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The September issue of ONCOLOGY features a rare case study on glioblastoma, discussions on end-of-life care, and insights into the field of pediatric oncology. 

September ONCOLOGY Publication

The consolidation of oncologists and the transition to bispecific antibodies and CAR T-cell therapies are among factors that have led to increasing cancer care costs.

What Has Impacted the Costs and Finances Associated With Cancer Care?

The high cost of cancer care is a mystery to nobody. While treatments have become more advanced and survival rates have increased, so too has the cost of these treatments. This is not the result of a single policy change or treatment, it is the culmination of many little decisions, policies, and advancements.

CancerNetwork® spoke with Loretta Nastoupil, MD, a practicing oncologist at Southwest Oncology in Durango, Colorado, an affiliate of CommonSpirit Oncology Mercy, about the finances and costs associated with cancer care from the perspective of a physician. While Nastoupil currently practices in a more rural, community center, her past history of working at MD Anderson Cancer Center, a large, institutional center, gives her a unique perspective into the reality and differences of both settings.

In her opinion, the consolidation of oncologists is one of the factors that has had the greatest impact on oncology over the last few years. As the prices associated with cancer care have risen, they have become “insurmountable” for many private practices; large academic groups have since begun purchasing community and private practices.

She also noted that the transition from traditional chemotherapy to newer, more expensive treatments like bispecific antibodies and CAR T-cell therapies has also led to changes, particularly in the payer mix.

What specific events have had a consequential effect on the economics of oncology?

For some background, I spent over a decade as an academic practicing oncologist at MD Anderson Cancer Center in Houston, Texas. I’m now a community oncologist in a rural community that’s a hospital-based practice. There are unique challenges in both settings. But what has really impacted the practice of oncology over the last few years is the consolidation of oncologists. The cost of drugs and the delivery of therapy in terms of supporting office staff have become insurmountable for most private practices. To address this, most have consolidated. You have these large academic groups that are buying up community or private practices. They have a better outreach into the community because we know that most patients in the US receive their care in community practice. [Additionally], you have these large hospital groups that are coming in and buying up smaller practices, and that’s currently where I practice.

Transitioning away from traditional chemotherapy to immune therapy, bispecific antibodies, and CAR T-cell therapies are major transition points. Married to that, because the cost of delivery of that care is so high, we’re seeing changes in the payer mix as well. This is going to [become] even more challenging over the next few years. For instance, where I practice, we provide care for patients who have Medicaid, Medicare, and even patients in the VA system, as there’s no VA hospital near us. We probably provide care for fewer privately insured patients, given that we have a large mix of retirees in this community. That’s also going to pose even greater challenges as we move forward.

Videos

Treatment with zanzalintinib plus atezolizumab led to improvements in OS and PFS vs regorafenib alone in patients with metastatic colorectal cancer.

The FDA has accepted a new drug application (NDA) for the combination of zanzalintinib (XL092) and atezolizumab (Tecentriq) as a treatment for patients with metastatic colorectal cancer (CRC) who have been previously treated with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy, according to a press release from the developer, Exelixis, Inc.

 The indication also extends to pretreatment with an anti-EGFR therapy if the patient has 

 wild-type disease. The agency has set a Prescription Drug User Fee Act (PDUFA) action date of December 3, 2026.

The submission is supported by results from the pivotal 

, which represents the first phase 3 study of an immune checkpoint inhibitor–based combination to demonstrate a statistically significant overall survival (OS) improvement in this specific patient population. These results were shared at the 

European Society of Medical Oncology (ESMO) 2025 Congress

 Zanzalintinib is a novel, oral multi-kinase inhibitor targeting MET, VEGFR, and TAM kinases (TYRO3, AXL, and MER), which may enhance the antitumor activity of immunotherapy.

“We are encouraged by this meaningful progress toward addressing the needs of patients with previously treated metastatic [CRC], for whom effective therapies have been limited and treatment outcomes remain poor,” Dana T. Aftab, PhD, executive vice president of research and development at Exelixis, stated in the press release.

