Citations

392 Background: Cancer-associated fibroblasts (CAFs) are a major component of the tumor microenvironment, exerting both tumor-promoting and tumor-restrictive effects, and in some cases, dual roles. CAFs are heterogeneous and have been implicated in tumor progression, metastasis, and therapeutic resistance. Recent translational evidence suggests the existence of at least two CAF subtypes: CAV1+ CAFs and FAP+FN1+ CAFs. The clinical utility of subclassifying CAFs in prostate cancer remains undefined. In this study, we aimed to examine the correlation of CAF subtypes in localized prostate cancer with Decipher genomic classifier (GC) scores, Grade Group (GG), and the presence of adverse pathological features (APF). Methods: We retrieved de-identified transcriptomic and pathological data from 55,329 radical prostatectomy (RP) samples tested with the Decipher prostate genomic classifier (Veracyte, San Diego, CA) between 2016 and 2024, available through the GRID registry (NCT02609269). A subset of 855 patients (META855 cohort) treated with RP was utilized for outcomes analyses. CAF subtypes were defined based on the expression of key biomarkers (FN1, FAP, and CAV1), normalized to total CAF estimates. Correlation analyses and multivariable Cox regression models were performed to evaluate the association of CAF subtypes with GC scores, GG, APF. Metastasis-free survival (MFS) estimates were generated using Kaplan–Meier methodology. Results: FAP and FN1 normalized expressions were highly correlated (r=0.61) and weakly correlated with CAV1 suggesting that they represent two distinct subtypes of CAF. Samples with high expression (top 25%) of FN1 (FN1+) and FAP (FAP+) were enriched with very high Decipher (> 0.85, VHD) and GG4-5. As such, 37% and 32% of FAP+ were VHD and GG4-5 respectively compared to ~18% for low FAP(low 25%). While for FN+ 33.9% were VHD, and 31.5% GG4-5. Patients with FAP+FN1+, 42.5% and 37.1% were VHD, and had GG4-5. Samples with high CAV1 (CAV1+) were associated with lower rate of VHD (15.5%) or GG4-5 (20.8%) compared to low CAV1 (35.4% for VHD and 24.5% for GG4-5). When evaluating VHD in FAP+FN1+CAV1- subgroup, 58% were VHD compared to 6.4% in FAP-FN1-CAV1+. The 5-year MFS was 78% in FAP+FN1+CAV- compared to 96% in FAP-FN1-CAV1+ (p<0.01). When evaluating the biological implications of FAP+FN1+, we found that FAP and FN1 expression is highly correlated to angiogenesis and EMT pathways, radiation sensitivity signature (PORTOS). Conclusions: FAP+FN1+CAV- is a unique subset of CAFs that is associated with aggressive prostate cancer behavior. Our findings may lay the foundation for future efforts to modulate CAFs in localized prostate cancer with existing therapeutics targeting FAP or FN1.

