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PURPOSE We investigated time to pregnancy, efficacy and safety of fertility preservation, and assisted reproductive technologies (ARTs) in women with early hormone receptor–positive breast cancer (BC) desiring future pregnancy. PATIENTS AND METHODS POSITIVE is an international, single-arm, prospective trial, in which 518 women temporarily interrupted adjuvant endocrine therapy to attempt pregnancy. We evaluated menstruation recovery and factors associated with time to pregnancy and investigated if ART use was associated with achieving pregnancy. The cumulative incidence of BC-free interval (BCFI) events was estimated according to the use of ovarian stimulation at diagnosis. The median follow-up was 41 months. RESULTS Two hundred seventy-three patients (53%) reported amenorrhea at enrollment, of whom 94% resumed menses within 12 months. Among 497 patients evaluable for pregnancy, 368 (74%) reported at least one pregnancy. Young age was the main factor associated with shorter time to pregnancy with cumulative incidences of pregnancy by 1 year of 63.5%, 54.3%, and 37.7% for patients age <35, 35-39, and 40-42 years, respectively. One hundred and seventy-nine patients (36%) had embryo/oocyte cryopreservation at diagnosis, of whom 68 reported embryo transfer after enrollment. Cryopreserved embryo transfer was the only ART associated with higher chance of pregnancy (odds ratio, 2.41 [95% CI, 1.75 to 4.95]). The cumulative incidence of BCFI events at 3 years was similar for women who underwent ovarian stimulation for cryopreservation at diagnosis, 9.7% (95% CI, 6.0 to 15.4), compared with those who did not, 8.7% (95% CI, 6.0 to 12.5). CONCLUSION In POSITIVE, fertility preservation using ovarian stimulation was not associated with short-term detrimental impact on cancer prognosis. Pregnancy rates were highest among those who underwent embryo/oocyte cryopreservation followed by embryo transfer.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769 ), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047 ), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

e13740 Background: Hepatocellular carcinoma (HCC) ranks as the 6th most common cancer and as the 3rd leading cause of cancer-related mortality. With immunotherapy improving survival rates, the relevance of major adverse cardiovascular and cerebrovascular events (MACCE) is increasing. We aim to explore the racial disparities in MACCE among patients with HCC, thus leading to a better understanding of the interplay of these conditions with social determinants of health. Methods: Using ICD-10 codes, patients with HCC were identified from National Inpatient Sample 2019 database. We included all-cause in-hospital mortality (ACIHM), acute myocardial infarction (AMI), atrial fibrillation (AF), cerebrovascular accident (CVA), and sudden cardiac death (SCD) as MACCE for the outcomes. Baseline characteristics including demographics, comorbidities; and MACCE outcomes were compared using chi-square for categorical or ANOVA for continuous data (statistical significance determined as p-value <0.05) and results were stratified based on patient’s races. Results: Out of the total sample size of 89,615 patients admitted with a diagnosis of HCC, 60.14% (53,895) were White, 13.67% (12250) were Black, 15.64% (14015) were Hispanic, 6.48% (5805) were Asian/Pacific Islander, 0.8% (720) were Native American, while 3.27% (2930) belonged to other ethnicities. There were significant racial differences in comorbidities with hypertension being most prevalent in Black patients (42.53%), diabetes mellitus in Native American patients (45.14%) and dyslipidemia in Asian/Pacific Islander patients (32.39%). When compared to White patients, ACIHM was the significantly higher in Black patients with adjusted odds ratio (aOR) of 1.305 (95% CI 1.123-1.517, p=0.001), Asian/Pacific Islander patients with aOR 1.271 (95% CI 1.024-1.578, p=0.03) and Other races patients with aOR 1.578 (95% CI 1.2-2.076, p=0.001). AF was significantly lower in all races when compared to White patients. CVA was significantly higher in Black patients with aOR 1.654 (95% CI 1.329-2.059, p<0.001) compared to White patients. SCD was significantly higher in Asian/Pacific Islander patients with aOR 2.22 (95% CI 1.364-3.612, p=0.001) when compared to White patients. https://docs.google.com/document/d/1wM_b0jmNjChKEfpyj5SL6HmSKEhDo0N3X5H76jC-w0I/edit?usp=sharing Conclusions: In patients with HCC, Asian/Pacific Islander patients had higher ACIHM and SCD while Black patients had higher ACIHM and CVA as compared to White patients. This study highlights the importance for development of healthcare strategies stratified by race which may aid to mitigate the higher risk of MACCE in certain races. Further research involving possible genetic influences and social determinants of health contributing to poorer outcomes in people of color becomes imperative.