 “Zanzalintinib has the potential to become an important advancement in a challenging treatment landscape, and if approved, zanzalintinib in combination with atezolizumab would provide a novel mechanism of action for patients with previously treated metastatic [CRC].”

In the primary OS analysis of the intention-to-treat (ITT) population, the combination of zanzalintinib and atezolizumab demonstrated a statistically significant improvement in survival compared with regorafenib (Stivarga). The median OS was 10.9 months in the combination arm vs 9.4 months in the regorafenib arm (HR, 0.80; 95% CI, 0.69-0.93; 

 = .0045). Notably, a trend toward improved OS was observed in the dual primary end point population of patients without liver metastases, with a median OS of 15.9 months for the combination vs 12.7 months for regorafenib (HR, 0.77; 95% CI, 0.59-1.01).

Secondary efficacy end points also favored the combination regimen. The median progression-free survival (PFS) was 3.7 months with zanzalintinib plus atezolizumab compared with 2.0 months with regorafenib (HR, 0.68; 95% CI, 0.59-0.79). The objective response rate (ORR) was 4% (95% CI, 2%-6%) for the combination and 1% (95% CI, 0%-3%) for regorafenib, while the disease control rate (DCR) reached 54% (95% CI, 49%-58%) and 41% (95% CI, 36%-45%), respectively.

“STELLAR-303 is the first phase 3 trial to show improved OS with an [immune checkpoint inhibitor]–based combination in metastatic CRC that is not [microsatellite instability–high (MSI-H) or mismatch repair deficient (dMMR)],” said lead study author Anwar Saeed, MD, an associate professor of medicine and the chief of the Gastrointestinal Medical Oncology Program at the University of Pittsburgh Medical Center, and coauthors, in the presentation.

 “Zanzalintinib plus atezolizumab represents a potential novel chemotherapy-free treatment option for heavily pretreated patients with metastatic CRC.”

The randomized, open-label, phase 3 STELLAR-303 study enrolled 901 patients with metastatic CRC that was documented as not MSI-H or dMMR. Patients were randomly assigned 1:1 to receive either the combination therapy or regorafenib monotherapy. The experimental regimen consisted of zanzalintinib at a dose of 100 mg administered orally once daily plus atezolizumab at 1200 mg administered intravenously every 3 weeks. Those in the comparator group received regorafenib at 160 mg orally once daily for the first 21 days of each 28-day cycle.

Eligibility criteria required patients to have metastatic CRC that had radiographically progressed on or was refractory or intolerant to prior standard therapies, including fluoropyrimidine, irinotecan, and oxaliplatin with or without an anti-VEGF antibody. Patients with 

 wild-type tumors must have received an anti-EGFR antibody, and those with a known 

 V600E mutation must have received a BRAF inhibitor.

The safety profile of the combination was generally consistent with the known profiles of the individual agents. Any-grade treatment-related adverse events (TRAEs) occurred in 95% of patients in the combination arm compared with 92% in the regorafenib arm. Grade 3 or higher TRAEs were reported in 59% of patients receiving zanzalintinib plus atezolizumab and 37% of those receiving regorafenib.

The most frequent any-grade TRAEs for the combination included diarrhea (50%), hypertension (34%), fatigue (33%), and nausea (31%). Serious TRAEs were reported in 26% of patients in the combination arm vs 10% in the regorafenib arm. AEs led to the discontinuation of all study treatments in 18% of the combination group and 15% of the regorafenib group. Fatal TRAEs in the combination arm included intestinal perforation (n=2), pneumonitis (n=1), renal failure (n=1), and altered state of consciousness (n=1).

