OncologyLive® is the flagship publication of OncLive®. Each issue delivers expert insights and clinical oncology news and updates, which impact the day-to-day clinical practice of oncology professionals who work tirelessly to help improve patient outcomes.

As technology and cancer care continue to become intertwined at every level, there is an imperative need to effectively process and use vast amounts of data to provide the highest level of care for patients. Learning health care systems represent an evolving model of cancer data integration and application that has the potential to positively affect care for many patients. 

“What we try to do [with learning health care systems] is to make it easier for providers to take all the information at their disposal and use it in real time to come up with the best treatment option and care plan for their patient,” Duncan Allen, MHA, the senior vice president of clinical services at OneOncology in Nashville, Tennessee, said in an interview with 

. “We need to make sure that the systems we’re [using] can ‘talk’ to each other. Do we have the right data, infrastructure, and interfacing in place, from when a new approval comes out to the time when providers are putting that new therapeutic regimen into practice?”

The Institute of Medicine describes the ideal learning health care system as one where, “…science, informatics, incentives, and culture are aligned for continuous improvement and innovation—with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by-product of the delivery experience.”

The American Society of Clinical Oncology’s CancerLinQ (Learning Intelligence Network for Quality) is a learning health care system designed to collect clinical data from electronic medical records (EMRs) and provide clinical decision support based on available guidelines. The developers of CancerLinQ also designed the learning health system to capture processes and outcomes, allowing investigators to track trends and identify areas of unmet need (FIGURE).

Results of a prototype leveraging CancerLinQ showed that the system was able to accumulate data from 130,000 cases of patients with previously treated breast cancer from the individual EMR systems of 5 large practices, surpassing the original target goal of 30,000 cases.

 The system then used the data to provide recommendations via a decision-support dialogue box within an open-source EMR that can be accessed by the clinician. Additionally, 10 Breast Cancer Quality Oncology Practice Initiative performance measures with compliance ratings were accessible. The system also included software that enabled the clinician to visualize the data set. The CancerLinQ prototype was assembled in 5 months.

Nearly a decade after the initial design, investigators continue to use the CancerLinQ system. For example, in 2021, Ray et developed a prognostic tool using CancerLinQ data to predict risk of death within 30 days of a clinical encounter in patients with metastatic breast cancer (MBC). Data drawn from the EMR included age, vital signs, laboratory values, performance status, pain score, and time since chemotherapy, as well as estrogen receptor, progesterone receptor, or HER2 status from January 2000 to June 2020.

The system identified 9270 patients, representing 586,801 encounters. The model had a prediction accuracy of 86%, positive predictive value of 50%, sensitivity of 70%, and specificity of 88%. Specifically, predictors of mortality within 30 days for patients with MBC included chemotherapy within 1 year but not the past 30 days (odds ratio [OR] 1.92; 95% CI, 1.67-2.20), opiate use (OR, 1.71; 95% CI, 1.17-2.52), and high pain score with no opiate use (OR, 1.27; 95% CI, 1.10-1.48).

CancerLinQ is currently used by more than 100 oncology practices and contains real-world data representing more than 6 million patients.

A major proposed addition to the learning health care system is the integration of genomic data. Targeted therapies that require precise knowledge to be effective—ie, mutations are being expressed in a disease—are becoming increasingly prevalent in cancer care. The addition of genomic profiling to the learning health care system will allow clinicians to quickly identify agents that will be effective for a patient depending on their specific mutations. Similarly, these data can be used to match patients with the appropriate clinical trials for their unique disease, Allen explained. 

To achieve this, investigators have determined that the primary infrastructure elements of the learning health care system must include a common cancer genomic profiling (CGP) vendor, a common EMR system, integrated genomic results, and access to clinical trials. The CGP and EMR systems are then integrated to include clinical and genomic data together; these data are then moved into the point of care so to be easily accessed by the clinician.

“The biggest elements are data and information consumption, making sure that you have solutions across the types of information that a provider requires to be practicing at the top of their license [and] then making sure you have the right connectivity built so it can be seamless for [clinicians] to figure out what treatment is best for their patients,” Allen said. 

One of the biggest roadblocks to incorporating genomic profiling in a learning health care system is working to ensure that all patients who are eligible for genomic profiling receive it. Strategies to overcome this challenge include increased patient education efforts by clinicians to help patients understand all their treatment options. 

In the hematology space, investigators who are part of the American Society of Hematology Research Collaborative, a nonprofit organization, are seeking build a data infrastructure platform designed to support learning health systems. The goal of the project is to provide the most effective treatments to improve the lives of patients by generating and applying clinical evidence from clinical, administrative, laboratory, and patient-reported sources. The organization is comprised of 2 primary initiatives: the data hub and the clinical trials network.

