Jazieh, Khalid

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