Citations

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) frequently recurs after neoadjuvant therapy (NT) and curative-intent resection. Although major pathologic response predicts favorable outcomes, most patients achieve only minor response with a heterogeneous recurrence risk. We asked whether the spatial organization of residual PDAC encodes clinically relevant biology beyond residual tumor burden. Experimental Design: In a retrospective cohort of 203 patients with resected PDAC treated with NT and restricted to minor pathologic response, routine hematoxylin and eosin (H&E) whole-slide images were segmented into cancer and stroma using an artificial intelligence–enabled pipeline. Spatial composition (patch density, edge density) and configuration (compactness/complexity, intermixing) were quantified and tested for associations with disease-free survival (DFS) using multivariable models adjusted for standard clinicopathologic factors. Results: Shorter DFS was associated with a fragmented, interface-rich tumor–stroma ecology featuring higher edge density and diversity and reduced homotypic aggregation, independent of clinicopathologic variables. Two spatial risk models were independently prognostic: (i) cancer mean shape index plus stromal shape index variability [adjusted hazard ratio (HR), 1.71; P = 0.003] and (ii) mean stromal patch area plus edge density (adjusted HR, 2.19; P = 0.002). Both models stratified outcomes in which pathologic response grading and residual cancer area did not. High-risk configurations were further associated with reduced intratumoral tumor-infiltrating lymphocyte (TIL) density and infiltration ratio, with relative TIL accumulation at the cancer periphery and within the stroma, consistent with an immune-excluded phenotype. Conclusions: Residual cancer–stroma topology quantified from standard H&E slides yields independent prognostic signals after NT in PDAC, provides a cellular immune correlate for spatial risk, and motivates prospective validation and spatially informed adjuvant strategies.

130 Background: The COVID-19 pandemic markedly affected the U.S. health care system and may have altered the diagnosis and management of pancreatic cancer. We examined national trends in pancreatic cancer diagnoses before and throughout the first two years after the onset of COVID-19 in the United States, using the latest data from the Surveillance, Epidemiology, and End Results (SEER) database. Methods: We queried the SEER database for cases of pancreatic cancer diagnosed between 2019 and 2021 using ICD-O-3 codes C25.0-C25.9. Disease stage was categorised as localised, regional, distant, or unknown according to the SEER combined summary staging system. Case counts and incidence rates were compared across 2019, 2020, and 2021, with year-to-year differences assessed for statistical significance using χ² tests. Results: The overall number of cases of PDAC diagnosed in 2019, 2020, and 2021 (including year-to-year changes) were 13,457, 13,153 (-2.3%, p<0.05), and 13,998 (+6.4%, p<0.001). Among the known SEER summary staging for PDAC, 52.3% of cases were categorised as “distant” at the time of diagnosis in 2019, compared to 53.6% (+2.4%, p<0.05) in 2020, and 52.0% (-2.8%, p<0.05) in 2021. This reflected an overall change of -0.5% in “distant” PDAC diagnoses from 2019 to 2021 (p>0.05). Conclusions: Significantly fewer cases of PDAC were diagnosed in 2020 compared with 2019, followed by a significant increase in 2021 to above pre-pandemic levels. The proportion diagnosed as distant was significantly higher in 2020 than in 2019 but did not differ significantly between 2019 and 2021. These findings suggest a transient shift toward more advanced-stage PDAC diagnoses during the first year of the COVID-19 pandemic with likely delays in diagnosis, which returned to baseline in 2021.

