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136 Background: The ECOG performance status (PS) is a critical measure for evaluating functional capacity and determining clinical trial eligibility in patients with advanced prostate cancer. We aim to assess the capability of large language models (LLMs) to accurately infer ECOG PS from unstructured oncology notes. Methods: This retrospective study included patients with metastatic castration-resistant prostate cancer (mCRPC) receiving Lutetium-177–PSMA-617 ( 177 Lu) at the Mayo Clinic (2022-2023). Baseline ECOG PS scores were manually curated by a trained clinician from clinical notes recorded within four weeks prior to 177 Lu initiation. Structured zero-shot prompts were then used to prompt GPT-4 to infer ECOG PS scores from unstructured oncology notes. Total dataset was randomly sampled to prompt development (20%) and held-out test set (80%). Three experimental setups were employed to assess model performance: (i) utilizing unmasked clinical notes, (ii) clinical notes with only numerical ECOG PS scores masked while retaining narrative descriptive/assessment by oncologist of ECOG score, and (iii) clinical notes with both numerical scores and narrative ECOG descriptors masked. Final performance was assessed using evaluation metrics (precision, recall, F1 score) on the held-out test set. Results: A total of 240 patients (n: 50 prompt development; n: 190 test set) were included in the analysis. The median age was 70 (IQR: 66-76); a majority of patients were White (n: 229; 95%) and non-Hispanic (n: 233; 97%). The most prevalent ECOG PS score was 0 (n: 140; 58%), followed by 1 (n: 88; 37%), and 2 (n: 12; 5%). The performance was numerically higher when using unmasked notes (weighted average precision: 0.89; recall: 0.89; F1: 0.89), compared to using notes with masked scores only (weighted average precision: 0.76; recall: 0.79; F1: 0.75) and notes with both scores and narrative masked (weighted average precision: 0.57; recall: 0.53; F1: 0.48). Metrics by each ECOG PS score is outlined (Table). Conclusions: Large language models demonstrate significant potential in precisely extracting ECOG performance status from unstructured oncology notes, offering valuable support for treatment decision-making and clinical trial enrollment. However, model performance declines as reliance on implicit reporting within clinical notes increases. Future efforts focusing on prediction of ECOG using a series of notes over time will be the next step. ECOG Unmasked oncology notes ECOG Score masked only ECOG Score + ECOG narrative marked Precision Recall F1 Score Precision Recall F1 Score Precision Recall F1 Score 0 0.89 0.92 0.91 0.75 0.93 0.83 0.59 0.74 0.66 1 0.88 0.86 0.87 0.76 0.74 0.75 0.19 0.47 0.27 2 1.00 0.82 0.90 0.78 0.33 0.47 0.78 0.16 0.26

134 Background: Prostate cancer patients with visceral metastases at diagnosis are often treated using one-size-fits-all approach. For example, CHAARTED criteria treats any visceral metastasis as high volume. Therefore, we aimed to assess overall survival (OS) by site of visceral involvement in patients with metastatic PCa. Methods: Surveillance, Epidemiology, and End Results (SEER) database (2010-2021) was queried to obtain case listing data on metastatic PCa patients from 17 registries. The patients were categorized into three groups based on visceral metastasis at diagnosis: lung metastasis, liver metastasis, and others. Kaplan-Meier survival analysis was performed to estimate median OS with 95% confidence interval (CI). Log-rank test was conducted to assess if survival was significantly different among the groups. Cox proportional hazard regression analysis was performed to assess the magnitude of difference among the groups. P-value <0.05 established statistical significance. Results: This analysis included 21,007 metastatic PCa patients (lung: n=319; liver: n=123; brain: 107; bone: 20538). Metastatic PCa population with lung metastasis exhibited a median OS of 60 months (95% CI: 48-72) compared to 24 months (95% CI: 12-36) in population with liver metastases and to 36 months (95% CI: 36-36) in population with other metastases. The difference in OS among the groups was statistically significant (p < 0.001). Compared to population with lung metastasis, those with liver (HR: 1.91; 95% CI: 1.41-2.57) but not those with other metastases (1.16; 0.97-1.39) had significantly