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Evidence-Based Oncology August 2016
Solutions for Reducing Patient Cost Sharing for Medications
Marialanna Lee, MSC; Brian Connell; Elisa Weiss, PhD; and Louis J. DeGennaro, PhD
Charitable Assistance Among Economically Vulnerable Cancer Patients: Patient Access Network Foundation Summary Statistics 2011-2015
Helaine E. Resnick PhD, MPH; Bruce Barth; and Daniel Klein, MHS
The Toll of Cancer Care - Clinical and Financial Toxicity
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Surabhi Dangi-Garimella, PhD
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Jeffrey W. Chell, MD
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Finding Solutions for Cancer Patients: The American Cancer Society's Health Insurance Assistance Service
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Precision Oncology: Why Payers Should Initiate CGP Coverage Now!
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Precision Oncology: Why Payers Should Initiate CGP Coverage Now!

Jerry Conway and Ingrid Marino, MS, CGC
Precision oncology, or the clinically and financially efficient use of genomically matched treatments and clinical trials, is evolving as a potentially important starting point for cancer care within successful alternative payment models.
According to the 2016 Genentech Oncology Trends Survey Report,1 the top 3 most pressing challenges faced by the 100 payers surveyed are:
  1. Control of cancer specialty drug costs
  2. Control of overall cancer care costs
  3. Balancing treatment standardization with personalization
Payers are responding to these challenges by implementing a number of alternative payment models or APMs (eg, clinical pathways, medical home, and bundled payments) that are designed to shift from a “pay for volume” to a “pay for value” paradigm. Precision oncology, or the clinically and financially efficient use of genomically matched treatments and clinical trials, is evolving as a potentially important starting point for cancer care within successful APMs.

The use of validated comprehensive genomic profiling (CGP)2 at initial diagnosis for patients with particularly aggressive or metastatic cancer is playing an important role in routine clinical care and new payment approaches. This is due to CGP being a clinically efficient and cost-effective3-5 means of identifying the presence or absence of genomically matched targets to FDA-approved drugs covered by payers (typically those with National Comprehensive Cancer Network [NCCN] Category 1 and 2A levels of evidence). CGP also has the potential to provide clinical trial alternatives to patients when covered drugs are not an option, as well as accurately identifying clinically relevant mechanisms of resistance or even a complete lack of genomically matched treatment options to help eliminate futile or potentially harmful treatment. This biomechanistic and highly personalized precision oncology approach ensures that the mechanism of action or sensitivity is truly present before approving access to high-cost, FDA-approved specialty oncology drugs. Therefore, CGP is becoming a pragmatic solution that drives successful management strategies to effectively address the top 3 challenges identified by payers, and therefore, should justify the necessity of payer coverage today when used in the appropriate clinical setting.


Approximately 14.5 million Americans with a history of cancer were alive in 20146 and that number is slated to grow to 18.1 million in 2020.7 Cancer care costs in the United States were estimated to be $124.57 billion in 2010 and are projected to increase to between $158 billion and $173 billion by 2020, a 27% to 39% increase.7 Factors driving these dynamics include the growth and aging of the US population, an overall reduction in mortality due to increase in cancer survival, the earlier detection of cancer, the shift of care delivery to hospital outpatient settings,8,9-12 and the rapid growth of new and often very expensive oncology care products and services.

The projected cost increase by 2020 assumes that past trends continue: the 5-year survival rate for all cancers diagnosed between 2005 and 2011 was 69%, up from 49% during 1975 to 1977,6 and a 2012 study identified a 1.5% annual decline in cancer mortality for the decade examined.13 However, despite substantial advances in diagnosis and treatment, the 5-year relative survival for advanced or metastatic (ie, Stage IV) cancers has remained relatively stagnant since 1973, which is when such data was first collected in the SEER database.14,15

Alarmingly, the costs associated with the use of biologic therapies are growing faster than any other aspect of cancer care and have escalated to 335% growth in Medicare and 485% in the commercial payer market between 2004 and 2014.16 As precision oncology continues to gain traction, these trends will be further accelerated with the broadened utilization of the existing 50-plus FDA-approved targeted drugs and immuno-oncology agents, the majority of which were approved after 2010. This is compounded by the coming bolus of new drugs—770 targeted and immuno-oncology agents in various stages of FDA review, which are currently being evaluated in more than 3000 clinical trials.17 Another important trend is the use of high-cost targeted and immuno-oncology agents in sequence and/or in combination, and perhaps for longer durations, as the number of responding patients grows.

