A Flexible Algorithm for a Variable Disease: Treating Pheochromocytoma and Paraganglioma

Endocrine News speaks with Camilo Jimenez, MD, about his JCEM paper “Approach to the patient with metastatic pheochromocytoma and paraganglioma: advances in systemic therapy” that focuses on treating a patient with pheochromocytomas and paragangliomas, its complexity, and his team’s algorithm that created a novel approach to guiding treatment decisions.

Pheochromocytomas and paragangliomas (PPGLs) are all treated as having metastatic potential, despite the fact that three quarters of PPGLs remain localized, because clinicians currently have no biochemical or other markers to predict PPGL behavior. The TNM staging system uses primary tumor size and anatomical location to predict metastatic spread, but it remains incomplete. Meanwhile, several new therapies (e.g., radioligands, tyrosine-kinase inhibitors, systemic and targeted therapies) have emerged that avoid some of the toxicity of cytotoxic chemotherapy with cyclophosphamide, vincristine, and dacarbazine (CVD), but PPGL heterogeneity complicates decisions about what to use and when.

While the means to clinically characterize these neuroendocrine tumors continues to evolve, Camilo Jimenez, MD, and team from the Department of Endocrine Neoplasia and Hormonal Disorders at the University of Texas MD Anderson Cancer Center, in Houston, have developed a treatment algorithm that can help fill some gaps in the meantime. In “Approach to the patient with metastatic pheochromocytoma and paraganglioma: advances in systemic therapy,” published in JCEM in February, they explore new advances in treatment, present a case highlighting the complexity of treating PPGLs, and unveil their algorithmic framework that integrates clinical phenotype and tumor genotype as a novel approach to guiding treatment decision-making.

Algorithm in Practice

The algorithm classifies patients into one of four groups based on molecular profile, then subclassifies them by rate of disease progression, and finally offers first- and second-line treatment options or entry into clinical trials. The patient they describe in the paper exemplifies how it can be put to use, especially when disease evolves and changes. In 2020, a 67-year-old man presented with progressive fatigue, abdominal pain, hypertension, palpitations, and headaches over several weeks and was eventually diagnosed with a paraganglioma syndrome type 4. His large primary tumor was unresectable at presentation due its highly vascular location, and CVD chemotherapy was therefore selected over other therapies to shrink it for future resection, after which the patient was disease free for two years.

The recurrent tumor exhibited different characteristics, warranting an adjusted management approach and emphasizing the need to repeat functional imaging. Although the patient’s disease was deemed incurable, it was no longer classified as rapidly progressing. Radiopharmaceutical therapy with lutetium-177-DOTATATE was initiated to avoid the toxicity associated with other therapies possible in this scenario; however, it required intensive care unit admission to administer.

“I understand that we have limitations. But the point is that people in other places can start thinking in a more sophisticated way about these complex tumors, similar to other cancers, where we need to focus on molecular pathways and tumor origin to make progress.” – Camilo Jimenez, MD, Department of Endocrine Neoplasia and Hormonal Disorders, University of Texas MD Anderson Cancer Center, Houston

Some symptoms temporarily improved; others grew worse. Enter newly U.S. Food and Drug Administration–approved belzutifan. On this convenient, oral medication, the patient has experienced sustained improvement ever since. Belzutifan is now listed as a potential  first option for patients with pheochromocytoma characterized by pseudohypoxia. Although his case does not follow the algorithm exactly, says Jimenez, “that’s because of the historical timing of when each therapy became available, not because the algorithm was wrong for him.”

But the algorithm not only provides an important resource in the absence of clinical guidelines for how to approach systemic therapy, it also helps democratize treatment, and such accessibility is a big part of why Jimenez and team developed it. In fact, Jimenez participates on the European Society for Medical Oncology (ESMO) guideline panel for PPGLs and knows firsthand how complicated treatment can be. “The algorithm is a very useful way to guide how to treat patients with pheochromocytoma and paraganglioma, but I have to recognize that in most countries around the world, people won’t easily be able to apply all of it,” he explains.