worse OS adjusting for Gleason score, PSA and race (Table). Conclusions: In metastatic PCa, patients with lung-only metastasis have significantly better overall survival and should be considered differently in prognostication to liver metastases. Consideration of site of visceral metastasis is critical for treatment intensification decisions. Limitations of this analysis include lack of accounting for confounding relationships at individual patient level. Variable Hazard Ratio (95% CI) Metastases (Lung) REFERENCE Metastases (Liver) 1.91 (1.41-2.57) Metastases (Other) 1.16 (0.97-1.39) Gleason score≥8 REFERENCE Gleason score <8 0.68 (0.64 -0.72) PSA - ng/dL 1.01 (1.00 – 1.01) Race (White) REFERENCE Race (Black) 0.99 (0.94 – 1.05) Race (Asian or Pacific Islander) 0.70 (0.64 – 0.76)

132 Background: Distant metastasis at the time of prostate cancer (PCa) diagnosis is associated with increased morbidity and mortality. This study aimed to assess the impact of sociodemographic characteristics on distant metastasis at the time of PCa diagnosis. Methods: The Surveillance Epidemiology and End Results (SEER) database (2000-2021), including PCa patients from 17 registries, was queried. Patients with late-stage diagnosis (LSD) were defined as those who were initially diagnosed with stage IV disease, indicating distant metastasis. Sociodemographic predictors included race, ethnicity, age, marital status, residential status, and median household income. Multicollinearity was assessed using variance inflation factors (VIF). Univariable logistic regression was performed to identify significant predictors of LSD, which were further analyzed in multivariable logistic regression using a maximum likelihood estimation approach. Odds ratios with 95% confidence intervals (CI) were computed with a p-value of <0.05 indicating a statistically significant association. Results: Of the 1,089,736 PCa patients diagnosed, 64,983 (6%) had an LSD. The majority were white (80%), non-Hispanic/Latino (HL) (91%), aged ≥65 years (60%), married (75%), residents in metropolitan areas (88%), and had an annual house income of ≥$70,000 (70%). Multivariable logistic regression identified Black (OR: 1.24; 95%CI: 1.22-1.27), Asian or Pacific Islander (1.35; 1.30-1.40), and American Indian/Alaska Native (1.70; 1.53-1.89) to have higher odds of LSD compared to White patients (Table). In addition, HL ethnicity compared to non-HL (OR: 1.45; 95% CI: 1.42-1.49), age ≥65 compared to <65 (1.68; 1.65-1.71), unmarried status compared to married (1.88; 1.85-1.91), residency in non-metropolitan areas compared to metropolitan (1.10; 1.07-1.12), and household income <$70,000 compared to ≥$70,000 (1.03; 1.01-1.05) had a significant association with LSD. Conclusions: Older, non-White (Black, Asian/Pacific Islander, American Indian/Alaska Native), Hispanic/Latino, unmarried men, residents of non-metropolitan areas, or those with lower annual household incomes have higher odds of late-stage diagnosis. Interventions targeting early detection in these at-risk groups may improve prostate cancer outcomes in the US. Variable Odds Ratio (95% CI) p-value Race (Black vs White) 1.24 (1.22-1.27) <0.01 Race (Asian or Pacific Islander vs White) 1.35 (1.31-1.40) <0.01 Race (American Indian/Alaska Native vs White) 1.70 (1.53-1.89) <0.01 Ethnicity (Hispanic/Latino vs non-/Hispanic/Latino) 1.45 (1.42-1.49) <0.01 Age (≥65 vs <65) 1.68 (1.65-1.71) <0.01 Marital status (unmarried vs married) 1.88 (1.85-1.91) <0.01 Residence status (non-metropolitan vs metropolitan) 1.10 (1.07-1.12) <0.01 Household income (<$70,000 vs ≥$70,000) 1.03 (1.01-1.05) <0.01

129 Background: Few studies have explored the use of focal therapies to address select sites of resistant disease in men receiving 177-Lu-PSMA-617 for metastatic castrate resistant prostate cancer (mCRPC). Our institutional practice is to offer SBRT for patients with up to 5 sites of oligoprogression or non-responding lesions while undergoing 177Lu-PSMA-617 (every 6 weeks for 6 cycles total). This is determined by PSMA or choline PET imaging during the course of 177Lu-PSMA-617. Herein, we evaluated the safety of adding target SBRT during treatment with 177Lu-PSMA-617. Methods: This retrospective single institution analysis was conducted via systematic chart review to evaluate for adverse events during or after treatment. Grading of treatment-related adverse events was conducted