Citations

Abstract Artificial intelligence (AI) holds significant potential to enhance various aspects of oncology, spanning the cancer care continuum. This review provides an overview of current and emerging AI applications, from risk assessment and early detection to treatment and supportive care. AI‐driven tools are being developed to integrate diverse data sources, including multi‐omics and electronic health records, to improve cancer risk stratification and personalize prevention strategies. In screening and diagnosis, AI algorithms show promise in augmenting the accuracy and efficiency of medical image analysis and histopathology interpretation. AI also offers opportunities to refine treatment planning, optimize radiation therapy, and personalize systemic therapy selection. Furthermore, AI is explored for its potential to improve survivorship care by tailoring interventions and to enhance end‐of‐life care through improved symptom management and prognostic modeling. Beyond care delivery, AI augments clinical workflows, streamlines the dissemination of up‐to‐date evidence, and captures critical patient‐reported outcomes for clinical decision support and outcomes assessment. However, the successful integration of AI into clinical practice requires addressing key challenges, including rigorous validation of algorithms, ensuring data privacy and security, and mitigating potential biases. Effective implementation necessitates interdisciplinary collaboration and comprehensive education for health care professionals. The synergistic interaction between AI and clinical expertise is crucial for realizing the potential of AI to contribute to personalized and effective cancer care. This review highlights the current state of AI in oncology and underscores the importance of responsible development and implementation.

The indications for immune checkpoint inhibitor (ICI) use in cancer treatment continue to expand. This is attributable to their proven anticancer activity in addition to their tolerability and favorable toxicity profile as compared to conventional chemotherapeutic agents. ICIs work by blocking the inhibitory signals between tumor cells and T-cells, thereby enhancing the T-cell cytotoxic activity to inhibit tumor growth. Because of their immune-stimulating effect, ICIs are linked to adverse renal outcomes in both native and transplanted kidneys. The risk of kidney allograft rejection in the setting of ICI use has been reported to be around 40%, leading to an increased risk of graft loss. In this report, we review the literature examining outcomes in kidney transplant recipients receiving ICIs for various oncologic indications.

e17155 Background: Localized PCa is classified into six NCCN risk categories, each with specific treatment recommendations. However, treatment concordance across these categories and its variation by race in clinical practice remain unexplored. Therefore, we aim to describe patterns of guideline-concordant treatment receipt for localized PCa across risk groups and race. Methods: Surveillance, Epidemiology, and End Results (SEER) database (2018–2020) was queried to identify patients with localized PCa from 17 registries. Data regarding clinical T stage, Gleason patterns, PSA level, biopsy cores and initial treatment received (radiation, radical prostatectomy, systemic therapy) was obtained. Each patient was then stratified into one of six NCCN-based risk categories using a rule-based algorithm. Using the stratified risk category of each patient, treatment recommendations were obtained from the NCCN guidelines. Concordance was assessed by comparing the received treatment and guideline-recommended treatment. A focused bi-variate logistic regression analysis was performed adjusting for risk groups, and race. Odds ratio (OR) with 95% confidence intervals (CI) were computed to quantify the magnitude of guideline-discordant treatment receipt. Results: This analysis included 69,584 patients with localized PCa (White: 53,875 [77.4%]; Black: 11,265 [16.2%]; Asian/Pacific Islander: 4,133 [5.9%]; American Indian/Alaska Native: 311 0.5%]). In terms of risk groups, patients in higher risk categories had increased odds of discordance compared to the lower risk groups (Table). In terms of race, Black men had significantly higher odds of receiving guideline-discordant therapy (OR:1.67, 95% CI:1.58–1.76), while no statistically significant difference was observed with American Indian/Alaska Native men (OR:1.21, 95% CI: 0.92–1.61) and Asian/Pacific Islander men (OR:1.05, 95% CI:0.97–1.14) compared to White men. Conclusions: Population level data, based on limited sample size in some groups, suggests that treatment concordance with NCCN guidelines varies by risk group and race in localized PCa. Black patients, and those with higher risk groups were more likely to receive guideline-discordant therapy. These findings highlight the need for strategies and prospective studies at individual patient level to evaluate and enhance guideline adherence to promote personalized care for these patients. Variable Discordant Treatment (%) OR (95% CI) White 22168 (41.1) REF Black 5653 (47.5) 1.67 (1.58-1.76) * Asian/Pacific Islander 1822 (44.1) 1.05 (0.97-1.14) American Indian/Alaska Native 191 (61.4) 1.22 (0.92- 1.61) Very Low Risk 770 (9) REF Low Risk 146 (2) 0.16 (0.13-0.19) * Favorable Risk 35 (0.4) 0.03 (0.02-0.04) * Unfavorable Risk 15125 (83.2) 36.30 (33.72-39.25) * High/Very High Risk 13441 (50) 7.32 (6.83-7.86) * * p <0.05.

