BACKGROUND:Federally mandated breast density notifications motivate consideration of supplemental breast magnetic resonance imaging (MRI). OBJECTIVE:To evaluate supplemental breast MRI strategies. DESIGN:Simulation of women at average to 4 times higher-than-average relative risk (RR) for breast cancer incidence undergoing screening digital breast tomosynthesis (DBT) with or without supplemental MRI. DATA SOURCES:Breast Cancer Surveillance Consortium and literature. TARGET POPULATION:Women aged 40 years or older. TIME HORIZON:Lifetime. PERSPECTIVE:U.S. federal payer. INTERVENTION:Screening with DBT with or without breast density-targeted MRI by starting age (40, 45, or 50 years) and interval (annual or biennial). OUTCOME MEASURES:Breast cancer deaths averted, false-positive biopsy recommendations, harm-benefit ratios, and incremental cost-effectiveness ratios (ICERs). RESULTS OF BASE-CASE ANALYSIS:Across all starting ages and intervals, DBT averted 7.4 to 10.5 breast cancer deaths per 1000 average-risk women screened and 23.2 to 33.6 per 1000 women with 4 times higher-than-average risk. Across all RR levels, DBT with supplemental MRI for women with extremely dense breasts (DBT+MRId) averted 0.1 to 0.8 additional breast cancer deaths and resulted in 22 to 186 additional false-positive biopsy recommendations. False-positive biopsies per breast cancer death averted for biennial DBT+MRId for women with 2 times higher-than-average risk were similar to those associated with DBT in average-risk women. For all risk groups, biennial DBT+MRId starting at age 50 years was more effective but less cost-effective than DBT starting at age 45 years. RESULTS OF SENSITIVITY ANALYSIS:The ICERs were sensitive to cancer risk, MRI costs, and false-positive biopsy rates. LIMITATION:Subgroups considered risk and breast density only. CONCLUSION:Supplemental MRI for women aged 40 years or older with extremely dense breasts and higher-than-average risk (RR ≥2.0) had harm-benefit ratios similar to biennial DBT alone and could be cost-effective if MRI costs and false-positive biopsy rates are reduced. PRIMARY FUNDING SOURCE:National Cancer Institute.

Importance:General mammography screening guidelines target women at average risk within a specified age range (age based) and do not consider absolute risk of individual women at a given age (risk based). Objective:To compare outcomes of mammography screening strategies that vary by 5-year risk of invasive breast cancer vs age-based strategies. Design, Setting, and Participants:This decision analytical model used 2 established Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer models and simulated US women born in 1980 who were aged 40 years or older without a prior history of breast cancer. Modeling analyses were conducted from April 2023 to April 2025. Intervention:Digital breast tomosynthesis delivered via 50 screening strategies (3 age based and 47 risk based) vs a no-screening scenario. Five-year absolute invasive breast cancer risk was based on the validated Breast Cancer Surveillance Consortium, version 3 calculator. Women's 5-year breast cancer risk was categorized as low, average, intermediate, or high. Main Outcomes and Measures:Primary outcomes included lifetime number of breast cancer deaths averted and false-positive screening recalls. Lifetime outcomes were averaged across models and expressed per 1000 women screened. Results:Nine risk-based screening strategies were associated with a comparable or greater number of deaths averted than biennial age-based screening from ages 40 to 74 years (B40-74) (range across strategies for mean model estimates, 6.8-7.5 per 1000 women vs 6.8 per 1000 women) as well as reduced false-positive recalls by 8% to 23% (1050-1257 per 1000 women for risk-based screening strategies vs 1365 per 1000 women for B40-74). For example, a risk-based approach using a combination of biennial screening (for women at low risk aged 55-74 years, at average risk aged 50-59 years, at intermediate risk aged 45-54 years, and at high risk aged 40-49 years) and annual screening (for women at average risk aged 60-74 years, at intermediate risk aged 55-74 years, and at high risk aged 50-74 years) would be associated with 6% more breast cancer deaths averted than B40-74 (7.2 vs 6.8 per 1000 women) and 13% fewer false-positive recalls (1190 vs 1365 per 1000 women). Results were consistent across the 2 CISNET models, and the relative difference in breast cancer deaths averted between B40-74 and risk-based screening strategies was more pronounced than for life-years gained. Conclusions and Relevance:In this decision analytical modeling study of breast cancer screening, population risk-based screening using 5-year invasive breast cancer risk was associated with similar or greater benefits than age-based screening as well as reduced false-positive recalls. As personalized medicine advances, risk-based screening is poised to become a cornerstone of breast cancer prevention, offering a more nuanced and tailored approach to patient care.

