Pressure on regulators to reduce healthcare costs could be a response to the estimated $1 trillion in US expenditures from poor care coordination, administrative burdens, and fraud, according to Jeff Mortier, partner at Farragut Partners, who spoke at the Community Oncology Alliance (COA) Payer Exchange Summit on October 29-30, 2018, in Tyson&rsquo;s Corner, Virginia.

&ldquo;Congress continues to ask us the same questions [about the cost of healthcare], and we continue looking for different answers. Value-based agreements [VBAs] are the current innovative solution&rdquo; to improving quality and reducing healthcare costs, said Mortier. &ldquo;Adequate treatment and adherence in chronic conditions can save $213 billion,&rdquo; he explained.

But there are barriers to operationalizing VBAs, said Mortier, which echoed the thoughts of Bo Gamble, director of strategic practice initiatives at COA, who highlighted regulatory and cultural challenges as a hurdle to VBAs during a session on the first day of the meeting.

Operational challenges, which include anti-kickback laws, drug pricing proposals, administrative burdens, and government pricing &ldquo;all add layers of complexity to existing structural impediments,&rdquo; Mortier explained.

Mortier explained that HHS&rsquo; focus on lowering list prices and introducing competition within the Medicare Part B space via step therapy are just some of the operational challenges that manufacturers face. He highlighted the contradiction between the government wanting to lower drug list prices and introducing value-based contracts. UnitedHealthcare&rsquo;s pilot study that was launched in 2009 reported substantial savings (34%) in can- cer costs over the 3-year period of the program, &ldquo;but the drug cost went up 179%,&rdquo; said Mortier. &ldquo;So, we are a little bit at odds with this administra- tion that wants to adopt value-based models, but [also wants] to lower the list price [of drugs].&rdquo;

There is a need, he said, to fill Congress&rsquo; knowledge gap in the space. &ldquo;Additionally, data and reporting challenges continue to mar provider practices that do not necessarily have the time to dedicate a team for doing this,&rdquo; Mortier said. &ldquo;Interoperability and meaningful use, or &lsquo;meaning- less use&rsquo; as some like to call it, continue to burden practice economics as they try to engage in VBAs.&rdquo;

Following this policy update by Mortier was a surprise all-pharma panel that COA convened to discuss the progress and challenges with VBAs from the drug manufacturer&rsquo;s outlook. Participants included Erin Darling, executive director of Merck; Prasun Subedi, MD, senior director of patient and health impact at the Center for Health Systems Innovation Leadership at Pfizer; Tamar Thompson, MHS, of government affairs, alliance development, and policy at Bristol-Myers Squibb; and Eric Turowski, director of oncology payer marketing, pricing, and market access at Eli Lilly and Company.

&ldquo;The meetings helped us understand where there are alignments between us, COA [providers], payers, and employers as well,&rdquo; said Turowski when asked to describe major learnings from the VBA meeting.

Thompson agreed, adding that the meetings drew attention to patient-centricity and quality measures in a meaningful way. &ldquo;It was interesting to learn that providers want to be a significant part of this conversation,&rdquo; said Darling, even though such arrangements have historically been between manufacturers and payers.

Subedi added that as VBAs stand today, stakeholders want specific questions about the value of a particular treatment answered. He believes that access to patients and the opportunity to create data are vital to the process. According to Subedi, the best VBAs are the ones that clearly articulate the relation between the product and its value. &ldquo;Simplicity is key,&rdquo; he said.

One learning for Turowski was that providers have interest in getting down to the individual patient-level performance, not just the aggregate comparisons that VBAs today are built to measure.

Although data are vital to this conversation, Subedi said that providers don&rsquo;t need to have all the answers when they come to the table; rather, they should be patient and gain an understanding of the process, which may not be very fast paced.

Darling pointed out that current regulations, such as the federal antikickback statutes, are a major roadblock to innovation in the value-based care process, because of associated legal and business risks. &ldquo;It prevents us from providing value to our stakeholders: patients, providers, and payers,&rdquo; she said. &ldquo;We need safe harbors in the space to help us pull through collaborations that will be good for patients, but we cannot [do so] within the current frameworks of the law.&rdquo;

Thompson pointed to waivers that were introduced for payers and providers to allow accountable care organization (ACO) collaborations and the launch of the Oncology Care Model (OCM). She pointed out how important it is for manufacturers to understand the government&rsquo;s position on what they can or cannot do, similar to changes that facilitated collaborations in the ACO and OCM environment.

Whereas manufacturers have figured out ways to work on agreements within the existing guidance, &ldquo;These are very simple agreements, and so we cannot innovate,&rdquo; Darling told the audience. She urged the providers and payers in the room for assistance to develop a more meaningful process.

Additionally, cultural barriers include that the manufacturerphysician relationship has always existed within the sales or marketing environment, Thompson said. Infusing policy conversations into the space would require a big cultural shift.

The panelists agreed that we have traveled only a short distance of this path and a lot lies ahead, primarily because of the lack of support from infrastructure, technology, and regulatory rules. Darling believes that we require shifts along those dimensions and that with growing capabilities, we will move quicker.

&ldquo;We have different views of value, but we need to find the center of the Venn diagram, because that&rsquo;s where the patient sits,&rdquo; Darling said.

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.

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Pressure on regulators to reduce healthcare costs could be a response to the estimated $1 trillion in US expenditures from poor care coordination, administrative burdens, and fraud, said Jeff Mortier, partner at Farragut Partners, during the Community Oncology Alliance Payer Exchange Summit.

Value-Based Agreements Take Center Stage at COA Summit

The FDA-approved chimeric antigen receptor (CAR) T-cell therapies have instituted a new era of effective cancer therapies for patients and are the most expensive treatments to date. Now, physicians are faced with financial implications before introducing these novel agents into clinical practice.

