Bryce, Alan H.

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.

155 Background: Primary results from the randomized, multicenter, open-label, phase 3 TRITON3 (NCT02975934) study of rucaparib, a poly(ADP-ribose) polymerase inhibitor (PARPi) in patients with chemotherapy-naive mCRPC and BRCA1/2 (BRCA) vs the control arm of physician’s choice of DTX or ARPI (abiraterone acetate [ABI] or enzalutamide [ENZ]) demonstrated that rucaparib significantly improved radiographic progression-free survival (rPFS, primary efficacy endpoint) vs physician’s choice. Here, we report final OS and safety results from TRITON3. Methods: Patients with disease progression after 1 prior second-generation ARPI in any setting were randomized 2:1 to rucaparib 600 mg BID or physician’s choice of DTX, ABI, or ENZ (control). OS was a key secondary endpoint tested initially in the BRCA subgroup, followed by the intent-to-treat (ITT) population in an ordered step-down multiple-comparisons procedure. Crossover from placebo to rucaparib was allowed after radiographic progression was confirmed by independent radiology review. Results: As of March 1, 2024 (final analysis data cutoff),patients with BRCA (N = 302) and ATM (N = 103) alterations were randomized (ITT, N = 405). After an overall median follow-up of 44.0 months, median OS in the BRCA subgroup in the rucaparib arm was 23.2 months vs 21.2 months for the physician’s choice control arm (HR, 0.91 [95% CI, 0.68–1.20]; P = 0.5044; Table). Hierarchical testing did not continue due to lack of statistical significance. No OS benefit was observed in the ITT population or ATM subgroup (Table). Median duration of treatment in rucaparib and physician’s choice arms was 8.3 and 5.1 months, respectively. The most frequent any-grade treatment emergent adverse event (TEAE) in the rucaparib (n = 270) and physician’s choice (n = 130) arms was asthenia/fatigue (61.5% and 63.1%, respectively). The most frequent grade ≥3 TEAE was anemia (23.7%) with rucaparib, and asthenia/fatigue (9.2%) with physician’s choice. Of the 135 patients in the physician’s choice arm, 77 patients had radiographic progression and 70 crossed over to rucaparib. Conclusions: Rucaparib remains the only PARPi to show improved rPFS vs a DTX-containing control arm and has a similar OS even when most patients cross over to rucaparib. Safety was consistent with prior reports. These data support rucaparib as a treatment option for patients with BRCA-mutated mCRPC. Clinical trial information: NCT02975934 . Median OS at final analysis. Group Rucaparib, n Physician's choice, n Rucaparib, months Physician's choice, months HR (95% CI) a BRCA 201 101 23.2 21.2 0.91 (0.68–1.20) ITT 270 135 22.8 21.7 0.99 (0.78–1.26) ATM 69 34 18.4 22.1 1.21 (0.77–1.90) a Calculated by stratified Cox proportional hazard model.

Indications for and implications of germline genetic testing (GGT) in patients with prostate cancer have expanded over the past decade, particularly related to precision therapies and management. GGT has become the standard of care for many cancers such as breast, ovarian, colorectal, pancreatic, and metastatic prostate cancer, and it is imperative that patients be offered timely and equitable access to testing as it can inform patient-physician shared decision making for management of the current cancer as well as anticipatory guidance for disease progression. Additionally, GGT guides screening for and prevention of secondary malignancies for the patient and cascade testing for at-risk family members. Here, we present data supporting the notion that clinicians should offer all patients with prostate cancer the opportunity to undergo comprehensive GGT for pathogenic germline variants known to be associated with familial cancer and/or known to have implications for treatment and management.