e13718 Background: Colorectal cancer (CRC) is the third-leading cancer worldwide and racial minorities bear a disproportionate burden of this disease. Methods: We searched the clinicaltrials.gov database for all the completed clinical trials conducted on adult patients until 2023 in the United States. In intervention trials, we manually abstracted data on the racial distribution of enrollees, phases, tumor histology, intervention type, and year of completion. We divided interventions into chemotherapy, radiotherapy, surgery, immunotherapy, behavioral, diagnostic tests, and others. To quantify the racial disparity, we calculated the enrolment ratio (ER) as the observed ratios of racial participation in the study compared to the prevalence in colorectal cancer per the 2009-2019 Surveillance, Epidemiology and End Results (SEER) database. We also conducted subgroup racial enrollment based on clinical trial and type of intervention. Results: We identified 394 studies, of which 252 studies (64%) had racial distribution published, including 138814 participants. Most studies were phase 2 trials (168), followed by phase 1/2 trials (49) and phase 3 studies (43). The racial breakdown included 88677 White participants (63.9%), 23230 were African Americans (16.7%), 9963 were Asians (7.1%), 4398 were of other races (3.2%), and 12546 were of unknown race (9.0%). The frequency of including racial data was 100% in Phase 1 studies, 56.5% in Phase 2, 58.1% in Phase 3, and only 16% in Phase 4. A total of 185 were immunotherapy trials, out of which 63 studied chemotherapies, radiotherapy and/ or surgery along with immunotherapy. Racial enrolment data was reported in 68.6 %, 58% and 59.3% in immunotherapy, chemotherapy, and radiotherapy interventions respectively. The ERs of whites, blacks, and Asians were 0.8, 1.3, and 0.9, respectively (Table). However, ER in subgroups with specific interventions, such as chemotherapy, immunotherapy, and radiotherapy, were 0.5, 0.4, and 0.6, respectively. Conclusions: African Americans are underrepresented in CRC intervention trials. Equal access and tailored strategies for cultural and linguistic differences are needed for fair participation. [Table: see text]

1614 Background: Despite the unique ability of machine learning (ML) techniques to uncover complex interactive effects in datasets, studies exploring predictors of clinical trial enrollment have largely used standard statistical methods to discern associations. Furthermore, there have been limited applications of ML to close existing disparities in clinical trial enrollment of underrepresented patients in neuro-oncology. This study aims to use supervised machine learning to define and validate primary contributors of therapeutic clinical trial enrollment for a) all patients, b) women and c) NIH-designated minority patients with low- and high-grade glioma. Methods: Adult glioma patients who received care from the UCSF Brain Tumor Center between 1997- 2017 were identified in a prospective registry. Bootstrap forest (BF) and Recursive Partitioning (RP) models were created by randomly dividing patients in a 70/30 split into development (DEV) and validation (VAL) cohorts among all patients, women, and NIH-designated minority patients, separately. Model performance was assessed using the area under the curve (AUC) in the DEV and VAL cohorts. Results: Among 1042 patients, 350 patients (33.6%) enrolled in a therapeutic clinical trial. There were 445 women (42.7%), of which 144 (32.4%) enrolled, and 141 minority patients (13.5%), of which 39 (27.7%) enrolled. For all patients, in order of decreasing influence, the BF model selected median neighborhood household income, age, neighborhood poverty level, distance from hospital, tumor location, tumor volume, treatment with chemotherapy, occupation, KPS, insurance status, employment status, seizure at presentation, and volumetric extent of resection (EOR) to predict trial enrollment (DEV AUC: 0.984; VAL AUC: 0.746). For women, the BF model selected distance from hospital, age, household income, neighborhood poverty level, tumor location, treatment with chemotherapy, and KPS for trial prediction (DEV AUC: 0.972; VAL AUC: 0.746), whereas for minority patients, the BF model selected neighborhood poverty level, age, occupation, distance from hospital, tumor volume, insurance status, employment status, and EOR to predict trial enrollment (DEV AUC: 0.9830; VAL AUC: 0.769). The RP model for women designated those with non-White race as less likely to enroll (DEV AUC: 0.735; VAL AUC: 0.665) while the RP model for minority patients characterized those who preferred a non-English language or who were divorced or widowed as less likely to enroll (DEV AUC: 0.775; VAL AUC: 0.601). Conclusions: Supervised machine learning models achieved similar predictive performance among patient subgroups, while uncovering interactions between gender identity, minority status, and sociodemographic variables. These findings can guide targeted recruiting efforts to advance equitable trial enrollment for women and minorities.