129 Background: Pancreatic ductal adenocarcinoma (PDAC) presents with significant morbidity and mortality. Five-year survival at 13% consistently remains among the lowest of all cancers. We undertook a population-level risk analysis of sociodemographic risk factors (sex, age, ethnic, and geographic) that may inform closer monitoring of those with increased likelihood of developing PDAC. Methods: PDAC incidence data from 2000 to 2022 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, representing approximately 37% of the US population. Age-adjusted incidence rates (AAIRs) were calculated by race, sex, age group, and county-level rural–urban classification. Incidence is reported per 100,000 population. Temporal trends were assessed using annual percent change (APC) estimated via weighted least-squares regression. Results: Between 2000 and 2022, the overall AAIR of PDAC was 12.6. Incidence was highest among Black individuals (16.1), followed by White (12.7) and Hispanic (11.7) individuals, and was consistently higher in males (14.3) than in females (11.2). Temporal trends did not differ significantly by sex, with annual increases of +0.8% in males and +0.9% in females. Incidence increased progressively with age across all racial and ethnic groups in both sexes. While overall incidence was comparable between urban and rural counties, rural counties experienced a significantly faster rise in incidence (+1.3% vs. +0.8% APC; p<0.05). Conclusions: PDAC incidence has increased from 2000 to 2022 across both sexes at all ages and across all ethnicities. Those most at risk include males and Black individuals, with rates rising faster in rural counties. Better epidemiological understanding of developing trends of at-risk patients may inform screening strategies for patients at high risk of developing PDAC. Incidence rate (per 100,000 population) and annual change in PDAC (95% CI with Tiwari modification). Rate Trend Sex Male 14.3 (14.2-14.4) 0.8 (0.7-0.9) Female 11.2 (11.1-11.3) 0.9 (0.8-1.0) Age 40-44 years 2.7 (2.6-2.8) 1.3 (0.8-1.8) 45-49 years 5.6 (5.4-5.8) 0.8 (0.5-1.1) 50-54 years 10.9 (10.8-11.1) 0.6 (0.4-0.9) 55-59 years 19.2 (19.0-19.5) 1.0 (0.7-1.3) 60-64 years 30.8 (30.0-31.1) 0.8 (0.5-1.0) 65-69 years 45.9 (45.0-46.4) 0.9 (0.7-1.0) 70-74 years 62.2 (62.0-62.8) 0.8 (0.6-0.9) 75-79 years 79.7 (79.0-80.6) 1.0 (0.8-1.2) 80-84 years 94.7 (94.0-95.8) 0.9 (0.7-1.1) 85-89 years 104.6 (103-106.1) 0.8 (0.5-1.1) 90+ years 101.7 (100-103.6) 0.4 (0.1-0.8) Race White 12.7 (12.6-12.8) 1.1 (1.0-1.2) Black 16.1 (16-16.3) 0.3 (0.2-0.5) American Indian/Alaska Native 10.5 (10.0-11.1) 1.4 (0.4-2.4) Asian or Pacific Islander 10.2 (10.0-10.4) 0.6 (0.4-0.8) Hispanic 11.7 (11.5-11.8) 0.7 (0.4-0.9) Location Urban 12.6 (12.5-12.7) 0.8 (0.7-0.9) Rural 12.6 (12-12.7) 1.3 (1-1.5)

9010 Background: BO among oncology professionals is prevalent and may have changed following the COVID-19 pandemic. We conducted a meta-analysis of MENA studies to evaluate temporal trends in overall burnout and subdomains, identify contributing predictors, and assess the screening performance of thought of quitting oncology (TQ). Methods: Ten cross-sectional studies (N = 2,486) reporting Maslach Burnout Inventory (MBI) outcomes were included: six pre-COVID and four post-COVID. Pooled prevalence estimates were generated for emotional exhaustion (EE), depersonalization (DP), personal accomplishment (PA), and overall BO. Study-level meta-regression evaluated the effects of time period (pre- vs post-COVID), demographics, specialty, and their interaction on observed trends. Performance of TQ was assessed as a screening tool with pooled sensitivity, specificity, and predictive values. Results: The pooled prevalence of BO was 57.1% (95% CI, 40.6–72.8), increased from 48.2% in the pre-COVID period to 77.2% post-COVID (Δ +29.0 percentage points). High EE increased from 41.3% pre-COVID to 70.9% post-COVID (Δ +29.6 percentage points). DP increased from 36.8% to 55.8% (Δ +19.0 percentage points). Low PA showed minimal change (35.4% pre-COVID vs 35.1% post-COVID; Δ −0.3 percentage