&ldquo;There are 2 components for a patient to move forward financially with CAR T-cell therapy,&rdquo; said Duncan Allen, MHA, of the Vanderbilt-Ingram Cancer Center, during a panel discussion at the Association of Community Cancer Centers&rsquo; 35th National Oncology Conference. &ldquo;There is the medical authorization that has to be in place with the insurance company, and then there is your financial mechanism. Those 2 pieces need to be in place to ensure financial viability for your patient.&rdquo;

The clinical utility has already been proved. The CD19-directed CAR T-cell therapy tisagenlecleucel (Kymriah) was originally approved for the treatment of relapsed or refractory pediatric and young adult patients with B-cell precursor acute lymphoblastic leukemia and has since been approved for adult patients with relapsed or refractory large B-cell lymphoma after 2 or more lines of systemic therapy. Based on updated findings from the phase II JULIET study, patients with relapsed or refractory diffuse large B-cell lymphoma (DLBCL) demonstrated durable responses from treatment with an objective response rate (ORR) of 54% (95% CI, 41%-62%) after a median follow-up of 19 months.

Soon to follow, axicabtagene ciloleucel (axi-cel; Yescarta), also a CD19-directed CAR T-cell therapy, was approved for the treatment of relapsed or refractory large B-cell non-Hodgkin lymphomas, including DLBCL. Long-term findings from the phase II ZUMA-1 trial showed that at 2 years, 39% of patients continue to respond to therapy by investigator assessment.

&ldquo;Patients with B-cell malignancies after relapse are in bad shape because most of the time, it is no longer a curable [disease],&rdquo; said Olalekan Oluwole, MBBS, MPH, assistant professor of medicine at Vanderbilt University Medical Center and coauthor of the ZUMA-1 trial, during the discussion. &ldquo;With CAR [T-cell] therapy, we have had durable responses, and with follow-up, it looks as if this is another opportunity for these patients to be cured. This is an opportunity that did not exist a few years ago.&rdquo;

Although much enthusiasm has been generated from these promising findings, it was quickly burdened by the overwhelming list prices for CAR T-cell therapy: $475,000 for tisagenlecleucel and $373,000 for axi-cel. These list prices do not even include the hefty hospitalization fees associated with treatment, which can drive the total cost to over $1 million per patient in some instances.

Policy and reimbursement, in addition to insurance coverage, remain the most prominent rate-limiting steps for CAR T-cell treatment implementation, according to Allen, assistant director at Vanderbilt-Ingram Cancer Center. Under the fiscal year (FY) 2019 Inpatient Prospective Payment System Final Rule, the Centers for Medicare & Medicaid Services (CMS) said it will categorize the inpatient administration of CAR T-cell therapy under the revised title of Medicare Severity-Diagnosis Related Groups (MS-DRG) 016: Autologous Bone Marrow Transplant CC/MCC or T-cell Immunotherapy and assigned procedure codes.

This categorization stems from CMS&rsquo; belief that patients who receive CAR T-cell therapy will have characteristics similar to those of patients treated with autologous bone marrow transplantation. Generally, Allen said he is pleased with this adjustment, as it will provide clarity for practices on the payment structure for patients treated with the novel agents on-site.

CMS also approved a temporary new technology add-on payment (NTAP) for the use of CAR T-cell therapy with a maximum reimbursement of $186,500, although practices argue this will barely put a dent in the total cost. NTAP payments are used by CMS to afford additional compensation for predefined breakthrough technologies in the Medicare Hospital Inpatient Prospective Payment System.

&ldquo;One of the biggest downsides of what we have seen from a CMS perspective is the issuance of the FY19 Proposed Rule,&rdquo; said Allen. &ldquo;The cost [for CAR T-cell therapy] is around $373,000. When you bundle in the NTAP payment with the case rate and the outlier, you still don&rsquo;t reach the drug cost alone. This is not an ecosystem in which centers can continue to live.&rdquo;

Vanderbilt University and other practices are currently looking to administer CAR T-cell therapy in the outpatient setting. CMS announced payment rates for outpatient administration of the 2 FDA-approved agents in April: $395,380 for axi-cel and $500,839 for tisagenlecleucel.

Many practices are concerned, however, that even if patients receive CAR T-cell therapy in the outpatient setting, they will need to be monitored for potentially serious adverse events (AEs). In such cases, all payments will become a part of the inpatient stay under CMS&rsquo; 3-day payment window policy.

Some toxicities from CAR T-cell therapy occur within hours of administration, yet cytokine release syndrome (CRS) can generally appear within 1 to 14 days after infusion. This timeline coincides with that of maximal T-cell expansion.

Treating CRS requires immediate on-site access to tocilizumab (Actemra), with a minimum of 2 doses available for administration within 2 hours of CAR T-cell infusion, according to Kathryn A. Culos, PharmD, BCOP, of Vanderbilt-Ingram Cancer Center, who also spoke during the panel discussion.

Additionally, the current challenges associated with pricing and reimbursement of CAR T-cell therapy could be further heightened as additional indications for CAR T-cell therapy are granted FDA approval and the patient population eligible for the treatment modality increases. Clinical trials investigating the novel treatment for patients with multiple myeloma, DLBCL after first relapse, and solid tumors, among other forms of cancer, are ongoing.

Allen encourages centers to speak with their local representative for a better payment structure. &ldquo;We can work with our health policy departments to write white papers so that we can get the information out to the community,&rdquo; he said.

