Publication

Article

Evidence-Based Oncology

August 2016
Volume22
Issue SP12

Precision Oncology: Why Payers Should Initiate CGP Coverage Now!

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.

CURRENT SITUATION

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.

THE VALUE OF PRECISION ONCOLOGY

FIGURE

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 ().

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

IMPORTANCE OF CGP: ACHIEVING THE GOALS OF CANCER MOONSHOT

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.

A significant advantage of CGP is the opportunity to eliminate workflow inefficiency, costly use of suboptimal tests, and unnecessary biopsy procedures. As evidence rapidly evolves, updates in the CGP knowledge base happen in real time to reflect the very latest in curated data, translating into additional value at no extra cost to payers and patients. For stakeholders who would otherwise struggle to keep pace with the rapid advances in precision oncology, this is a critical advantage. Further, emerging evidence shows that CGP can enable effective utilization and cost management of the increasing number of targeted and immuno-oncology therapies available within the patient’s medical and pharmacy benefit.

For a majority of patients, if genomically matched options are not available, at the time of profiling, alternatives can be offered that forego the expensive use of futile and potentially harmful treatment. Finally, clinical trial options and navigational support available through CGP providers represent a cost-effective alternative for patients and payers when no covered treatment is recommended, or is otherwise unavailable. This is a result of drug costs in clinical trials being borne by the biopharma manufacturer. Clearly, investing in CGP, even at a price point of $3000 to $4000 or higher, is smart business when one considers decisions involving coverage, especially in the face of the price of precision oncology drugs, which can easily cost considerably more than $100,000 per patient per year.45

CGP is a valuable, core navigational aid for payer coverage, payment, and cancer care management programs when used as a frontline solution at initial diagnosis of particularly aggressive or metastatic disease. It enables standardization, personalization, and timely consideration for all available genomically matched treatment and clinical trial options consistent with coverage policies and relevant guidelines, including those from the NCCN (Category 1 and 2A levels of evidence), American Society of Clinical Oncology (ASCO), and the FDA. In essence, CGP is becoming a standardized “universal genomic pathway solution” for payers, specialty pharmacies, pathways organizations, and all other stakeholders engaged in managing the quality and costs of cancer care. This is entirely consistent with ASCO’s Choosing Wisely top 10 list for oncology.46

#10 -Do not use a targeted therapy intended for use against a specific genetic aberration unless a patient’s tumor cells have a specific biomarker that predicts an effective response to the targeted therapy.

A TIPPING POINT: THE UNIVERSAL GENOMIC PATHWAY SOLUTION

There is a growing body of published literature to demonstrate, characterize, or quantify the positive impact of precision oncology in the context of specific and broad ranges of tumors and clinical settings. Recent publications, health economic models, and positive coverage decisions indicate that early-adopter payers are proactively pivoting toward embracing precision oncology as an opportunity to align the need for improved clinical outcomes with cost-effectiveness.

Since 2014, NCCN has endorsed broad molecular profiling, like CGP, in the NCCN NSCLC Guidelines.47 Suh et al23 have proposed that CGP is clinically efficient and cost-effective by facilitating implementation of the NCCN Guidelines for NSCLC, including the identification of “pan-negative” patients who may benefit from enrollment in mechanism-driven clinical trials without additional tissue use or cost. The Center for Medical Technology Policy published a consensus white paper, Initial Medical Policy and Model Coverage Guidelines for Clinical Next Generation Sequencing in Oncology, outlining coverage guidelines for CGP—several national payers participated in developing the paper (CMS, Palmetto GBA, Anthem, Aetna, and Humana),48 and a number of national and regional payers have started to cover, and are in the process of reimbursing academic and commercial providers such as Foundation Medicine for CGP.49-53 These early-adopter payers recognize the pragmatic value of precision oncology informed by validated CGP. They realize that a biomechanistic approach ensures that patient-specific sensitivity and unique mechanisms of resistance are identified before approving or restricting access to expensive, FDA-approved specialty oncology drugs, or referring patients to clinical trial alternatives in the absence of FDA-approved options. CGP effectively addresses the 3 top challenges identified by payers.