The data hub draws on information from EMR integration, direct data entry via electronic data capture, and external data sources to better develop clinical care delivery sites for hematologic diseases. It optimizes the exchange of information via interconnected dashboards, queries, and research contributions, highlighting gaps in care and patient outcomes. 

Multiple myeloma was chosen as an initial disease area of focus for the initiative because data sharing opportunities using real-world data are especially timely. Additionally, investigators note that multiple myeloma represents a prime opportunity for the learning health care system model because large data sets are required for the development and validation of prognostic biomarkers and because therapy sequencing decisions becoming more complex. 

Investigators designed the data hub to encompass disease-specific end points, clinical guidelines, and other evidence-based documents to serve as core metrics. Baseline computable phenotypes (e-phenotypes) for various clinical concepts are formed using value sets from clinical terms drawn from EMR documentation codes. Data that may not be reliably recorded in individual patient EMRs are also sourced, leveraging local research data and/or disease-progression metrics. All data are funneled into the site dashboard, where trends may be referenced by the clinician. 

The collective plans to develop a comprehensive e-phenotype knowledge base, with an emphasis on being able to easily share this information and having the e-phenotypes mature and inform treatment decisions over time. Developers plan to create algorithms based on an inclusive list of codes used to determine the sensitivity for capturing information to predict the positive value of the proposed concept. Machine learning and artificial intelligence can then be used to determine contributors to the e-phenotypes when rules do not exist or are not applicable. 

“What we can do today that we weren’t able to do 15 to 20 years ago is take aggregated patient information that is deidentified and HIPAA [Health Insurance Portability and Accountability Act] compliant and utilize it in making the best treatment decisions for patients,” Allen said. “With all the information we’ve gathered, including clinical, genomic, financial, and operational data, we can help select the best therapeutic regimen for our patients. From a patient perspective, they significantly benefit from how the field of informatics has developed to a state where we can leverage big data to make much [better] decisions.”

It is important to note that learning health care systems are not perfect by any means and that constant work is being done to improve and optimize the model, Allen said. In many instances, connectivity issues impede fast and accurate communication between the EMR and CGP vendors. Fragmentation of the workflow can negate many advantages provided by the learning health care system model. 

To address these shortcomings, firms such as OneOncology are using physician-driven councils to provide ongoing feedback on the systems they are building. These physician advisory boards can help inform the developers of learning health care systems what areas to focus on next, the biggest issues for practicing oncologists in the clinic, and how to continue to streamline the systems for ease and speed of use. Clinicians are also working to improve the interoperability between different EMR systems to better facilitate their integration into a learning health care system model.

“Like everything [today], health care is getting smarter,” Allen said. “Much of that intelligence is driven from how you marry data together to extract more value. The future of learning health systems is that they’re much more automated. You’ll see more consolidation, especially in the oncology space, around partners where people are coming up with full suites of software that can help [further] unlock the learning health system approach.”

Articles

Oncology Live®

As technology and cancer care continue to become intertwined at every level, there is an imperative need to effectively process and use vast amounts of data to provide the highest level of care for patients. 

 Advances in Learning Health Care Systems Strive to Optimize Cancer Care

Differentiated thyroid cancer (DTC) makes up approximately 95% of all thyroid cancers and is becoming more prevalent worldwide.

 A decade ago, treatment options for DTC were limited but today a plethora of targeted treatments are available. “There are not a lot of cancer types [in which] such great research, collaboration, and advancements have happened,” Marcia S. Brose, MD, PhD, FASCO, said during a recent 

Brose was among a panel of thyroid cancer experts who shared their insights into the evolving DTC treatment landscape. They reviewed the use of VEGF receptor (VEGFR) inhibitors and some of the precision medicine treatments now identified for molecularly selected subsets of patients with DTC, such as BRAF, RET, and TRK inhibitors.

The DTC classification includes papillary thyroid cancer (PTC), follicular thyroid cancer, and Hürthle cell cancer (FIGURE

 The 2 main lineages, papillary and follicular, have differences in epidemiological profiles and clinical course, noted Giuseppe Barbesino, MD. “Papillary thyroid cancer is the most common type. It is seen across [all] ages with mostly nodal metastasis, occasionally other organs,” he said. “The follicular type…tends to metastasize to the bone, but the lungs can also be involved.”

Although initial therapy for localized DTC is often effective, tumor recurrences have been observed in up to 30% of patients.

 During the past 10 years, kinase inhibitors have been introduced for patients with metastatic or recurrent DTC, starting with agents directed at the angiogenic pathway.

“Thyroid cancers are very vascular tumors. They respond very well to VEGFR inhibitors,” Maria E. Cabanillas, MD, said. For this reason, anti-VEGFR inhibitors have become a mainstay of treatment for thyroid cancer across histological subtypes. The panelists focused on 3 VEGFR inhibitors that the FDA has approved for patients with radioactive iodinerefractory DTC: sorafenib (Nexavar) and lenvatinib (Lenvima), which are approved as first-line treatments, and cabozantinib (Cabometyx), which is approved as a second-line treatment.

