Maughan, Benjamin L.

Background Immune checkpoint inhibitor-based combinations represent the standard of care for advanced renal cell carcinoma. The OMNIVORE trial investigated a response-adaptive strategy, including treatment discontinuation in early nivolumab responders (Arm A) and salvage ipilimumab addition in non-responders (Arm B). Here we report outcomes with extended follow-up. Methods OMNIVORE was a phase II response-adaptive trial in which patients received induction nivolumab monotherapy. Patients achieving a confirmed complete or partial response discontinued nivolumab and entered observation (Arm A), while patients with stable disease or progressive disease received two doses of ipilimumab added to ongoing nivolumab (Arm B). This analysis characterizes long-term overall survival across the full study cohort and durability of response among patients who discontinued nivolumab following an early objective response. Results Of 83 patients who initiated treatment, 12 (14%) were allocated to Arm A and 57 (69%) to Arm B, with a median follow-up among living patients of 59.4 months (range 29.1–85.4 months) in Arm A and 31.4 months (range 4.6–62.6 months) in Arm B. The 3-year overall survival rate from nivolumab initiation was 64% (95% CI 51% to 74%) in the overall cohort, 83% (95% CI 48% to 96%) in Arm A, and 63% (95% CI 47% to 76%) in Arm B. Of the 12 Arm A patients, 6 (50%) remained off nivolumab at 1 year following treatment discontinuation, of whom 5 maintained responses beyond 43 months off therapy, with all remaining alive at last known follow-up, with overall survival ranging from 48.8 to 85.4 months from nivolumab initiation. Of the six patients who resumed treatment, only one achieved a durable complete response remaining on treatment at 83.2 months from nivolumab initiation. All 57 Arm B patients discontinued treatment with a median treatment duration of 3.7 months (range 1–24.8 months) and a median progression-free survival from nivolumab plus ipilimumab initiation of 4.6 months (95% CI 2.7 to 6.5 months). Conclusions With extended follow-up, a meaningful subset of patients achieving an early objective response to nivolumab maintained prolonged treatment-free survival following a short course of treatment. Salvage ipilimumab in nivolumab non-responders demonstrated limited benefit, reinforcing that upfront concurrent dual checkpoint blockade remains the preferred approach. Trial registration number NCT03203473 .

This cohort study examines patterns of bone-modifying agent use from 2013 to 2024 among men with metastatic castration-resistant prostate cancer.

e15509 Background: Large language models (LLMs) are increasingly explored for oncology decision support, yet comparative evidence evaluating medical-specific versus general-purpose LLMs using expert-reviewed clinical cases is limited. We compared a medical-specific LLM (Google MedGemma 27B) with a general-purpose LLM (ChatGPT-5) using gastrointestinal (GI) and genitourinary (GU) oncology vignettes. Methods: This cross-sectional study evaluated 32 de-identified oncology vignettes (26 GI, 6 GU) created by a U.S. board-certified medical oncologist and informed by real-world cases. Vignettes included text-only information on the clinical context, description of pathology, tumor staging, biomarkers, and relevant comorbidities. Both LLMs were prompted to provide National Comprehensive Cancer Network(NCCN) guideline-based treatment recommendations, monitoring strategies, maintenance therapy considerations, and references, along with a self-reported confidence score (0–100). Board-certified U.S. medical oncologists independently reviewed outputs using a structured instrument; two disease specific expert oncologists evaluated each case. Outcomes included correctness and comprehensiveness (1–10 scales), hallucinations (factually fabricated or unsupported statements), NCCN traceability, potential patient harm, and clinician trust. Associations between accuracy and comprehensiveness were assessed using correlation coefficients. Inter-rater reliability was assessed using a two-way random-effects intraclass correlation coefficient (ICC). Results: ChatGPT-5 demonstrated higher mean correctness (8.65 vs 4.68) and comprehensiveness (8.68 vs 5.22) scores compared with MedGemma 27B. Accuracy and comprehensiveness were strongly correlated overall (Pearson r = 0.93, p < 0.001), with significant model-specific correlations (ChatGPT-5 r = 0.86, p < 0.001; MedGemma r = 0.77, p < 0.001). Hallucinations occurred less frequently with ChatGPT-5 (12.3% vs 65%), and NCCN-traceable recommendations were more common (75.4% vs 36.7%). Responses judged as potentially harmful occurred in 18.5% of ChatGPT-5 outputs versus 70% of MedGemma outputs. Clinician trust favored ChatGPT-5 (84.6% vs 15%). Inter-rater reliability improved with rater averaging (ICC(A,k): correctness 0.72; comprehensiveness 0.64). Conclusions: In expert-reviewed GI and GU oncology cases, ChatGPT-5 demonstrated higher clinical accuracy, comprehensiveness, and guideline alignment than a medical-specific LLM; however, a substantial rate of hallucinations and potentially harmful recommendations persisted across models. These findings underscore that, despite performance differences, current LLMs require rigorous clinician oversight and should not be used as standalone decision-support tools in oncology.