&ldquo;We can also draft letters to CMS to advocate for better coverage,&rdquo; added Allen. &ldquo;CMS has specifically said that they want to hear from the centers...now they want to hear from us.&rdquo;

Schuster SJ, Bishop MR, Tam C, et al. Sustained disease control for adult patients with relapsed or refractory diffuse large B-cell lymphoma: an up- dated analysis of Juliet, a global pivotal phase 2 trial of tisagenlecleucel. Presented at: 2018 American Society of Hematology Annual Meeting and Exposition; December 1-4, 2018; San Diego, CA. Abstract 1684. ash.confex. com/ash/2018/webprogram/Paper115252.html.

Neelapu SS, Ghobadi A, Jacobson CA, et al. 2-year follow-up and high-risk subset analysis of Zuma-1, the pivotal study of axicabtagene ciloleucel (axi- cel) in patients with refractory large B cell lymphoma. Presented at: the 2018 American Society of Hematology Annual Meeting and Exposition; December 1-4, 2018; San Diego, CA. Abstract 2967. ash.confex.com/ash/2018/web- program/Paper111368.html.

Fiscal year (FY) 2019 Medicare Hospital Inpatient Prospective Payment System (IPPS) and Long-Term Acute Care Hospital (LTCH) Prospective Pay- ment System final rule (CMS-1694-F). CMS website. cms.gov/newsroom/ fact-sheets/fiscal-year-fy-2019-medicare-hospital-inpatient-prospective- payment-system-ipps-and-long-term-acute-0. Published August 2, 2018. Accessed December 13, 2018.

The FDA-approved CAR T-cell therapies have instituted a new era of effective cancer therapies for patients and are the most expensive treatments to date. Now, physicians are faced with financial implications before introducing these novel agents into clinical practice.

Does the Cost Outweigh the Benefit for CAR T-Cell Therapy?

In November 2018, the FDA issued a draft guidance recommending metastasis-free survival (MFS) as an endpoint in drug trials for nonmetastatic castration-resistant prostate cancer (nmCRPC), suggesting a major change in expectations for treatment of this tumor type.

&ldquo;Whereas radiographic progression-free survival has been standardized as an endpoint in metastatic settings, there was previously no earlier endpoint for nmCRPC trials. The FDA has now recognized that a prolonged delay in development of metastatic disease is an objective and clinically relevant measure,&rdquo; officials from the FDA wrote in a perspective summary.

&ldquo;Future agents may be approved on the basis of MFS only if substantial effects on this transition are demonstrated and the safety profile is acceptable for a medication taken long term.&rdquo;

James Mohler, MD, associate director and senior vice president for Translational Research at Roswell Park Comprehensive Cancer Center in Buffalo, New York, described the FDA&rsquo;s move as &ldquo;a landmark change&rdquo; considering the agency&rsquo;s tendency to favor overall survival (OS) as an endpoint.

&ldquo;There is great value in delaying the development of metastasis,&rdquo; said Mohler in an interview with

. &ldquo;I applaud the FDA for looking at an intermediate endpoint that is really meaningful for patients. This is a tremendous breakthrough.&rdquo;

Prior to the approval of apalutamide (Erleada), in February 2018, no therapies existed exclusively for the treatment of nmCRPC. As a result, many patients were unprotected against disease progression once androgen-deprivation therapy (ADT) had failed.

This approval was based on the results of the double-blind, phase III SPARTAN trial, in which MFS was used as the primary endpoint. Administration of apalutamide was associated with a median MFS of 40.5 months compared with 16.2 months in patients taking placebo, representing roughly a 2-year improvement (HR 0.28; 95% CI, 0.23-0.35;

Participants (n = 1207) were randomized 2:1 to receive oral apalutamide at 240 mg daily or placebo in conjunction with ADT. High-risk, castration-resistant disease was defined as occuring with a PSA doubling time of 10 months or less during ADT.

Officials said the drug was &ldquo;well-tolerated&rdquo; and had similar incidence rates of serious adverse outcomes in the apalutamide and control groups.

They added that patient-reported outcomes showed &ldquo;no notable adverse signals in symptom or functional effects despite the long treatment duration.&rdquo;

In the interview, Mohler said too little attention has been paid to an important adverse event statistic in the study: the any-grade bone fracture rate of 11.7% in the apalutamide group compared with 6.5% in the placebo group.

Investigators on the apalutamide trial determined that &ldquo;MFS has a significant association with OS and is predictive of OS in high-risk nmCRPC&rdquo; and is therefore &ldquo;a meaningful and valid intermediate clinical [endpoint] for OS.&rdquo;

Recognizing that the evolution from nmCRPC to metastatic disease is a clinically relevant event, the FDA Oncologic Drugs Advisory Committee (ODAC) discussed endpoints in therapies for nmCRPC in a 2011 meeting. Although they recommended that MFS could reasonably be used as an endpoint in clinical trials, they added that &ldquo;ensuring clinical benefit of a drug would require a substantial magnitude of improvement and a favorable benefitrisk evaluation.&rdquo;

Another ODAC examined a randomized, placebo-controlled trial of denosumab in nmCRPC that reported an improvement of 4 months in bone-only MFS. ODAC members concluded that longer MFS would be required to justify an approval based on this endpoint.

Enzalutamide Enters the Picture for nmCRPC

Another option in nmCRPC came in July 2018 when the FDA granted enzalutamide (Xtandi) approval for a new indication after the phase III PROSPER trial in which 1401 patients were randomized 2:1 to oral enzalutamide at 160 mg or placebo once daily. All patients had been previously treated with ADT or bilateral orchiectomy. Median MFS was higher in the enzalutamide group than in the placebo cohort, at 36.6 and 14.7 months, respectively (HR 0.29; 95% CI, 0.24-0.35;

Enzalutamide was previously recommended for the treatment of patients with metastatic disease only. Meanwhile, dozens of trials are exploring the use of apalutamide and enzalutamide in conjunction with other forms of treatment such as medication and surgery.