AbstractCurrent US clinical practice guidelines for advanced prostate cancer management contain recommendations based on high‐level evidence from randomized controlled trials; however, these guidelines do not address the nuanced clinical questions that are unanswered by prospective trials but nonetheless encountered in day‐to‐day practice. To address these practical questions, the 2024 US Prostate Cancer Conference (USPCC 2024) was created to generate US‐focused expert clinical decision‐making guidance for circumstances in which level 1 evidence is lacking. At the second annual USPCC meeting (USPCC 2024), a multidisciplinary panel of experts convened to discuss ongoing clinical challenges related to 5 topic areas: biochemical recurrence; metastatic, castration‐sensitive prostate cancer; poly [ADP‐ribose] polymerase inhibitors; prostate‐specific membrane antigen radioligand therapy; and metastatic, castration‐resistant prostate cancer. Through a modified Delphi process, 34 consensus recommendations were developed and are intended to provide clinicians who manage prostate cancer with guidance related to the implementation of novel treatments and technologies. In this report, the authors review the areas of consensus identified by the USPCC 2024 experts and evaluate ongoing unmet needs regarding translational application of the current clinical evidence.

4591 Background: EV-302 and CheckMate 901 demonstrated significant survival benefit with enfortumab vedotin-pembrolizumab (EVPembro) and gemcitabine-cisplatin-nivolumab (GemCisNivo) as 1L therapy, respectively, in patients (pts) with la/mUC. However, whether these treatments are cost-effective or not remains unclear. Methods: A three-state Markov model (progression-free, progression and death) was developed. State utilities were derived from published literature. State transition probabilities were informed from point-probabilities and hazard ratios for OS and PFS obtained from the latest follow-up of eligible trials. Average sales price (2024 USD) for individual treatments (excluding ancillary charges) were obtained from the center of medicare and medicaid services (US payer’s perspective). Treatment strategies were modeled in accordance with the dose/schedule reported in the eligible trials. Pts who received GemCis or Gem-carboplatin (GemCarbo) and did not progress were modeled to receive Avelumab maintenance. Half-cycle corrected costs and utilities were accrued over a 10-year lifetime horizon and were discounted at 3%. Monte Carlo simulation was used to estimate quality adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). A willingness-to-pay threshold (WTP) of 100,000$ per QALY was used. Results: In cisplatin-eligible pts, GemCisNivo demonstrated a 0.8 QALY gain over GemCis at an ICER of 21,127 ($/QALY). GemCisNivo was also associated with an incremental net monetary benefit (INMB) of 63,099$ relative to GemCis. EVPembro demonstrated a 2.4 QALY gain over GemCis at an ICER of 915,283 and a 1.6 QALY gain over GemCisNivo at an ICER of 1,406,308. In cisplatin-ineligible pts, EVPembro demonstrated a 2.4 QALY gain over Gem-carboplatin (GemCarbo) at an ICER of 934,761. Price threshold analyses demonstrated that EVPembro is likely to be cost-effective at a cost of 12,344$ for cisplatin-eligible and 13,374$ per cycle for cisplatin-ineligible pts (original cost: 35,665.60$ per cycle). Sensitivity analysis using a total of 12 cycles for EVPembro showed cost-effectiveness at an ICER of 69,594 relative to GemCisNivo in cisplatin-eligible pts, and at an ICER of 53,099 relative to GemCarbo in cisplatin-ineligible pts. Conclusions: In terms of US payer’s perspective, GemCisNivo is most likely to be cost-effective in cisplatin-eligible pts at the WTP of 100,000 $/QALY. Limiting the number of cycles for EVPembro may render it as a cost-effective 1L treatment in la/mUC pts regardless of cisplatin-eligibility status.