4559 Background: Baseline QOL has been linked to survival in mRCC therapy clinical trials (Cella, 2024); however, there is a paucity of prospectively collected real-world QOL data across front-line management strategies. We used data from ODYSSEY to examine the relationship between baseline QOL and early death. Methods: ODYSSEY is a multi-site, prospective observational study of 468 US pts with mRCC. Pts must have mRCC (any histology); have no prior systemic therapy (ST) or be within 3 months of starting ST; and follow up at a PCORnet study site. Exclusion criteria include treatment for cancer except mRCC. The primary objective is to determine patterns of change in QOL and symptom burden of pts with mRCC. Early death was defined as death within 12 months post-enrollment. All pts with non-missing FKSI-19 or FKSI-DRS at enrollment were included. Cumulative event probabilities as a function of time were stratified by either < or ≥ median QoL value and plotted as a step function vs time since enrollment to create cumulative event curves. To determine association between QoL at enrollment and early death, separate Cox proportional hazards models (unadjusted and adjusted) for time-to-first-event as a function of baseline QoL were fit. The adjusted model controlled for the following baseline covariates: IMDC risk (favorable vs intermediate or poor), histology (clear cell vs non). Results: As of 1/5/26, 468 pts were enrolled; 425 had non-missing FKSI-19 or FKSI-DRS at enrollment (329 immediate ST, 96 deferred ST [DST]). ST included 129 IO-IO, 108 IO-TKI, 92 Other. DST included 57 Active Surveillance, 22 Local Therapy Planned, 17 Other/Missing. 209 and 190 pts have < median FKSI-19 (score = 59) and FKSI-DRS (score = 29), respectively; 216 and 235 pts have ≥ median FKSI-19 and FKSI-DRS, respectively. Those below the median have lower rates of nephrectomy, worse IMDC risk and KPS, shorter time since RCC diagnosis, and higher rates of bone metastasis (all p<0.05). Cumulative event probabilities for death at 12 months are 21% and 7% in those < and ≥ median baseline FKSI-19, respectively; and 21% and 7% in those < and ≥ median baseline FKSI-DRS, respectively. For FKSI-19, the unadjusted hazard ratio (HR) for early death is 0.55 (95% CI: 0.43 – 0.70; p<0.001) and adjusted HR is 0.65 (0.49 – 0.85; p = 0.002) per 1 SD higher score. For FKSI-DRS, the unadjusted HR for early death is 0.57 (95% CI: 0.46 – 0.71; p<0.001) and adjusted HR is 0.66 (0.51 – 0.86; p =0.002) per 1 SD higher score (higher score indicates better QOL). Conclusions: Across management strategies in our ODYSSEY cohort of systemic therapy naïve mRCC patients, better baseline QOL was associated with better survival. This is to our knowledge the largest reported real world mRCC cohort with prospectively collected PROs. Future analyses will focus on association of outcomes with longitudinal PROs. Clinical trial information: NCT04919122 .