FDA officials hypothesized that the use of MFS could require significant adjustment. They commented that &ldquo;increasing sensitivity [of medical imaging] may increase the sensitivity and specificity of metastasis detection, potentially affecting the interpretation of study results and even changing the baseline characteristics of enrollees over time.&rdquo;

Data about OS in apalutamide and enzalutamide are not yet available. &ldquo;It will be interesting if apalutamide does not result in a change in OS,&rdquo; Mohler said. &ldquo;Even if OS does not differ, the value of delaying metastatic disease and its morbidity is probably worth use of the drug.&rdquo;

Analyses of the drug&rsquo;s long-term impact will need to consider its high cost, its adverse effects, and perhaps factors such as quality-adjusted life years gained, Mohler concluded.

Beaver JA, Kluetz PG, Padzur R. Metastasis-free survival  a new endpoint in prostate cancer trials.

2018;378(26):2458-2460. doi: 10.1056/NEJMp1805966.

Smith MR, Saad F, Chowdhury S, et al; SPARTAN Investigators. Apalutamide treatment and metastasis-free survival in prostate cancer.

2018;378(15):1408-1418. doi: 10.1056/NEJMoa1715546.

Smith MR, Mehra M, Nair S, Lawson J, Small EJ. Association of metastasis-free survival (MFS) and overall survival (OS) in nonmetastatic castration-resistant prostate cancer (nmCRPC).

2018;36(suppl 15):5032. doi: 10.1200/JCO.2018.36.15_suppl.5032.

Hussain M, Fizazi K, Saad F, et al. Enzalutamide in men with nonmetastatic, castration-resistant prostate cancer.

2018;378(26):2465-2474. doi: 10.1056/NEJ- Moa1800536.

In November 2018, the FDA issued a draft guidance recommending metastasis-free survival as an endpoint in drug trials for nonmetastatic castration-resistant prostate cancer, suggesting a major change in expectations for treatment of this tumor type.

FDA Advances the Use of Metastasis-Free Survival as an Endpoint in nmCRPC

Differences in insurance status, tumor biology, stage at diagnosis, and adverse effects of treatment could contribute to patients&rsquo; nonadherence,

, and these factors may disproportionately influence black women.

The study included patients aged 20 to 74 years who had received a diagnosis of first primary invasive breast cancer between May 2008 and July 2013. Patients were sampled from the Carolina Breast Cancer Study phase III cohort and were sent a 2-year follow-up survey containing endocrine therapyrelated questions; 1280 reports were included in the data.

Overall, black women were more likely to report underuse and nonadherence to their ET regimen, as well as difficulty sticking with their prescribed treatment

. Black women were also more likely to report forgetting to take their pills while traveling (26.2% vs 19.5%) and trouble remembering to take their medication (27.2% vs 13.2%). Skipping pills due to cost was also seen more commonly in black women (17.1%) than in white women (6.7%).

Compared with white women, black women were more likely to report experiencing adverse effects (AEs) of endocrine therapy &ldquo;quite a bit&rdquo; or &ldquo;very much&rdquo; in the preceding 7 days. Symptoms of endocrine therapy included hot flashes, joint pain, night sweats, weight gain, breast sensitivity, mood swings, and bloating

. However, white women were more likely to report sexually related AEs like vaginal dryness and painful sex, than black women.

Black patients were most likely to report their perceived risk of disease recurrence as &ldquo;very low&rdquo; if they completed their endocrine therapy as directed; however, they were also more likely than white women to report that they did not perceive a change in the risk of cancer recurrence if they did not take their pills

Certain factors, such as age at diagnosis and annual income, were independent predictors of treatment adherence regardless of patient race. Women aged <45 years were most likely to underuse (26%) compared with those aged >65 years, who were least likely to report underuse (14.1%). Those making more than $50,000 annually were most likely to adhere to their treatment (84.1%), whereas those making less than $15,000 were most likely to report underuse.

When the participants were divided based on insurance status at diagnosis, those with private insurance were most likely to adhere to their treatment schedule, whereas patients on Medicaid were most likely to underuseeven more than those who were uninsured

Addressing these identified, modifiable predictors of nonadherence may prove more useful in developing a multifaceted intervention than prior attempts with educational materials, which showed little benefit. Supportive AE management, strategies for overcoming cost barriers, and moti- vational interviewing are some suggested tactics to help ensure endocrine therapy adherence in this patient population.

Wheeler SB, Spencer J, Pinheiro LC, et al. Endocrine therapy nonadherence and discontinuation in black and white women [published online September 20, 2018].

Nonadherence to endocrine therapy may explain why black women with hormone receptor&ndash;positive breast cancer have higher mortality rates than white women, despite historically lower incidence rates.

Adjustable Predictors of ET Use in Black Women Could Improve Adherence

The use of big data is revolutionizing many industries, allowing greater insights by drilling into evidence with more detail. Pair that with personalized medicine, where clinicians can tailor a patient&rsquo;s cancer treatment based on biomarkers, genetic aberrations, or other individual characteristics, and oncologists gain powerful insight that can help predict the best course of treatment for each patient that is based on individual disease characteristics, not just cancer type and stage. Medical centers are also taking unique approaches, but they all have 2 things in common: technology and data.

The Dana-Farber Cancer Institute (DFCI) Clinical Pathways program was conceived in 2012 when the growth of their satellite sites necessitated the development of a system to ensure uniform quality of care throughout the network, said David M. Jackman, MD, medical director of the Pathways program. &ldquo;We recognize that there are commercial pathways out there,&rdquo; he said. &ldquo;But we are a center of excellence. We want to make sure any system we use we are proud to put our name on.&rdquo; They recruited DFCI physicians to develop Pathways in house, using a commercial vendor for their information technology platform. Program investigators wanted to create an &ldquo;electronic roadmap&rdquo; that leads physicians to the best treatments currently available, according to the program&rsquo;s website.