 In addition to VEGFRs, each of these drugs inhibits other kinases associated with angiogenesis, tumor growth, and cancer progression.

Demonstrating an overall survival benefit in pivotal VEGFR trials for sorafenib and lenvatinib has proved challenging because patients from the placebo arms were permitted to transition to the study drug, noted Lori J. Wirth, MD, who served as moderator of the Peer Exchange program. “Patients [receiving] placebo when they had disease progression were allowed to cross over and receive the active drug and the majority of patients all received the active drug…so that could negate an overall survival benefit.”

In 2013, sorafenib became the first VEGFR inhibitor approved by the FDA for patients with radioactive iodine–refractory locally recurrent or metastatic DTC, Brose said.

 The FDA’s approval was based on data from the phase 3 DECISION trial (NCT00984282), in which investigators randomly assigned 417 patients 1:1 to receive sorafenib (n = 207) or placebo (n = 210).

 Patients receiving placebo who progressed were allowed to cross over to open-label sorafenib. The primary end point was progression-free survival (PFS) by central independent blinded review.

Sorafenib therapy resulted in significantly improved PFS vs placebo, with a median PFS of 10.8 months (95% CI, 9.1-12.9) vs 5.8 months (95% CI, 5.3-7.8), respectively (HR, 0.59; 95% CI, 0.45-0.76; 

 < . 0001). Improvement in PFS with sorafenib was seen regardless of whether patients’ tumors harbored 

 family mutations. There was no statistically significant difference in the secondary end point of OS between the treatment arms, and the median OS was not reached in either arm.

 In the final OS analysis, which adjusted for crossover, the data suggested that the true OS treatment effect with sorafenib was larger than observed in the intention-to-treat (ITT) analysis.

The FDA approved lenvatinib for radioactive iodine–refractory locally advanced or metastatic DTC in 2015 based on findings from the phase 3 SELECT study (NCT01321554), whose investigators randomly assigned 392 patients with progressive radioiodine-refractory DTC 2:1 to lenvatinib (n = 261) or placebo (n = 131).

 As in the DECISION study, patients who progressed on placebo could receive open-label lenvatinib. The primary end point was PFS, with secondary end points including response rate, OS, and safety.

The median PFS was 18.3 months (95% CI, 15.1-not estimable [NE]) in the lenvatinib arm vs 3.6 months (95% CI, 2.2-3.7) in the placebo arm (HR, 0.21; 99% CI, 0.14-0.31; 

 The response rate was 64.8% (n = 169) in the lenvatinib arm, with 4 complete responses (CRs) and 165 partial responses (PRs), compared with a response rate of 1.5% (n = 2) in 131 patients in the placebo arm, with 2 PRs (odds ratio [OR], 28.87; 95% CI, 12.46-66.86; 

 < . 001). The median OS was not reached in either arm.

“I think many people have switched to make lenvatinib their first-line therapy based on these really strong results from the SELECT trial,” Brose said.

Cabozantinib is the latest VEGFR inhibitor to be approved, in September 2021. The FDA approved the agent for adult and pediatric patients 12 years and older with locally advanced or metastatic DTC that has progressed following prior VEGFR-targeted therapy and who are ineligible for or refractory to radioactive iodine.

Approval was based on data from the phase 3 COSMIC-311 trial (NCT03690388), in which investigators randomly assigned 187 patients 2:1 to cabozantinib (n = 125) or placebo (n = 62).

 All patients had been previously treated with sorafenib, lenvatinib, or both. Crossover to cabozantinib following progression on placebo was allowed. The primary end points were objective response rate (ORR) in the first 100 randomly assigned patients and PFS in all randomly assigned patients (ie, ITT population).

“That trial was halted early because it reached one of its primary end points after only 100 patients had been on study for 6 months. So at its f irst data analysis point, it reached its primary end point, and the data safety monitoring committee recommended it be stopped because it had already shown its efficacy,” Brose said.

As of data cutoff in February 2021, 258 patients had been randomly assigned in the ITT population, with 170 receiving cabozantinib and 88 receiving placebo. In the final analysis, which had a longer median follow-up of the ITT population than the preplanned interim analysis (10.1 months vs 6.2 months, respectively), the median PFS was 11.0 months (96% CI, 7.4-13.8) for cabozantinib compared with 1.9 months for placebo (95% CI, 1.9-3.7), which translated into a 78% reduction in risk of progression (HR, 0.22; 96% CI, 0.15-0.32; P < . 0001).11 The ORR was 11.0% (95% CI, 6.9%-16.9%) for cabozantinib vs 0% (95% CI, 0.0%-4.1%) for placebo (TABLE

“[The COSMIC-311] setting is very different from the first line and the SELECT and DECISION trials because [the COSMIC-311 patients] were rapidly progressing. It’s important for people to know that when things start to go badly and people have already been on sorafenib, lenvatinib, or both for a long time, many times the speed of the disease has really picked up,” Bose said. Subsequently, she said it is essential for clinicians to line up their next therapy at the first hint that a patient has multiple sites of disease that are progressing. If they have not prepared for this, she warned that the patient could decline so quickly that there would no longer be an opportunity to treat them, especially because some drugs can take weeks to obtain.