using Common Terminology Criteria for Adverse Events Version 5.0 (CTCAE v5). Results: Thirty-one patients receiving 177Lu-PSMA-617 with 51 sites of oligoprogressive or non-responding metastatic disease were treated with SBRT. The median number of sites treated was 1 (range 1-4). Most patients received SBRT immediately after cycle 6 (32%) or after cycle 3 or 4 (42%). Bone was the most commonly treated site of disease (90%) with the majority (54%) of bone sites being spine or sacrum, followed by lymph nodes (10%). Ultimately, 84% of patients completed all 6 cycles of 177Lu-PSMA-617 (range 4-6). The median follow-up time was 19.1 months (IQR 15.5-22.4) after 177Lu-PSMA-617 therapy start. A total of 2 patients experienced a pathologic fracture within the SBRT treatment field that could possibly be related to radiotherapy. One patient experienced a grade 2 neuropathy which may have been related to radiation therapy. Other potential adverse events are listed (Table). Conclusions: Our data demonstrates a low rate of significant toxicity with the use SBRT during treatment with 177Lu-PSMA-617. Further study is indicated to determine the oncologic efficacy and potential late side effects of this treatment strategy. Adverse events. Event All Grades Grade > 3 Any Adverse Event 104 2 Anemia 29 (94%) 0 Low Platelets 11 (35.5%) 1 (3.2%) Any Pathologic Fracture 7 (22.5%) 1 (3.2%) Possible SBRT-related Pathologic Fracture 2 (6.5%) 1 (3.2%) Bone Pain Flare 3 (9.6%) 0 Neuropathy 1 (3.2%) 0

341 Background: Specialist clinicians (oncologists, urologists, radiation oncologists) read through free text reports of prostate MRI and biopsy reports to risk stratify patients during initial consultation of localized PCa. This laborious and time-consuming process is repeated for each day during the clinic. Herein, we propose a hybrid stratification framework utilizing a combination of large language model (LLM) and rule-based programming to automate this process. Methods: This retrospective study included patients with localized PCa (2004-2024) presenting to care at Mayo Clinic with at least one positive prostate biopsy and MRI report available. The state-of-the-art LLM – GPT4 – was utilized using a structured zeroshot prompt to extract relevant phenotypic variables (clinical T stage, Gleason patterns, grade group, extent of specimen/cores involved, prostate size/volume) from unstructured MRI and biopsy reports. Using a rule-based algorithm, the extracted variables and PSA at PCa diagnosis were used to categorize each patient into one of the six NCCN risk categories (very low [VL], low [L], favorable intermediate [FInt], unfavorable intermediate [UFInt], high risk (HR), very high risk [VHR]). Prompts were iteratively developed using ~5% of the total dataset and validated on ~10% of the dataset. Final performance was assessed against a held-out expert annotated test dataset using evaluation metrics (accuracy, F1-score, precision, recall). Additionally, manual annotation was conducted by two independent novice reviewers to compare machine annotated and novice-human annotated risk categorization. Results: A total of 397 patients were included in the evaluation. The median age at diagnosis was 64.8 (IQR: 59.7-68.5); majority of the men were White (n: 366; 92%) and non-Hispanic (n: 371; 94%). The most prevalent risk category was UFint (n: 151; 38%) followed by FInt (n: 80; 20.2%), HR (n: 76; 19.1%), VHR (n: 64; 16.1%), L (21: 5.3%), and VL (n: 5; 1.3%). Novice reviewers achieved an accuracy of 79%, precision of 80%, recall of 82% and a F1-score of 0.81. The hybrid stratification framework using GPT4 achieved an accuracy of 89%, precision of 89%, recall of 88% and a F1-score of 0.88. Among 43 errors by GPT4 risk stratification, majority of the errors were due to miscategorization of clinical T-stage (n: 21; 49%) followed by erroneous number of positive cores (n: 13; 30%). However, additional evaluation showed that GPT4 achieved numerically higher performance (accuracy: 90%; precision: 91%; recall: 90%; F1: 0.90) compared to novice reviewers (accuracy: 77%; precision: 89%; recall: 77%; F1: 0.82) for ascertaining clinical T-stage. Conclusions: Large language models exhibited superior performance than novice clinicians for risk stratification in patients with localized PCa. As the next step, we intend to validate our framework for automated risk classification in a prospective manner.

