Boyle, Ashton W.R.

PURPOSE Artificial intelligence (AI) has been rapidly evolving in medicine. While there are existing data about the perceptions and concerns of health care workers regarding AI, those of the hematology and oncology (HemOnc) workforce remain unknown. We assessed opinions of physicians (faculty and fellows), advanced practice providers (APPs), and nurses in HemOnc on integrating AI in medical education (MedEd) and clinical practice (CP). METHODS Group-specific electronic surveys were developed. The HemOnc workforce from the three Mayo Clinic sites was invited to participate. Participation was anonymous, with data collection between November 7, 2024, and January 20, 2025. Results were reported as proportions, with 95% binomial CI when appropriate. RESULTS A total of 344 participants responded, 118 physicians (77 faculty, 41 fellows), 49 APPs, and 177 nurses. Most had used AI although less than half felt very or moderately knowledgeable about it. A total of 95% of fellows, 97% of faculty physicians, 96% of APP, and 92% of nurses believe that AI will be integrated in MedEd. A total of 94% of physicians and 88% of nonphysicians believe that this integration would be beneficial. In CP, 98% of fellows, 96% of faculty physicians, 100% of APPs, and 92% of nurses believe in AI's integration. However, 51% of physicians and 68% of nonphysicians had some concerns, including technology time, medical costs, and burnout. Nonetheless, 85% of fellows, 94% of faculty physicians, 98% of APPs, and 86% of nurses would embrace AI. CONCLUSION The majority of this single health system HemOnc's workforce endorsed AI integration into MedEd and CP but highlighted relevant concerns. Proper education, effective partnership among all stakeholders, and well-organized integration are essential for optimizing AI's incorporation into HemOnc's MedEd and CP and ensuring that it fully supports the mission of providing high-quality patient care.

Despite European colorectal liver metastases (CRLM) transplant trials having been performed entirely using deceased donor liver transplant (DDLT), there has been speculation about whether similar results can be achieved in the United States, given the lack of MELD score prioritization. A formal transplant protocol for unresectable CRLM was implemented in our center at the start of 2022 with the plan to utilize DDLT. Between 2022 and 2025, 86 patients with CRLM were referred to our program, and 19 patients underwent a formal transplant evaluation. Median time from listing until transplant was 31 days (range 3–115 d). Median allocation MELD was 8 (range 6–15). The donor livers were from DCDs, older donors, or National Share livers, which had been declined by all other centers. All but 2 of the cases underwent advanced perfusion. There were no cases of primary nonfunction, postreperfusion syndrome, acute kidney injury, hepatic artery thrombosis, or ischemic cholangiopathy. The length of stay for the median posttransplant was 5 days. Graft and patient survival were 100% at the time of maximal follow-up. Recurrence developed in 3 recipients (25.0%), 1 of whom was treated and has no evidence of disease. These findings support the viability of DDLT for CRLM using advanced perfusion, contingent on strict protocol adherence. Center-specific waitlist dynamics must inform the choice between DDLT and living donor liver transplant (LDLT).

9002 Background: The field of AI is rapidly evolving. With recent development of more user-friendly AI software, its integration into healthcare across different medical specialties, including HemOnc has emerged. Data detailing the perception and concerns of the HemOnc workforce about AI’s roles is lacking and is needed if AI is to be integrated in HemOnc CliPr and MedEd. Methods: Questionnaires about the perception and concerns regarding AI in CliPr and MedEd were created on REDCap and approved by IRB. We surveyed the entire HemOnc workforce at the 3 Mayo Clinic major sites between 11/07/24 and 01/20/25, including physicians, both faculty (FAC) and fellows (FEL), advanced practice providers (APP), and nurses (RN). Participation was voluntary. Simple statistical analyses were employed for the results. Results: 344 participants (PTP) responded to the survey, 118 physicians (41 FEL and 77 FAC), 49 APP, and 177 RN. 64% of PTP report having used AI but only 31% used it in HemOnc MedEd, and 28% in HemOnc CliPr, with 67% considering themselves to have little to no knowledge about AI. 94% of PTP believe AI will be integrated in HemOnc MedEd, with such integration being seen as beneficial by 90%. Among physicians, 85% of FEL and 92% of FAC report that fellowship programs should incorporate AI training into curricula. 95% of PTP believe AI will be incorporated into HemOnc CliPr. Meanwhile, 62% of PTP (50.8% of physicians, and 68% of APP and RN) are concerned about risks it may pose to CliPr. Nevertheless, 90% of PTP would embrace AI’s use in HemOnc. Table 1 details the perceptions and concerns about AI in HemOnc MedEd and CliPr. The main perceived risks are decreased time spent with patients (pts), and inaccuracies or worse pt care. Meanwhile, 33% believe AI would increase efficiency and quality of care, while 30% believe it would increase time spent with pts. 14% of PTP worry their role could be replaced by AI. Conclusions: To the best of our knowledge, this is the largest assessment of HemOnc workforce’s perception and concerns about AI. Based on our survey, the HemOnc workforce, in general, endorses AI use, but with some concerns raised. While incorporation in MedEd is perceived with excitement, many envision the use in CliPr involves risks and challenges. Proper systematic education of the workforce about AI, with well-designed CliPr integration methods are needed to mitigate the legitimate existing concerns. Perceptions & concerns about AI in HemOnc MedEd & CliPr. FEL % APP % RN % FAC % AI will assist documentation in CliPr 98 82 79 92 AI will be used in pt communication 73 80 78 87 AI will screen pts for clinical trial enrollment 85 86 76 96 AI will increase the efficiency and quality of CliPr 43 37 24 46 AI will increase time spent with pts 39 27 25 38 AI will decrease time spent with pts 29 41 48 23 AI will lead to inaccuracies or worse CliPr 12 20 25 20 AI may replace the HemOnc workforce 11 16 19 5