Managing Toxicities of Anti-VEGFR Therapy

Inhibition of the VEGF signaling pathway is associated with distinct adverse effects (AEs), some of which can be life threatening if proper precautions are not taken. “The toxicity profiles among these 3 [VEGFR inhibitors] are, I would say, comparable. It’s like a bouquet of flowers with the same flowers. Of course, no 2 bouquets are exactly alike, even if they have the same flowers,” Brose said.

She noted that VEGFR inhibitors are associated with varying degrees of hand-foot skin reactions, diarrhea, and hypertension. With lenvatinib, she said, hypertension is the most significant and worrisome AE initially, as it can happen very quickly. To prevent complications from this AE, she calls in prescriptions for antihypertensives before patients start treatment so they can take those therapies if their blood pressure exceeds 150/90 mm Hg, especially at a time when the clinic might be closed. Regarding the hand-foot skin reactions, she tells patients that taking ibuprofen can be helpful.

Brose emphasized the importance of educating patients about AEs associated with VEGFR inhibitors to ensure these events are caught early on, which minimizes risks and enables patients to remain on treatment. “Most adverse events don’t become grade 3 without being grade 1 or 2 first. And if you can intervene at that point, that can make a huge difference,” she said.

Somatic BRAF V600E mutations have been observed in 37% to 50% of patients with PTC and are associated with aggressive tumor features and decreased uptake of radioiodine.

 Although BRAF inhibition has elicited antitumor activity against DTC in several clinical trials, the only FDA-approved therapy directed at this pathway is indicated for patients with anaplastic thyroid cancer (ATC)

, a rare and aggressive undifferentiated tumor type.

 In May 2018, the FDA approved the combination of dabrafenib (Tafinlar), a BRAF inhibitor, plus trametinib (Mekinist), a MEK inhibitor, for patients with locally advanced or metastatic ATC with a 

 V600E mutation and no satisfactory locoregional treatment options.

National Comprehensive Cancer Network guidelines note that BRAF inhibitors can be considered for patients with advanced BRAF-mutated PTC who are not candidates for radioiodine therapy, clinical trials, or other systemic therapy.

 During the Peer Exchange program, the panelists noted that BRAF inhibitory agents are particularly interesting because data from small studies have shown they can restore the ability of thyroid cancer cells to take up radioiodine (ie, a redifferentiation therapy), potentially reopening the door to radioiodine treatment.

Vemurafenib (Zelboraf) was the first BRAF inhibitor assessed in a clinical trial for thyroid cancer, Cabanillas said. It was evaluated in an open- label, nonrandomized, multicenter, phase 2 study (NCT01286753) that enrolled 51 patients with 

 V600E–mutated metastatic or recurrent PTC. The participants included 26 who had never received VEGFR inhibitor therapy and 25 who previously had had such treatment.12 All patients received vemurafenib 960 mg orally twice daily. The primary end point was investigator-assessed best overall response in the VEGFR inhibitor– naïve cohort.

After a median duration of follow-up of 18.8 months in the VEGFR inhibitor–naïve cohort, the best overall response was PR, which investigators observed in 38.5% (n = 10) of patients (95% CI, 20.2-59.4).

 The median PFS was 18.2 months (95% CI, 15.5-29.3). In the previously treated cohort, after a median follow-up of 12.0 months, the best overall response was a PR in 27.3% of patients (6 of 22 patients, as 3 originally enrolled in this cohort were deemed ineligible or withdrew consent). The median PFS was 8.9 months (95% CI, 5.5-NE).

Cabanillas said that vemurafenib has a slightly different AE profile compared with dabrafenib, noting that it causes more issues with arthralgias and skin toxicities, including hand-foot skin reactions. She said vemurafenib also can cause squamous cell carcinomas of the skin and alopecia (usually just hair thinning), which are class effects of BRAF inhibitors. In the phase 2 trial, grade 3 or 4 AEs occurred in 65% or more of patients in both cohorts, with squamous cell carcinoma of the skin, lymphopenia, and increased γ-glutamyltransferase levels being the most common.

Dabrafenib was assessed in a randomized phase 2 trial (NCT01723202) that evaluated this agent alone and in combination with trametinib in 53 patients with 

-mutated PTC, 25% of whom had been previously treated with a multikinase inhibitor.14,15 In the study, 26 patients received dabrafenib monotherapy and 27 patients received dabrafenib plus trametinib. Crossover from monotherapy to combination therapy was allowed at the time of progression. The study’s primary end point was ORR, defined as PRs plus minor responses (ie, 20%-29% decrease in the sum of diameters of target lesions).