476 Background: Lack of standardized reporting and collection of patient-reported outcomes (PROs) limits cross-trial comparisons of first-line IO-based regimens for mRCC. Prospectively collected real world data may fill this important knowledge gap. Pts with stable/improved QoL at 3 mo versus baseline have longer median OS than pts with worse/unobserved HRQoL versus baseline (Cella, 2024). Methods: ODYSSEY is a multi-site, prospective observational study of 468 US pts with mRCC. Pts must have mRCC (any histology), no prior systemic therapy (ST), and follow up at a PCORnet study site. Exclusion criteria include treatment for cancer except mRCC. Descriptive statistics are used to show PRO score changes from baseline. We evaluate longitudinal change from baseline in PRO scores using least squares mean (LSM). Minimally important differences (MID) are 3 points for FKSI-19 total score, 1 point for the FKSI-Disease Related Symptoms (DRS) subscale and 7 points for FACT-G. Higher score indicates better QOL. The primary objective is to determine patterns of change in QOL and symptom burden of pts with mRCC. Results: As of 10/1/25, 360 pts were managed with ST, including 266 pts on IO-based combinations: 35 cabozantinib + nivolumab (C+N), 49 lenvatinib + pembrolizumab (L+P), 40 axitinib + pembrolizumab (A+P), and 142 ipilimumab + nivolumab (I+N). Overall median follow-up is 12.1 mos (IQR 6, 24). Age, sex and race were similar across regimens. Prior nephrectomy (50%) was lower than in trials. C+N and L+P pts had less clear cell (56 and 65%) versus A+P and I+N pts (94 and 82%). A+P pts had more favorable IMDC risk (19%) and less poor risk (14%). Baseline QOL was variable across regimens, with L+P generally the lowest. Absolute changes in PROs from enrollment to mo 3 (early change) by regimen are shown in the Table. LSM change from baseline in FKSI-19 and FKSI-DRS favored IO-IO versus IO-TKI at 3 mos but not at 6 mos (not shown). Conclusions: While early change in PROs did not meet the MID threshold between the IO-TKI and I+N cohorts, different patterns of early change are apparent among specific IO-TKI regimens. IO-TKI regimens exhibited higher variation in early PRO change vs I+N. As the data matures, we will associate baseline PROs and early PRO changes with early death and other outcomes. Clinical trial information: NCT04919122 . 3 month change. Instrument C+N (N=35) L+P (N=49) A+P (N=40) All IO-TKI(N=124) I+N(N=142) FKSI-19, N (%) 26 (74) 33 (67) 33 (83) 92 (74) 104 (73) Mean (SD) -0.3 (11) 2.8 (13) -3.2 (12) -0.2 (12) 0.7 (10) Median (IQR) 1.4 (-7, 6) 5.0 (-7, 11) -1.0 (-14, 5) 1.4 (-10, 8) -0.3 (-5, 6) FKSI-DRS, N (%) 26 (74) 33 (67) 33 (83) 92 (74) 104 (73) Mean (SD) -0.8 (5) 1.5 (7) -1.8 (6) -0.3 (6) 0.8 (5) Median (IQR) -0.5 (-5, 3) 2.0 (-5, 5) -1.0 (-5, 3) 0.0 (-5, 4) 0.0 (-2, 4) FACT-G, N (%) 27 (77) 32 (65) 29 (73) 88 (71) 102 (72) Mean (SD) 2.1 (14) 5.2 (16) -3.5 (15) 1.4 (15) 0.3 (13) Median (IQR) 4.0 (-4, 10) 1.2 (-6, 13) -6.4 (-11, 4) 1.6 (-8, 10) 1.6 (-7, 8)

ImportancePatients with metastatic castration–resistant prostate cancer (mCRPC) harboring BRCA1/2 alterations are eligible to receive poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitors as single agents or in combination with an androgen receptor pathway inhibitor after these agents showed survival improvement in their landmark clinical trials. However, data are limited regarding the uptake of PARP inhibitors in these patients.ObjectiveTo investigate the use of PARP inhibitors in patients with mCRPC harboring BRCA1/2 alterations.Design, Setting, and ParticipantsThis retrospective cohort study used the deidentified Flatiron-Health electronic health record–derived database of US community and academic practices to extract patient-level data. The data cutoff date was May 31, 2024. Patients with mCRPC with evidence of harboring BRCA1/2 alterations and alive after August 15, 2020 (ie, 3 months after the approval of the first PARP inhibitor, rucaparib, in mCRPC) were included. Statistical analysis was performed from September 2024 to May 2025.ExposuresAge, race and ethnicity, insurance status, and practice type at the time of mCRPC diagnosis.Main Outcomes and MeasuresThe receipt of PARP inhibitors. Multivariable logistic regression was conducted to assess the association between the exposures and the main outcome.ResultsOf 24 105 patients with metastatic prostate cancer, 443 male patients (median [IQR] age, 72 [65-79] years) had mCRPC with BRCA1/2 alterations and were eligible and included in our analysis. Of these patients, 227 (51.2%) received a PARP inhibitor, whereas 216 (48.8%) did not. Compared with patients covered by a commercial health plan, those covered by Medicare were significantly more likely to receive a PARP inhibitor (odds ratio, 1.91; 95% CI, 1.02-3.66; P = .047). The odds of receiving a PARP inhibitor were not significantly higher in patients treated in community practice compared with those treated in academic centers (odds ratio, 1.64; 95% CI, 1.00-2.70; P = .05).Conclusions and RelevanceThis retrospective cohort study of patients with mCRPC and evidence of BRCA1/2 alterations found that approximately half of patients did not receive PARP inhibitors despite evidence of survival improvement in this population. These findings highlight the need to increase awareness of the survival data and access to life-prolonging therapies in patients with mCRPC.