1611 Background: Due to its high prevalence, colorectal cancer (CRC) forms a considerable burden on the healthcare system. Advancements in treatment modalities like immunotherapy have led to significant improvement in the 5-year survival. This, along with the cardiotoxic therapy regimens results in a remarkable incidence of major cardiovascular and cerebrovascular events (MACCE). Thus, it becomes imperative to address the intricacies of factors including racial disparities in MACCE, as these aid with facilitating equitable management of all CRC patients. Methods: Using ICD-10 codes, patients with CRC were identified from National Inpatient Sample 2019 database. We included all-cause in-hospital mortality (ACIHM), acute myocardial infarction (AMI), atrial fibrillation (AF), cerebrovascular accident (CVA), and sudden cardiac death (SCD) as MACCE for the outcomes. Baseline characteristics including demographics, comorbidities; and MACCE outcomes were studied using chi-square for categorical or ANOVA for continuous data (statistical significance determined as p-value < 0.05) and results were stratified based on patient’s races. Results: A total sample patient population of 171,695 patients with a diagnosis of CRC were identified of which 70.71% (121,410) were White, 13.85% (23,790) were Black, 9.15% (15,720) were Hispanic, 3.23% (5,555) were Asian/Pacific Islander, 0.5% (840) were Native American, and 2.55% (4380) belonged to Other races. Substantial differences in the prevalence of comorbidities were noted with hypertension (46.32%) and renal failure (24.74%) being more common in Black patients, diabetes mellitus (37.5%) in Native American patients, and dyslipidemia (37.89%) in White patients. Upon comparison with White patients, the ACIHM was higher in Black patients with adjusted odds ratio (aOR) of 1.23 (95% CI 1.057-1.432, p = 0.007) and Asian/Pacific Islander patients with aOR of 1.359 (1.014-1.823, p = 0.04). While AMI was found to be lower in all races, as compared to White patients, AF was remarkably higher in all races. CVA was higher in Black patients as compared to White patients with aOR of 1.626 (95% CI 1.401-1.886, p < 0.001). SCD was substantially higher in Black patients with aOR 2.059 (95% CI 1.478-2.869, p < 0.001), and in Hispanic patients with aOR 1.743 (95% CI 1.1-2.761, p = 0.018), when compared to White patients. Conclusions: The study noted higher prevalence of MACCE across the board with poorer outcomes in non-White populations, which highlights the urgent need for resource allocation to improve outcomes. This has to be done in pre and post cancer treatment patients, especially in high risk populations. Additionally, the role of cardio-oncology service at every stage of management of CRC appears to be crucial.