382 Background: Androgen receptor signaling drives prostate cancer (PC) progression, and genes involved in androgen production, uptake, and conversion (APUC) are key therapeutic targets. We previously defined a 6-APUC gene set ( HSD3B1, HSD3B2, CYP3A43, CYP11A1, CYP11B1, and CYP17A1 ), that identified metastatic PC with favorable prognosis and predict docetaxel benefit. However, the expression landscape and clinical relevance of APUC genes have not been interrogated in localized PC. Methods: We analyzed the expression of 21 APUC genes in 55,329 radical prostatectomy tumor samples that underwent Decipher prostate genomic classifier (GC) testing (Veracyte Inc) between 2016-2024. Baseline clinical/pathologic factors were retrieved from Decipher GRID database (NCT02609269). Associations between gene expression quartiles with PathoGenomic Risk Factors (PGRF) including Very High Decipher score >0.85 (VHD), Grade Group (GG) 4-5, LNI and SVI were examined. Associations with distant metastatic (DM) outcomes and metastasis free survival (MFS) were evaluated using logistic regression in Mayo545 and Cox regression in Meta855 RP cohorts, respectively. Results: High expression of SRD5A2 was associated with favorable PGRF (lower odds ratio (OR), p<0.0001), lower rate of development of DM (OR 0.36, p<0.05), and longer MFS (Hazard ratio (HR) 0.51, p<0.05). HSD17B6 showed similar results for PGRF (lower OR, p<0.0001), DM (OR 0.58, p<0.05) and longer MFS (HR 0.39, p<0.05) despite being associated with GG4-5 and SVI+ in samples with VHD. In contrast, high expression of SRD5A3 and HSD17B10 had high OR for PGRFs (p<0.0001). High expression of SLCO2B1 , an androgen uptake gene, had the strongest association with GG4-5 and SVI/LNI (p<0.001 for both). We noted that SRD5A2 lacked correlation with SRD5A1 and SRD5A3 , which instead correlated with each other. Compared to all APUC genes, SRD5A2 had limited correlations with almost all APUC genes, including ones that exhibited robust cross correlation with each other . Similar to our prior finding, most APUC genes demonstrated negative correlation with AR expression and AR activity signatures. Key outcomes were validated based on transcriptomic data from 492 samples from TCGA database. Conclusions: Comprehensive analysis of 21 APUC genes in over 55,000 PC identified distinct, context-dependent associations with metastatic outcomes and clinical and molecular risk factors. Notably, high SRD5A2 expression was associated with lower odds of high-risk features and metastatic outcomes, whereas SRD5A1 and SRD5A3 linked to adverse outcomes, suggesting critical yet divergent roles among 5-alpha-reductase family members. These findings underscoring androgen-metabolic heterogeneity and highlighting SRD5A2 as a potential biomarker of indolent biology in localized prostate cancer.

369 Background: MRI-guided transurethral ultrasound ablation (TULSA) uses MRI to target, monitor, and control thermal ablation of prostate tissue with high intensity directional ultrasound, demonstrating favorable histologic control and preservation of genitourinary function in single-arm studies [1,2]. CAPTAIN (NCT05027477) is a post-market, multi-center randomized controlled trial (RCT) of TULSA vs RARP for intermediate-risk prostate cancer, and is the first such study to meet its enrolment target. Here we compare baseline patient characteristics, treatment parameters, and periprocedural outcomes. Methods: CAPTAIN enrolled men with treatment-naïve, organ-confined, Grade Group 2 or 3 prostate cancer at 23 centers including academic and private clinics in the USA (20), Canada (2), and Finland (1). Patients were randomized 2:1 to TULSA or RARP, without crossover. Endpoints include pad-free urinary continence (EPIC) and erections sufficient for penetration (IIEF Q2) at 1 year, salvage treatment at 3 years, and survival to 10 years. Periprocedural metrics include length of stay, blood loss, catheter time, and 30-day patient diary (EQ-5D-5L, NRS pain score). Results: 211 patients were treated from Jan 2022 to Aug 2025 (70% TULSA, 30% RARP), surpassing the enrolment target of 201. Arms had similar baseline characteristics: median (IQR) age for TULSA vs. RARP was 63 (58–68) vs 65 (60–69) years (p=0.12), PSA was 6.5 (4.9–9.6) vs 7.2 (5.6–9.7) ng/mL (p=0.63), Grade Group 2/3 proportions were 76%/24% vs 77%/23% (p=0.88). RARP involved bilateral, unilateral, or no nerve sparing in 89%, 5.7%, and 5.7% of cases. TULSA ablation plans included whole-gland (68%) and ≥hemi-ablation (32%). Median (IQR) blood loss was lower during TULSA vs RARP: 0 (0–0) vs 100 (100–200) mL (p<0.001). Hospital stay was shorter for TULSA: 0.29 (0.27–0.32) vs 1.24 (1.12–1.36) days (p<0.001). Catheter duration was longer post-TULSA: 13 (11–15) vs 8 (8–10) days (p<0.001). Patients reported lower NRS pain scores after TULSA to post-operative day 6, and less decline in overall health on the EQ-5D-5L 0-100 visual analog scale over 30 days (p<0.05). Fewer patients reported extreme inability on EQ-5D-5L after TULSA vs RARP over the first month for mobility (0% vs 15%), self-care (1% vs 18%), and usual activities (18% vs 38%) (all p<0.05). Conclusions: CAPTAIN is the first multicenter RCT comparing ablation to radical prostate cancer treatment to meet its enrollment target. Early perioperative results from CAPTAIN demonstrate that TULSA had no blood loss or overnight hospitalization, reduced post-procedural pain, and faster return to baseline activities and overall health. Data collection to 1 and 3 years post-treatment continues to readout of the primary safety and oncological outcomes. [1] Klotz et al 2021, JUrol 205(3):769-779. [2] Eggener et al 2024, UrolOnc 42:S83. Clinical trial information: NCT05027477 .

