Assessment of PSMA PET/CT derived predictive markers for <sup>177</sup> Lu-PSMA-617 treatment outcomes: Results from the U.S. Expanded-Access program.
Abstract
5079 Background: 177 Lu-PSMA-617 (Lu-PSMA) contributes to prolong progression-free survival (PFS) and overall survival (OS) in metastatic castration-resistant prostate cancer (mCRPC) patients who progressed after chemotherapy. Pretherapeutic prostate-specific membrane antigen (PSMA) PET/CT information can be used to predict Lu-PSMA therapy response patterns and outcomes, with various quantitative and visual methods proposed. We aimed to test various proposed PSMA PET/CT-derived outcome predictors in the U.S. expanded-access program (EAP) cohort. Methods: Patients enrolled in the EAP (NCT04825652) for Lu-PSMA at 3 institutions with available pretherapeutic PSMA PET/CT and outcomes were included in this analysis. Quantitative analysis was performed for all tumor lesions on PSMA PET/CT with semi-automatically contouring. Total tumor volume (TV), total tumor SUVmean, total tumor SUVmax, total lesion uptake (TLU = TV * SUVmean), total lesion quotient (TLQ = TV / SUVmean), and quantitative PSMA PET tumor–to–salivary gland ratio (qPSG: high, ≥ 1.5; intermediate, 0.5–1.5; low, ≤ 0.5) were calculated for each patient. For visual analysis, visual PSG (vPSG: high, most of the lesions showed higher uptake than the parotid glands; intermediate, neither low nor high; low, most of the lesions showed lower uptake than the parotid glands) and heterogeneity and intensity of tumors (HIT: 1, SUVmax < 15; 2, 15–79 with heterogeneous intensity; 3, 15–79 with homogeneous intensity; 4, ≥ 80) scores were used for assessment. Outcomes included a prostate-specific antigen (PSA) PFS, and OS. We evaluated the predictive performance of each model using Cox proportional hazards regression analysis and assessed their performance with the concordance index (c-index). Results: In total, 88 patients who received Lu-PSMA within the EAP between May 2021 and March 2022 were eligible and included in this analysis. For the PSA PFS, the total tumor SUVmean achieved the highest c-index of 0.678 (HR 0.91 [95% CI, 0.85–0.97], p = 0.004), followed by the total tumor SUVmax with a c-index of 0.640 (HR 0.99 [95% CI, 0.99–1.00], p = 0.034). For OS, the TLQ achieved the highest c-index of 0.658 (HR 1.01 [95% CI, 1.00–1.01], p < 0.001), followed by the total tumor SUVmean with a c-index of 0.634 (HR 0.89 [95% CI, 0.83–0.96], p = 0.004). The HIT score showed the third highest c-index of 0.632; however, when using score 1 as the reference, the HR did not exhibit a sequential trend across ordinal categories as anticipated. Conclusions: Quantitative analysis outperformed visual analysis in predicting the outcome of mCRPC with Lu-PSMA therapy in the EAP cohort. Total tumor SUVmean was identified as the most robust predictor for PSA PFS, while TLQ showed promise as a predictor for OS. Incorporating these predictors into clinical decision-making for pre-Lu-PSMA therapy could aid in patient selection and treatment planning. Clinical trial information: NCT04825652 .
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (16)
Koichiro Kimura
Ahmanson Translational Theranostics Division, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Los Angeles, CA
Vishnu Murthy
University of California, Los Angeles, Los Angeles, CA
Andrew F. Voter
Abuzar Moradi Tuchayi
University of California, San Francisco, San Francisco, CA
Surekha Yadav
Department of Radiology and Biomedical Imaging, University of California San Francisco, San Fransciso, CA
Lilja B. Solnes
Lela Theus
Department of Molecular and Medical Pharmacology Ahmanson Translational Theranostics Division David Geffen School of Medicine at UCLA, Los Angeles, CA
Andrew Thi Ai Nguyen
Department of Molecular and Medical Pharmacology Ahmanson Translational Theranostics Division David Geffen School of Medicine at UCLA, Los Angeles, CA
Vinicius Ludwig
Ahmanson Translational Theranostics Division, Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, CA
Adrien Holzgreve
Lena Unterrainer
Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Munich, Germany
Tristan Grogan
Johannes Czernin
Ahmanson Translational Theranostics Division, University of California, Los Angeles, Los Angeles, CA
Thomas A. Hope
Irbaz Bin Riaz, MD, PhD; R. Bryan Rumble, MSc; Thomas A. Hope, MD; Giuseppe Procopio, MD; and Neha Vapiwala, MD; Mayo Clinic, Phoenix, AZ; American Society of Clinical Oncology, Alexandria, VA; University of California, San Francisco, San Francisco, CA; Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy; and University of Pennsylvania Abramson Cancer Center, Philadelphia, PA
Andrei Gafita
Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
Jeremie Calais
Luca F. Valle, MD, Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA, Radiation Oncology Service, Greater Los Angeles VA Healthcare System, Los Angeles, CA, University of California Los Angeles Jonsson Comprehensive Cancer Center, Los Angeles, CA, Jeremie Calais, MD, PhD, University of California Los Angeles Jonsson Comprehensive Cancer Center, Los Angeles, CA, Department of Nuclear Medicine, University of California Los Angeles, Los Angeles, CA, Amar U. Kishan, MD, Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA, University of California Los Angeles Jonsson Comprehensive Cancer Center, Los Angeles, CA