5076 Background: C and Lu are both life-prolonging therapies for pts with mCRPC after progression on androgen receptor pathway inhibitor (ARPI) and docetaxel (D). Herein, our objective was to assess the comparative effectiveness of C vs. Lu in pts with mCRPC with prior progression on D and ARPI in real-world pts in the USA. Methods: A de-identified nationwide Flatiron Health electronic health record (EHR)-derived database was used to extract pt-level data. Eligibility: pts with mCRPC who progressed on D and ARPI and received for the first-time single-agent C or Lu. Pts who received alternative Lu or C in a later line of therapy (LOT) were excluded. Endpoints: real-world time to next therapy (rwTTNT) and real-world overall survival (rwOS). These were summarized via Kaplan-Meier survival estimates with a 95% confidence interval (CI) and compared in the context of propensity score (PS) matching weighted analysis using the Cox proportional hazard model. PS model included the following covariates: age, race-ethnicity, socioeconomic status, treatment year, Gleason score, ECOG performance status, log2PSA, alkaline phosphatase, hemoglobin, creatinine, LOT, insurance, and practice type. All the covariates achieved balance after PS matching weighting. Results: Among 24,105 pts with metastatic prostate cancer in the dataset, 1,445 met the eligibility criteria and were included (1,227 treated with C, 218 treated with Lu). In C cohort: median age was 73 (IQR 67 – 78), 66.9% had Gleason score ≥ 8, and median LOT was 4 (IQR 3-4). In Lu cohort: median age was 75 (IQR 67.25 – 80), 68.1% had Gleason score ≥ 8, and median LOT was 4 (IQR 3-5). In PS matching weighting analysis, there was evidence that pts receiving Lu had a significantly improved rwTTNT (median 8.3 months [mo], 95% CI 6.3 – 9.8) compared to those receiving C (median 4.7 mo, 95% CI 4.2 – 5.4) (HR 0.49, 95% CI 0.37 – 0.63, p < 0.001), which persisted after adjusting for covariates (HR 0.43, 95% CI 0.32 – 0.57, p < 0.001). Additionally, there was evidence that rwOS was longer in pts receiving Lu (median 10.3, 95% CI 8.9 – 12.8) compared to those receiving C (median 8.8 mo, 95% CI 6.6 – 10.8) (HR 0.69, 95% CI 0.51 – 0.92, p = 0.01). This improvement in rwOS with Lu compared to C persisted after adjusting for covariates (HR 0.61, 95% CI 0.44 – 0.84, p < 0.001). Conclusions: This is the largest real-world data to date assessing the comparative effectiveness of Lu vs. C, and it showed significantly longer rwTTNT and rwOS with Lu compared to C in pts with mCRPC pretreated with ARPI and D. Limitations: retrospective nature, selection bias, missingness, lack of randomization, etc. and residual confounding in real-world datasets. Upon external validation, these findings could guide treatment selection in the clinic and design of clinical trials.