Physicians using the system are led through important diagnostic criteria, including disease stage, line of therapy, and genomics, before they are directed to the correct branch in the pathway. The system offers pertinent clinical trials, standard treatments for that setting, dose scheduling, and more. The goals are to help physicians avoid checking multiple sources and to give curated recommendations.

tested whether the Pathways program impacted clinical outcomes and costs.

It included 370 patients with stage IV nonsmall cell lung cancer (NSCLC) receiving treatment at DFCI; the 2 cohorts were defined as those being treated before the rollout of the Pathways program (n = 160; the &ldquo;prepathways&rdquo; group) and those receiving care guided by the new technology (n = 210; the &ldquo;postpathways&rdquo; group). The prepathways group consisted of patients who got their diagnosis in 2012, which allowed at least 12 months of follow-up before the program was implemented, and the postpathways cohort consisted of patients who received their diagnosis after the NSCLC pathway rollout in January 2014. The Pathways program prioritized clinical options first by efficacy, followed by toxicity and cost.

Researchers found that the clinical outcomes were similar, with median overall survival times of 10.7 months for the prepathways cohort versus 11.2 months for the post-pathways group (

= .08). The study results also showed an unadjusted regression cost savings of $15,993 per patient in the postpathways group (

= .03). The savings were slightly higher, at $17,085, when adjusted for factors such as age, sex, race, and distance from DFCI (

The center is currently revamping the Pathways program and moving it to a different healthcare technology vendor, making changes based on what they learned when incorporating it into the physician workflow. This is to ensure that their custom technology gives all of their clinicians the same access to expert recommendations without needing to consult multiple sources and is based on every scenario an oncologist may encounter. They intend to make the system commercially available in 2019 through Philips IntelliSpace.

The new system has 31 medical oncology and 28 radiation oncology pathways. &ldquo;The pathway portfolio accounts for about 95% of what we or any oncology practice would see, including major and rare cancers,&rdquo; he said.

Currently, the Pathways program does not incorporate artificial intelligence (AI), although Jackman said that will come in the future. Instead, the DFCI expert panel for each tumor type regularly meets to fine-tune treatment decisions based on the latest publications, data, and FDA approvals and to discuss granular solutions.

Eventually they would like to incorporate AI. &ldquo;If we are going to take the time to capture the information, we want to learn from ithow physicians behave, how patients do. The process of navigating a pathway provides information to help curate a meaningful database,&rdquo; Jackman said.

Jackman used the example of a patient with advanced disease and a specific genetic mutation, such as stage IV colon cancer with wild-type

mutation, and said AI can help analyze their response to the medications they are prescribed. Using AI, however, will require caution since the creators of the technology want to ensure the process is transparent.

&ldquo;There are a lot of concerns about computer learning,&rdquo; Jackman said. &ldquo;How and when to incorporate this into Pathways is aspirational.&rdquo;

Another prominent institution is also using machine learning to predict the best ovarian cancer treatment based on patients&rsquo; RNA genomic mutations and past response data from other patients.

Machine learning looks for correlations, said John F. McDonald, PhD, professor in the School of Biological Sciences and director of the Integrated Cancer Research Center at the Georgia Institute of Technology (Georgia Tech) in Atlanta. &ldquo;The big thing in science is to make predictions; who has cancer, who does not,&rdquo; he said. That would be a diagnostic use. The other prediction type is for treatmentwhich therapy would best work for a patient.

The first way to do that is to understand the cause-and-effect relationship that underlies the disease. &ldquo;If you understand what causes cancer, you can design a drug to target the entity causing it,&rdquo; he said. However, some clinicians do not sufficiently understand the cause-and-effect relationship to design a drug, and that is where machine learning comes in, he said.

&ldquo;We are looking for tumors with a particular genomic profile, to see how well they have responded to a particular drug,&rdquo; he said. &ldquo;That does not presume that we understand anything about the cause-and-effect relationships. It is purely correlative,&rdquo; he said.

A study published in Scientific Reports, for which McDonald was an investigator, used gene expression profiles from RNA analysis collected from 152 patient records to predict which chemotherapy treatment would produce the best outcome.

The algorithm used 114 test or learning datasets for the model and 38 cases as testing datasets.

The system predicted the correct chemotherapy option, providing the best outcome more than 80% of the time.

To build out the system, metabolites will be analyzed in blood through mass spectroscopy in healthy women to compare with those in women with ovarian cancer. They will then use the computer program to identify correlates, determine disease biomarkers, and eventually develop a diagnostic test.

McDonald said they initially used ovarian cancer tumor data to build the model but then found that they get more accurate models by using RNA data from other cancers that use the same chemotherapy drugs. &ldquo;We interpret that as cancers are better defined by genomic profiles rather than tissue or origin,&rdquo; he said. Getting better predictions when using data from all cancers was an unexpected finding.

&ldquo;The beauty of machine learning is that it allows you an interim solution to the problem of cancer,&rdquo; McDonald said. It gives insights on what therapies to use for a patient, even if clinicians do not understand why those drugs work. &ldquo;We can get fairly accurate predictions and we are getting more data every day.&rdquo; He anticipates that in the near future, every tumor will be profiled on a genomic level, which will provide larger data sets.

