Validation of Prognostic and Predictive Models for Therapeutic Response in Patients Treated with [(177)Lu]Lu-PSMA-617 Versus Cabazitaxel for Metastatic Castration-resistant Prostate Cancer (TheraP): A Post Hoc Analysis from a Randomised, Open-label, Phase 2 Trial
- Author(s)
- Gafita, A; Martin, AJ; Emmett, L; Eiber, M; Iravani, A; Fendler, WP; Buteau, J; Sandhu, S; Azad, AA; Herrmann, K; Stockler, MR; Davis, ID; Hofman, MS;
- Journal Title
- European Urology Oncology
- Publication Type
- Online publication before print
- Abstract
- BACKGROUND: Prognostic models have been developed using data from a multicentre noncomparative study to forecast the likelihood of a 50% reduction in prostate-specific antigen (PSA50), longer prostate-specific antigen (PSA) progression-free survival (PFS), and longer overall survival (OS) in patients with metastatic castration-resistant prostate cancer receiving [(177)Lu]Lu-PSMA radioligand therapy. The predictive utility of the models to identify patients likely to benefit most from [(177)Lu]Lu-PSMA compared with standard chemotherapy has not been established. OBJECTIVE: To determine the predictive value of the models using data from the randomised, open-label, phase 2, TheraP trial (primary objective) and to evaluate the clinical net benefit of the PSA50 model (secondary objective). DESIGN, SETTING, AND PARTICIPANTS: All 200 patients were randomised in the TheraP trial to receive [(177)Lu]Lu-PSMA-617 (n = 99) or cabazitaxel (n = 101) between February 2018 and September 2019. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Predictive performance was investigated by testing whether the association between the modelled outcome classifications (favourable vs unfavourable outcome) was different for patients randomised to [(177)Lu]Lu-PSMA versus cabazitaxel. The clinical benefit of the PSA50 model was evaluated using a decision curve analysis. RESULTS AND LIMITATIONS: The probability of PSA50 in patients classified as having a favourable outcome was greater in the [(177)Lu]Lu-PSMA-617 group than in the cabazitaxel group (odds ratio 6.36 [95% confidence interval {CI} 1.69-30.80] vs 0.96 [95% CI 0.32-3.05]; p = 0.038 for treatment-by-model interaction). The PSA50 rate in patients with a favourable outcome for [(177)Lu]Lu-PSMA-617 versus cabazitaxel was 62/88 (70%) versus 31/85 (36%). The decision curve analysis indicated that the use of the PSA50 model had a clinical net benefit when the probability of a PSA response was ≥30%. The predictive performance of the models for PSA PFS and OS was not established (treatment-by-model interaction: p = 0.36 and p = 0.41, respectively). CONCLUSIONS: A previously developed outcome classification model for PSA50 was demonstrated to be both predictive and prognostic for the outcome after [(177)Lu]Lu-PSMA-617 versus cabazitaxel, while the PSA PFS and OS models had purely prognostic value. The models may aid clinicians in defining strategies for patients with metastatic castration-resistant prostate cancer who failed first-line chemotherapy and are eligible for [(177)Lu]Lu-PSMA-617 and cabazitaxel. PATIENT SUMMARY: In this report, we validated previously developed statistical models that can predict a response to Lu-PSMA radioligand therapy in patients with advanced prostate cancer. We found that the statistical models can predict patient survival, and aid in determining whether Lu-PSMA therapy or cabazitaxel yields a higher probability to achieve a serum prostate-specific antigen response.
- Keywords
- Lu-PSMA; Nomogram; Predictive models; Prostate-specific membrane antigen positron emission tomography; Theranostics
- Department(s)
- Cancer Imaging; Medical Oncology
- Publisher's Version
- https://doi.org/10.1016/j.euo.2024.03.009
- Open Access at Publisher's Site
https://doi.org/10.1016/j.euo.2024.03.009- Terms of Use/Rights Notice
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Creation Date: 2024-07-09 04:06:19
Last Modified: 2024-07-09 04:14:02