varied but often large predicted impacts on simulated outcomes in 2060. Effect on the number of new drug introductions ranged from a 81.1% reduction to a 45.5% increase, and the effect on population-level life expectancy ranged from a 15.6% reduction to a 11.4% increase compared to baseline estimates. CONCLUSION: The uncertainty surrounding the consequences of increased clinical evidence generation and use on innovation calls for a carefully measured approach to CER implementation, balancing near-term benefits to spending and health with long-term implications for innovation.

The value of specialty pharmaceuticals - a systematic review.

OBJECTIVES: Novel specialty biopharmaceuticals hold promise for patients living with complex and chronic conditions. However, high research and development costs, special handling, and other necessary enhancements to patient support programs all contribute to frequently higher prices for these products. This study sought to assess the value of specialty pharmaceuticals through an examination of the clinical, functional, and economic benefits of these treatments for the top 3 disease areas by pharmaceutical spend: rheumatoid arthritis (RA), multiple sclerosis (MS), and breast cancer (BC). STUDY DESIGN: Systematic literature review. METHODS: A systematic review of market research and cost-effectiveness articles was conducted for each disease area to assess clinical, functional, and economic outcomes associated with specialty medicine treatments versus the previous standard of care. RESULTS: All RA clinical (American College of Rheumatology) and functional (Health Assessment Questionnaire) outcome articles were classified as positive. The median cost-effectiveness ratio was $38,900 per quality-adjusted life year (QALY). All MS clinical outcome (relapse rate) articles were positive. The MS functional outcome (Expanded Disability Status Scale) findings were less conclusive. The median cost-effectiveness ratio was $248,000 per QALY. The majority of BC articles yielded statistically inconclusive results for survival. All functional outcome (Quality of Life Questionnaire- Core 30) articles were positive. The median cost-effectiveness ratio was $51,900 per QALY. CONCLUSIONS: Novel specialty therapies hold promise for arresting disease progression and improving quality of life for the 3 conditions associated with the highest specialty pharmaceutical spend. These findings demonstrate a strong value proposition for specialty pharmaceuticals, and suggest even greater potential individual patient benefit with consideration of patient heterogeneity.

The emerging relevance of heterogeneity of treatment effect in clinical care: a study using stage IV prostate cancer as a model.

AIM: Heterogeneity of treatment effect (HTE) occurs when patient factors modify a treatment's effect on health outcomes due to interactions between these factors and the treatment. This article reviews evidence regarding HTE in stage IV prostate cancer (S4PC). METHOD: A systematic literature review was conducted in the MEDLINE and PubMed databases. Inclusion criteria required that articles examine the treatment-related impact of HTE factors on survival, adverse events or health-related quality of life in S4PC patients. The quality of evidence was graded good, fair or poor based on Agency for Healthcare Research and Quality guidelines. RESULTS: The search identified 2659 articles, of which 92 met the inclusion/exclusion criteria. HTE in S4PC was studied for biologic factors including age, race, clinical signs/symptoms, measures of S4PC disease severity, genetic factors, laboratory data, prior treatment, concurrent medications and comorbidities. Nonbiologic factors that were studied included social, geographic and dietary factors. Age and race seldom showed any correlation with S4PC outcomes. CONCLUSION: Diverse biologic and nonbiologic factors contribute to HTE in S4PC. This review in S4PC also provides an approach for examining HTE for other medical conditions. Ultimately, such knowledge can help oncologists prescribe more personalized medicine, help patients make more informed treatment choices, and inform policy-making and treatment coverage decisions.