Payers can benefit, now, by proactively taking strategic steps to integrate precision oncology into coverage and alternative payment models, by:

  1. Acknowledging cancer as a disease of the genome by modifying the existing coverage and payment policy framework to align with cancer biology, the N-of-1 personalized reality of treatment decision making, and first-line coverage at initial diagnosis in the particularly aggressive or metastatic cancer setting.
  2. Recognizing CGP as a “universal genomic pathway solution” for genomically matched treatment and clinical trial decision making; managing medically indicated specialty drug growth cost-effectively while reducing total costs of care by minimizing the use of ineffective drugs and costs associated with unnecessary biopsies, testing, cytotoxic treatments, and downstream ED visits and hospitalizations.
  3. Establishing Pan-Cancer precision oncology coverage and payment policies for members with particularly aggressive or metastatic cancer, based on a CGP first-line testing “universal genomic pathway solution” strategy to successfully manage the rapidly growing costs associated with diagnostic testing and genomically matched treatments.
  4. Creating a genomic benefit management program that seamlessly integrates highly validated CGP data with exexpert decision support, and other value-added services as the primary tools informing evidence-based treatment utilization and cost management solutions; For example, integrate CGP as part of the first-line pathway to optimized use of genomically matched treatments and clinical trials in accountable care organizations, oncology medical homes, pay-for-performance partnerships, bundled payments, limited provider networks, nurse navigator programs, end-of-life support and survivorship support programs, and/or personalized treatment pathways.
  5. Partnering only with a limited network of CGP providers capable of committing to long term “pay for value” relationships based upon consistently meeting or exceeding high-performance standards2 (ie, analytic validation, clinical validation, clinical utility, and cost-effectiveness), providing comprehensive data integration solutions with decision support, and a willingness to participate in data sharing with public databases.42,43

Harnessing the power of comprehensive genomic profiling will allow the field of oncology to more rationally match patients to efficacious therapies, and ultimately enable all stakeholders to recognize the true potential of precision oncology. EBOJerry Conway is vice president, payer relations and reimbursement, Foundation Medicine.

Ingrid Marino, MS, CGC, is director, Payer Medical Affairs, at Foundation Medicine.

Address for correspondence

Jerry Conway

150 Second Street

Cambridge, MA 02141

References

E-mail: jconway@foundationmedicine.com

1. The 2016 Genentech oncology trend report: perspectives from managed care, specialty pharmacies, oncologists, practice managers, and employers. https://www.genentech-forum.com/content/dam/gene/managedcare/forum/pdfs/2016_Genentech_Oncology_Trend_Report.pdf. Published February 2016. Accessed July 18, 2016.

2. Frampton GM, Fichtenholtz A, Otto GA, et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat Biotechnol. 2013;31(11):1023-1031. doi: 10.1038/nbt.2696.

3. Heger M. Intermountain Healthcare demonstrates cost effectiveness of NGS testing for late-stage cancer. genomeweb website. https://www.genomeweb.com/cancer/intermountain-healthcare-demonstrates-cost-effectiveness-ngs-testing-late-stage-cancer. Published June 2, 2015. Accessed July 1, 2016.

4. Li Y, Bare LA, Bender RA, et al. Cost effectiveness of sequencing 34 cancer-associated genes as an aid for treatment selection in patients with metastatic melanoma. Mol Diagn Ther. 2015;19(3):169-177. doi: 10.1007/s40291-015-0140-9.

5. Sabatini LM, Mathews C, Ptak D, et al. Genomic sequencing procedure microcosting analysis and health economic cost-impact analysis: a report for the Association of Molecular Pathology. J Mol Diagn. 2016;18(3):319-328. doi: 10.1016/j.jmoldx.2015.11.010.

6. Cancer facts & figures 2016. The American Cancer Society website. http://www.cancer.org/acs/groups/content/@research/documents/document/acspc-047079.pdf.%20%20%20ublished%202016http://www.cancer.org/acs/groups/content/@research/documents/document/acspc-047079.pdf. Published 2016. Accessed July 21, 2016.