Background: Solid organ transplant (SOT) recipients are living longer and, consequently, more of them require elective total hip arthroplasty (THA) to restore mobility and improve quality of life. Because these patients are chronically immunosuppressed and often burdened by multiple comorbidities, their peri-operative risk profile may differ substantially from that of the general THA population. This study aimed to evaluate risk factors associated with acute medical and surgical complications, implant survivorship, and overall mortality in patients with a history of SOT who underwent THA. Methods: A total of 173 THA procedures were reviewed in patients with previous SOT. Among them, 64 had undergone liver transplantation (LT), 83 had received renal transplants (RT), and 26 had experienced more than one type of organ transplant (MT). Kaplan–Meier survival analysis was employed to estimate median survival. Complications were examined using univariate analysis through mixed-effects logistic regression, while Cox regression was utilized to assess mortality risk. The median follow-up period extended to 99 months. Results: The proportion of patients experiencing at least one acute medical event was 27% in the LT group, 33% in the RT group, and 38% in the MT group, with no statistically significant difference between groups (p = 0.5). American Society of Anesthesiologists Class (ASA) 4 (Odds Ratio (OR) = 28; p = 0.006) and treatment with bisphosphonates (OR = 2.25; p = 0.03) were associated with higher risk of acute medical complications. Increased age at the time of SOT was linked to a reduced likelihood of surgical complications (OR = 0.94, p = 0.008), as was older age at the time of undergoing THA (OR = 0.92, p = 0.001). The observed rates of reoperation and implant revision were 3% and 1%, respectively. The estimated patient survivorship rates at 1, 5, and 10 years were 98.6, 82, and 58.4%, respectively. Older age at SOT (Hazard Ratio (HR) = 1.06, p < 0.001), at THA (HR = 1.08, p < 0.001), ASA 4 at THA (HR = 7.57, p = 0.02), and atrial fibrillation (AFib) (HR = 3.13, p = 0.02) were associated with higher mortality. Conclusions: ASA 4 and bisphosphonates were associated with a higher risk of acute medical complications, whereas older age was associated with lower surgical complications. Additionally, older age, ASA 4, and AFib were associated with higher mortality.

ABSTRACTBackgroundThe treatment landscape for multiple myeloma continues to evolve. Recently, the addition of anti‐CD38 monoclonal antibodies (mAbs) to the triplet regimen, comprising a proteasome inhibitor, an immunomodulatory agent, and a steroid, for transplant‐eligible newly diagnosed multiple myeloma (TENDMM) has shown promising results.AimsTo evaluate the overall efficacy and safety of quadruplet therapy with an anti‐CD38 mAb compared to a triplet regimen.MethodsA systematic search of Medline, Scopus, and EMBASE databases from inception to July 2024 identified relevant randomized controlled trials (RCTs). Efficacy and safety outcomes were derived using random‐effects meta‐analysis. Summarized outcomes include hazard ratios (HR) for progression‐free survival (PFS) and overall survival (OS), odds ratios (OR) for response rates, measurable residual disease (MRD) negativity rate, and grade 3 or higher adverse events (G ≥ 3 AEs).ResultsFive RCTs involving 2963 patients were included. A statistically significant PFS was observed for quadruplet therapy when compared to the triplet regimen (HR 0.44; 95% Confidence Interval [CI] 0.35–0.56). PFS benefit was consistent for the standard risk (SR) group (HR 0.38; 95% CI 0.27–0.52) and high risk (HiR) group (HR 0.62; 95% CI 0.41–0.92). No statistically significant benefit was observed for OS (HR 0.55; 95% CI 0.28–1.08). A statistically significant benefit was observed for the overall response rate (OR 1.77; 95% CI 1.02–3.06) and MRD negativity rate (OR 2.67; 95% CI 1.79–3.99). No significant differences were observed for G ≥ 3 AE (OR 1.21; 95% CI 0.92–1.58), lymphopenia (OR 1.09; 95% CI 0.62–1.89), and anemia (OR 1.06; 95% CI 0.83–1.37). However, a significantly increased risk was observed for all‐grade thrombocytopenia (OR 1.64; 95% CI 1.37–1.97), neutropenia (OR 2.24; 95% CI 1.67–3.02) and infections (OR 1.88; 95% CI 1.07–3.31).ConclusionQuadruplet therapy demonstrated a favorable efficacy and safety profile, with consistent benefit across subgroups. The findings support its potential as the new standard of care for TENDMM.