In the monotherapy arm, 11 of 22 evaluable patients responded, including 10 with PRs and 1 with a minor response, for an ORR of 50%. In the combination arm, 13 of 24 assessable patients responded, including 9 with PRs and 4 with minor responses, for an ORR of 54%. The median PFS was 11.4 months (95% CI, 3.8-not reached) among those who received monotherapy and 15.1 months (95% CI, 11.7-not reached) for those treated with the combination.

“The number one problem that we have with dabrafenib is fever…; [it] tends to go away after about 2 or 3 months [in most patients] but it is difficult to manage in some patients,” Cabanillas said. She noted that some other AEs associated with dabrafenib include anemia, fatigue, nausea, skin disorders, and alopecia.

Although VEGFR inhibitors are the recommended FDA-approved first-line treatments for locally advanced or metastatic radioiodine-refractory DTC, Cabanillas said that she will often start appropriate patients on a BRAF inhibitor. She favors this off-label approach because the toxicities associated with VEGFR inhibitors can be difficult for some patients to tolerate, particularly those who are older.

“When I think about treating systemically, I’m thinking about that marathon that we’re starting. Yes, I’ll get more partial responses with lenvatinib, but in terms of how long we’re going to have a response or stability, that’s really what’s going on in my mind—how can we get the most out of every single drug,” she said. She explained that if she starts a patient on a VEGFR inhibitor and they lose a significant amount of weight while on treatment and become debilitated, they may no longer be able to receive a second-line treatment, whereas if she first starts them on a BRAF inhibitor, they might be in better shape to start the VEGFR inhibitor when they progress.

Naifa L. Busaidy, MD, FACP, FACE, who like Cabanillas practices at The University of Texas MD Anderson Cancer Center, concurred. She said the general practice at their institution is to obtain biomarker testing and then proceed with whatever selective therapy is appropriate in the first line. “It doesn’t mean it’s necessarily the right thing to do, but if you’re worried about [getting] the anti-VEGF [agent] in the second line, now we have an official indication [with cabozantinib],” she said.

 fusions are less frequent actionable targets that are mostly found in patients with PTC. “We’re going to see [

 fusions] in about 8% to 10% of PTCs, whereas 

 fusions we see in about 3%,” Cabanillas said. She discussed 2 RET inhibitors, selpercatinib (Retevmo) and pralsetinib (Gavreto), and 2 TRK inhibitors (kinases encoded by 

 genes), larotrectinib (Vitrakvi) and entrectinib (Rozlytrek), that the FDA has approved.

The FDA granted accelerated approvals for selpercatinib, a selective RET inhibitor, for adult and pediatric patients (≥ 12 years) with 

 fusion–positive, radioiodine-refractory advanced or metastatic thyroid cancer, adult and pediatric patients with RET-mutant medullary thyroid cancer (MTC), and adults with 

 fusion– positive non–small cell lung cancer (NSCLC).

 fusion–positive thyroid cancer indication is based on findings from the phase 1/2 LIBRETTO-001 trial (NCT03157128), which included 19 patients with previously treated 

 fusion–positive thyroid cancer. Among these were 13 patients with PTC, 3 with poorly differentiated tumors, 1 with Hürthle cell carcinoma, and 2 with ATS. Patients with 

 fusion–positive NSCLC were enrolled in separate cohorts. After the dose-escalation portion of the trial, patients received selpercatinib orally at 160 mg twice daily.

 fusion–positive thyroid cancer cohort, the ORR by independent review was 79% (95% CI, 54%-94%), including 1 CR (5%) and 14 PRs (74%).

 After a median follow-up of 13.7 months, 64% (95% CI, 37%-82%) of patients were progression free at 1 year. All patients included in the study had been previously treated with 1 or more VEGFR inhibitors and had tumors refractory to radioiodine, other than participants with ATS, a subtype for which radioiodine is not used.

Overall, treatment was well tolerated. The discontinuation rate with selpercatinib for treatment-emergent AEs was only 2%, Cabanillas said, noting that this was for the entire study population of 531 patients. In those with thyroid cancer, the most common AEs of grade 3 or worse severity included hypertension, increased liver enzymes, hyponatremia, and diarrhea.

Pralsetinib has gained accelerated approvals from the FDA for patients 12 years and older with advanced or metastatic 

 fusion–positive thyroid cancer who require systemic therapy and are radioiodine-refractory (if such therapy is appropriate), as well as for adult and pediatric patients with advanced or metastatic 

 Its safety and efficacy were established in the phase 1/2 ARROW trial (NCT03037385) in patients with locally advanced or metastatic 

-altered solid tumors, including 20 patients with 

 Among the 9 participants who were evaluable for response, all of whom had PTC, the ORR was 89% (95% CI, 52%-100%), all PRs. Although the median PFS and OS were not reached, 81% of patients were progression free at 1 year and the estimated 1-year OS was 91%.