360 Background: Adding NHT to androgen deprivation therapy (ADT) improves survival in mCSPC, but their comparative impact on patient-reported QoL and time to deterioration (TTD) across FACT-P domains remains underexplored. Methods: MEDLINE and Embase were systematically searched from each database’s inception through August 21, 2025, to identify Phase III trials assessing NHT treatment in mCSPC. Time to FACT-P (total, physical, emotional, functional, and social/family well-being) deterioration across trials with the latest follow up were extracted. Hazards ratios (HRs) and 95% confidence intervals (CIs) were pooled and mixed treatment comparisons were made using network meta-analysis. P-scores were computed; a higher score indicated better QoL. Results: A total of 4 trials (12 references) with 4,037 patients met the inclusion criteria with median follow up ranging from 14.4 months to 30 months. Median time to QoL deterioration ranged from 11.4 to 12.9 months. In terms of FACT-P overall, darolutamide (DARO)+ADT (HR: 0.76; 95% CI: 0.62-0.93), abiraterone acetate (AAP)+ADT (0.85; 0.73-0.98) significantly improved TTD as compared to ADT alone. DARO+ADT was associated with significant improvement in TTD when compared to APA+ADT (0.75; 0.56-0.98). In terms of FACT-P social/family wellbeing, DARO+ADT significantly improved TTD when compared to AAP+ADT (0.75; 0.57-0.96), and ADT (0.79; 0.64-0.98). Likewise, ENZA+ADT significantly improved TTD when compared to AAP+ADT (0.77; 0.63-0.95), APA+ADT (0.88; 0.61-0.99) and ADT (0.82; 0.70-0.95). However, there was no statistically significant difference between DARO+ADT and ENZA+ADT. In terms of FACT-P physical wellbeing, AAP+ADT was associated with statistically significant improvement in TTD when compared to APA+ADT (0.66; 0.52-0.83), ENZA+ADT (0.74; 0.61-0.90), and ADT (0.75; 0.65-0.87). In terms of FACT-P functional wellbeing, DARO+ADT was associated with statistically significant improvement in TTD when compared to ADT (0.78; 0.63-0.96). The ranking analysis is showed in Table. Conclusions: Novel hormonal therapies significantly delay QoL deterioration in mCSPC, particularly across overall, emotional, and functional domains. Domain-specific analyses suggest darolutamide may preserve social/family and functional well-being, while abiraterone favors physical well-being. Rank table. Rank (P-score) FACT-Ptotal FACT-Psocial/family FACT-Pphysical FACT-Pfunctional FACT-Pemotional AAP+ADT 2 (0.73) 5 (0.18) 1 (0.98) 2 (0.62) 3 (0.52) APA+ADT 5 (0.17) 4 (0.22) 5 (0.07) 4 (0.33) 4 (0.52) DARO+ADT 1 (0.90) 1 (0.88) 2 (0.68) 1 (0.92) 2 (0.66) ENZA+ADT 3 (0.50) 2 (0.84) 4 (0.36) 3 (0.52) 1 (0.67) ADT 4 (0.18) 3 (0.38) 3 (0.42) 5 (0.11) 5 (0.13)

357 Background: Prostate cancer (PCa) is the most incident cancer in adult males in the United States, and the second highest in the world. CTCAE is the standardized method to grade the severity of treatment-related adverse events (AEs), but are tedious to collect and subject to inter-observer variability. This study aimed to evaluate the performance of LLMs in automatically extracting and grading CTCAE toxicities from clinical notes and patient-reported outcomes of PCa patients from a clinical trial. Methods: A total of 55 patients from NCT02874014 trial, undergoing proton therapy (PT) for localized PCa, were included. The ground truth of CTCAE graded toxicities was obtained from the trial’s results. Clinical notes within 3 days, and the most recent patient questionnaires within 90 days of toxicity assessment were retrieved from the electronic health record. A comprehensive prompt was developed to extract and CTCAE grade toxicities from the retrieved records. LLMs used for this analysis were OpenAI GPT-4o and Gemini 2.0 Flash. Phase 1 evaluated both LLMs' performance against the ground truth. To ensure the metrics reflected the models’ performance based only on the information available in the text provided, cases where both LLMs contradicted the ground truth were manually reviewed. Phase 2 recalculated LLMs' performance metrics