The growth of precision oncology therapies and molecular or companion diagnostic testing options used to guide the selection of these therapies is overwhelming the ability of physicians, payers, patients, and other stakeholders to keep pace with innovation. When researchers from the National Institutes of Health conducted a landscape scan of test offerings as part of the Institutes’ Genetic Testing Registry in February 2016, they found that oncology test options had grown considerably to more than 5000 tests—a 153% increase over the previous 12 months.18 Uncontrolled costs associated with trying to manage this high volume of expanding test options, while addressing quality issues that have been recently documented with standard-of-care (SOC) companion diagnostic tests, further complicate the situation.19-23

Combining these findings with those of the Genentech survey described earlier,1 clearly shows an urgent need for innovative clinical and cost management strategies and tools to ensure that patients have affordable access to next-generation diagnostics and therapies. The current SOC in oncology is often based on trial and error, without the benefit of biomarker data to inform treatment decisions, thus resulting in suboptimal outcomes and wasted dollars. Adverse events associated with invasive procedures, non-targeted treatment toxicity and unnecessary testing, as well as unnecessary emergency department (ED) visits and hospitalizations, all drive substantial human and financial costs associated with comorbidity, reduced quality of life, and even mortality.24 The idea of 1 empiric treatment approach for every patient with a particular cancer (eg, breast cancer) is not yielding the results required to make meaningful improvements in care.14,15 Because of failures with the empiric approach and the new understanding that cancer is a disease of the genome, testing and treatment are rapidly moving toward precision oncology care.


As discussed in earlier issues of Evidence-Based Oncology,15,25 cancer diagnosis and treatment is being transformed with the knowledge that cancer is a disease of the genome,26-29 and the genomic “blueprint” responsible for driving cancer is unique to each patient—the so-called personalized “malignant snowflake.”30 Data indicate that genomically matched treatments and clinical trials, or precision oncology, are often less toxic, more efficacious,19, 31-39 and less expensive than traditional cytotoxic chemotherapy. Targeted and immuno-oncology therapies have the potential to improve patient outcomes and quality of life, in addition to yielding cost savings.3-5,34-37 This is especially true when used as a first-line treatment option in the advanced or metastatic setting.3 Integrating CGP into the initial diagnostic work-up optimizes interventional efficiency by enabling genomic data to be immediately available in the medical record. This enables informed treatment decision making in real time versus using CGP as a “rescue” strategy after a patient has already failed multiple lines of therapy. Bottom line is that investing in precision oncology to transition patients from cytotoxic to genomically matched treatments and clinical trials is a smart solution that meets the core objectives of payer-initiated APMs—evidence-based care coordination that yields improved outcomes and quality of life through increased safety, efficacy, and cost-effectiveness of treatment (FIGURE).

Several in silico modeling data published recently indicate the potential for substantial health and economic benefits of genomic sequencing in non–small cell lung cancer (NSCLC) and melanoma.4-5 However, one of these studies relies on directionally correct, but overly aggressive assumptions that are not reflected in current practice such as precipitous reductions in cytotoxic utilization (decrease from 83% to 20%), and impractical expectations for clinical trial enrollment (increase from 4% to 54%).5 As outlined in a real-world study by Newcomer et al,24 increased treatment costs can be significantly offset by the total cost-effectiveness achieved, primarily by:
  • Eliminating unnecessary molecular tests19-23
  • Eliminating unnecessary biopsies19,40
  • Reducing cytotoxic chemotherapy use4,5
  • Optimizing FDA-approved targeted and immuno-oncology therapy utilization19,31-39
    • Increasing clinical trial enrollment as an alternative to noncovered off-label use15,41
  • Reducing emergency department visits24
  • Reducing hospitalizations24
  • Reducing futile treatment4,5

The White House Cancer Moonshot initiative, announced at President Obama’s State of the Union address on January 12, 2016, and subsequently led by Vice President Biden, relies heavily on precision oncology as its central feature. CGP is a key component of routine clinical care and national initiatives like “Moonshot.” The journey from “more precise” to “precision” diagnosis and treatment will require multi-stakeholder standardization, integration, and data sharing42,43 to simultaneously match patients with covered treatment options while advancing the genomic knowledge base. The administration can play a key role in energizing “Moonshot” by using its authority to overcome reluctance by CMS and private payers to pay for the personalized diagnostics and therapies that the administration champions. In an editorial published by Science in April of this year, Harold Varmus, MD, former director of the National Cancer Institute, recommended that “The Administration could also exercise its regulatory authority—most potently, to direct the Centers for Medicare and Medicaid Services (CMS) to allow reimbursement for molecular profiling of cancers. That would vastly increase the data available for analysis, accelerate interpretation of genetic profiles, provide a test bed for true sharing of clinical information, and allow future coverage determinations by CMS to be made more quickly and sensibly.”44

For select patients with life-threatening advanced cancer, access to a single, clinically effective and cost-efficient test with a rapid turnaround time and posttest decision support is essential. However, a value-based CGP program includes much more than the testing alone. CGP should include, but not be limited to, robust provider education on appropriate ordering and interpretation, benefit investigation and prior authorization to enable patient out-of-pocket cost transparency, electronic workflow integration and data sharing, patient assistance programs, and effective medical decision support and clinical trial navigation services. These additional valueadded investments, beyond the testing portion only, must be adequately reflected in payer reimbursement.

Copyright AJMC 2006-2018 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
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