184 Background: We update evidence on mHSPC when new evidence becomes available (PMID: 36862387). ARANOTE trial prompted us to assess the comparative efficacy of darolutamide (DARO) with other ARPi agents in mHSPC using the living network meta-analysis (LNMA). Methods: This LNMA is conducted using the living interactive evidence (LIvE) synthesis framework. Phase III trials assessing systemic treatments in mHSPC are included. Mixed treatment comparisons were made using a frequentist network meta-analysis. P-scores were computed to assess relative treatment rankings with higher values indicating potentially better efficacy. Results: This report of LNMA includes a total 11 trials (12628 patients; 12 unique treatment options) as of October 1 st , 2024. Overall results were consistent with prior updates. Analysis limited to the ARPi trials showed that inhigh volume, abiraterone acetate (AAP)+androgen deprivation therapy (ADT) (HR: 0.46; 95% CI: 0.40-0.53; rank 1), apalutamide (APA)+ADT (0.53; 0.41-0.68; rank 3), DARO+ADT (0.60; 0.44-0.81; rank 4) and enzalutamide (E)+ADT (0.48; 0.41-0.56; rank 2) significantly improved radiographic progression-free survival (rPFS) compared to ADT alone. No statistically significant differences were observed with DARO+ADT compared to AAP+ADT (1.30; 0.94-1.82), APA+ADT (1.14; 0.77-1.67) and E+ADT (1.24; 0.89-1.79). Inlow volume, AAP+ADT (0.48; 0.37-0.63; rank 4), APA+ADT (0.36; 0.22-0.58; rank 3), DARO+ADT (0.30; 0.15-0.60; rank 1) and E+ADT (0.32; 0.25-0.41; rank 2) significantly improved rPFS compared to ADT. E+ADT significantly improved rPFS compared to AAP+ADT (0.67; 0.47-0.96) in low volume. No statistically significant differences were observed with DARO+ADT compared to AAP+ADT (0.62; 0.30-1.30), APA+ADT (0.83; 0.36-1.92) and E+ADT (0.93; 0.45-1.94). In synchronous disease, AAP+ADT (0.58; 0.51-0.67; rank 4), APA+ADT (0.49; 0.39-0.62; rank 2), DARO+ADT (0.59; 0.44-0.79; rank 3) and E+ADT (0.42; 0.36-0.50; rank 1) significantly improved rPFS compared to ADT. E+ADT significantly improved rPFS compared to AAP+ADT (0.73; 0.59-0.89) in synchronous disease. In metachronous disease, DARO+ADT (0.34; 0.17-0.67; rank 1), APA+ADT (0.41; 0.22-0.77; rank 2) and E+ADT (0.44; 0.35-0.57; rank 3) significantly improved rPFS compared to ADT. No statistically significant differences were observed with DARO+ADT compared to APA+ADT (0.83; 0.33-2.08) and E+ADT (0.76; 0.37-1.57) in metachronous disease. The results were consistent for overall survival. Conclusions: Current evidence suggests no significant differences for darolutamide as compared to other ARPi agents. Enzalutamide may be preferred over AAP in low-volume or synchronous disease. Given similar efficacy, choice of ARPi requires careful consideration of patient-specific factors including cost, accessibility and toxicity.