7. Mariotto AB, Yabroff KR, Shao Y, Feuer EJ, Brown ML. Projections of the cost of cancer care in the United States: 2010-2020. J Natl Cancer Inst. 2011;103(2):117-128. doi: 10.1093/jnci/djq495.

8. Total cost of cancer care by site of service: physician office vs outpatient hospital. Community Oncology Alliance website. http://www.communityoncology.org/pdfs/avalere-costof-cancer-care-study.pdf. Published March 2012. Accessed July 18, 2016.

9. Berkley Research Group. 340B growth and the impact on the oncology marketplace. Community Oncology Alliance website. http://www.communityoncology.org/pdfs/BRG_COA_340B-Report_9-15.pdf. Published September 2015. Accessed July 21, 2016.

10. Pyenson BS and Fitch KV. Site of service cost differences for Medicare patients receiving chemotherapy. Milliman website. http://us.milliman.com/insight/health/Site-of-Service-Cost-Differences-for-Medicare-Patients-Receiving-Chemotherapy/. Published October 19, 2011. Accessed July 18, 2016.

11. Fitch K, Iwasaki K, Pyenson B. Comparing episode of cancer care costs in different settings: an actuarial analysis of patients receiving chemotherapy. Milliman website. http://us.milliman.com/uploadedFiles/insight/2013/comparing-episode-cancer-care.pdf. August 29, 2013. Accessed July 18, 2016.

12. Hayes J, Hoverman JR, Brow ME, et al. Cost differential by site of service for cancer patients receiving chemotherapy. Am J Manag Care. 2015;21(3):e189-e196.

13. Howlader N NA, Krapcho M, Garshell J, et al (eds). SEER Cancer Statistics Review, 1975-2012. National Cancer Institute website. http://seer.cancer.gov/archive/csr/1975_2012/. Updated November 18, 2015. Accessed July 18, 2016.

14. SEER*stat databases: November 2013 Submission. National Cancer Institute website. http://seer.cancer.gov/data/seerstat/nov2013/. Accessed July 18, 2016.

15. Conway J and Oldroyd M. Precision oncology: are payers on the right pathway? Am J Manag Care. 2015;21(SP12):SP404-SP406.

16. Fitch K, Pelizzari PM, Pyenson B. Cost drivers of cancer care: a retrospective analysis of Medicare and commercially insured population claim data 2004-2014. Community Oncology Alliance website. http://www.communityoncology.org/pdfs/Trends-in-Cancer-Costs-White-Paper-FINAL-20160403.pdf. Published April 2016. Accessed July 18, 2016.

17. Medicines in development: cancer. PhRMA website. http://www.phrma.org/sites/default/files/pdf/2014-cancer-report.pdf. Published 2014. Accessed July 1, 2016.

18. Genetic test registry finds growth of oncology, ngs-based tests. G2 intelligence website. http://www.g2intelligence.com/genetic-test-registry-finds-growth-of-oncology-ngs-basedtests/?utm_source=06-28-16-featured1&utm_medium=genetic-test-registry-finds-growthof-oncology-ngs-based-tests&utm_campaign=06-28-16-LPInsider. Published June 27, 2016. Accessed July 18, 2016.

19. Drilon A, Wang L, Arcila ME, et al. Broad hybrid capture-based next-generation sequencing identifies actionable genomic alterations in lung adenocarcinomas otherwise negative for such alterations by other genomic testing approaches. Clin Cancer Res. 2015;21(16):3631-3639. doi: 10.1158/1078-0432.CCR-14-2683.

20. Schrock AB, Frampton GM, Herndon D, et al. CGP identifies frequent drug sensitive EGFR exon 19 deletions in NSCLC not identified by prior molecular testing. Clin Cancer Res. 2016;22(13):3281-3285. doi: 10.1158/1078-0432.CCR-15-1668.

21. Ali SM, Hensing T, Schrocket AB, et al. Comprehensive genomic profiling identifies a subset of crizotinib-responsive ALK-rearranged non-small cell lung cancer not detected by fluorescence in situ hybridization. Oncologist. 2016;21(6):762-770. doi:10.1634/theoncologist.2015-0497.