points). The heterogeneity estimate was high due to inter-study differences related to time period, setting, and baseline burnout prevalence, which were statistically adjusted for. TQ screening demonstrated reasonable sensitivity (82.4%) and PPV (79.9%), but low specificity (46.5%) and NPV (50.5%). Table 1 shows study-level factors contributing to BO prevalence trends. Conclusions: BO among oncology professionals increased post-COVID in the MENA region. The rise was driven by age-dependent effects plus time period. EE increased uniformly, while DP and low PA showed more complex patterns. A single-item question assessing TQ demonstrated strong rule-in screening utility for identifying clinicians at risk. Meta-regression analysis of study-level moderators of BO prevalence. Outcome Best Predictor(s) R² Pattern EE Period + Age + Med Onc. % 86.2% Additive effects: Post-COVID, younger, more Med Onc. independently increase EE DP None significant 0.0% PA Period × Age 50.4% Moderation: Age moderates pandemic effect on PA Overall Burnout Period × Age 55.3% Moderation: Age moderates pandemic effect on BO

813 Background: Epidemiological data on gastrointestinal (GI) cancers in conflict-affected regions such as Syria are severely limited. Our study aims to fill in significant gaps in data by evaluating the demographics of Syrian patients diagnosed with new GI malignancies over a three-year period. Methods: This is a retrospective epidemiological study conducted at Al-Bairouni University Hospital – Syria’s national cancer center serving 60-70% of the country’s cancer patients. We included all patients diagnosed with GI malignancies (esophagogastric [EG], hepatocellular [HCC], biliary tract [BTC], pancreatic [PC], colorectal [CRC] cancers, and others) between Jan 2022 - Dec 2024. Data extracted from hospital records included sex, age at diagnosis, cancer stage, smoking status, and governorate of residence. Patients were grouped by disease group and year to assess annual trends. Institutional ethical approval was obtained to perform the study. Results: A total of 3,493 patients were diagnosed with GI cancers during the study period: 1,220 in 2022, 905 in 2023, and 1,368 in 2024 (Table 1). Across all years, a consistent male predominance was observed (60.1%). The average age at diagnosis was 59 years, 37.8% of patients were smokers, and 48.3% of all cases had advanced/metastatic disease at diagnosis. CRC (1,779) and EG (830) were the most common GI cancers. The highest patient loads originated from Damascus (17.6%) and Rural Damascus (17.5%), followed by central governorates such as Homs (9.7%) and Hama (9.3%). Notably, patients from more distant and underserved governorates such as Deir ez-Zor (7.0%), Aleppo (6.58%), and Al-Hasakeh (6.79%) accounted for a significant proportion of the GI cancers presenting to our center. Conclusions: To our knowledge, this study provides the first comprehensive multi-year dataset of GI cancers in Syria, with representation from all 14 governorates in the country. More than a third of our cohort were smokers and nearly half were diagnosed with advanced disease, demonstrating a need for public heath efforts to tackle tobacco use and improve screening & early detection. This dataset offers a foundation for future public health planning and research efforts in the region. Demographics of GI cancers diagnosed 2022-2024. Diagnosis 2022 Cases 2023 Cases 2024 Cases Total Cases Average Age Male Sex (%) Smokers (%) Advanced/Metastatic at diagnosis EG 311 217 302 830 56.1 519 (62.5%) 379 (45.7%) 370 (44.6%) HCC 88 46 61 195 59.2 134 (68.7%) 82 (42.1%) 116 (59.5%) BTC 34 43 54 131 58.4 69(52.7%) 40 (30.5%) 79 (60.3%) PC 118 122 160 400 58.4 249 (62.3%) 180 (45%) 247 (61.8%) CRC 620 444 715 1779 57.6 1008 (56.7%) 582 (32.7%) 805 (45.2%) Others (anal, small intestine, unknown primary) 49 33 76 158 55.5 75 (47.5%) 59 (37.3%) 69 (43.7%)