Exelixis announces U.S. FDA acceptance of New Drug Application for zanzalintinib in combination with atezolizumab for previously treated metastatic colorectal cancer. News release. Exelixis, Inc. February 2, 2026. Accessed February 2, 2026. https://tinyurl.com/4fkupzrk

Saeed A, Park YS, Tabernero J, et al. Zanzalintinib plus atezolizumab vs regorafenib in patients with previously treated metastatic colorectal cancer: primary overall survival analysis from the randomized, open-label, phase 3 STELLAR-303 study. Presented at: European Society for Medical Oncology Congress 2025; October 17-21, 2025; Berlin, Germany. LBA30.

Hecht JR, Park YS, Tabernero J, et al. Zanzalintinib plus atezolizumab versus regorafenib in refractory colorectal cancer (STELLAR-303): a randomised, open-label, phase 3 trial.

Published online October 19, 2025. doi:10.1016/S0140-6736(25)02025-2

Articles

FDA Accepts NDA for Zanzalintinib/Atezolizumab in Pretreated Metastatic CRC

Artificial intelligence (AI) has emerged as the “connective tissue” that will facilitate oncology practice and deliver enhanced care to patients, according to Arturo Loaiza-Bonilla, MD, MSEd, FACP.

Loaiza-Bonilla, systemwide chief of Hematology and Oncology at Saint Luke’s University Health Network, spoke with CancerNetwork® about his insights regarding recent advancements for AI in oncology and provided a recap of some of the key developments with these technologies in 2025.

Loaiza-Bonilla began by discussing the application of AI in radiology scans, particularly for mammograms and early detection of cancer in lung nodules, as well as in predictive models for pancreatic cancer detection, which will enhance screening speed and efficiency and eliminate the need for double review on scans. Additionally, he cited ventures, such as ai.RECIST by Friends of Cancer Research, which aim to embed these algorithms into measurements for lesions.

He further touched upon AI’s implementation into cardio-oncology through foundational models, which will help detect cardiovascular abnormalities in patients undergoing treatment for cancers. Additionally, Loaiza-Bonilla further discussed advances in breast cancer screening, such as population-level validation, recurrence prediction models, and radiomics to determine response to therapy. Moreover, he highlighted an ability for AI to democratize pathology by providing biomarkers, even in the absence of a pathologist.

He concluded by providing his thoughts regarding AI’s evolving role in oncology, as well as a need to ensure that tools for patient and clinician use are properly regulated and vetted for accurate use and efficiency to better deliver guideline-concordant care.

CancerNetwork: How is AI being used to supplement scans conducted by radiologists?

Radiologists now, particularly in oncology, are mostly focused on 2 major trends. Mammography is one of them; [we] try to optimize times because there are many patients who require screening and [it’s a] significant amount of [time and] work. We are now using AI to assist with that, to decrease the amount of double review on those mammograms, and it’s also being run on clinical trials. We have data from Europe, but now there’s a number of efforts in the US as well, because our population is different in terms of breast density and beyond. I’m excited to see the results of those algorithms as they get deployed.

Other [trends] that we are looking [at] closely are in finding lung nodules and detecting them in real time so we can find lung cancer early through screening, even from X-rays found in the emergency department. There are some efforts doing [that]. More advancement is on the use of RECIST criteria for clinical trials. There’s an effort from Friends of Cancer Research where they are trying to do ai.RECIST criteria, where we just embed the algorithms and have been able to measure the lesions in a more effective and scalable way. Radiologists are a key part of that.

Lastly, [AI is being used in] some predictive models. There are some efforts, like the PANORAMA trial results, where they show that … CT scans can detect pancreatic cancer early.

 This is one of the diseases that we want to find them early, before they really become metastatic, as most of them are either locally advanced/resectable or metastatic. Very promising on the radiology side.

What I hope for is to start using those models in real practice. As of now, many of the models that we use in radiology have been localized to those couple use cases and for the emergency department, such as finding fractures, but now, with oncology being one of those very high stakes diseases, we have an opportunity here.