“The adverse event profile is similar [to] but not really the same [as that of selpercatinib]. It’s interesting that pralsetinib tends to cause more anemia. [The investigators] also reported more musculoskeletal pain and constipation,” Cabanillas said. Like selpercatinib, pralsetinib was associated with hypertension and increased liver enzymes.

 Both agents can elevate liver enzymes, but Cabanillas has switched from one agent to the other when a patient develops this AE. “It’s been OK on the opposite drug, so that is worth trying,” she said. In the safety population of 142 patients with 

-altered thyroid cancer, the discontinuation rate with pralsetinib was 4%.

Larotrectinib and entrectinib are both approved by the FDA for the treatment of solid tumors harboring NTRK gene fusions (also called TRK fusions), Cabanillas said. She noted that larotrectinib has the most data to support its use in DTC.

Cabanillas and colleagues presented longterm efficacy and safety data for larotrectinib in DTC at the 90th Annual Meeting of the American Thyroid Association in 2021. In an assessment of data from several trials, which included 21 evaluable patients with DTC, the ORR was 86% (95% CI, 64%-97%), which include 2 CRs.

 “There was no best response progression, so [these were] really stellar outcomes. The median follow-up time was 22 months, and with that, we had a median progression-free survival of 51 months, and overall survival was not reached. But at 2 years, 92% of patients were alive,” she said.

Additionally, no patients discontinued treatment because of AEs, Cabanillas noted. Higher-grade AEs included anemia and low lymphocyte counts. She also noted some dizziness and nausea but said that the dizziness tends to resolve as patients adjust to the therapy. 

Regarding entrectinib, Cabanillas said that very little is known about the use of this agent in thyroid cancer. She noted that the only data thus far come from an integrated analysis of 54 patients with advanced or metastatic solid tumors harboring 

 fusions, only 5 of whom had thyroid cancer, with their subtypes not specified.

 Among these patients, there was only 1 PR. “We think it’s probably a similar drug [to larotrectinib], but it does have other targets and so may lead to some off-target effects,” she said.

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Marcia S. Brose, MD, PhD, FASCO, and a panel of thyroid cancer experts share their insights into the evolving treatment landscape, including the use of VEGF receptor inhibitors and some of the precision medicine treatments now identified for molecularly selected subsets of patients with differentiated thyroid cancer, such as BRAF, RET, and TRK inhibitors.

Targeted Treatment Boom Reshapes Differentiated  Thyroid Cancer Landscape

Advances in the development of tyrosine kinase inhibitors (TKIs) that target the breakpoint cluster region–Abelson murine leukemia 1 (

) fusion have changed the treatment landscape for patients with Philadelphia chromosome–positive chronic myeloid leukemia (CML).

 Patients of receive their initial CML diagnosis in the chronic phase, during which time disease may be controlled with treatments with approved TKIs such as imatinib mesylate (Gleevec). Second generation TKIs have elicited durable responses among patients treated in the first- and second-line setting. However, up to 20% of patients may develop resistance via acquired mutations such as the gatekeeper 

Overcoming resistance mechanisms in this patient population has resulted in the development of the agents asciminib (Scemblix) and ponatinib (Iclusig). Asciminib was granted accelerated approval by the FDA in October 2021 for patients with Philadelphia chromosome–positive CML in chronic phase who were previously treat with 2 or more TKIs. The agent also received regular approval for patients with Philadelphia chromosome–positive CML in any phase who present with a 

 Ponatinib carries the same designations from the FDA but comes with a boxed warning for arterial occlusive events, venous thromboembolic events, heart failure, and hepatoxicity.

 video program, Elias J. Jabbour, MD, joined moderator Matthew S. Davids, MD, MMSc, to review data on both agents in the post–second generation TKI setting that were presented at the 63rd American Society of Hematology (2021 ASH) Meeting and Exposition. Specifically, the pair discussed recent data from the phase 3 ASCEMBL trial (NCT03106779) evaluating asciminib vs bosutinib (Bosulif) and contextualized new findings for ponatinib from a post hoc analysis of the dose-optimization phase 2 OPTIC trial (NCT02467270).

In ASCEMBL, investigators presented updated findings for patients who had at least 48 weeks of treatment with asciminib (n = 157) vs those who received bosutinib (n = 76). Major molecular response (MMR) rates at 48 weeks were 29.3% among those who received asciminib and 13.2% for those who received bosutinib (common treatment difference 16.1%; 95% CI, 5.7%-26.6%).

 of 1% or less was reported among 50.5% of patients who received asciminib vs 33.7% of patients who received bosutinib. More results from the trial are highlighted in TABLE 1.