Kidney transplantation remains the gold standard for managing end-stage kidney disease, providing superior survival and quality-of-life outcomes compared to dialysis. Despite the ongoing gap between organ availability and demand, it is inevitable that kidney transplantation will continue to grow. This is owed to broader organ sharing, increased comfort of transplant programs with marginal kidney utilization, and the expansion of paired exchange among living donor kidneys. The evolution of kidney transplantation could not have been possible without the availability of effective immunosuppressive regimens that prevent rejection and maintain graft function. Mycophenolic acid and calcineurin inhibitors continue to serve as the foundation of modern maintenance immunosuppression. While these agents have markedly reduced acute rejection rates, their long-term efficacy in graft survival remains suboptimal. Alternative immunosuppressive therapies, including belatacept and mammalian target of rapamycin inhibitors, have demonstrated potential benefits. However, concerns regarding an increased risk of rejection have limited their widespread adoption as primary treatment options. In addition to ongoing efforts to refine steroid- and calcineurin inhibitor-sparing strategies, the identification of practical and quantifiable biomarkers for predicting long-term graft survival remains a critical objective. This review evaluates contemporary immunosuppressive protocols, highlights existing challenges, and explores future directions for optimizing long-term transplant outcomes.

261 Background: Clinicians use next-generation sequencing (NGS) to tailor targeted treatments for PCa patients. However, the results are often available in unstructured formats and are saturated with technical jargon, making them inaccessible for patients. Therefore, we aimed to assess the efficacy of LLMs to accurately extract genomic characteristics from unstructured reports and generate patient-friendly summaries for ease of variant interpretation in PCa patients. Methods: This retrospective study included patients with PCa who underwent NGS from 2023-2024. The GPT4 model was utilized using structured zero-shot prompts to extract genomic characteristics from unstructured reports in a non-decomposed manner. Prompt development was conducted iteratively using a 2% random sample of the dataset. Genomic characteristics ascertained by LLM were assessed against held out vendor-curated test dataset for evaluation. Performance was assessed using weighted evaluation metrics (precision, recall, and F1-score). Additionally, the extracted variables were organized using rule-based criterion and presented as a separate prompt to GPT4 to generate summaries for interpretation at the level of each biologically relevant variant. Mean Flesch-Kincaid scores and Vocd-D statistic with standard deviations were computed to assess readability and lexical diversity of LLM-generated variant interpretation summaries. Results: A total of 331 patients (370 NGS reports) were included in the study. Evaluation on the held-out test dataset (Table) showed that the weighted average precision ranged from 80% for extracting tumor mutational burden to 100% for extracting the CtDNA fraction from unstructured reports. The weighted average recall ranged from 85% for extracting CtDNA tumor fraction to 99% for ascertaining variant/alteration. The weighted average F1-scores varied from 0.83 for extracting tumor mutational burden to 1.0 for extracting specimen site from NGS reports. The mean Flesch-Kincaid score was 8.29 ± 1 indicating average/standard readability ease. The mean Vocd-D statistic was 7.55 ± 1 indicating focused summaries, however, with limited lexical diversity. Conclusions: This study suggests that large language models can effectively extract genomic characteristics from unstructured reports and can potentially improve genomic literacy among prostate cancer patients by providing easy-to-interpret variant summaries. However, targeted prompting may be required to increase lexical diversity for improved engagement. Performance across different genomic characteristics. Category Precision Recall F1-Score Altered gene 0.86 0.97 0.89 Variant/alteration type 0.98 0.99 0.98 Variant allele fraction 0.96 0.96 0.96 Test name/type 1 0.99 1 Specimen site 1 0.99 1 Tumor mutational burden 0.8 0.93 0.83 CtDNA tumor fraction 1 0.85 0.92 MSI status 0.99 0.97 0.98