How might the inclusion of EKG AI models help facilitate cardio-oncology processes and improve outcomes for patients with cancer?

These topics are about foundational models. Foundational models mean very large data sets that include hundreds or hundreds of thousands, sometimes millions, of tests, all labeled and being built for [generalizability] to a specific use case. In this case, it could be the detection of arrhythmias or risk factors such as Qt prolongation in patients taking [tyrosine kinase inhibitors] or [adverse] effects that are emerging, particularly for patients who may have predispositions such as cardiovascular disease.

The use of EKGs in foundational models is becoming a new trend. There are several companies doing so at this moment, trying to show the FDA the validity of those tests and those foundational models. What I anticipate is, because these EKGs are so easy to use now, they’re ubiquitous, we hopefully can help to do some clearances for either potential surgeries the patients may have, or if they are on treatment, predicting the risk of having complications from the drugs that we use. It’s a combination of the EKG models plus other algorithms that are more data-driven in terms of integration with the [electronic medical record (EMR)], which are going to be helpful to really move the needle. More to follow on that; we are going to probably be hearing more in the next year or so.

What advances in breast cancer screening have been made in 2025, and what are the next steps for research and development in this area?

In breast cancer, the new steps are, first, validation at the population level. Each country and each region is doing its own clinical trials. I’m currently running for early detection with mammograms and others. We also have seen that the implementation of AI into the genomic testing, or the biomarker testing, done on our patients is becoming relevant.

There were some updates from [the San Antonio Breast Cancer Symposium] showing how a potential transformer-based architecture can predict potential recurrence in patients. It can optimize those recurrent response scores that we are seeing from different vendors in a more meaningful way, and find those niche patients that need either more screening or early detection of other things, such as germline alterations or risk factors, when we use any combination with other data sets.

In this case, for example, we can use radiomics. We know that with radiomics, we can, just by looking at a CT scan, understand if the patient is going to respond to, for example, endocrine therapy. That’s something that, for us, is mind blowing, because we did not have that information before, but now, using the data sets for many clinical trials that have been done before––the [phase 3 TAILORx trial (NCT00310180)] and others––that has been a major validation point for many of those models that are being deployed in the clinic, or at least in the clinical practice for further validation.

How might AI help democratize pathology, particularly among resource-constrained regions, and how do foundational models lead to the development of tools with better generalizability?

We are, at this moment, very short globally, not only in low- and middle-income countries, but in counties in the United States that do not have pathologists readily available to review slides and give us support. One of the things that we've seen now is with these big foundational models of millions of slides being taken, whole slide imaging pictures, we can leverage those models to look at just the H&E stain. Sometimes even without the H&E stain, just simply the slide itself can give us biomarkers. We may have the ability to get immediate readouts, but we have an algorithm deployable that is just sent by cloud and [can be] downloaded into a local computer that everyone usually has. Then it can really solve a lot of problems in terms of first screening for, for example, malignancy. Someone needs to be seen right away for additional treatment options. And we know about these deserts of cancer care where we don't have an oncologist or pathologist within 100 miles, which is crazy and even happens in the United States.

If we can use these tools at scale, where we just simply have the slide that anyone has…you simply take the picture and deploy and say, "Hey, this may have an EGFR mutation or this sample may be [estrogen receptor]/[progesterone receptor]-positive or have PL1 positivity.” It can be consequential in the use of the pathology. I believe that multidisciplinary efforts need to happen across [practices] to implement this, but the promise is tremendous.

What other advances in AI’s application to oncology do you believe will have the potential to transform practice for patients?

2026 is going to be a key year because we are seeing a signal of what I call the industrialization of AI in oncology. There are no longer services that are infrastructure embedded; even pharmaceutical companies and health systems are investing in licensing the foundational models, and training them on their own proprietary data sets and putting that into the drug discovery, traditional workflows, and Agentic AI for the final determination of steps. The idea here is to make this full loop closer together from, drug discovery to getting the drug in front of the patient. That’s the goal post now.