10517 Background: Current cancer physical activity guidelines recommend clinicians offer individualized ‘physical activity prescriptions’ to cancer survivors. However, there are limited data to support individualized physical activity prescriptions for breast cancer survivors in clinical settings. We aimed to develop a simulation model-based ‘calculation engine’ for a clinical decision tool that could generate individualized breast cancer outcomes associated with physical activity considering the individual characteristics of breast cancer survivors. Methods: We adapted an established and validated simulation model developed within the Cancer Intervention and Surveillance Modeling Network (CISNET) to estimate breast cancer-specific mortality, all-cause mortality, and life-years gained with post-treatment physical activity for women aged 50-75 years at diagnosis with stage I-III breast cancer. Model inputs were derived from clinical trials, cohort studies, national survey, and registry data. Breast outcomes were generated for 41,472 unique subgroups based on all possible combinations of age, hormone status, HER2 status, stage, tumor size, grade, body mass index, surgery, and treatment. External validation was conducted using an independent data source. We summarized 10-year breast cancer and all-cause mortality rates for varying combinations of weekly aerobic (e.g., 2.5-5.0 hours/week) and muscle-strengthening (e.g., ≥2 days/week) activity. Results: Overall, the 10-year breast cancer-specific and all-cause survival rates for stages I-III were 89.1% and 83.2%. These results varied by individual characteristics and physical activity levels. For example, in a 65-69-year-old-woman diagnosed with stage I, hormone receptor-positive, HER2-negative breast cancer, and a body mass index of ≥30kg/m2, the 10-year breast cancer-specific and all-cause survival rates for 0-0.5 hours/week of physical activity were 87.1% and 80.1%, respectively. If the woman was to increase aerobic activity to 0.5-2.5 hours/week, 10-year breast cancer survival increased to 88.5%, and all-cause survival increased to 81.1%. Meeting physical activity guidelines (i.e., 2.5-5.0 hours/week of moderate-intensity aerobic activity; and ≥2-days/week of muscle strengthening activity) was associated with increases in 10-year breast cancer and all-cause survival rates to 93.0% and 82.9%, respectively. The model closely replicated observed rates in independent data. Conclusions: These data provide a calculation engine for a clinical decision tool to support individualized physical activity prescriptions and discussions for breast cancer survivors.

BACKGROUND:Guidelines recommend primary care practitioners ("PCPs") engage women ≥ 75 years in shared decision-making (SDM) around mammography screening. Therefore, we aimed to develop a web-based conversation aid about mammography screening for women ≥ 75 using output from established simulation models to provide screening outcomes based on > 23,000 combinations of individual women's health and breast cancer risk factors. METHODS:We used an end-user centered design approach to develop a prototype web-based conversation aid incorporating feedback. From July 2023 to April 2024, 10 PCPs from a Boston-area health system and a safety-net hospital used the prototype aid during encounters with women ≥ 75 without breast cancer or dementia (n = 30; 1-5 patients per PCP). We observed aid use and assessed clinician effort to involve patients in SDM using OPTION5 (assesses five components of SDM, scores range 0-100). We surveyed PCPs and patients about the aid's acceptability. Patients completed the SDM-process scale (scores range 0-4) to rate the SDM quality experienced. Participants' comments were subject to thematic analysis. RESULTS:Of 10 PCP-participants, seven were female and four were community-based. Of 30 patient-participants, 22 (73%) were non-Hispanic White, 9 (30%) had ≥ 2 Charlson comorbidities and mean age was 78.5 years (SD 2.8). Nine PCPs agreed that the aid helped them with SDM and was easy-to-use; six felt it had too much information; and seven planned to continue using the aid. Patients rated the SDM-process highly (scores = 3.0 [SD 0.9]) and we observed high SDM (mean OPTION5 = 77.9 [SD 20.6]). Participants felt the aid was "empowering" and "helpful for decision-making." After SDM discussions, seven patients intended to stop screening, nine to screen less frequently, and 14 to continue screening regularly. CONCLUSIONS:We developed a novel conversation aid that supports SDM about mammography screening with women ≥ 75 years. Lessons learned will guide revisions of a final tool for testing in a clinical trial.