809 Background: Barriers to necessary care can pose a significant burden on patients with cancer, even more so in places of conflict. Following a devastating 14-year war in Syria, there is limited data published on access to cancer care and the impact that barriers to management have on our patients. We surveyed patients presenting for cancer care to better understand the challenges they faced. Methods: This cross-sectional study included adult patients with a confirmed gastrointestinal (GI) cancer diagnosis presenting to Al-Bairouni University Hospital for care. Data was collected through face-to-face interviews using a structured questionnaire adapted for the Syrian context. The survey covered six key areas: Demographic & Clinical, Healthcare System Barriers, Financial Barriers, Geographic & Security Barriers, Reasons for Diagnostic Delays, and Psychosocial Impact. Multivariate analysis via logistic regression was conducted to determine which responses were associated with a higher odds ratio (OR) of having a late-stage (III/IV) cancer diagnosis. Results: A total of 122 patients diagnosed with a GI cancer were enrolled. The mean age was 57.4 years (±11.2 SD), with a male predominance (68%, n=83). Advanced diagnostics (CT/MRI/biopsy) and radiation therapy were inaccessible for 55% (n =67) and 61% (n =74) of patients, respectively. Systemic therapy drugs were "rarely" or "never" available for 35% (n=43) of patients, and 12% (n=15) reported waiting over three months for an appointment. The costs of medications "greatly" or "very greatly" impacted 88% (n=107) of patients. Over two-thirds of patients reported that essential pain control medications (e.g., morphine) were "rarely" or "never" available (68%, n=83). Nearly two-thirds (65%, n =79) reported that security concerns "greatly" or "somewhat" affected their ability to access treatment. An overwhelming 87% (n=106) of patients reported a negative psychological impact from their treatment course. Patient responses associated with a higher OR of late-stage cancer diagnosis are present in the table. Conclusions: Patients in Syria with GI cancers face profound systemic, financial, geographic, and psychosocial challenges throughout their care journey. More than half were diagnosed at advanced stages, with diagnostic delays strongly linked to prolonged waiting times and financial strain. Financial toxicity was highly evident, resulting in treatment compromise and asset liquidation. This data should serve as a reference for future public health and humanitarian efforts in the region. Factors associated with late-stage (III/IV) diagnosis of GI malignancies (multivariate logistic regression). Variable Adjusted Odds Ratio (aOR) 95% Confidence Interval p-value Waiting Time First Oncology appointment >1 month 3.10 1.45 - 6.62 0.003 * Unemployed due to cancer 2.85 1.20 - 6.78 0.018 * Sold Assets to Finance Care 2.40 1.10 - 5.25 0.028 * *Statistically significant at p < 0.05.

426 Background: Testing for DPYD gene variations prior to administration of fluoropyrimidines ([FP] e.g. 5-FU or capecitabine) can determine if patients are at risk of significant toxicity and may benefit from dose reduction or elimination of chemotherapy. Barriers to testing include lack of recommendations in US guidelines for routine DPYD testing, absence of insurance coverage, and limitations in provider support. We designed an electronic health record (EHR)-based intervention to support shared decision-making (SDM) between providers and patients regarding DPYD testing. Methods: We built an EHR alert identifying all patients initiating FP without DPYD testing. The alert fired to remind providers upon signing FP. Clinical decision support (CDS) was included in the alert to help with DPYD testing selection along with an educational note template containing the incidence of DPYD deficiency, rationale for testing, test costs, and turnaround time. Interactions with the EHR were recorded to determine why providers declined ordering pharmacogenomic testing. Testing rates and results for patients initiating FP were collected from the EHR. Finally, providers were surveyed to determine the impact of the alert on conversations with patients as well as the utility of the embedded CDS and