16 Background: In PSMAfore (NCT04689828), [ 177 Lu]Lu-PSMA-617 ( 177 Lu-PSMA-617) prolonged rPFS versus androgen receptor pathway inhibitor (ARPI) change in taxane-naive adults with PSMA-positive metastatic castration-resistant prostate cancer (mCRPC) progressing once on an ARPI. Baseline circulating tumor DNA (ctDNA) fraction was associated with rPFS at the second interim analysis (IA) of OS (ASCO 24). Here, we assessed the association of baseline and cycle 2 day 1 (C2D1) ctDNA fraction, and early ctDNA and prostate-specific antigen (PSA) dynamics, with rPFS and OS at the third IA of OS. Methods: Patients were randomized 1:1 to 177 Lu-PSMA-617 (7.4 GBq Q6W; x6) or ARPI change. Endpoints included rPFS (primary) and OS (key secondary). Plasma ctDNA fraction was analyzed at baseline and at C2D1 using an in-house custom panel. Cox regression (adjusted for 3 risk classes based on clustering of 17 baseline clinical features) and random forest (adjusted for 15 baseline clinical features) modeling were used to assess the association of ctDNA fraction and PSA with clinical outcomes at the Feb-27-2024 data cutoff. Results: Patients with plasma samples at baseline and C2D1 were included ( 177 Lu-PSMA-617, n/N = 82/234; ARPI change, n/N = 91/234). Cox regression models adjusted for clinical features in the 177 Lu-PSMA-617 arm showed that higher ctDNA fraction was associated with shorter rPFS and OS (Table). These associations were stronger for C2D1 than baseline, both when comparing individual models and within a model including both timepoints (Table). In random forest models including clinical features and C2D1 ctDNA fraction, the total area under curves were not improved by addition of baseline ctDNA fraction (rPFS, 0.87; OS, 0.86). In the overall population, fractional decreases from baseline to C2D1 in ctDNA ( p = 0.0015) and PSA ( p < 0.0001) were strongly associated with longer rPFS, and were weakly correlated with one another (correlation coefficient, 0.26). In the 177 Lu-PSMA-617 arm, fractional decrease in ctDNA ( p = 0.002) was more strongly correlated with OS than was decrease in PSA ( p = 0.12). Conclusions: This exploratory analysis suggested that C2D1 ctDNA fraction was more strongly associated than baseline ctDNA fraction with rPFS and OS. Early ctDNA fraction dynamics contributed additional information in the prediction of rPFS and OS beyond PSA dynamics alone. Clinical trial information: NCT04689828 . Cox regression models. a rPFS OS Baseline model, HR (95% CI); p 6.0 (1.6–23.0); 0.0095 12.0 (3.0–48.7); 0.00052 C-index ± SE 0.69 ± 0.04 0.75 ± 0.04 C2D1 model, HR (95% CI); p 47.7 (10.1–226.0); < 0.0001 82.7 (16.4–417.0); < 0.0001 C-index ± SE 0.72 ± 0.03 0.77 ± 0.03 Baseline + C2D1 model Baseline, HR (95% CI); p 3.1 (0.7–14.0); 0.14 2.1 (0.4–12.7); 0.41 C2D1, HR (95% CI); p 35.9 (7.2–180.0); < 0.0001 52.5 (7.6–362.0); < 0.0001 C-index ± SE 0.72 ± 0.03 0.79 ± 0.03 a HRs correspond to 1 unit change in ctDNA fraction.