1604 Background: Diversity in clinical studies is essential to address health disparities, but racial and ethnic minorities are often underrepresented in clinical studies, especially in precision medicine studies using genetic data (1). BASECAMP-1 (NCT04981119) is an ongoing prescreening study to identify patients with unresectable advanced or metastatic solid tumors and tumor-associated HLA-A*02 LOH for the EVEREST-1 and -2 Tmod chimeric antigen receptor T-cell therapy trials. When enrollment began in 2021, eligibility for Part 1 was restricted to patients with germline HLA-A*02:01 based on preclinical data. Additional analysis revealed the blocker in the Tmod construct had activity across HLA-A*02 subtypes (Mock, et al. Mol Ther Oncolytics.2022). Eligibility for Part 1 was then expanded to all HLA-A*02 subtypes, allowing enrollment of more diverse patient populations. HLA-A*02 allele subtypes vary by ethnicity and race; the frequency of HLA-A*02:01 is 96% in non-Hispanic Whites, but ranges from 53% to 73% in other ethnicities and races. The frequency of all other HLA-A*02 allele subtypes (HLA-A*02:XX) is <5% in non-Hispanic Whites but up to 66% in other ethnicities and races (2,3). Methods: Patients eligible for BASECAMP-1 were identified at United States study sites. All patients screened before January 16, 2024, for Part 1 were included for demographic and central lab HLA-A typing. The % increase in eligibility and % of heterozygous HLA-A*02 patients with HLA-A*02:XX were calculated by ethnicity and race. Results: A total of 1124 patients were screened for germline HLA-A*02 typing; 431 patients were HLA-A*02:01 heterozygous, of whom 37 (9%) were Hispanic, 14 (3%) African American (AA), 2 (<1%) American Indian or Alaska Native, 17 (4%) Asian or Pacific Islander (API), and 324 (75%) non-Hispanic White (Table). The eligibility expansion identified 62 patients with HLA-A*02:XX heterozygosity, of whom 6 (10%) were Hispanic, 6 (10%) AA, 19 (31%) API, and 25 (40%) non-Hispanic White. Conclusions: By expanding enrollment to include HLA-A*02:XX, 16% more Hispanic, 43% more AA, and 112% more API patients were identified, improving the diversity in this trial compared with that of initial enrollment. 1. Aldrighetti, et al. JAMA Netw Open 2021. 2. Ellis, et al. Human Immunol. 2000. 3. Gragert, et al. Human Immunol.2013. Clinical trial information: NCT04981119 . [Table: see text]

1597 Background: The impact of COVID19 pandemic on patient health beliefs and healthcare systems has adversely affected mammographic breast cancer screening (MBCS) during the initial stages of the pandemic. The aims of our study were to determine whether the initial decrease in MBCS rates persisted or if there was a rebound in later stages and to quantify the impact on urban and rural populations. Methods: This retrospective observational study analyzed data from March 2017 to March 2023 to assess whether eligible women received annual MBCS during this timeframe. We included women aged 40-75 years, drawn from the integrated Mayo Clinic system, encompassing nearly 60 primary care practices in Arizona, Florida, Iowa, Minnesota, and Wisconsin, representing a broad cross-section of the United States (US) population. US census data was utilized to classify a county as urban or rural. We divided the study period into 4 categories:1) pre-COVID-19 pandemic (March 1, 2017-March 10, 2020), 2) early pandemic (March 11, 2020-March 10, 2021; pre-vaccination period), 3) mid- pandemic (March 11, 2021-March 10, 2022; delta and omicron variant dominant period), and 4) late pandemic (March 11, 2022-March 1, 2023; recovery period). Utilizing the Poisson regression model, we compared the incidence rate ratio (IRR) for rates of MBCS across the 4 predefined time periods. Multivariable modeling was performed to assess the significance of MBCS rates with urbanicity while controlling for the year (2017-2022) and age. Results: By race and ethnicity, the women in this cohort were White (92%), Black (3.1%), Asian (3%) and other (1.9%). The median age was 57 years and the cohort included 239, 804 women aged 40-75 years. MBCS rates was 49.2% in 2017, 47.1% in 2018, 46.4% in 2019, and decreased to 42.1% in 2020 and improved to 44.7% in 2021 and 43.8% in 2022. Compared with the pre-COVID-19 pandemic period, there was a significant decrease in MBCS rate in the early pandemic (IRR= 0.886, 95% CI 0.879, 0.892, p<0.001). Though the MBCS rate improved in the mid-pandemic period, it remained below the pre-pandemic level (IRR=0.941, 95% CI 0.934, 0.948, p<0.001). Similarly, during the late stage of the pandemic, the MBCS rate remained lower than the pre-pandemic level (IRR=0.922, 95% CI 0.915, 0.928, p<0.001). Rural counties had a lower MBCS rate compared with urban counties (IRR = 0.936, 95% CI 0.931, 0.941, p<0.001). Conclusions: This study confirms the negative impact of the early COVID-19 pandemic on MBCS, and it revealed its persistent effect, as the current MBCS rate remains below the pre-pandemic rate. These findings were more evident in rural counties. Factors contributing to the long-lasting impact are being analyzed with the intent to develop and implement targeted solutions to improve the MBCS rate.