using this adapted ground truth. A conservative stepwise ensemble model was developed to leverage the complementary strengths of both LLMs. Results: In the conservative stepwise ensemble model, Gemini 2.0 Flash served as the initial screening platform to identify AEs in step 1. All cases with identified toxicity events were then reviewed and confirmed using OpenAI GPT-4o in step 2. This effectively reduced false positive rates while preserving high sensitivity. The ensemble model achieved strong performance metrics: binary accuracy (0.954), sensitivity (0.961), specificity (0.953), F1 score (0.836), and grade accuracy (0.932). Conclusions: This study demonstrates the feasibility of the use of LLMs for extraction and CTCAE toxicity grading in PCa patients treated with RT. The ensemble model achieved strong performance metrics. Further validation is needed for other cancer diagnosis and treatment modalities. Phase Model Binary Accuracy Precision Sensitivity Specificity F1 Score Grade Accuracy 1 Gemini 0.946 0.672 1.000 0.939 0.804 0.919 1 OpenAI 0.940 0.785 0.637 0.978 0.703 0.895 2 Gemini 0.956 0.735 1.000 0.950 0.848 0.927 2 OpenAI 0.954 0.917 0.679 0.991 0.780 0.903

352 Background: Glucagon-like peptide 1 (GLP1) receptor expression in prostate cancer tissue has raised concerns that GLP1 receptor agonists (GLP1A) may influence tumor growth or progression. We compared prostate cancer severity at diagnosis among patients receiving GLP1A versus other glucose lowering therapies. Methods: A retrospective chart review identified patients who received GLP1A or alternative second-line glucose lowering agents (DPP4/SGLT2 inhibitors) and were subsequently diagnosed with prostate cancer. Patients receiving both drug classes were excluded. Baseline demographics (race, ethnicity, age), comorbidities (diabetes, myocardial infarction, peripheral vascular disease) concomitant medications (insulin, metformin, statins), appointments (within past year) and laboratory values (HbA1c, eGFR) at therapy initiation were recorded. Primary outcomes included Gleason grade group and metastatic presentation within three months of diagnosis. Propensity score matching balanced baseline characteristics between groups. Mann-Whitney U tests compared grade groups. Chi-square tests compared metastatic presentation, reporting odds ratios (OR) with 95% confidence intervals (CI). Multivariable logistic regression identified predictors of grade group (low-grade: 1-2; high-grade: ≥3) and metastatic presentation, reporting OR with 95% CI. A p value <0.05 indicated a significant association. Results: Of 260 propensity-matched patients (GLP1A: 130, comparison: 130), 87% were White and 95% were Non-Hispanic/Non-Latino in each group. Median HbA1c was 7% (IQR: 6.4-8) in GLP1A group versus 7.5% (6.2-8.5) in comparison group. Median eGFR was 75mL/min/1.73m 2 (IQR: 61.5-90.0) in GLP1A group versus 60.0 (52.0-80.5) in comparison group. High-grade disease occurred in 33 (25%) GLP1A patients and 37 (29%) comparison patients. Among patients with available imaging (GLP1A: 40; comparison: 32), metastatic presentation occurred in 7 (18%) GLP1A group and 7 (22%) comparison group patients. No significant differences were observed in grade group (GLP1A median: 2; IQR: 1-2 vs. comparison median: 2; 1-3; p=0.44) or metastatic presentation (OR: 1.32; 95%CI: 0.41-4.25; p=0.64) between groups. In multivariable analysis, higher HbA1c was associated with high-grade disease in GLP1A group (OR: 1.83; 95%CI: 1.07-3.35; p=0.03) while higher eGFR was associated with low-grade disease in the comparison group (0.97; 0.93-0.99; p=0.04). Conclusions: GLP1A use was not associated with prostate cancer grade or metastatic presentation at diagnosis compared to alternative glucose-lowering agents. However, the association between elevated HbA1c and high-grade disease in GLP1A patients suggests a potential impact of poor glycemic control on tumor biology. Prospective studies are needed to elucidate the relationship between metabolic dysregulation and prostate cancer severity.