PURPOSE This investigation sought to evaluate the prognostic value of pretreatment of circulating tumor DNA (ctDNA) in metastatic biliary tract cancers (BTCs) treated with platinum-based first-line chemotherapy treatment. MATERIALS AND METHODS We performed a retrospective analysis of 67 patients who underwent ctDNA testing before platinum-based chemotherapy for first-line treatment for metastatic BTC. For analysis, we considered the detected gene with highest variant allele frequency as the dominant clone allele frequency (DCAF). Results of ctDNA analysis were correlated with patients' demographics, progression-free survival (PFS), and overall survival (OS). RESULTS The median age of patients was 67 (27-90) years. Fifty-four (80.6%) of 67 patients evaluated had intrahepatic cholangiocarcinoma; seven had extrahepatic cholangiocarcinoma, and six gallbladder cancers. Forty-six (68.6%) of the patients were treated with cisplatin plus gemcitabine, and 16.4% of patients received gemcitabine and other platinum (carboplatin or oxaliplatin) combinations, whereas 15% of patients were treated on a clinical trial with gemcitabine and cisplatin plus additional agents (CX4945, PEGPH20, or nab-paclitaxel). TP53, KRAS, FGFR2, ARID1A, STK11, and IDH1 were the genes with highest frequency as DCAF. The median DCAF was 3% (0%-97%). DCAF > 3% was associated with worse OS (median OS: 10.8 v 18.8 months, P = .032). Stratifying DCAF in quartiles, DCAF > 10% was significantly related to worse PFS (median PFS: 3 months, P = .014) and worse OS (median OS: 7.0 months, P = .001). Each 1% increase in ctDNA was associated with a hazard ratio of 13.1 in OS when adjusting for subtypes, metastatic sites, size of largest tumor, age, sex, and CA19-9. CONCLUSION DCAF at diagnosis of advanced BTC can stratify patients who have worse outcomes when treated with upfront platinum-based chemotherapy. Each increase in %ctDNA decreases survival probabilities.

4079 Background: Cell-free circulating tumor DNA (ctDNA) holds significant promise and is being used for clinical decision making in multiple tumors. This study aimed to evaluate the prognostic value of pre-treatment ctDNA in metastatic biliary tract cancers (BTC) treated with platinum based first-line chemotherapy treatment. Methods: We performed a retrospective analysis of 67 patients who underwent ctDNA testing before platinum-based chemotherapy for first-line treatment for metastatic BTC. For analysis we considered the detected gene with highest variant allele frequency (VAF). Results of ctDNA analysis were correlated with patients’ demographics, progression-free survival (PFS) and overall survival (OS). Results: The median age of patients was 67 y/o (27-90). 54 (80.6%) of 67 patients evaluated had intrahepatic cholangiocarcinoma; seven had extrahepatic cholangiocarcinoma and six gallbladder cancer. 46 (68.6%) of the patients were treated with cisplatin plus gemcitabine, 14 (21%) patients received gemcitabine and other platinum (carboplatin or oxaliplatin) combinations while 7 (10.4%) patients were treated on a clinical trial with gemcitabine and cisplatin plus additional targeted agents (CX4945 or PEGPH20). TP53, KRAS, APC, FGFR2 and IDH1 were the genes with highest frequency as dominant clone. The median dominant clone allele frequency (DCAF) was 3% (0-97%). DCAF >3% was associated with statistically significant worse PFS (median PFS: 4.05 vs. 7.70 months, p=0.046) and OS (median OS: 10.8 vs. 18.8 months, p=0.056). Each 1% increase in DCAF is associated with a hazard ratio of 26.21 in OS when adjusting for subtypes, age, treatment type, and CA19-9 [Table]. Conclusions: Patients with metastatic BTC with DCAF > 3% at diagnosis have worse PFS and OS compared to patients with low ctDNA when treated with upfront platinum-based chemotherapy.[Table: see text]