ImportanceCancer mortality has decreased over time, but the contributions of different interventions across the cancer control continuum to averting cancer deaths have not been systematically evaluated across major cancer sites.ObjectiveTo quantify the contributions of prevention, screening (to remove precursors [interception] or early detection), and treatment to cumulative number of cancer deaths averted from 1975 to 2020 for breast, cervical, colorectal, lung, and prostate cancers.Design, Setting, and ParticipantsIn this model-based study using population-level cancer mortality data, outputs from published models developed by the Cancer Intervention and Surveillance Modeling Network were extended to quantify cancer deaths averted through 2020. Model inputs were based on national data on risk factors, cancer incidence, cancer survival, and mortality due to other causes, and dissemination and effects of prevention, screening (for interception and early detection), and treatment. Simulated or modeled data using parameters derived from multiple birth cohorts of the US population were used.InterventionsPrimary prevention via smoking reduction (lung), screening for interception (cervix and colorectal) or early detection (breast, cervix, colorectal, and prostate), and therapy (breast, colorectal, lung, and prostate).Main Outcomes and MeasuresThe estimated cumulative number of cancer deaths averted with interventions vs no advances.ResultsAn estimated 5.94 million cancer deaths were averted for breast, cervical, colorectal, lung, and prostate cancers combined. Cancer prevention and screening efforts averted 8 of 10 of these deaths (4.75 million averted deaths). The contribution of each intervention varied by cancer site. Screening accounted for 25% of breast cancer deaths averted. Averted cervical cancer deaths were nearly completely averted through screening and removal of cancer precursors as treatment advances were modest during the study period. Averted colorectal cancer deaths were averted because of screening and removal of precancerous polyps or early detection in 79% and treatment advances in 21%. Most lung cancer deaths were avoided by smoking reduction (98%) because screening uptake was low and treatment largely palliative before 2014. Screening contributed to 56% of averted prostate cancer deaths.Conclusions and RelevanceOver the past 45 years, cancer prevention and screening accounted for most cancer deaths averted for these causes; however, their contribution varied by cancer site according to these models using population-level cancer mortality data. Despite progress, efforts to reduce the US cancer burden will require increased dissemination of effective interventions and new technologies and discoveries.

Purpose: The steady reduction in deaths from breast cancer has heightened the importance of breast cancer survivorship, as emphasized in the new phase of the Cancer Moonshot initiative. One key concern is the adverse effects of breast cancer therapies causing the early onset of other age-related diseases and deaths from non-cancer causes. Chemotherapy has been shown to increase the level of senescent cells in breast cancer survivors, measured using the expression level of the p16 protein. Senescent cells secrete phenotypes, including inflammatory cytokines and proteases, which are main factors behind several age-related diseases. In fact, mathematical modeling of stochastic accumulation and removal of senescence has been shown to model the mortality rate and the incidence rate of several age-related diseases in humans. Therefore, we need a computational approach to model the impact of breast cancer diagnosis and treatment on the enhanced accumulation of senescence and the subsequent increase in the non-cancer mortality rate.Method: We used a stochastic model of the accumulation and removal of senescent cells (SnC) with age to simulate the SnC trajectories for 6 scenarios, women without cancer, women with breast cancer but without senescence-enhancing therapies, and women with breast cancer and with 4 groups of chemotherapy regimens (for which the data on the change in p16 expression were available). The 4 groups of chemotherapy regimens were, (1) doxorubicin, cyclophosphamide, and paclitaxel, (2) docetaxel and cyclophosphamide +/- anti-HER2 therapy, (3) docetaxel and carboplatin + anti-HER2 therapy, and (4) doxorubicin and cyclophosphamide + paclitaxel and carboplatin. We used the probability distribution of SnC for each age in the non-cancer group as a biomarker for the true biological age. The clinical data on the change in p16 expression level due to breast cancer and subsequent chemotherapy was used to modify the parameters of the stochastic model to generate the SnC probability distributions for the other 5 scenarios. Biological age for the breast cancer and chemotherapy groups were estimated by using the difference in the SnC probability distributions in each of the 5 breast cancer groups vs. the non-cancer group. Non-cancer mortality rate for the 5 breast cancer groups was determined using the computationally-estimated biological age rather than the chronological age.Results: We obtained quantitative maps from chronological age to biological age for breast cancer survivors depending on two variables, the age at diagnosis of breast cancer and the chemotherapy regimen. The divergence of biological age from the chronological age is higher for women diagnosed with breast cancer at a younger age. This divergence can be as high as 30+ years for women diagnosed with breast cancer before the age of 50, leading to a significantly higher non-cancer mortality rate. Therefore, chemotherapy-enhanced senescence can be a critical factor for deciding the specific regimen for younger women with breast cancer.Conclusions: We present a novel computational approach to generate chronological age to biological maps and chronological age to non-cancer mortality rate maps for breast cancer survivors as a function of the age at diagnosis and the chemotherapy regimen. These maps can be useful for clinical decisions on the impact of different chemotherapy regimens on subpopulations of breast cancer survivors. The chronological age to non-cancer mortality rate maps also provides new inputs for epidemiological simulations of breast cancer survivorship, to discern the impact of different therapies on breast cancer survivorship. Furthermore, we will be able to incorporate tumor marker subtype and race/ethnicity as variables for generating these senescence-based maps as more data become available. Citation Format: Swarnavo Sarkar,Mina Sedrak, Clyde Schechter, Jeanne Mandelblatt. Estimation of biological aging and non-cancer mortality rate in breast cancer survivors due to chemotherapy using a computational model of senescence [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P5-10-13.