32 Background: PET-based radiopharmaceuticals targeting prostate-specific membrane antigen (PSMA) have become the mainstay of prostate cancer imaging; however, high urinary radioactivity from these primarily renally cleared compounds may obscure tumors in the prostate and peri-ureteric regions. We conducted the first intra-patient comparator study to assess the urinary radioactivity of two 18 F-labelled PSMA-PET radiopharmaceuticals, 18 F-piflufolastat and 18 F-flotufolastat. Methods: This multicenter, prospective, intra-patient comparator study (NCT06604442) enrolled men ≥ 18 years with low PSA (≤ 0.5 ng/mL) biochemical recurrence of prostate cancer ≥ 6 months after radical prostatectomy with undetectable PSA post-surgery, scheduled for a standard-of-care (SoC) 18 F-piflufolastat PET. Patients had a SoC PET/CT after IV 18 F-piflufolastat (target dose 333 MBq), and a second PET/CT 1–10 days later after IV 18 F-flotufolastat (target dose 296 MBq), both scans started approximately 60 min after administration and used the same scanner. The primary endpoint was the difference in urinary bladder radioactivity (mean standardized uptake value [SUV mean ]) between 18 F-piflufolastat PET and 18 F-flotufolastat PET. Secondary endpoints included patient and region-level detection rates (DR) for each radiopharmaceutical. Images were interpreted by two blinded central readers, with a third to resolve disagreements, allowing majority read results. Results: Between Oct 2024 and Jun 2025, 55 patients (mean PSA, 0.28 [range 0.09–0.50] ng/mL) were included in the primary efficacy analysis. Median bladder SUV mean was significantly higher with 18 F-piflufolastat (29.0; interquartile range [IQR], 18.9–40.8) than 18 F-flotufolastat (10.9; IQR, 6.0–18.5) with a median difference of 15.1 (IQR, 8.5–27.0; p<0.001 [Wilcoxon signed-rank test]). The patient-level DR was 27.3% (15/55) for 18 F-piflufolastat and 45.5% (25/55) for 18 F-flotufolastat (majority read). Among the 21 patients with very low PSA levels (≤ 0.2 ng/mL), 38.1% had a positive 18 F-piflufolastat scan compared with 52.4% for 18 F-flotufolastat scans (majority read). Regional and sub-regional DRs are shown in the table. Conclusions: In this intra-patient study, 18 F-flotufolastat showed significantly lower urinary radioactivity, and a higher overall DR than 18 F-piflufolastat indicating it may offer improved image assessment in regions close to the bladder. Clinical trial information: NCT06604442 . Region 18 F-Piflufolastat DR* n (%)N=55 18 F-Flotufolastat DR*n (%)N=55 Prostate bed 6 (10.9) 10 (18.2) Vesicourethral anastomosis 1 (1.8) 4 (7.3) Retrovesical 2 (3.6) 2 (3.6) Remnant seminal vesicles/ lateral surgical margin 2 (3.6) 4 (7.3) Pelvic lymph nodes 8 (14.5) 9 (16.4) Majority read. *≥ 1 PET positive lesion.