61 Background: 177 Lu-PSMA-617 was approved in March 2022 for patients with mCRPC pretreated with an androgen receptor pathway inhibitor (ARPI) and a taxane. There are limited data on the effectiveness of treatments post- 177 Lu-PSMA-617. The aim of this study was to describe prostate-specific antigen (PSA) responses among patients with mCRPC receiving a guideline-recommended therapy as the next therapy after 177 Lu-PSMA-617 treatment. Methods: This retrospective, observational study used real-world data from the PRECISION data platform, a proprietary dataset developed by Novartis, comprised of patient-level electronic health record and claims data that represent the US advanced prostate cancer population in the community, academic, urology, and medical oncology settings. Patients with mCRPC who received any guideline-recommended therapy at least 14 days after treatment with 177 Lu-PSMA-617 between March 23, 2022 and July 31, 2024 were included. Guideline-recommended therapies included abiraterone, enzalutamide, darolutamide, apalutamide, cabazitaxel, docetaxel, pembrolizumab, sipuleucel-T, niraparib, olaparib, talazoparib, rucaparib, and radium-223. Patients’ PSA values while on 177 Lu-PSMA-617 treatment were compared with their PSA values during the subsequent therapy course. Proportions of patients achieving reductions in PSA levels ≥50% (PSA50) and ≥80% (PSA80) were estimated. All analyses were descriptive. Results: A total of 152 patients receiving any subsequent guideline-recommended therapy after 177 Lu-PSMA-617 were identified. Mean age was 72.1 years. Most patients received an ARPI (n=93, 61.2%) – abiraterone (n=38), enzalutamide (n=37), darolutamide (n=10), or apalutamide (n=8) – as their subsequent therapy. Of patients who received a taxane (n=42, 27.6%), 24 received cabazitaxel and 18 received docetaxel. Median time to initiation of subsequent therapy was 206 days (interquartile range [IQR] 101–301 days) from 177 Lu-PSMA-617 initiation and 44 days (IQR 17–119 days) from 177 Lu-PSMA-617 discontinuation. Overall, among patients with sufficient information for PSA evaluation (n=30), 46.7% achieved PSA50 and 40.0% PSA80 post- 177 Lu-PSMA-617. Among patients receiving an ARPI, PSA50 was observed in 11/18 (61.1%) and PSA80 in 10/18 (55.6%). Among patients receiving a taxane, PSA50 and PSA80 were seen in 3/12 (25.0%) and 2/12 (16.7%), respectively. Conclusions: In this real-world analysis, the majority of patients who received guideline-recommended therapies after 177 Lu-PSMA-617 achieved at least a PSA50 response, suggesting that 177 Lu-PSMA-617 treatment does not preclude response to other subsequent therapies.

59 Background: There are several real-world data sources for prostate cancer (PC), each with its own limitations; the most notable limitation is an incomplete picture of the multidisciplinary clinical management of PC. The PRECISION data platform, the largest, most comprehensive, and continually updated real-world evidence source on patients with advanced PC to date, tries to address this limitation and shed light on PC management in both urology and oncology practices in both academic and community settings in the US. The platform includes a wide variety of PC-specific data variables among patients with metastatic hormone-sensitive PC (mHSPC) and metastatic castration-resistant PC (mCRPC) treated across the US. This study aims to provide an overview of the characteristics, treatment patterns, and clinical outcomes among patients with mHSPC and mCRPC included in PRECISION to date. Methods: A retrospective cohort study that included patients with a diagnosis of mHSPC or mCRPC (index date) in PRECISION between 2018 and 2024 (cohorts could overlap). For each cohort, patient characteristics and treatment patterns were evaluated descriptively. Results: The PRECISION platform currently includes 72,855 and 33,538 patients with mHSPC and mCRPC, respectively. Among the mHSPC cohort, the mean ± standard deviation (SD) age was 74.5±9.4 years; 67% and 33% were treated at oncology and urology centers, respectively; 40% and 60% were from academic and community settings, respectively. The average ± SD time from mHSPC to mCRPC was 11.2±11.7 months. Overall, 77.6% of patients were treated with androgen-deprivation therapy (ADT), of whom 64.7% had ADT combined with androgen receptor pathway inhibitors (ARPIs) including abiraterone acetate, enzalutamide, and apalutamide. Among the mCRPC cohort, the mean ± SD age was 74.1±9.3 years; similar treatment setting patterns as mHSPC were observed. Overall, 74.6% initiated a first-line (1L) therapy on/after mCRPC diagnosis; 52.1% had 1L ARPIs, 16.2% 1L immunotherapy, and 4.6% 1L taxane chemotherapy. In addition, 2.2% of patients received the recently US FDA-approved therapy, lutetium-177 vipivotide tetraxetan, at some point during their mCRPC disease duration. Conclusions: This analysis provides key insights into the patients included in the PRECISION data platform. This multidisciplinary dataset provides a 70/30 split between oncology and urology centers, and a 40/60 split between academic and community settings. The observed clinical profile, treatment patterns, and outcomes comprise the most comprehensive representation of current treatment practice in the US. Future analyses of clinical outcomes with existing and novel therapies could contribute significantly to our understanding of opportunities to improve the treatment of patients with mHSPC and mCRPC in the US.