We are seeing discovery cycles being compressed from years to now, sometimes months, and in a few cases, weeks. That is how we are going to see an improvement. From the clinical aspect, AI is becoming more like a connective tissue in the oncology continuum. It's not about, “Should I adopt it?” It's more, “How do I adapt my workflow to the advent of AI to the benefit of my practice and my patients?” We have seen Agentic AI supporting tumor boards, clinical trial matching, and we do pathway adherence, care coordination, and embedding with guidelines in ASCO and NCCN.

It’s not replacing physicians; it’s removing friction points that are happening in that continuum. The most meaningful deployments, I believe they are not going to be flashy or press releases. It is going to be if we can reduce documentation burden, if we can accelerate triage, if we can get access to trials faster and help teams execute, that is going to be the real value that we're going to see in deployments of these tools.

Is there anything else you would like to discuss that we might not have already covered?

Something important is that we are seeing the integration of AI also for patients. We have chatGPT Health, we have Claude, and many other patient-centric approaches, which are important because a lot of patients are seeking care through those outputs. The opportunities are huge, but they need to be aligned with evidence, with safety, with workflows, and of course, we want to avoid any misinformation.

That’s why I feel there has to be clinical involvement, governance, and some guardrails, at least with specialty-driven pathways. Hopefully, that translates into what I feel are the best use cases, which are speed, access, and execution. Did it bring therapies to patients faster, or were they very informed? Can we get access to clinical trials and guideline-concordant care faster? Did my team and [I] spend more time practicing medicine and less time fighting systems? If AI helped us do those things, they have earned their place in oncology. That's how it's going to come from a peripheral technology to an interesting foundational component of our workflows.

Ai.RECIST Project: Artificial Intelligence-Enabled Response Evaluation Criteria in Solid Tumors Project. Friends of Cancer Research. Accessed January 28, 2026. https://tinyurl.com/rx26459z

Alves N, Schuurmans M, Rutkowski D, et al. Artificial intelligence and radiologists in pancreatic cancer detection using standard of care CT scans (PANORAMA): an international, paired, non-inferiority, confirmatory, observational study. 

 2026;21(1):116-124. doi:10.1016/S1470-2045(25)00567-4

Krishnamurthy S, Feng C, Muhammad H, et al. Artificial intelligence predicts OncotypeDX recurrence scores directly from H&E-stained whole slide images of ER+/HER2- node-negative breast cancer surgical sections. Presented at: 2025 San Antonio Breast Cancer Symposium; December 9-12, 2025; San Antonio, TX. PS3-06-02

CancerNetwork spoke with Arturo Loaiza-Bonilla, MD, MSEd, FACP, regarding his insights about recent advancements for AI in oncology.

Taking Stock of AI Advancements in Oncology: Present and Future

Immune System Plays “Big Role” in Multiple Myeloma Development, Care Additional translational research may help inform the design of next-generation therapies for patients with multiple myeloma, said Manoj Bhasin, PhD, MS.

Bhasin 1

, Manoj Bhasin, PhD, MS, spoke about research that he and colleagues published in 

focusing on how a single-cell atlas may characterize the bone marrow immune microenvironment among patients with multiple myeloma. Findings showed that the immune system has a broad, treatment-independent influence on multiple myeloma outcomes.

Bhasin, professor in the Department of Pediatrics and in the Department of Biomedical Informatics at Emory University School of Medicine; and director of Genomics, Proteomics, Bioinformatics and Systems Biology and the Aflac Director of the Single Cell Biology Program at Children’s Healthcare of Atlanta, outlined how to adapt these translational findings to the development of novel anti-myeloma therapies. He noted that additional comprehensive, large-scale studies are necessary to help elucidate the complexity of multiple myeloma, which may inform other next-generation treatments.