27 Background: Validated homozygous loss detection is becoming increasingly important in clinical practice, with prostate NCCN guideline inclusion of BRCA1/2 loss (often portending durable PARP inhibitor benefit) and multi-tumor trials of PRMT5 and MAT2A inhibitors ongoing (biomarker: MTAP loss). Homozygous losses are challenging to detect and require intentional NGS assay design and validations. Using an FDA-approved NGS assay, we evaluated the most frequent losses identified in metastatic prostate cancer, evaluated prognostic associations on ARPI, and prevalence before and after ARPI treatments. Methods: This study used the nationwide (US-based) de-identified Flatiron Health-Foundation Medicine Prostate Cancer clinico-genomic database (FH-FMI CGDB), originating from approximately 280 US cancer clinics (~800 sites of care). Patients with metastatic prostate cancer and tissue tumor genomic testing by FoundationOne CDx were eligible for analysis. Alteration prevalence was compared between non-sequential groups of specimens obtained from patients naïve to ADT and ARPI, naïve to ARPI but not ADT, or exposed to any ARPI. Outcome analyses adjusted for: ECOG performance score, age, baseline PSA, and socioeconomic status. To limit immortal time confounding, outcome analyses were restricted to patients with specimens tested prior to initiation of ARPI. Results: 1990 specimens from 1984 unique patients met criteria for assessment. The most common losses and respective ADT & ARPI naïve vs ADT exposed & ARPI-naïve vs ARPI-exposed prevalence were PTEN (17.1% vs 24.8% vs. 33.5%, p < 0.001), FAS (2.4% vs 5.0% vs 5.8%, p = 0.003), BRCA2 (4.2% vs 3.2% vs. 2.8%, p = 0.36), RB1 (1.6% vs 3.0% vs 3.5%, p = 0.062), and TP53 (2.3% vs 2.3% vs 4.4%, p = 0.064). 227 patients had tissue specimens obtained and NGS results reported prior to initiation of ARPI. Sufficient patients with PTEN loss were present for nominal outcome associations, observing less favorable time to next treatment (HR: 1.81, 95%CI: 1.24 – 2.65, p = 0.002) and overall survival (HR: 1.65, 95%CI: 1.02 – 2.65, p = 0.040) from the initiation of ARPI. In the mHSPC (ADT and ARPI naïve) setting, 17.1% had PTEN loss, 32.8% had an HRR gene alteration, and 2.8% had both. Conclusions: Our results are consistent with homozygous losses of certain genes, notably PTEN , potentially being acquired resistance alterations to ARPI. Prostate cancer trials often do not specify timing of specimen acquisition relative to treatment initiation. For trials like IPATential-150 or CAPItello-280 that evaluate AKT inhibitors in post-ARPI setting, patients with PTEN status determined by archival tissue could be false negatives and reduce power of analysis in biomarker(+) group. Our results underscore the importance of clinical context, especially prior treatment exposures, when interpreting biomarker prevalence.