56 Background: The broad therapeutic arsenal for mCRPC, with overlapping indications, makes selecting the optimal treatment sequence challenging in clinical practice. The aim of this study was to evaluate the prostate-specific antigen (PSA) responses and overall survival (OS) among patients with mCRPC receiving 177 Lu-PSMA-617 based on prior ARPI and taxane treatment exposure. Methods: This retrospective, observational study used real-world data from the PRECISION data platform, a harmonized dataset of advanced prostate cancer patients in the US from diverse clinical settings. Patients with mCRPC who had received ≥1 dose of 177 Lu-PSMA-617 between March 23, 2022 and July 31, 2024, after prior treatment with ≥1 ARPI and ≥1 taxane, were included. To assess PSA response, the baseline PSA value obtained within 90 days before starting 177 Lu-PSMA-617 was compared with the on-treatment PSA value obtained ≥28 days after 177 Lu-PSMA-617 initiation. The number of patients achieving PSA reductions ≥50% (PSA50) and ≥80% (PSA80) were estimated, with patients classified into two cohorts based on prior ARPI and taxane exposure: (1) prompt cohort: after only 1 ARPI and 1 taxane, and (2) deferred cohort: >1 ARPI and/or >1 taxane. Patient characteristics and treatment patterns were evaluated descriptively. OS from 177 Lu-PSMA-617 initiation was estimated using Kaplan–Meier methodology. Results: A total of 431 patients were included: 177 patients in the prompt cohort and 254 patients in the deferred cohort. Of patients in the deferred cohort, 185 (72.8%) received ≥1 ARPI and 1 taxane, 32 (12.6%) received 1 ARPI and ≥1 taxane, and 37 (14.6%) received ≥1 ARPI and ≥1 taxane. Median (interquartile range age was 73 (67–78) years and most demographic characteristics were balanced between groups. Patients in the deferred cohort had higher median PSA levels at baseline (63.1 ng/mL vs 25.2 ng/mL). PSA50 was observed in 18/33 (55%) patients in the prompt cohort vs 28/66 (42%) in the deferred cohort. PSA80 was observed in 13/33 (39%) patients in the prompt cohort vs 21/66 (31%) in the deferred cohort. Across both cohorts, median OS was 18.0 months (95% confidence interval [CI]: 15.1 months–not reached [NR]). Median OS was NR in patients in the prompt cohort vs 15.1 months in patients in the deferred cohort (95% CI: 11.6 months–NR). Conclusions: In this large real-world study, prompt initiation of 177 Lu-PSMA-617 (after only 1 ARPI and 1 taxane) showed superior clinical outcomes versus deferred initiation of 177 Lu-PSMA-617. Patients were more likely to achieve a PSA reduction ≥50% and ≥80% and had longer OS with prompt initiation of 177 Lu-PSMA-617. These results may help to guide treatment sequencing in clinical practice.