McDonald&rsquo;s lab is using RNA analysis instead of DNA sequencing analysis to genomically profile tumors, as they find it more accurate in identifying gene expression data. They have data for 154 patients, including individual responses to chemotherapy, which comprise less data than they would like at this point. They need both the genomic profile and chemotherapy response for each patient. &ldquo;That kind of data are very limited,&rdquo; he said. &ldquo;Historically, people have not recorded it that way.&rdquo;

Georgia Tech is making the ovarian cancer treatment prediction algorithm available as an open source decision tool in order to improve it and advance the field. &ldquo;One of the reasons you cannot get the data you need is that some of the appropriate data are held by drug companies and it is not open source,&rdquo; he said. &ldquo;When people develop these algorithms, they are thinking [about] making money on it, so it is proprietary data and nobody knows what is behind the algorithm.&rdquo;

They put the technology on the software-development platform, GitHub, and invited others to use it and make improvements. &ldquo;I think it is a much better way to move forward,&rdquo; he said.

Currently, they are giving the data to clinicians at their institution as an additional diagnostic tool to consider, much like a CT scan. &ldquo;At this point, clinicians will use the standard-of-care therapies already established,&rdquo; he said, out of concern for legal implications.

They see the data helping in the short term for patients who fail standard-of-care therapy, where there are no other guidelines for subsequent lines of therapy. The clinician can then use the information to decide on an alternative treatment. &ldquo;We think, with these algorithms, there is a higher probability of success than randomly trying different drugs.&rdquo;

When the program has proven itself to a higher degree in the future, McDonald hopes clinicians will use the predictive responses for patients in the frontline setting. &ldquo;Before that, we need more validation of the accuracy of this approach.&rdquo;

To create a diagnostic test, they are also now creating metabolic profiles of 1000 patients with ovarian cancer so that machine learning can help predict cancers with a high malignancy potential compared with a low malignancy potential.

In 2018, Memorial Sloan Kettering Cancer Center formed a Computational Oncology Service focused on bringing together clinical-translational genomics research, including computational biology, cancer biology, and clinical oncology. They plan to use their research and data for quantitative analysis of cancer models, to predict responses and determine better treatments. They have already performed clinical tumor sequencing on more than 20,000 patients to use with machine learning and AI analyses.

According to McDonald, an emerging area of computer science is network, or graph, theory. It is used in network models that use a hub or a node with many connections. In cancer, researchers can study genes, which serve as the major hubs, and investigate their connections to other genes. That way, they can identify hubs that are attractive targets to break or disrupt the network.

Delivering therapeutics to the cancer cells is also being investigated with computer analyses. Nanotechnologists and chemists from Georgia Tech are working with computers to best target delivery of drugs to tumors, using an integrated approach. &ldquo;Nothing substantial has come out of it yet, but it looks highly promising for the future,&rdquo; McDonald said. He believes the big breakthroughs will come from the integration of specialties that have not worked together in the past.

&ldquo;Healthcare is an industry where we have been reluctant to let ourselves be transformed by data,&rdquo; said Jackman. &ldquo;It is very exciting to watch these and many other efforts and try to revolutionize and improve the care we can provide.&rdquo;

Jackman DM, Zhang Y, Dalby C, et al. cost and survival analysis before and after implementation of Dana-Farber Clinical Pathways for patients with stage IV nonsmall-cell lung cancer.

2017;13(4):e346-e352. doi: 10.1200/JOP.2017.021741.

Huang C, Clayton EA, Matyunina LV, et al. Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

2018;8(1):16444. doi: 10.1038/s41598-018-34753-5.

Open source machine learning tool could help choose cancer drugs [news release]. Atlanta, GA: Georgia Institute of Technology; November 6, 2018. eurekalert.org/pub_releases/2018-11/giot-osm110618.php. Accessed December 11, 2018.

Academic positions in computational oncology. Memorial Sloan Kettering Cancer Center website. mskcc.org/departments/epidemiology-biostatistics/jobs/academic-positions-computational-oncology. Accessed December 11, 2018.

The use of big data is revolutionizing many industries, allowing greater insights by drilling into evidence with more detail.

Computational Oncology: Predicting Best Cancer Responses Using Computer Algorithms

Increasing clinical relevance of less common gene signatures and alterations is leading to a benefit from broad-panel next-generation sequencing (NGS) testing for patients with metastatic nonsmall cell lung cancer (NSCLC), according to an expert at Memorial Sloan Kettering (MSK) Cancer Center.

Michael F. Berger, PhD, described the NGS landscape through the lens of his experience as the associate director of the Marie-Josée and Henry R. Kravis Center for Molecular Oncology during a presentation at the 13th Annual New York Lung Cancers Symposium hosted by Physicians&rsquo; Education Resource

, LLC. The center developed the MSK-IMPACT (integrated mutation profiling of actionable cancer targets) comprehensive panel for sequencing 468 cancer-associated genes.

The assay also evaluates tumor mutational burden (TMB) and mismatch repair deficiency (dMMR) or microsatellite instability (MSI).

&ldquo;What might have been done in the context of an individual tumor type for a small core set of genes or mutations has now expanded to all different cancer-associated genes, knowing that mutations that may be more commonly observed in one cancer may also be less frequently observed in other cancers but also can provide informed treatment decisions for those patients,&rdquo; said Berger.

mutations, which have been observed in approximately 50% of melanomas and have prompted the development of dual pathwaytargeting agents, including the combination of dabrafenib (Tafinlar) and trametinib (Mekinist). In NSCLC, the same combination gained FDA approval in 2017 for patients with metastatic disease that harbors

V600E mutations, which are found in 1% to 2% of lung adenocaricnomas.

MSK now seeks to offer NGS testing to patients with meta- static cancer across all solid tumor types, particularly those with NSCLC, Berger said. He added that some patients with earlier-stage cancers may also undergo testing if they are treated through surgical oncology.

In NSCLC, such testing is growing increasingly relevant, notably because of novel therapies being developed for less prevalent gene fusions, Berger said in an interview with

fusions, which have been identified in less than 3% of NSCLC cases. Larotrectinib (Vitrakvi), a selective tyrosine receptor kinase (TRK) inhibitor, and entrectinib (RXDX-101), an oral pan-TRK inhibitor, are among the drugs being developed in this space.