162 Background: Clinical trial conduct in advanced prostate cancer has changed dramatically with the continued development of new imaging approaches, molecular phenotypes and genetic subtypes, prognosis assessments, and effective therapies across a range of disease states. This created a need to redefine terminology and best practices for clinical trials. Methods: We convened PCWG4, an international expert committee of multidisciplinary working groups, between 2016 and 2025 to update and expand PCWG2-3 recommendations based on emerging evidence and clinical trial data in an innovative biomarker and imaging context to provide guidance for clinical trial design, eligibility, and endpoint assessments. Results: PCWG4 redefines terminology around disease states and prior therapies in a patient-centric context, considering imaging modalities, with a particular focus on PET-defined disease. New recommendations are provided for disease state terminology, defining eligibility criteria, imaging and non-imaging-based responses. We define delay/prevent endpoints including responses by pathology, ctDNA, circulating tumor cells, and PSA declines, and specify intervals for re-assessments including imaging, biomarker assessments, and patient reported outcomes. We propose new imaging-specific rPFS criteria including guidance with serial PSMA PET/CT imaging (Table). We provide recommendations in a biomarker-based context for the indication, reflective of patient benefit for specific interventions. We emphasize the need for development of validated PET imaging and molecular and phenotypic criteria as well as trial designs to appropriately risk stratify patients, predict and assess benefit, and measure post-treatment outcomes reliably in a trial framework. Conclusions: PCWG4 expands guidance on patient and tumor profiling, as well as therapy development, to include both androgen deprivation therapy sensitive and resistant settings, reflecting today’s more heterogeneous and diverse patient population to optimize outcomes. PCWG4-defined radiographic progression by imaging modality for patients with metastatic disease. Pretreatment Scan On-treatment Scan #1(≥week 8) On-treatment Scan #2 All Subsequent Scans Bone scintigraphy Comparator Comparator for subsequent scansPOD never called here POD:PCWG3 criteria (2+2 additional new lesions) POD:≤5 new lesions: PCWG3 criteria 2 new lesions confirmed≥6 new lesions CT/MRI Any measurable disease Comparator PCWG3/RECIST PCWG3/RECIST PCWG3/RECIST PSMA PET Bones, and lymph nodes and lung metastases (non-RECIST qualifying by + on PET only) Comparator POD:≤5 new lesions: 2 new lesions confirmed on a subsequent scan≥6 new lesions Same as prior Same as prior Liver and non-pulmonary viscera Comparator POD:Any single new lesion that represents disease Same as prior Same as prior

160 Background: To our knowledge, no tools are available to guide care in oligometastatic prostate cancer (omPC). Here, we leveraged individual patient-level data pooled from 8 randomized trials in the X-Met collaboration to construct CEREBRO, a tool for predicting patient-specific responses to various treatment scenarios. Methods: Patients with omPC from the STOMP, ORIOLE, SABR COMET, EXTEND continuous ADT, EXTEND intermittent ADT, ARTO, RADIOSA, and RAVENS trials were included. 6 patients (1%) with missing data were excluded. Treatment scenarios were defined as active surveillance (AS), metastasis-directed therapy (MDT), systemic therapy (ST), or MDT+ST. To account for varying baseline hazards, Weibull models were fit for overall survival (OS); progression-free survival (PFS); and castration-resistance free survival (CRFS) for patients with hormone-sensitive disease. Endpoint definitions were harmonized per X-Met framework. Results: Of 600 patients included (treatment scenarios: AS=50; MDT=153; ST=172; MDT+ST=225), 405 (67%) had hormone-sensitive omPC. With median follow-up of 38 months, median PFS, CRFS, and OS of all patients were 18, 70, and 84 months. In order of relative contribution, inputs for predicting outcomes were: treatment scenario, stage, prostate-specific antigen annotated by ADT status, metachronous vs synchronous presentation, imaging type, number of metastases, hormone sensitivity, and age. The model for each endpoint showed robust fit, calibration, superiority against the null model (per the likelihood ratio test), and risk stratification (Table). Median PFS times for model-defined low-, intermediate-, and high-risk strata were 46 months, 18 months, and 7 months ( p <0.0001). In addition, the PFS and OS models also showed strong discrimination via c index and a large interval of risk probabilities with additive clinical utility per decision-curve analysis (Table). A public webpage will be made available to facilitate prospective trial stratification, patient counseling for patient-specific outcome predictions for each potential treatment scenario, and forecasts comparing outcomes between treatment scenarios. Conclusions: CEREBRO is a high-performance tool, trained on robust prospective data from 8 randomized trials with routinely collected clinical variables, for predicting risk and treatment outcomes in omPC. Given the uncertainties in optimal timing of MDT and combination with ST, this tool has been built to facilitate current decision making. External validation is planned. Model summary. Endpoint C index (95% CI) Calibration Likelihood ratio p Risk strata p Net clinical utility observed between thresholds PFS 0.72 (0.70-0.75) 1.04 <0.0001 <0.0001 0.2-1.0 CRFS 0.63 (0.60-0.70) 1.01 0.02 0.004 0.2-0.5 OS 0.81 (0.76-0.86) 1.01 <0.0001 <0.0001 0.05-1.0