educational note template. Results: Within the first 8 months after alert activation, 34 patients completed DPYD testing of 444 starting FP (testing rate of 7.7%) vs the baseline testing rate in the 3 months prior to alert go-live of 6.8% (p = 0.86 via chi-squared analysis, two-tailed). Of the 34 patients, 5 were intermediate DPYD metabolizers. Reasons for alert dismissal per provider selection were: “Patient already tolerated prior fluoropyrimidines” (15.7%), “Patient declines” (12.9%), “Will order separately” (5.7%), “Not discussed as not appropriate” (5.3%), and “Not discussed, deferred” (60.4%). Thirty-nine providers (n = 77 eligible) responded to the survey; 22 prescribed FP in their practice and had encountered the alert. 21 (95.5%) of these reported the alert was “Very Useful” or “Somewhat Useful” and 18 (81.8%) used the DPYD testing options available in the alert. Sixteen (72.7%) discussed DPYD testing more frequently with patients as a result of the alert. Barriers to DPYD testing were “Concerned about the impact of lowering FP dosing” and “Lack of knowledge about DPYD testing”, while “Cost of DPYD testing” was scored lowest. Conclusions: Utilizing an EHR alert with embedded CDS had a positive impact on provider awareness and led to more discussions regarding DPYD pharmacogenomic testing with patients in line with current FDA recommendations. Limitations in provider knowledge regarding DPYD testing and concerns about lowering chemotherapy doses posed barriers to ordering testing. Further interventions including additional education are required.

406 Background: Anxiety is highly prevalent among oncology patients, often arising from uncertainty around diagnosis, treatment options, and prognosis. Elevated anxiety can impair decision-making, reduce treatment adherence, and diminish overall quality of life. Effective second opinion consultations may help mitigate anxiety and increase patients’ confidence in recommending healthcare services to others. Our study evaluates the impact of oncology second opinion (OSO) consultations on anxiety level (AL) and confidence in the organization (CIO) providing the second opinion, i.e., Cincinnati Cancer Advisors (CCA) and Naples Cancer Advisors (NCA). Methods: The study included patients with cancer diagnoses, age ≥18 years, who were served in person for OSO at CCA and NCA. A survey was used before and after consultation, measuring AL (scale 1- 10) and CIO level (scale 1 - 10), assessed by asking patients how likely they would refer loved ones to the organization. After the content and face validation, patients completed the survey anonymously, put it in a sealed envelope, and dropped it in a dedicated box. Data was analyzed using paired t-tests to compare the change from pre- to post-consultation scores. Spearman’s correlation test was used to assess the relation between the changes in AL and CIO. Statistical significance was assessed using an alpha-level of 0.05. Analyses were conducted via R and R Studio (version 2025.5.1.513). Results: Overall, 46 consecutive patients participated (45 completed AL pre and post visit survey and 43 completed the CIO pre and post visit survey). The mean pre-consultation anxiety score was 5.92 (SD = 2.58), and the post-consultation score was 3.87 (SD = 2.10), demonstrating a significant reduction (mean paired difference = -2.05; p < 0.0001). The mean pre-consult CIO was 8.21 (SD = 2.03), increasing to 9.73 post-consultation (SD = 0.53), indicating a significant improvement (mean paired difference = 1.66; p < 0.0001). The correlation between changes in AL and CIO was not statistically significant, which may be attributed to the high baseline CIO scores (ceiling effect) and the small sample size. Conclusions: Oncology second opinion was associated with a marked decrease in patient AL and a significant increase in CIO. The patient survey will continue to recruit additional participants to increase the sample size and explore the correlation between changes in AL and CIO. Studying the downstream impact on patient experience and outcome is warranted.