If you look at the landscape of multiple myeloma, all the risk-staging and stratification is mainly tumor genetic-[centered]. We are mainly focused on the tumor part and some clinical features, whereas the extrinsic factors like the immune system are not taken in consideration when we are stratifying the patient into high risk or standard risk. The basis for this study was to figure out [if] the immune system is playing a role in the emergence of multiple myeloma, the therapeutic response, as well as the outcome. This was one of the first comprehensive studies where we profiled more than 1.4 million cells from newly diagnosed [patients with] myeloma before they were given any therapy. This was a study to answer some of the important questions because it was built up on the Multiple Myeloma Research Foundation (MMRF) CoMMpass registry study [NCT01454297]. That is a study with 8 to 10 years of follow up on the patients with very comprehensive tumor genetics along with the clinical information to understand if the immune system plays a role in multiple myeloma. This is the study we planned 5 years back.

We learned that the immune system plays a big role in myeloma. [The] next step we need to take is compare it with other cancers because [for] other cancers, the immune system is considered as a key player in the outcomes. Then, to further make these findings more translatable and more [adapted] to designing new therapies, we need to compare them with other things like aging so that we can figure out [whether] the changes are just driven by the aging, or [if] they are cancer-specific changes. That will help us in designing next-generation therapies. We should also look at people who are coming from diverse backgrounds and diverse socioeconomic status; is that also playing a role in altering the immune system?

A lot more comprehensive, large-scale studies are needed to understand the complexity of myeloma, as well as other cancers. I look forward to people working more in this area and doing some of these studies, which will help us to understand the complexity of myeloma and design next-generation therapies.

Pilcher WC, Yao L, Gonzalez-Kozlova E, et al. A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma. 

2026;7:224-246. doi:10.1038/s43018-025-01072-4

Additional translational research may help inform the design of next-generation therapies for patients with multiple myeloma, said Manoj Bhasin, PhD, MS.

Immune System Plays “Big Role” in Multiple Myeloma Development, Care

A final analysis of the phase 3 TITAN trial reported a 35% reduction in the risk of death after a median follow up of 44 months.

Treatment with apalutamide (Erleada) exhibited a 51% reduction in the risk of death compared with darolutamide (Nubeqa) without docetaxel for the treatment of patients with metastatic castration-sensitive prostate cancer (CSPC) after 24 months of follow-up (HR, 0.49; 95% CI, 0.30-0.83; 

= .007) in a presentation given at the 36th Annual International Prostate Cancer Update (IPCU), according to a news release from the developer, Johnson & Johnson.

According to the developers, the study included a protocol pre-specified primary end point of overall survival (OS), which was designed to meet FDA guidance. Patients were identified between August 2022 and June 2025. Additionally, the OS data build upon findings from the phase 3 multinational, double-blind TITAN trial (NCT02489318).

After a median follow up of 22.7 months in the phase 3 trial, which evaluated apalutamide plus androgen deprivation therapy (ADT) vs placebo plus ADT in patients with metastatic CSPC, a 33% reduction in the risk of death was observed with apalutamide (HR, 0.67; 95% CI, 0.51-0.89; 

 A final analysis of the TITAN trial reported a 35% reduction in the risk of death after a median follow up of 44 months (HR, 0.65; 95% CI, 0.53-0.79; 

< .0001). Additionally, a 24-month OS rate of 92.1% in the real-world analysis was consistent with the 82.4% rate in the TITAN trial.

Additional findings from the trial revealed a 48-month OS rate of 65.1% among patients who initiated treatment with apalutamide at the final analysis of the TITAN trial.

“These real-world data show the survival benefit of apalutamide vs darolutamide in patients with [metastatic] CSPC without the concurrent use of docetaxel. The results are consistent with other datasets showing similar [OS] benefit vs other commonly used agents,” Mehmet Bilen, MD, director of the Genitourinary Medical Oncology Program at Winship Cancer Institute of Emory University, said in the news release.