270 Background: Inconsistent reporting of subgroup data across clinical trials makes interpretation and application of the evidence from trials challenging. We conducted a living systematic review to summarize evidence for American Society of Clinical Oncology (ASCO) guidelines for management of metastatic castration resistant prostate cancer (mCRPC). Here, we provide an overview of reporting patterns of subgroup data across mCRPC trials. Methods: MEDLINE and EMBASE were systematically searched from each database's inception through September 20 th , 2024, to identify phase II/III/IV randomized clinical trials assessing the efficacy and safety of treatment options in mCRPC. For outcomes of overall survival (OS) and progression free survival (PFS), data from the subgroup analyses was collected and compared across trials to assess heterogeneity in the reporting of subgroups. Results: This analysis included 141 trials (phase II: 83; phase III: 56; phase IV: 2). OS was reported by 113 (80%) trials; 32 (28%) reported OS by any subgroups with 95 unique subgroup categories. PFS was reported by 110 (78%) trials; 23 (21%) reported PFS by any subgroups with 63 unique subgroup categories. Even among consistently reported subgroups, such as age, ECOG performance status, race, geographical area, and Gleason score, considerable heterogeneity in different subgroup levels/thresholds was observed across trials. Top ten most commonly reported subgroups are summarized (Table). Conclusions: Lack of consistent reporting for subgroup analysis in mCRPC trials preclude meaningful conclusions about clinically relevant subgroup and synthesizing evidence for clinical guidelines. A standardized framework for consistent reporting of subgroup data across trials can help inform clinical practice and clinical practice guidelines. OS PFS Number of trials 113 110 Reporting subgroup analysis – N (%) 32 (28) 23 (21) Commonly reported subgroups – (N) Age (26)ECOG-PS (26)LDH (21)PSA (18)Geographic area (15)Alkaline phosphatase (14)Visceral disease (14)Gleason score (9)Race (9)Brief pain inventory level (8) Age (21) ECOG-PS (19)PSA (18)LDH (14)Geographic area (13)Visceral disease (11)Gleason score (10)Alkaline phosphatase (9)Bone metastasis (9)Disease location (9) Age – (N) <65 (14); ≥65 (9); ≤68 (1); ≥69 (1); <70 (5); ≥70 (5); ≤74 (4); 65-75 (5); ≤ 71 (1); >71 (1); ≥75 (11); >Median (1); <Median (1) <65 (12); 65-74 (6); ≥65 (6); <70 (5); ≥70 (5); <75 (4); ≥75 (10); 76-80 (1); >80 (1) ECOG-PS – (N) 0 (15); 0-1 (11), 1 (11); 1-2 (5); 2 (12) 0 (15); 0-1 (5), 1 (12); 1-2 (2); 2 (6) Race – (N) White (9)Non-white (6)African American/black (2)Asian (2) White (8)Non-white (5)African American/black (2)Asian (4) Geographic Area – (N) Europe (8)North America (14)United States (1)Australia (1)Asia (2) Europe (11)North America (13)United States (1)Australia (1)Asia (2)North and South America (2) Gleason Score – (N) 2-6 (1); 7 (1); 8 (1); <8 (8); ≥ 8 (8); 9-10 (1) <8 (10); ≥ 8 (10)