In OPTIC, updated outcomes regarding the benefit/risk analysis of different dosing strategies of ponatinib—cohort A: 45 mg to 15 mg (n = 93); cohort B: 30 mg to 15 mg (n = 93); cohort C: 15 mg (n = 91)—demonstrated that durable responses measured as 

 expression 1% or less was achieved in all cohorts. Patients in cohort A experienced the highest response rate measured as 

 of 1% or less at 12 months at 44.1% (98.3% CI, 31.7%-57.0%) meeting the prespecified statistical end point. Among those in cohort A who had a 

 mutation at baseline (n = 15), the response rate at 12 months was 60%. More results from the analysis are highlighted in TABLE 2.

: We’re going to start our discussion with the efficacy and safety [data] from ASCEMBL, a phase 3 study of asciminib, which is a first-in-class STAMP inhibitor, vs bosutinib in patients with CML and chronic phase after 2 or more prior TKIs. This is an update after 48 weeks. Dr Jabbour is going take us through this. Maybe if you could start with what is a STAMP [Specifically Targeting the ABL Myristoyl Pocket] inhibitor and why is this active with a 

: [To start,] I want to talk about asciminib, the new kid in block added to the treatment landscape in CML. Asciminib is different than ponatinib or other TKIs. It binds to the myristoyl pocket to inhibit 

, which is different than the prior TKIs, which use the ATP binding site to inhibit 

. It belongs to what we call the STAMP class of drugs.

Asciminib was already assessed in a phase 1 study [NCT02081378] with the recommended phase 2 dose established as 40 mg twice daily. With dose escalation, investigators determined a 200 mg twice daily dose as appropriate dose for patient harboring the 

ASCEMBL was a randomized phase 3 trial that randomly assigned patients with chronic phase CML who progressed following at least 2 TKIs and who did not have 

 mutations at baseline to asciminib 40 mg twice daily or bosutinib 500 mg once daily—the approved dose for patient who failed prior TKIs. The primary end point was MMR rate at 24 weeks, [data that were previously reported].

[The MMR rate was] 25.5% in favor of asciminib compared with 13.2% for bosutinib.

 This higher rate of MMR seen with asciminib led to the approval of the drug. Now, what we know as well, that patient enrolled here, they should have failed to prior TKI. If we look at the level of disease, some [individuals] had no disease whatsoever. 

 of 1% or less was reported among 9.1% of patients who received asciminib compared with 5.3% of those who received bosutinib.

At 2021 ASH, we had a long-term follow-up of this study at 48 weeks and the results were still in favor of asciminib. I would like to highlight discontinuation rates with bosutinib compared with asciminib. [Results showed that] 77.6% of patients who received bosutinib had to stop the drug compared with 42.7% with asciminib. Intolerance is an issue here, but the drug was still better than bosutinib.

One good question is why [is there no study] comparing asciminib with ponatinib? That has not been done yet. 

Moving on to ponatinib, the agent was approved a long time ago as a third-generation TKI effective against 

 mutations at a dose of 45 mg per day. Ponatinib was evaluated in patients who failed multiple TKIs, 2 or more, or who had a 

 mutation. So the patients who were enrolled were heavily pretreated, with 53% having received more than 3 TKIs.

The vast majority of patients were able to achieve complete response [55%] and responses were durable [not reached at 60 months follow-up]. Now with ponatinib at 45 mg per day, we did see vascular events, unfortunately. These vascular events were seen in nearly every patient at 45 mg per day and in patients at high risk of vascular events, therefore the drug was placed on hold for a short time.

Following the clinical hold, a trial called OPTIC [was designed to evaluate] dose optimization of ponatinib. When we lower the dose of ponatinib we can optimize the outcome. In OPTIC, patients who had received at least 2 TKIs were randomly assigned to ponatinib at 45 mg and reduced to 15 mg once the 

 of 1% or less was obtained; 30 mg reduced to 15 mg once the 

 was at 1% or less; or 15 mg [as a starting dose]. The primary end point was rate of 1% or less 

 at 12 months. In this study, the investigators have shown that dose optimization from 45 mg to 15 mg was the winner. In a way, it does offer the best efficacy and the best safety. This led to the change of the label of ponatinib being administered at 45 mg with reduction to 15 mg.

: That’s very helpful. I’m curious with asciminib, it’s early still, but have there been any resistance mechanisms identified yet?

: This is very important question. In fact, in ASCEMBL we reported mutations in a binding site of asciminib. Similarly, as we have seen with the ATP binding site with the other TKIs, already patients are expressing mutations, and there was a rationale to combine asciminib with other TKIs, and those investigations are ongoing right now.