4558 Background: In the past 7 years, 4 immuno-oncology (IO) based combinations have been approved for mRCC. However, QOL data on these combinations are limited to trials in which collection and reporting was not standardized, which further limits cross trial comparisons. Real-world QOL data with multiple treatment regimens are needed to understand how these regimens are tolerated in practice. Methods: ODYSSEY is a multi-site, prospective observational study of 500 US pts with mRCC. Pts must have mRCC (any histology), no prior ST, and follow up at a PCORnet study site. Exclusion criteria include treatment for cancer except mRCC. The primary objective is to determine patterns of change in QOL and symptom burden of pts with mRCC. Minimally important differences (MID) are 3 points for FKSI-19 total score, 1 point for the FKSI-Disease Related Symptoms (DRS) subscale and 7 points for FACT-G. Results: As of 1/6/25, 392 pts were enrolled of whom 299 were managed with ST. Of pts on ST, 114 were treated with IO-IO, 108 with IO-TKI, 33 with IO alone, 27 with Other, and 18 with TKI alone. Median follow up for all pts is 8.8 months (IQR 2.9, 16.2). IO-IO pts are median age 64 yrs, 81% male, 84% white, 56% prior nephrectomy, 84% clear cell; IO-TKI pts median age 66 yrs, 76% male, 92% white, 43% prior nephrectomy, 66% clear cell; IMDC risk profiles are similar. IO-IO pts are more likely to be KPS 100; whereas, IO-TKI pts have a higher median number of metastatic sites and are more likely to have bone or liver metastasis. With median follow-up of 6.0 (IQR 1.8, 14.9) and 8.8 months (4.5, 17.8) in the IO-IO and IO-TKI cohorts, 17 (15%) and 21 (19%) pts had died with a median time to death of 5.4 (2.5, 6.4) and 5.7 months (4.4, 12.8), respectively. 20 (18%) and 16 (15%) pts on IO-IO and IO-TKI had discontinued therapy at a median of 3.0 (IQR 2.0, 4.0) and 6.4 months (2.4, 13.0), respectively. Rates of discontinuation for disease progression and toxicity are similar. Baseline PROs for pts on ST are shown in the Table (higher score indicates better QOL), with RCT data for reference (NA, not assessed). Conclusions: In our prospective multi-center ODYSSEY study, we demonstrate that real world pts treated with contemporary ST have worse baseline QOL than those enrolled on pivotal RCTs. One-third of IO-IO and IO-TKI pts died or discontinued therapy within 6 months of initiation. Our data on real world vs RCT differences in baseline QOL may partially explain the limitations of current IO combination regimens in practice and support development of alternative treatment approaches. Instrument, Mean (SD) ODYSSEYIO-IO(N=114) CheckMate214(N=425) ODYSSEYIO-TKI(N=108) KEYNOTE426(N=402) CheckMate9ER(N=323) CLEAR(N=351) FKSI-19 total 56.0 (12.5) 60.1 (9.8) 53.8 (11.8) NA 58.7 (10.6) NA FKSI-DRS 27.5 (6.3) 30.7 (4.5) 27.0 (5.8) 32 (4.2) 30.2 (5.2) 31.3 (4.4) FACT-G 82.4 (16.7) 82.6 (15.0) 78.5 (16.0) NA NA NA

4553 Background: AS is a recognized strategy in select pts with mRCC to maximize QOL and delay potential toxicity of systemic therapy (ST); however, only 2 prospective studies of AS in mRCC have been published: only 1 with patient-reported outcomes (PRO) and none in the IO-TKI era. Methods: ODYSSEY is a prospective observational study of 500 US pts with mRCC. Eligible pts must have mRCC (any histology), no prior ST, age ≥19. Pts were excluded if treated for non-mRCC cancers or if not followed at a PCORnet study site. Pts completed QOL surveys at baseline, by phone every 3 months for 2 years and then every 6 months until end of follow up. The primary objective is to determine patterns of change in QOL and symptom burden of pts with mRCC. Minimally important differences (MID) are 3 points for FKSI-19 total score, 1 point for the FKSI-Disease Related Symptoms (DRS) subscale and 7 points for FACT-G. Here we report baseline pt characteristics in AS pts compared to ST pts, and baseline QOL differences between these cohorts. Results: As of 1/6/25, 392 pts were enrolled of whom 299 were managed with ST, and 93 pts deferred ST; of these, 53 pts (57%) were classified as AS. Pts on AS are median age 68 yrs, 