 “This real-world analysis utilized large contemporary datasets using rigorous methodology to support clinical decision-making in the absence of prospective head-to-head studies that are likely impractical to conduct.”

In the phase 3 TITAN trial, 1052 patients with metastatic CSPC were randomly assigned to receive apalutamide (n = 525) or placebo (n = 527), with patients in the placebo arm given the option to cross over to apalutamide following unblinding of the trial.

In the experimental and placebo arms, the median age was 69 years (range, 45-94) vs 68 years (range, 43-90), and most patients in each arm had a Gleason score of more than 7 (66.9% vs 67.9%). Additionally, most patients had an ECOG performance score of 0 (62.5% vs 66.0%), high disease volume (61.9% vs 63.6%). A total of 11.0% vs 10.4% of patients received previous docetaxel, and 17.9% vs 15.0% received prior therapy for localized disease.

The dual primary end points were OS and radiographic progression-free survival (PFS). Secondary end points included time to initiation of cytotoxic chemotherapy, time to pain progression, time to chronic opioid use, and time to skeletal-related events.

Overall incidence of treatment-emergent adverse effects (TEAEs) was similar between the apalutamide, placebo, and crossover groups, with exposure-adjusted rates of TEAEs of interest per 100 patient-years of 40.0%, 22.4%, and 41.9%, respectively. Furthermore, cumulative rates of first grade 3 or 4 TEAEs and serious AEs were also similar between each group.

“Real-world comparisons can provide critical information to support patient care when conducted in a rigorous and methodologically sound manner,” Mahadi Baig, MD, MHCM, vice president of US Medical Affairs at Johnson & Johnson Innovative Medicine, concluded in the release.

 “We have now seen in repeated real-world examinations the [OS] benefit of apalutamide versus other agents and this head-to-head analysis supports apalutamide being a key standard of care treatment for patients with [metastatic] CSPC.”

Real-world head-to-head analysis shows 51% reduction in risk of death for patients with metastatic castration-sensitive prostate cancer treated with ERLEADA® (apalutamide) versus darolutamide without docetaxel through 24 months. News release. Johnson & Johnson. February 2, 2026. Accessed February 2, 2025. https://tinyurl.com/45b73b9b

Chi KN, Chowdhury S, Bjartell A, et al. Apalutamide in patients with metastatic castration-sensitive prostate cancer: final survival analysis of the randomized, double-blind, phase III TITAN study. 

 2021;39(20):2294-2303. doi:10.1200/JCO.20.03488

Real-world data presented at the 36th Annual IPCU build upon findings from the phase 3 TITAN trial evaluating apalutamide in this CSPC population.

Apalutamide Reduces Risk of Death by 51% in Metastatic CSPC

Rivoceranib plus camrelizumab achieved a median OS of 23.8 months vs 15.2 months with sorafenib alone in patients with unresectable hepatocellular carcinoma.

The FDA has accepted a new drug application (NDA) resubmission for the combination of rivoceranib and camrelizumab as a first-line systemic treatment for patients with unresectable hepatocellular carcinoma (HCC), according to a press release from the developer, Elevar Therapeutics.

 The agency has assigned a Prescription Drug User Fee Act target action date of July 23, 2026.

Previously, the NDA for this combination in the aforementioned patient population has received 2 complete response letters (CRLs) from the FDA, with the first coming in 

 The CRL issued by the FDA in May 2024 cited deficiencies related to the FDA’s inspection of the camrelizumab manufacturing facility, and in March 2025, the FDA requested more information on the treatment. The developer noted that the CRL did not identify any concerns regarding the clinical efficacy or safety of the combination therapy or the manufacturing process for rivoceranib.

“We will continue to work closely with Hengrui to ensure full readiness throughout the FDA review process, including the inspection of relevant manufacturing facilities,” stated Dong-Gun Kim, CEO of Elevar Therapeutics, in the press release. “We will also maintain proactive communication with the FDA and remain focused on achieving a successful outcome.”