The National Cancer Institute-funded Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer mathematical models have been increasingly utilized by policymakers to address breast cancer screening policy decisions and influence clinical practice. These well-established and validated models have a successful track record of use in collaborations spanning over 2 decades. While mathematical modeling is a valuable approach to translate short-term screening performance data into long-term breast cancer outcomes, it is inherently complex and requires numerous inputs to approximate the impacts of breast cancer screening. This review article describes the 6 independently developed CISNET breast cancer models, with a particular focus on how they represent breast cancer screening and estimate the contribution of screening to breast cancer mortality reduction and improvements in life expectancy. We also describe differences in structures and assumptions across the models and how variation in model results can highlight areas of uncertainty. Finally, we offer insight into how the results generated by the models can be used to aid decision-making regarding breast cancer screening policy.

Background: CGM is a standard of care for diabetes management, yet its adoption in primary care remains limited where the majority of people with diabetes are served. Examining contributors to CGM prescriptions in primary care may identify new targets for intervention that could improve diabetes population health. Methods: We examined CGM prescription behaviors of primary care providers within a large safety net hospital in the Bronx, NY. We extracted data from the electronic health record on all adults ≥18 years with type 2 diabetes and at least one primary care visit from July 31, 2020, to July 31, 2023. We used competing risk regression to model factors associated with CGM prescription. Results: Out of 40,791 people with type 2 diabetes (mean age 62 years, 60% female, 39% Hispanic, 39% Non-Hispanic Black, 77% English-speaking, 47% publicly insured, 27% seen by trainee physicians), 4,129 (10.1%) were prescribed CGM. CGM was 40% less likely to be prescribed for Spanish vs. English-speaking (SHR 0.60 [0.54-0.68]), 15% less likely with public insurance (SHR 0.85 [0.79-0.91]), and 25% less likely with diabetes complications (microvascular SHR 0.73 [0.67-0.79], macrovascular SHR 0.77, [0.69-0.86]). Conversely, CGM was 30% more likely to be prescribed with each additional HbA1c percentage point (SHR 1.31 [1.30-1.34]) and 6% more likely with each additional prescriber year of experience (SHR 1.06, [1.05-1.07]). CGM prescriptions increased in a dose-response manner with treatment intensification (non-insulin SHR 2.08 [1.76, 2.46]; basal insulin SHR 3.94 [3.27-4.75]; multiple daily insulin SHR 5.03 [4.17-6.07]). Conclusion: Our analysis of a large primary care network of people with diabetes can inform strategies to support more widespread CGM use in primary care. New targets could include Spanish language support services; aid for better prior authorization procedures for public insurance; and increased education of CGM benefits for providers with less years of experience. Disclosure J. Milosavljevic: None. P.M. Mathias: None. C. Schechter: None. S. Agarwal: Research Support; Dexcom, Inc. Advisory Panel; Medtronic. Consultant; Beta Bionics, Inc.