66% male, 94% white, 81% clear cell, 50% favorable risk, 44% intermediate risk. Compared with ST pts, AS pts were more likely to have undergone nephrectomy (91% vs 53%), favorable risk profile (50% vs 15%), pancreatic metastasis (15% vs 5%), and longer time since RCC diagnosis (median 58 vs 3.3 months); and less likely to have bone, brain, or liver metastasis. After median 8.8 months follow-up (IQR 2.9, 16.2), 2 pts (4%) on AS had died compared with 45 pts (15%) on ST. One pt (2%) on AS started first-line therapy and 45 pts (15%) discontinued ST. Mean baseline QOL (FKSI-19 total, DRS and FACT-G) for AS and ST ODYSSEY pts is shown in the Table (higher score indicates better QOL), with RCT data for reference (NA, not assessed). ODYSSEY pts on AS had higher QOL for all measures compared with ODYSSEY pts on ST. FSKI-DRS was the same or lower for pts on AS compared to the pivotal trials, while ODYSSEY pts on ST had both lower FKSI-19 total and DRS. Conclusions: In our large prospective cohort from ODYSSEY, pts on AS had higher median QOL scores than pts on ST, but similar to those included in RCTs. These results suggest that some RCT pts could have benefitted from AS. Further follow up is needed to determine long term outcomes in pts on AS and how they respond to deferred ST. Clinical trial information: NCT04919122 . Instrument, Mean (SD) ODYSSEY AS (N=53) ODYSSEY ST (N=299) ODYSSEY Difference, AS vs ST (95% CI) CheckMate 214 (N=425) KEYNOTE 426 (N=402) CheckMate 9ER (N=323) CLEAR (N=351) FKSI-19 total 63.4 (9.2) 56.3 (12.5) 7.0(4.0, 10.1) 60.1 (9.8) NA 58.7 (10.6) NA FKSI-DRS 30.8 (4.2) 27.9 (6.0) 2.9(1.5, 4.7) 30.7 (4.5) 32 (4.2) 30.2 (5.2) 31.3 (4.4) FACT-G 87.9 (14.0) 82.4 (16.7) 5.6(1.1, 10.0) 82.6 (15.0) NA NA NA

4545 Background: The treatment landscape of front-line nccRCC has evolved with recent trials demonstrating the efficacy of combination systemic therapy. However, the efficacy of treatment after combination therapy is unknown. This study evaluates the efficacy of VEGF-based regimens in nccRCC patients (pts) previously treated with combination regimens. Methods: ORACLE is a real-world, multi-center, retrospective database that includes nccRCC patients that received combination systemic therapies (IO+IO, IO+VEGF and VEGF+ mTOR) in any line. Subsequent treatments were categorized as VEGF only regimens (cabozantinib vs other VEGF), IO+ VEGF and VEGF+ mTOR. The primary endpoint was objective response rate (ORR) assessed by investigator review using RECIST 1.1. Secondary endpoints included disease control rate (DCR), defined as the proportion of patients achieving complete or partial responses or stable disease, time to treatment progression (TTP), calculated from the date of VEGF-based initiation to progression or last follow-up using the Kaplan-Meier method. Differences between groups were estimated with the log-rank test, and categorical outcomes were compared with the chi-square test. Results: 105 pts who received VEGF – based regimens after combination therapy were included in the analysis. Baseline characteristics: median age: 59years, 71 % male, 58% white, 25% black, 87% ECOG 0-2. IMDC-risk categories included:21% favorable, 59% intermediate and 20% poor risk. Histology included papillary (40%), unclassified (32%), chromophobe (16%) and other rare subtypes (12%). Prior combination therapies included IO+IO: 62%, IO+ VEGF: 34% and VEGF+ mTORi:4%. 70% pts received combination therapy in the first line setting while the remainder received combination therapy in a second or later line. Outcomes with subsequent treatments are described in Table1. IMDC risk score correlated with TTP. Conclusions: Modest antitumor activity was observed with VEGF- based approaches in combination therapy refractory nccRCC. Optimal management of nccRCC remains an unmet need. Outcomes of nccRCC patients by treatment and histologic type. Outcomes per Treatment n ORR (%) DCR (%) mTTP (mo.) Cabozantinib 56 18 47 3.6 VEGF/mTOR 19 16 42 9.3 IO+VEGF 17 29 47 5.6 Other VEGF 13 15 46 5.5 Outcomes per Histology Papillary 42 19 43 6.5 Unclassified 33 21 42 6.1 Chromophobe 17 29 59 8.9 Other * 13 0 46 NR