Workgroup proposes treatment-related amyloid clearance (TRAC) as a framework to characterize patients and guide clinical management of these therapies
A breakthrough treatment in the fight against Alzheimer’s disease is a class of therapies called anti-amyloid antibodies. These monoclonal antibodies – proteins made in a laboratory intended to stimulate the immune system – have been shown to slow the progression of the disease by targeting amyloid plaques in the brain that are characteristic of Alzheimer’s.
Biomarkers, such as measures derived from PET scans that reflect amyloid plaques in the brain, were instrumental in FDA approval of anti-amyloid therapies, like lecanumab (Leqembi) and donanemab (Kisulna), and have been shown to reduce plaques in the brains of Alzheimer’s patients. Yet despite FDA approval, there is still a clinical need to better understand how to monitor the efficacy and safety of these treatments.
To this end, the Alzheimer’s Association convened a workgroup of scientists and clinicians with experience in Alzheimer’s disease, including clinical trials of anti-amyloid therapies and biomarkers, to propose a framework to characterize the response of patients receiving these treatments.
The framework was published Nov. 26 in the Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association.
“This framework identifies an individual’s response to anti-amyloid treatment and will help guide clinical management and decisions to switch treatment, or describe their current amyloid load,” said Maria C. Carrillo, PhD, Alzheimer’s Association chief science officer and medical affairs lead and senior author of the paper. “Additionally, these measures could be required for inclusion in future trials.”
The first quantitative measure
The workgroup, led by UCSF’s Renaud La Joie, PhD, has proposed using a standard called “Treatment-Related Amyloid Clearance” (TRAC) to reflect changes in the Alzheimer’s patients based on biomarker evidence for clearance of amyloid-beta deposits.
The consortium recommended defining TRAC with amyloid-positron emission tomography (Amyloid-PET) in patients with pre-treatment biomarker confirmation of cerebral amyloid-beta deposition and who were subsequently treated with an amyloid-beta targeting therapy. TRAC uses this biomarker evidence to determine the degree of plaque clearance, providing a quantitative measurement of the effect of therapies (pharmacodynamic changes), rather than using clinical symptoms as a standard.
TRAC identifies two levels of clearance of amyloid deposits:
- Full TRAC indicates that PET levels have dropped below a predetermined positivity threshold.
- Partial TRAC means that PET levels dropped significantly but remain above the threshold.
This framework is designed to be adapted over time in response to evolving biomarker and clinical advances, and with the accumulation of real-world data on patients receiving anti-amyloid therapies. The framework provides a terminology for clinicians and patients to use to describe their treatment outcomes as related to the biological evidence in the brain.
“We still have a lot to learn about what these drugs do and how they work, said guidelines first author Renaud La Joie, the Edward and Pearl Fein Endowed Professor in Precision Care for Memory Disorders at UCSF. “Even though they are being used and prescribed in the real world, there's actually a little bit of a gray area about how to handle them long-term. For example, donanemab treatment may be stopped when a patient reaches full TRAC, similar to the design of the phase 3 clinical trial.”
Plaque clearance correlates highly with symptom improvement
The clinicians and scientists in the workgroup performed a literature review of all data related to randomized clinical trials (RCT) of these therapies. Within a given trial, higher doses and longer treatment duration were associated with higher rates of full TRAC. The workgroup also found that when comparing across RCTs, those achieving high rates of participants with full TRAC were those most associated with a significant slowing of clinical decline. In contrast, trials with low full TRAC rates were not associated with significant clinical benefits.
“What we tried to do in our workgroup was to create a global framework to help develop best practices in the continued treatment of patients receiving these therapies,” said La Joie. “Since plaque clearance correlates highly with symptom improvement, it provides a standard for clinicians to follow in future trials and treatment.”
However, the relationship between amyloid-PET changes and clinical benefit has still not been established at the individual patient level and examining these relationships is a key goal of developing the TRAC framework.
“One thing that we need to emphasize is that TRAC is not about demonstrating a cure. TRAC represents a measure of the disease that is no longer detectable,” said La Joie. “While disease is still there, it’s a modified version of the disease and there will be continued cognitive decline, but at a slower pace than if they had not been treated. We think TRAC provides clinicians a way to help patients and caregivers better understand the changes in the disease state.”
The authors suggest that future studies with biomarker monitoring and assessment of clinical outcomes should specifically investigate optimal treatment regimens after TRAC. Such studies will help clarify the relevance of measuring TRAC from a personalized medicine perspective and establish if TRAC should trigger a change in patient management, for example, treatment termination or transition to maintenance dosing. Future trials may also need to incorporate plasma-based biomarkers since neither fluid biomarkers nor amyloid-PET can completely depict the whole spectrum of Alzheimer’s disease progression.
Additional Authors: Renaud La Joie, Jeffrey L. Cummings, Jeffrey L. Dage, Douglas Galasko, Milos D. Ikonomovic, Thomas K. Karikari, Susan M. Landau, Jorge J. Llibre-Guerra, Catherine J. Mummery, Rik Ossenkoppele, Julie C. Price, Shannon L. Risacher, Ruben Smith, Christopher H. van Dyck, and Maria C. Carrillo.
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