The submission is supported by data from the pivotal, global, randomized, open-label phase 3 CARES-310 trial (NCT03764293), which compared the combination of rivoceranib and camrelizumab against the standard of care, sorafenib (Nexavar).

 Rivoceranib is a small-molecule tyrosine kinase inhibitor that highly selectively inhibits VEGFR-2, whereas camrelizumab is a PD-1 blocking antibody. In the study, the combination demonstrated a statistically significant and clinically meaningful improvement in the dual primary end points of overall survival (OS) and progression-free survival (PFS).

According to the trial results, the median OS for patients receiving the combination therapy was 23.8 months (95% CI, 20.6-27.2) compared with 15.2 months (95% CI, 13.2-18.5) for those treated with sorafenib (HR, 0.64; 95% CI, 0.52-0.79; 

 < .0001). The median PFS also favored the combination arm at 5.6 months (95% CI, 5.5-7.4) vs 3.7 months (95% CI, 3.1-3.7) in the sorafenib arm (HR, 0.54; 95% CI, 0.44-0.67; 

 < .0001). These survival benefits were consistent across various subgroups, including those defined by etiology and geographical region.

The CARES-310 study enrolled 543 patients who were randomly assigned 1:1 to receive either the combination or sorafenib monotherapy.

 The treatment regimen for the experimental arm consisted of camrelizumab administered at 200 mg via intravenous infusion every 2 weeks combined with rivoceranib at 250 mg taken orally once daily. In the comparator arm, patients received sorafenib at 400 mg orally twice daily.

Patient sorting and eligibility required participants to have histologically or cytologically confirmed unresectable or metastatic HCC with no prior systemic therapy. Participants were required to have at least 1 measurable lesion per RECIST v1.1, an ECOG performance status of 0 or 1, and Child-Pugh class A liver function. The primary end points were OS and PFS as assessed by a blinded independent central review, whereas secondary end points included overall response rate, duration of response, and disease control rate.

Safety findings from the CARES-310 trial indicated that the combination was generally manageable, with a profile consistent with the known toxicities of each agent. The most common grade 3 or 4 treatment-related adverse events in the combination arm included hypertension (38%), increased aspartate aminotransferase level (17%), and increased alanine aminotransferase level (13%). Palmar-plantar erythrodysesthesia syndrome was also observed in 12% of patients in the combination group. One patient each experienced treatment-related deaths in the combination regimen group and the sorafenib group, being due to multiple organ dysfunction syndrome and respiratory failure/circulatory collapse, respectively.

Elevar Therapeutics announces FDA acceptance of new drug application resubmission for rivoceranib in combination with camrelizumab as a first-line systemic treatment for unresectable hepatocellular carcinoma. News release. Elevar Therapeutics. January 30, 2026. Accessed February 2, 2026. https://tinyurl.com/35kfv6nk

Announcement on receipt of complete response letter regarding camrelizumab for injection. News release. Jiangsu Hengrui Pharmaceuticals Co Ltd. May 17, 2024. Accessed February 2, 2026. https://tinyurl.com/3kdz97k9

Heo JY. HLB, Antengene fail to gain U.S. FDA approval for liver cancer drug combo. ChosunBiz. March 21, 2025. Accessed February 2, 2026. https://tinyurl.com/3jcd2j5m

Qin S, Chan SL, Gu S, et al. Camrelizumab plus rivoceranib versus sorafenib as first-line therapy for unresectable hepatocellular carcinoma (CARES-310): a randomised, open-label, international phase 3 study. 

. 2023;402(10408):1133-1146. doi:10.1016/S0140-6736(23)00961-3

A Study to Evaluate SHR-1210 in Combination With Apatinib as First-Line Therapy in Patients With Advanced HCC. ClinicalTrials.gov. Updated February 6, 2024. Accessed February 2, 2026. https://tinyurl.com/ymndkrsp