To illustrate this point, Jimenez points to how the algorithm is ordered, which reflects U.S. conditions specifically. Although considered first line in certain circumstances, belzutifan is not yet universally available. “For the first time, we have a therapy for this disease that’s approved by multiple regulatory agencies around the world, but can I generalize that to the rest of the world?” he asks. “No.” The same goes for the molecular subtyping that is a cornerstone of the algorithm; it is not universally available due to lack of equipment and technology as well as because of costs.

Global Implications

Nevertheless, the beauty of the algorithm comes down to its practicability; it can help clinicians think through the full set of options and their respective trade-offs available to them rather than defaulting to chemotherapy with its many adverse effects. “Here are the options,” says Jimenez, “use the most optimal one in terms of efficacy, safety, and toxicity available to you and depending on patient and tumor characteristics.” Thus, in some lower-resource settings, chemotherapy remains the most realistic option, not because it is the best choice for every tumor, but because it is often the only accessible one. “So, the algorithm is designed with everybody around the world in mind: Base the decision on rate of progression, think about the molecular origin of the tumor, and look for the best option that’s actually obtainable in that setting.”

Indeed, Jimenez describes the paper as a contribution to the Endocrine Society but with reach far beyond the United States, even while some of the algorithm’s assumptions do not align with all practices, as one colleague pointed out. Jimenez counters that, saying “I understand that we have limitations. But the point is that people in other places can start thinking in a more sophisticated way about these complex tumors, similar to other cancers, where we need to focus on molecular pathways and tumor origin to make progress.”

This perspective has landed well in the field, so much so that Jimenez was specifically invited by JCEM to submit this paper after a talk he gave at ENDO 2025 that generated many audience questions and a lot of interest. “I was honest with the audience: I told them that a lot of published data in this field has real limitations, and that we have to be careful, because these decisions affect patient care, so we need data that’s as strong as possible.” He again points to belzutifan, which is a selective small-molecule inhibitor of the protein hypoxia-inducible factor 2α (HIF2α) approved in 2025 for PPGL treatment after 25 years of development. “It’s a lovely medication, but we still need to do more work,” says Jimenez. “It doesn’t work for everyone, it doesn’t cure the disease, but it works for some patients for some time. It’s not the final answer; it’s the beginning of finding better answers.”

“This is an orphan disease, so it’s very difficult to recruit a large enough population for a phase 3 trial, and it would require many countries working together. It’s not impossible, but it would take a long time, and it’s difficult to fund.” – Camilo Jimenez, MD, Department of Endocrine Neoplasia and Hormonal Disorders, University of Texas MD Anderson Cancer Center, Houston

As to wider adoption of the algorithm and what that would take, Jimenez is honest and realistic. “This is an orphan disease, so it’s very difficult to recruit a large enough population for a phase 3 trial, and it would require many countries working together. It’s not impossible, but it would take a long time, and it’s difficult to fund,” he says. “One of my very senior co-authors, who has real expertise in this area, felt strongly that we needed to just say plainly how things actually are. I agreed, and we included the algorithm to open the door for people to think more broadly. I don’t think that’s a bad thing.”

Back to the patient, “we know belzutifan won’t cure him, and it may eventually stop working,” says Jimenez, “so we always have to be thinking about what local options exist next, which is exactly the idea behind the algorithm. Tumors’ underlying biology may be the same no matter where in what country they occur, but patients’ individual situations are very different. This paper is really focused on inclusivity, being mindful of how diverse the patient population is around the world, while still offering practical guidance for how to think about treating these patients wherever they are.”

Horvath is a freelance writer based in Baltimore, Md. In the August issue, she wrote “Realizing the Promise: Artificial Intelligence in Endocrinology” based on the ENDO 2026 session, “Artificial Intelligence in Endocrinology: Practical Uses, Lessons Learned, and What Comes Next.”