22. Lim SM, Kim EY, Kim HR, et al. Genomic profiling of lung adenocarcinoma patients reveals therapeutic targets and confers clinical benefit when standard molecular testing is negative. Oncotarget. 2016;7(17):24172-24178. doi: 10.18632/oncotarget.8138.

23. Suh JH, Johnson A, Albacker L, et al. Comprehensive genomic profiling facilitates implementation of the National Comprehensive Cancer Network Guidelines for lung cancer biomarker testing and identifies patients who may benefit from enrollment in mechanism-driven clinical trials. Oncologist. 2016;21(6):684-691. doi: 10.1634/theoncologist.2016-0030.

24. Newcomer LN, Gould B, Page RD, Donelan SA, Perkins M. Changing physician incentives for affordable, quality cancer care: results of an episode payment model. J Oncol Pract. 2014;10(5):322-326. doi:10.1200/JOP.2014.001488.

25. Conway J. The role of companion diagnostic testing in payer decision-making. Am J Manag Care. 2013;19(SP1):SP44-SP45.

26. Alexandrov LB, Nik-Zainal S, Wedge DC, et al; Australian Pancreatic Cancer Genome Initiative; ICGC Breast Cancer Consortium; ICGC MMML-Seq Consortium; ICGC PedBrain. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415-421. doi:10.1038/nature12477.

27. The benefits of looking across many cancer genomes: a perspective [press release]. Bethesda, MD: National Cancer Institute; August 12, 2014. http://www.cancer.gov/newsevents/press-releases/2013/PanCanPerspective2013. Accessed July 19, 2016.

28. Targeting molecular tumor types. Nat Genet. 2013;45(10):1103. doi:10.1038/ng.2780.

29. Chmielecki J, Ross JS, Wang K, et al. Oncogenic alterations in ERBB2/HER2 represent potential therapeutic targets across tumors from diverse anatomic sites of origin. Oncologist. 2015;20(1)7-12. doi: 10.1634/theoncologist.2014-0234.

30. LaFee S. Precision medicine is practiced medicine. University of California at San Diego website. http://health.ucsd.edu/news/features/Pages/2015-03-06-precision-medicine-atucsd-health-system.aspx. Accessed July 1, 2016.

31. Schwaederle M, Zhao M1, Lee JJ, et al. Association of biomarker-based treatment strategies with response rates and progression-free survival in refractory malignant neoplasms; a meta-analysis [published online June 6, 2016]. JAMA Oncol. 2016. doi: 10.1001/jamaoncol.2016.2129.

32. Schwaederle M, Zhao M, Lee JJ, et al. Impact of precision medicine in diverse cancers: a meta-analysis of phase II clinical trials. J Clin Oncol. 2015;33(32):3817-3825. doi: 10.1200/JCO.2015.61.5997.

33. Jardim DL, Schwaederle M, Wei C, et al. Impact of a biomarker-based strategy on oncology drug development: a meta-analysis of clinical trials leading to FDA approval. J Natl Cancer Inst. 2015;107(11). pii:djv253. doi: 10.1093/jnci/djv253.

34. Wheler JJ, Janku F, Naing A, et al. Cancer therapy directed by comprehensive genomic profiling: a single center study. Cancer Res. 2016;76(13):3690-3701 doi: 10.1158/0008-5472.CAN-15-3043.

35. Barlesi F, Mazieres J, Merlio JP, et al; Biomarkers France contributors. Routine molecular profiling of patients with advanced non-small-cell lung cancer: results of a 1-year nationwide programme of the French Cooperative Thoracic Intergroup (IFCT). Lancet. 2016;387(10026):1415-1426. doi: 10.1016/S0140-6736(16)00004-0.

36. Rodriguez-Rodriguez L, Hirshfield KM, Rojas V, et al. Use of comprehensive genomic profiling to direct point-of-care management of patients with gynecologic cancers. Gynecol Oncol. 2016;141(1):2-9. doi: 10.1016/j.ygyno.2016.02.021.