e17059 Background: It is unclear if patients with different HRR gene-mutated mCRPC derive consistent benefit from treatment with PARPi and API combination. Approval labels for PARPi+API are inconsistent across regulatory bodies in the US (Food and Drug Administration, FDA) and Europe (European Medical Agency, EMA), adding to confusion among practicing clinicians. Therefore, we aimed to assess the differential efficacy of PARP+API therapy by different genes using up-to-date trial evidence. Methods: We maintain a living meta-analysis on mCRPC treatments that is updated when new data becomes available. Here, we report data from phase III randomized control trials (RCTs) assessing PARPi+API in 1L mCRPC. The outcomes of interest included radiographic progression-free survival (rPFS) and overall survival (OS). Hazard ratios (HR) for rPFS and OS by different genes were summarized using random effects meta-analysis via inverse variance approach. Results: We have screened 27376 references since the inception of this living review. Here, we report data from three trials (15 references) with a total of 1618 patients. Frequently reported HRR gene mutations in the included trials were BRCA2 (35%), ATM (21%), CDK12 (12.2%), CHEK2 (12.2%), BRCA1 (4.6%), and PALB2 (3.4%). In terms of rPFS, statistical benefit was observed in BRCA (0.28; 95% CI: 0.13-0.59) and CDK12 (0.58; 95% CI: 0.35-0.95) subgroups, whereas no statistically significant benefit was seen in PALB2 (0.53; 95% CI: 0.21-1.32), ATM (0.93; 95% CI, 0.57-1.53), and CHEK2 (0.92; 95% CI: 0.53-1.61) subgroups. For OS, benefit was observed in BRCA (0.47; 95%CI: 0.31-0.71) subgroup. While not statistically significant, a signal of meaningful OS benefit was observed in PALB2 (0.33; 95%CI: 0.10-1.16) but no OS benefit was observed in ATM (0.97; 95% CI: 0.57-1.67), CDK12 (0.80; 95% CI: 0.36-1.78), and CHEK2 (0.81; 95% CI: 0.37-1.75) subgroups. Conclusions: Current results show that mCRPC patients with BRCA and CDK12 alterations had delayed disease progression with PARPi+API as 1L therapy. BRCA mutations are also associated with improved OS, while patients with CHEK2 and ATM derived no significant benefit with PARPi+API combination. [Table: see text]

5006 Background: The PRESTO trial (NCT03009981) showed that in patients with biochemically relapsed prostate cancer following radical prostatectomy with a PSA doubling time of ≤ 9 months and without evidence of metastatic disease by conventional imaging, intensified androgen receptor blockade for 52 weeks (androgen deprivation therapy [ADT] plus apalutamide [Apa], or ADT plus Apa and abiraterone acetate [Abi] plus prednisone) prolonged PSA progression-free survival compared to ADT alone (Aggarwal et al, JCO 2024). Here we report the HRQOL results. Methods: HRQOL measures included the Hot Flash Related Daily Interference Scale (HFRDIS), Expanded Prostate Cancer Index Composite (EPIC)-26 Sexual domain, PROMIS Fatigue Short Form and EQ-5D-5L, which assesses overall HRQOL in the 504 randomized patients. Published minimally important difference thresholds for these HRQOL measures are: HFRDIS 1.66 points, EPIC Sexual 10-12, PROMIS Fatigue 3-5, and EQ-5D-5L 0.06. General linear mixed modeling was used to estimate between-arm mean differences in HRQOL according to an intent-to-treat approach. Results: Mean changes from baseline to end of treatment (EOT) for each arm and for each HRQOL measure are summarized in Table. No statistically significant mean difference was reported between intensified androgen receptor blockade (Arm B, Arm C) vs ADT alone (Arm A) in any HRQOL measure. Further, numerical differences across arms for all HRQOL measures are below published minimally clinically important difference thresholds. Conclusions: Intensified androgen receptor blockade with Apa or Apa/Abi added to 52 weeks of ADT improves PSA progression-free survival without negatively affecting HRQOL. These HRQOL results add further support to intensification of androgen blockade in patients with high-risk biochemically recurrent prostate cancer. Clinical trial information: NCT03009981 . [Table: see text]