e14626 Background: Despite advancements in neoadjuvant therapy and surgical techniques, patients with pancreatic ductal adenocarcinoma (PDAC) often experience high recurrence rates after total neoadjuvant therapy (TNT) and resection. Existing tumor response scoring systems, such as the College of American Pathologists (CAP) guidelines, fail to stratify recurrence risk effectively, emphasizing the need for novel, objective approaches. Methods: This study evaluated spatial characteristics of residual cancer and stroma in a multi-site cohort of 203 patients with resected PDAC following TNT, not having achieved a major pathologic response (CAP 2 or 3). Whole slide images (WSI) of hematoxylin and eosin-stained sections were digitized and analyzed using artificial intelligence to perform tissue segmentation. Metrics quantifying spatial morphology and configuration, inspired by principles of landscape ecology, were computed to explore spatial features of the tumor microenvironment (TME). Statistical models (recursive partitioning and regression tree [RPRT] model and Cox model with backwards eliminations) incorporating these features were developed to stratify recurrence risk. Results: Five metrics were used for risk classification model build. Three models successfully classified patients into high- and low-risk groups based on spatial metrics. Models demonstrated moderate discriminatory power (C-statistics: 0.560–0.566) and showed that increased tumor fragmentation, like stromal patch density and cancer patch shape index, were strongly associated with improved outcomes. Conclusions: Integrating spatial metrics of cancer-stroma configuration enhances risk stratification beyond conventional scoring systems. Given increased tumor fragmentation is associated with improved outcomes, these data indirectly suggest ecological mechanisms of treatment resistance. This approach offers a pathway toward personalized post-operative management strategies to improve outcomes in PDAC. Risk classification models. Model Description Event/n Median DFS (95% CI) HR(95% CI) p-value C-statistics 1(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 87 / 101 8.22(5.72 – 10.1) 1.64(1.20 – 2.25) 0.002 0.562 Low risk: log standard deviation of the stroma shape index ≤ 0.651 71 / 102 11.90(9.24 – 25.1) Ref 2(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 & mean cancer shape index ≤ 1.775 58 / 63 7.23(5.19 – 9.63) 1.82(1.31 – 2.52) 0.0003 0.560 Low risk: (log standard deviation of the stroma shape index > 0.651 & mean cancer shape index > 1.775) or log standard deviation of the stroma shape index ≤ 0.651 100 / 140 11.57(9.24 – 17.92) Ref 3(Backwards elimination) High risk: PI * > median 86 / 101 8.02(6.08 – 9.86) 1.73(1.26 – 2.37) 0.0007 0.566 Low risk:PI * ≤ median 72 / 102 15.72(9.97 – 25.05) Ref *PI: (0.2701 * log mean stroma area) + (0.3905 * log edge density).

Abstract Purpose: KRAS G12C inhibitors can treat KRASG12C-mutant advanced colorectal cancers and pancreatic ductal adenocarcinomas (PDAC), but alterations in Kirsten rat sarcoma (KRAS), EGFR, BRAF, MAP2K1, and other genes bypass KRAS inhibition and reduce therapy efficacy. Our study evaluates the genetic landscape of candidate primary resistance alterations relevant to KRAS targeting in KRASG12C-mutant colorectal cancer and PDAC. Experimental Design: We analyzed two cohorts (national database and Mayo) of patients with advanced colorectal cancer or PDAC tested with next-generation sequencing of ctDNA via Guardant360. Cohorts were divided into three groups: KRASG12C alone (KRASG12C without a resistance gene), KRASG12C with resistance (KRASG12C and ≥1 candidate resistance gene), and KRAS not detected. Candidate resistance mutations were inferred from the reported literature. Results: Among the national (13,603 colorectal cancer and 5,016 PDAC cases) and Mayo (741 colorectal cancer and 422 PDAC cases) cohorts, resistance alterations were identified in a considerable number of KRASG12C cases (46.5% of national colorectal cancer, 16.4% of national PDAC, 53.8% of Mayo colorectal cancer, and 36.4% of Mayo PDAC). The presence of resistance alterations was associated with a trend toward worse overall survival in KRASG12C colorectal cancer (P = 0.05). Conclusions: Putative resistance alterations are prevalent in PDAC and colorectal cancer and may limit monotherapy efficacy. Identifying these alterations has potential implications in optimal patient selection for targeted therapies and the development of combination therapy strategies to overcome primary resistance.