37. Rosenberg JE, Hoffman-Censits J, Powles T, et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet. 2016;387(10031):1909-1920. doi: 10.1016/S0140-6736(16)00561-4.

38. Rizvi NA, Hellmann MD, Snyder A, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non—small cell lung cancer. Science. 2015;348(6230):124-128. doi: 10.1126/science.aaa1348.

39. Snyder A, Makarov V, Merghoub T, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371(23):2189-2199. doi: 10.1056/NEJMoa1406498.

40. Medicare costs analysis indicates need for decreasing use of biopsies as diagnosis tool for lung cancer. ScienceDaily website. http://www.sciencedaily.com/releases/2014/10/141030133053.htm. Published October 30, 2014. Accessed July 1, 2016.

41. Schork NJ. Personalized medicine: time for one person trials. Nature. 520(7549):609-611. doi: 10.1038/520609a.

42. Foundation Medicine announces release of molecular information from FoundationCORE™ to the National Cancer Institute in support of the National Cancer Moonshot and Precision Medicine Initiatives [press release]. Cambridge, MA: Foundation Medicine, Inc; June 29, 2016. http://investors.foundationmedicine.com/releasedetail.cfm?ReleaseID=977617. Accessed July 19, 2016.

43. Foundation Medicine’s molecular information supports discovery of precision therapeutics for pediatric cancers [press release]. Cambridge, MA: Foundation Medicine, Inc; April 18, 2016. http://investors.foundationmedicine.com/releasedetail.cfm?ReleaseID=965637. Accessed July 19, 2016.

44. Varmus H. The transformation of oncology. Science. 2016;352(6282):123. doi: 10.1126/science.aaf7301.

45. Price & value of cancer drug. Memorial Sloan Kettering Cancer Center website. https://www.mskcc.org/research-areas/programs-centers/health-policy-outcomes/cost-drugs. Accessed July 1, 2016.

46. American Society of Clinical Oncology: ten things physicians and patients should question. Choosing Wisely website. http://www.choosingwisely.org/societies/american-society-ofclinical-oncology/. Accessed July 1, 2016.

47. NCCN clinical practice guidelines in oncology: non-small cell lung cancer. National Comprehensive Cancer Network website. https://www.nccn.org/professionals/physician_gls/pdf/nscl.pdf. Accessed July 1, 2016.

48. Initial medical policy and model coverage guidelines for clinical next generation sequencing in oncology. Center for Medical Technology Policy website. http://www.cmtpnet.org/resource-center/view/initial-medical-policy-and-model-coverage-guidelines-for-clinical-ngs-inon. Published August 17, 2015. Accessed July 1, 2016.

49. Approved gene testing (M00041, V16). Palmetto GBA website. http://www.palmettogba.com/palmetto/MolDX.nsf/DocsCat/MolDx%20Website~MolDx~Browse%20By%20Topic~Covered%20Tests~9BMLRK6738?open. Updated January 27, 2016. Accessed July 1, 2016.

50. Molecular profiling to guide cancer treatment. UnitedHealthcare website. https://www.unitedhealthcareonline.com/ccmcontent/ProviderII/UHC/en-US/Assets/ProviderStatic-Files/ProviderStaticFilesPdf/Tools%20and%20Resources/Policies%20and%20Protocols/Medical%20Policies/Medical%20Policies/Molecular_Profiling.pdf. Accessed July 1, 2016.

51. Multi-marker tumor panels (Medical policy No. 91609-R0). Priority Health website. https://www.priorityhealth.com/provider/manual/auths/~/media/documents/medicalpolicies/91609.pdf. Accessed July 19, 2016.

52. Expanded molecular panel testing of cancers to identify targeted therapies. Policy number: 790. BCBS Massachusetts website. http://www.bluecrossma.com/common/en_US/medical_policies/790%20Expanded%20Molecular%20Panel%20Testing%20of%20Cancers%20to%20Identify%20Targeted%20Therapies%20prn.pdf. Accessed July 1, 2016.

53. Clinical guidelines: lab management program. (Page 497). Evicore website. https://www.evicore.com/labmanagement/highmark%20lab%20management%20guidelines.pdf. Accessed July 1, 2016.

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