e16619 Background: Should patients (pts) with MIBC receive aIO given the DFS benefit seen in AMBASSADOR and CheckMate 274 trials is an important clinical question. Thus, we aimed to quantify the magnitude of absolute benefit across different subgroups to aid clinicians in shared decision-making with their patients. Methods: Phase III trials evaluating aIO as compared to observation or placebo (obs/plac) in pts with MIBC were considered eligible. Outcomes of interest included DFS and OS. Pre-specified subgroups included disease location, PDL1 status, neoadjuvant chemotherapy (NAC) receipt, and tumor and nodal (TN) staging. Pairwise comparisons were made using a DerSimonian-Lairds (DL) random-effects meta-analysis. Stratified baseline risks (obtained from clinical trials) and relative effect estimates were used to estimate corresponding intervention risks (CIRs). The difference in CIRs and baseline risk was calculated to present absolute risk differences (ARDs) in each subgroup category. Results: Analysis included three trials with 2220 pts (pembrolizumab, nivolumab, and atezolizumab assessed in each). No significant difference was observed in OS with aIO compared to obs/plac (hazard ratio: 0.91; 0.76-1.09). However, aIO significantly improved DFS compared to obs/plac (0.76; 0.64-0.91) in the overall population. In pts with bladder/lower tract disease, aIO improved DFS compared to obs/plac (0.72; 0.56-0.92); however, no significant difference was observed in DFS in pts with upper tract disease. There was a statistically significant effect modification by disease location (p: 0.01). Adjuvant IO significantly improved DFS in PDL1- (0.78; 0.64-0.94) but not in PDL1+ pts (0.75; 0.52-1.08). Likewise, aIO significantly improved DFS in pts who received NAC (0.69; 0.53-0.90) but not in pts who did not receive NAC (0.89; 0.75-1.05). In terms of TN staging, aIO improved DFS in T2-3N0 (0.73; 0.57-0.94), T4N0 (0.76; 0.61-0.95), and in T2-4N1 patients (0.75; 0.59-0.95). No statistically significant modifications were observed among these subgroups. Stratified ARDs for DFS by each subgroup are outlined (Table). Conclusions: When delayed disease progression is a vital consideration, a risk-adapted strategy for the optimal patient selection to receive aIO should be considered. Disease location (lower tract/bladder), node positivity, and receipt of NAC emerged as groups likely to derive greater benefit with aIO. [Table: see text]

e16579 Background: Recent results from EV 302 and CheckMate 901 have transformed the treatment landscape of untreated locally advanced/metastatic urothelial cancer (Ia/mUC). Here, we present the most up-to-date evidence of comparative efficacy and safety of first line (1L) treatment options in Ia/mUC with emphasis on Enfortumab vedotin (EV)-pembrolizumab (P) and gemcitabine (Gem)-cisplatin (Cis)-nivolumab (N). Methods: This living systematic review used the living interactive evidence (LIvE) synthesis framework. Full-text and abstract publications of phase II/III randomized clinical trials comparing 1L immunotherapy combined with chemotherapy (IO+C) or immunotherapy alone (IO) regimens with platinum-based chemotherapy (Plat) in Ia/mUC were included. Outcomes of interest included overall survival (OS), progression-free survival (PFS) and treatment-related grade 3 or greater adverse events (≥G3 TRAE). Mixed treatment comparisons were made using network meta-analysis. P-scores were computed to assess relative treatment rankings. Results: A total of 5 trials (8 references) with 4,749 patients and 9 unique treatments were included. EV-P and Gem-Cis-N were ranked first and second in terms of OS and PFS improvement. EV-P improved OS compared to Gem-Cis-N (HR: 0.60; 0.45-0.81), Gem-Plat-atezolizumab(A) (0.55; 0.42-0.72), durvalumab(D)- tremelimumab(T) (0.55; 0.42-0.72), Gem-Plat-P (0.55; 0.42-0.72), P (0.51; 0.39-0.68), D (0.47; 0.36-0.63), A (0.48; 0.36-0.63) and Gem-Plat (0.47; 0.38-0.58). EV-P also improved PFS compared to Gem-Cis-N (0.63; 0.48-0.82), Gem-Plat-A (0.55; 0.43-0.69), D-T (0.42; 0.33-0.53), Gem-Plat-P (0.58; 0.45-0.74), P (0.34; 0.26-0.44), D (0.35; 0.27-0.44) and Gem-Plat (0.45; 0.38- 0.54). For ≥G3 TRAE, A was ranked first with the lowest adverse events compared to others. EV-P (rank 5) had significantly fewer events compared to Gem-Plat, Gem-Plat-A, Gem-Cis-N and Gem-Plat-P. Gem-Cis-N was ranked last with significantly greater events compared to A, P, D, D-T, Gem-Plat, EV-P, and Gem-Plat-A (Table with ranks [p-scores]). Conclusions: Current evidence suggests that patients with untreated la/mUC experience improved survival and slower disease progression with EV-P when compared to other contemporary options. Gem-Cis-N may be a reasonable alternative in patients who are cisplatin-eligible. Cost and access to these treatments are crucial and should be considered to facilitate shared decision making. [Table: see text]