&ldquo;The broad testing allows us to capture not just the common but also the rare mutations, and it also gives us information about more complex mutational signatures that are increasingly important for predicting response to immunotherapy,&rdquo; Berger said.

TMB is being explored as a biomarker in NSCLC. The FDA is currently considering a supplemental biologics license application for the combination of nivolumab (Opdivo) plus low-dose ipilimumab (Yervoy) for the frontline treatment of patients with advanced NSCLC with TMB &ge;10 mutations per megabase.

Although dMMR/MSI is &ldquo;very rare in lung cancer,&rdquo; Berger says patients with this signature may be candidates for pem- brolizumab (Keytruda), a PD-1 inhibitor that is approved for patients with unresectable or metastatic MSI-high or dMMR solid tumors who have progressed following prior treatment and who have no satisfactory alternative treatment options.

In describing the current landscape for NGS testing, Berger said there are 3 main test categories: hotspot panel, with amplicon capture of approximately 10 to 50 genes; cancer gene panel, with hybridization capture of about 100 to 500 genes; and whole exome sequencing, with hybridization capture of approximately 20,000 genes. At one end of the spectrum, hotspot panel testing is a lower-cost option that offers a fast turnaround, while at the other end, whole exome sequencing provides the greatest potential for discovery.

&ldquo;There is a sweet spot in the middle, and this has been our approach,&rdquo; he said, referring to MSK-IMPACT. &ldquo;It is cheaper, more rapid, more economical than the more comprehensive approaches, and in some ways more clinically suited.&rdquo;

At the same time, Berger said the choice of NGS strategy depends on clinical and practical factors. &ldquo;There is really no one right approach. It depends on the disease, the lab, the resources available, the throughput in the laboratory, the turnaround time requirements, and cost consider- ations,&rdquo; he said.

One advantage of the MSK-IMPACT test, he said, is that it analyzes DNA from tumor cells and a matched normal control sample for comparison; in lung cancer, blood is the source used in the normal test.

&ldquo;When we set up this program and developed the test, it was really with the goal of identifying individual muta- tions that might elicit responses to particular targeted therapies,&rdquo; Berger said. &ldquo;But we can move beyond that, and that is enabled largely by the fact that we are sequencing both tumor and matched normal [samples].&rdquo;

Thus far, more than 32,000 tumors have been sequenced with MSK-IMPACT, with approximately 200 additional tumors tested every week, Berger said. In 2017, the FDA approved the test, which is typically available only to patients treated at MSK, as an in vitro diagnostic.

Commercially available NGS tests approved by the FDA include the FoundationOne CDx assay, which tests for 324 genes; the Praxis Extended RAS Panel, which detects 56 mutations in

family genes; and the Oncomine Dx Target Test, which analyzes 23 genes and

fusions. The FoundationOne and Oncomine tests are approved as companion diagnostics for NSCLC drugs that target specific mutations.

Evaluation of automatic class III designation for MSK-IMPACT (integrated mutation pro- filing of actionable cancer targets): decision summary. FDA website. accessdata.fda.gov/ cdrh_docs/reviews/DEN170058.pdf. Accessed December 7, 2018.

Planchard D, Smit EF, Groen HJM, et al. Dabrafenib plus trametinib in patients with previ- ously untreated BRAFV600E-mutant metastatic non-small-cell lung cancer: an open-label, phase 2 trial. Lancet Oncol. 2017;18(10):1307-1316. doi: 10.1016/S1470-2045(17)30679-4.

3. Drilon A, De Braud FG, Siena S, et al. Entrectinib, an oral pan-Trk, ROS1, and ALK inhib- itor in TKI-naïve patients with advanced solid tumors harboring gene rearrangements: up- dated phase I results [AACR abstract CT007]. Cancer Res. 2016;76(suppl 14):CT007. doi: 10.1158/1538-7445.AM2016-CT007.

Increasing clinical relevance of less common gene signatures and alterations is leading to a benefit from broad-panel next-generation sequencing testing for patients with metastatic non&ndash;small cell lung cancer, according to an expert at Memorial Sloan Kettering Cancer Center.

Broad-Panel NGS Benefits Metastatic NSCLC

Although researchers and physicians have made advances in treatment options for patients with

-positive nonsmall cell lung cancer (NSCLC), a true understanding of the development of resistance to therapy is yet to emerge, according to D. Ross Camidge, MD, PhD.

Camidge, director of Thoracic Oncology at the University of Colorado, said osimertinib (Tagrisso) is the best frontline therapy choice for patients with advanced

-driven NSCLC, frontline treatment with alectinib (Alecensa) should be the standard of care.

Osimertinib, a third-generation EGFR tyrosine kinase inhibitor (TKI), gained FDA approval in the frontline setting in April 2018 based on data from the phase III FLAURA study, in which frontline osimertinib reduced the risk of progression or death by 54% versus standard TKI therapies erlotinib (Tarceva) and gefitinib (Iressa). The median progression-free survival (PFS) was 10.2 months for standard therapy and 18.9 months with osimertinib (HR, 0.46; 95% CI, 0.37-0.57;

-positive NSCLC, alectinib improved PFS by 47% compared with crizotinib (Xalkori) (HR, 0.53; 95% CI, 0.38-0.73;

<.0001) in the phase III ALEX study, which led to the FDA approval of alectinib in the frontline setting in November 2017.