Other things to consider are that already even with the short follow-up there was a 5% rate of vascular events reported. Mechanistically, we do not know how [these are occurring], but that’s something to keep in mind. Finally, the dose of asciminib is different, whether you prescribe it for non–

-mutant disease, which is 40 mg twice daily, or 

-mutant disease, which is 200 mg twice daily. Of course, price plays a role here because then you have to pay more for those with 

: You said that probably we’re not going have head-to-head data for asciminib and ponatinib.

: I think ideally that should have happened because we know in the third-line setting the best drug is ponatinib. We should have compared asciminib with ponatinib and the winner will get it all.

: Without that comparative data, you have a patient sitting in front of you, how do you weigh the pros and cons of these 2 drugs? How do you decide?

: Well, so far with ponatinib we have 10 years of follow-up. It’s extremely effective. I think it’s one of the most effective TKIs available. I start 45 mg in non-

-mutant disease and then reduce the dose and maintain the response. We also get to use this drug in Philadelphia chromosome–positive acute lymphoblastic leukemia as well, where the 45 mg reduction to 15 mg was safe and effective.

If there is a patient with vascular events who had an event recently, I would not be encouraged to use ponatinib for this patient. I may use asciminib but must be cautious. Yes, the rate of vascular events is lower, but the follow-up is still shorter. That said, I would be more inclined to use asciminib for these patients. At my institution, we have been using a using second-generation TKI up front, ponatinib, and then asciminib thereafter.

: We talked a lot about both ponatinib and asciminib here. There were 2 other abstracts out of 2021 ASH that focused on ponatinib. Do you want to go into those specifically?

Jabbour: The focus of a post-hoc analysis of response to ponatinib in patients with CML by baseline 

 mutation [attempted to answer the question]: Do we need 45 mg for [every patient]? In the OPTIC trial, the dose was 45 mg per day for all comers and reduced to 15 mg, 30 mg to 15 mg, and 15 mg all along. Investigators did not decide based on mutation profile.

In this abstract, data were presented by mutation. Essentially the message is for patients with 

 mutations up front, the recommended starting dose is 45 mg because at the lower dose the complete cytogenetic response rates were lower [TABLE 2]. We see the advantage in progression-free survival in 45 mg per day compared with 30 mg and 15 mg. Therefore, I think for 

-mutant disease—and I will always check for mutation at the baseline—start with 45 mg per day and reduce the dose later.

 mutation or other mutation, I still think there are advantages for 45 mg per day is my first choice, but then if an individual has no mutations and I’m concerned about hypertension or other vascular risk factors, I may use 30 mg and 15 mg, and the data are reassuring in that sense.

Finally, the last abstract presented was 2550,7 dose-modification dynamics of ponatinib in chronic phase CML from the patients in the OPTIC [and PACE] trials. In the phase 2 PACE trial [NCT01207440]—the original trial that led to the approval of ponatinib—the dose adjustment was based on adverse events: if a patient receives 45 mg and has adverse events, the dose is reduced to 30 mg and then 15 mg. We’ve shown that dose adjustment did not compromise efficacy.

In the OPTIC trial, the dose adjustment was based on efficacy, so you don’t have to wait for the safety concerns to happen to reduce the dose. By adjusting based on a response and efficacy, we had a better outcome. Therefore, the thresholding was determined in 2 ways: No. 1, you do not need full dose all along, and No. 2, reducing the dose based on dynamic of response is better than waiting for safety concerns.

This approach will preserve response and give you the best long-term outcome. Therefore, that led to the change of the label of the drug where you adjust the dose based on response. We have plenty of data on that now, and that dose reduction has become the standard of care.

: Some great abstracts in CML, very nicely summarized. Another great ASH meeting for this disease as well.

Sampaio MM, Santos MLC, Marques HS, et al. Chronic myeloid leukemia-from the Philadelphia chromosome to specific target drugs: a literature review. 

. 2021;12(2):69-94. doi:10.5306/wjco.v12.i2.69

Scemblix. Prescribing information. Novartis; 2021. Accessed March 11, 2022. bit.ly/3t3CjeX

Iclusig. Prescribing information. ARIAD Pharmaceuticals, Inc; 2022. Accessed March 11, 2022. bit.ly/3tPVurP

Elias J. Jabbour, MD, and Matthew S. Davids, MD, MMSc, review data on asciminib and ponatinib in the post–second generation TKI setting for chronic myeloid leukemia that were presented at the 2021 ASH Meeting and Exposition.

Vol. 23/No. 7 | Oncology Live®

Advances in Learning Health Care Systems Strive to Optimize Cancer Care

Targeted Treatment Boom Reshapes Differentiated Thyroid Cancer Landscape

Treatment Optimization Efforts Seek to Overcome Resistance in Advanced CML

Matulonis’ Passion Drives Gynecologic Cancer Research Into the Next Era

Pacritinib Paves a “Unique Lane” of Treatment for Select Myelofibrosis

Unexpected but Potentially Actionable Cancer Clinical Trial Results: What Happens Next?