Integration of PSMA-Targeted Theranostics into Multidisciplinary Care for Improved Efficiencies and Patient Care
The widespread success of <sup>177</sup>Lu-PSMA-617 for prostate cancer has generated unprecedented volume in theranostics. Prostate-specific membrane antigen-targeted theranostics is possibly the most complex program in nuclear medicine, requiring interpretation of prostate-specific membrane antigen PET according to specific criteria, incorporating laboratory tests, and on-treatment imaging to guide patient management. Adding to the complexity, these patients often have aggressive disease biology, toxicities from multiple failed therapies, and significant comorbidities. This combination of complexity and growing number of patients has created the critical need for efficient integration of theranostics into regular practice. We describe here the key components of our evolving program and protocols that have improved patient care delivery within our health system. At the core of the program is the establishment of a dedicated multidisciplinary team and regular conference to provide a forum to discuss challenging cases and issues. The creation and distribution of guidelines for imaging and laboratory criteria are critical for streamlining care so that cases are properly selected for further discussion.
Authors
- Phillip H. Kuo (ORCID: https://orcid.org/0000-0002-4957-8298)
- Kathleen A. Burns (ORCID: https://orcid.org/0000-0002-0470-166X)
- Alex Chehrazi‐Raffle (ORCID: https://orcid.org/0000-0001-5205-4527)
- Sandy Liu (ORCID: https://orcid.org/0000-0001-8478-4540)
- Charles B. Nguyen (ORCID: https://orcid.org/0000-0002-1898-5501)
- Erasmus Poku
- Maria Parayno
- Tanya Barauskas Dorff (ORCID: https://orcid.org/0000-0001-5990-298X)
- Abhishek Tripathi
- Ngot-Swan Chong
- Dave Yamauchi
- Benjamin S. Gerendash
- H. Susan
Institutions
- City Of Hope National Medical Center (US)
Publication Details
- Journal
- Journal of Nuclear Medicine Technology
- Published
- 2025-09-30
- DOI
- https://doi.org/10.2967/jnmt.125.270053
- Citations
- 1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.50