520 Background: The annual incidence of renal cancer is 0.02% among the general United States population. End stage renal disease (ESRD) and exposure to dialysis are thought to be the primary drivers of increased risk of renal cancer in renal transplant patients rather than immunosuppression. This has been evidenced by how the incidence of RCC in heart transplant recipients is no different than the normal population. In this study, we aim to characterize RCC incidence among kidney transplant patients (usually exposed to ESRD/dialysis) versus other solid organ transplant patients (usually unexposed to ESRD/dialysis). Methods: We used CPT codes to search for patients who had received a solid organ transplant (kidney, liver, heart, lung, pancreas) at all Mayo Clinic sites from 1/1/2018 to 1/1/2024. Within this cohort, we identified those who had been diagnosed with kidney cancer after initiating dialysis or receiving a transplant, and retrospectively extracted data related to demographics, cancer diagnosis, and transplant details. Results: We identified 10873 patients who had received a solid organ transplant (Table 1). Of these, 178 (1.76%) were diagnosed with kidney cancer after either starting dialysis or receiving a transplant. These 178 patients were of median age 56 years at time of cancer diagnosis (STD 12), 71% male, 70% white, 20% black, 4.5% Asian, 2.8% American Native. Of 5792 patients who had received a kidney transplant (with or without another solid organ transplant), 172 (2.97%) were diagnosed with kidney cancer after having started dialysis or receiving a kidney transplant. Of these 172, 156 (91%) were exposed to dialysis (107 primarily hemodialysis and 48 peritoneal). Of 4392 patients who had received a solid organ transplant other than kidney (liver, heart, lung, and/or pancreas), 6 (0.14%) were diagnosed with kidney cancer after having received a kidney transplant. Of these 6, none underwent dialysis. Conclusions: Patients with kidney transplants are at increased risk of kidney cancer compared to patients with non-kidney solid organ transplants (2.97% vs 0.14%). This supports prior evidence showing ESRD plays a significant role in the pathogenesis of kidney cancer. Patients who received solid organ transplants at Mayo Clinic from 2018-2024 and were subsequently diagnosed with kidney cancer. n % With RCC after TXP 178 1.7587% Cancer Diagnosis after Kidney HD/TXP 172 2.9696% Cancer Diagnosis after Other TXP 6 0.1386% Patients who received solid organ transplants at Mayo Clinic from 2018-2024 n % Unique Patients 10121 100% Kidney Transplant 5792 57.23% Alone 5088 50.27% &Liver 332 3.28% &Heart 119 1.18% &Lung 8 0.08% &Pancreas 245 2.42% Non-kidney Transplant (Liver, Heart, Lung, or Pancreas) 4329 42.77% TXP: Transplant, HD: Hemodialysis.

745 Background: The combination of EV-P therapy has recently been approved as first-line (1L) therapy for patients with LA/mUC based on the results of the EV-302 trial. Herein, we report the updated results from a cohort of patients with LA/mUC who received EV-P in real world clinical setting. Methods: This retrospective study included patients with LA/mUC (07/2022-08/2024) at the Mayo Clinic who completed at least one cycle of EV-P. The best overall response (BOR) was evaluated using radiographic imaging and was adjudicated as complete response (CR), partial response (PR), stable disease (SD), mixed response (MR), or progressive disease (PD). The median progression-free survival (PFS), defined as the time from treatment initiation to disease progression or death, was estimated using the Kaplan-Meier method. Patients who had not experienced disease progression by their last follow-up were censored for the PFS analysis. Results: A total of 120 patients were included; 79 (65.8%) were males, 41 (34.1%) females, 109 (91%) White, and 119 (99%) were non-Hispanic/Latino. The median age was 72 years (IQR: 65-77). Of these, only 22 (18.3%) had locally advanced disease while the remaining had mUC; 62 (51.6%) had lower tract urothelial carcinoma (LUTC), 36 (30%) had upper tract urothelial carcinoma (UTUC). The median follow-up time was 7.1 months (IQR: 4.93-9.26). In terms of BOR, 56 patients (46.6%) experienced PR, 34 (28.3%) CR, 12 (10%) PD, 7 (5.8%) MR, and 8 (6.6%) experienced SD. 3 (2.5%) patients were not evaluable. The BOR across subgroups, LA and mUC, including LUTC and UTUC, is summarized in the table. Among the responders, the median number of treatment cycles to first response was 3 (IQR: 2.25–4). Within the follow-up, 28 patients (23.3%) experienced eventual radiographic disease progression; death was observed in 25 patients (20.8%). The median PFS was 12.7 months (95% CI: 9.8-NE), and OS was 25.1 months (16.3-NE). Conclusions: In real world setting, the combination of EV-P in LA/mUC demonstrated clinical efficacy compatible with the findings from the EV-302 trial. Our results showed comparable efficacy with EV-P in both UTUC and LUTC, highlighting it's broad therapeutic potential. However, clinical data at longer follow-up is required to fully evaluate overall survival and the durability of response. mUC LA Overall LUTC UTUC Total patients 98 62 36 22 BOR CR 23 (23.4%) 13 (20.9%) 10 (28.5%) 11 (50%) PR 49 (52.6%) 31 (50%) 18 (50%) 7 (31.8%) SD 6 (6.4%) 2 (3.2%) 4 (11.4%) 2 (9.0%) PD 10 (10.7%) 9 (15.5%) 1 (2.8%) 2 (9.0%) MR 7 (7.5%) 5 (8.6%) 2 (5.7%) 0 (0%)