, Camidge discussed the crowded landscape of oncogene-driven NSCLC at the 13th Annual New York Lung Cancers Symposium hosted by Physicians&rsquo; Education Resource

What have been some of the most significant findings in the EGFR space?

mutations, the field is pretty much solidified in that osimertinib, a third-generation TKI, is your initial choice. People are looking at adding bevacizumab [Avastin] to osimertinib [or] adding chemotherapy. These are both hard sells, though. If you have a pill that is going to control your disease for a number of years, you want a short leash in the infusion center. Another thing we have to understand is why people eventually progress on osimertinib and what [the] rational combinations [are] to overcome this. If you try to do them more up front, maybe it applies only to a subgroup.

Is there any insight into why patients become resistant to these targeted agents?

If you biopsied somebody who initially responded to osimertinib and then progressed, we [would] understand some of the mechanisms. [For example,] you can develop an additional mutation called C797S. [Investigators] are looking at adding antibodies to this, such as cetuximab [Erbitux]. This will bring in added toxicity, but [it may] control the disease for a significant period of time. [Investigators] are looking to [develop] a drug specifically targeting C797S.

The other actionable area is MET amplification. We knew this was a resistance mechanism to first- and second-generation TKIs. It could be [occurring in] up to 30% of patients on osimertinib. The one challenge is that it is a continuous variable. Where do we determine that MET is a true second driver and that you need combination therapy?

Where do you see the newly approved EGFR inhibitor dacomitinib (Vizimpro) fit in?

Dacomitinib is a second-generation, irreversible inhibitor in the same class as afatinib [Gilotrif]. The ARCHER 1050 trial led to this FDA approval, and technically it was a positive study.

Median PFS was [14.7 versus 9.2 months in patients treated with gefitinib]. This is a very toxic drug, [and 66% of] patients needed dose reductions.

Immunotherapy has not made much of an impact in this space. Will it have a role one day?

-positive NSCLC, immunotherapy is going through some growing pains. Initially, in second-line studies [examining] pembrolizumab [Keytruda], nivolumab [Opdivo], and atezolizumab [Tecentriq] compared with pretty poor chemotherapy regimens such as docetaxel; [the checkpoint inhibitors] could not even beat docetaxel. We are seeing response rates as high as 12% and as low as 3% or 4%.

There is a very small subset of patients who are

-positive who will benefit from immunotherapy, but it is obviously less than the general lung cancer population. The patients who benefit may also have severe [adverse] effects.

What does the landscape look like for ALK-driven therapies?

There are 3 different categories here. One is somebody who is already on crizotinib. Post crizotinib, the response rates under the next-generation inhibitors all look pretty much the same. Where they differ is in the median PFS. Brigatinib [Alunbrig] is the standout winner. We may not understand why, and the preclinical modeling suggests this should not be happening. But that tells us the model is not perfect.

The second group [comprises patients] with

-positive disease. What do they start therapy on? The drugs with a first-line license are crizotinib, ceritinib [Zykadia], and alectinib. We already know alectinib beats crizotinib head-to-head.

Ceritinib has been tested against chemotherapy [only], and it did better than chemotherapy. I think it is clear that alectinib is the first-line choice.

The third category is [for those patients who progress] on a next-generation inhibitor. Very recently, lorlatinib [Lorbrena] got a license for patients who progress on 1 or more next-generation inhibitors.

The really exciting thing about this field is that these hazard ratios can mature over time. We now understand why. The maturation is coming from controlling differences in extra CNS penetration. It takes 7 or 8 months to even start out separating the curves.

Ramalingam S, Reungwetwattana T, Chewaskulyong B, et al. Osimertinib vs standard of care (SoC) EGFR-TKI as first-line therapy in patients (pts) with EGFRm advanced NSCLC: FLAURA. Presented at: 2017 ESMO Congress; Madrid, Spain; September 9-12, 2017. Abstract LBA2_PR.

FDA Approves Genentech&rsquo;s Alecensa (Alectinib) as First-Line Treatment for People with Specific Type of Lung Cancer [news release]. Genentech website. Published November 6, 2017. http://bit.ly/2zmLda7?rel=0" . Accessed November 6, 2017.

Mok T, Cheng Y, Zhou X, et al. Dacomitinib versus gefitinib for the first-line treatment of advanced EGFR mutation positive non-small cell lung cancer (ARCHER 1050): a randomized, open-label phase 3 trial.

Passaro A, de Marinis F, Dacomitintib in EGFR-positive nonsmall cell lung cancer: and attractive but broken option.

2018;7(Suppl 2):S100-S102. doi: 10.21037/tlcr.2018.02.09.

D. Ross Camidge, MD, PhD,&nbsp;discusses the crowded landscape of oncogene-driven non&ndash;small cell lung cancer.

Resistance to Therapy Clouds Treatment Successes in EGFR-, ALK-Positive NSCLC

Genetic aberrations across cancer types were the driving force behind drug approvals in 2018. The year saw the first initial approval based on a genetic mutation, rather than a specific tumor type, with larotrectinib (Vitrakvi), which is indicated in solid tumors with an NTRK gene fusion.

In addition, BRAF and MEK inhibitor combinations were approved for multiple indications in melanoma, and they accounted for the first approval in anaplastic thyroid cancer.

Olaparib (Lynparza), which has indications in ovarian cancer, including 1 new recent indication, was approved for use in patients with deleterious germline

-mutated (gBRCAm), HER2-negative metastatic breast cancer following chemotherapy in January.

In response to the year&rsquo;s first approval for a targeted therapy, Richard Pazdur, MD, director of the FDA&rsquo;s Oncology Center of Excellence and acting director of the Office of Hematology and Oncology Products in the FDA&rsquo;s Center for Drug Evaluation and Research, said, &ldquo;This approval demonstrates the current paradigm of developing drugs that target the underlying genetic causes of a cancer, often across cancer types.&rdquo;

Standard-of-care therapies in nonsmall cell lung cancer (NSCLC) saw approvals expanded to include different

Genetic aberrations across cancer types were the driving force behind drug approvals in 2018.

January 2019