10025 Background: Survivors of pediatric lymphoma previously treated with chest radiation are at high risk for subsequent breast cancer. Although early initiation of breast cancer screening is recommended, the clinical benefits and harms of adding tamoxifen to reduce breast cancer deaths among these women are unknown. Methods: We adapted a Cancer Intervention and Surveillance Modeling Network (CISNET) breast model using data from the Childhood Cancer Survivor Study (CCSS) to reflect the elevated risks for breast cancer and competing mortality for 5-year survivors previously treated with chest radiation (RT). Breast cancer risk was based on age, chest RT field, timing of RT relative to menarche, menopause status, anthracycline exposure, and family history. Premature menopause risk varied by cumulative ovarian RT and alkylator dose. Based on the US Preventive Services Task Force 2019 Evidence Summary, we assumed tamoxifen (20mg daily for 5 years) reduced estrogen receptor positive (ER+) breast cancer risk by 42% (RR = 0.58 [0.42-0.81]) for 20 years and increased risks for venous thromboembolism, deep vein thrombosis, coronary heart disease, stroke and endometrial cancer during treatment. Strategies included no screening or tamoxifen, annual screening with mammography and MRI starting at age 25, annual screening with mammography and MRI starting at age 25 with the addition of tamoxifen at ages 25, 30 or 35. Model outcomes included cumulative breast cancer risk, number of childbearing years before age 45 (defined as years menstruating without tamoxifen use or a breast cancer diagnosis or having survived breast cancer for at least 3 years), and number of tamoxifen-related side-effects. Results: Among a cohort of 20-year-old 5-year lymphoma survivors previously treated with mediastinal RT without primary ovarian failure, an estimated 20% were projected to develop breast cancer and 2.6% would die from the disease before age 50 in the absence of screening or tamoxifen use. Survivors would have on average 22 childbearing years before age 45. Early initiation of breast cancer screening at age 25 would reduce breast cancer deaths before age 50 by 56.3%. Depending on age at initiation, tamoxifen would further reduce breast cancer deaths by 8.0 to 9.6 percentage points for an overall 64.3% to 65.9% reduction and reduce the average number of childbearing years by 17% to 21%. For each breast cancer death averted, a reduction of 1950 to 3740 childbearing life years and 11 to 20 side-effects would occur and varied by the tamoxifen start age compared to mammography and MRI screening. Conclusions: Tamoxifen use for primary breast cancer prevention among pediatric lymphoma survivors may further reduce breast cancer deaths but decisions might depend on survivor preferences for side effects vs. avoiding breast cancer and consideration of timing for childbearing.

Importance Breast cancer mortality in the US declined between 1975 and 2019. The association of changes in metastatic breast cancer treatment with improved breast cancer mortality is unclear. Objective To simulate the relative associations of breast cancer screening, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer with improved breast cancer mortality. Design, Setting, and Participants Using aggregated observational and clinical trial data on the dissemination and effects of screening and treatment, 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models simulated US breast cancer mortality rates. Death due to breast cancer, overall and by estrogen receptor and ERBB2 (formerly HER2) status, among women aged 30 to 79 years in the US from 1975 to 2019 was simulated. Exposures Screening mammography, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer. Main Outcomes and Measures Model-estimated age-adjusted breast cancer mortality rate associated with screening, stage I to III treatment, and metastatic treatment relative to the absence of these exposures was assessed, as was model-estimated median survival after breast cancer metastatic recurrence. Results The breast cancer mortality rate in the US (age adjusted) was 48/100 000 women in 1975 and 27/100 000 women in 2019. In 2019, the combination of screening, stage I to III treatment, and metastatic treatment was associated with a 58% reduction (model range, 55%-61%) in breast cancer mortality. Of this reduction, 29% (model range, 19%-33%) was associated with treatment of metastatic breast cancer, 47% (model range, 35%-60%) with treatment of stage I to III breast cancer, and 25% (model range, 21%-33%) with mammography screening. Based on simulations, the greatest change in survival after metastatic recurrence occurred between 2000 and 2019, from 1.9 years (model range, 1.0-2.7 years) to 3.2 years (model range, 2.0-4.9 years). Median survival for estrogen receptor (ER)-positive/ERBB2-positive breast cancer improved by 2.5 years (model range, 2.0-3.4 years), whereas median survival for ER-/ERBB2- breast cancer improved by 0.5 years (model range, 0.3-0.8 years). Conclusions and Relevance According to 4 simulation models, breast cancer screening and treatment in 2019 were associated with a 58% reduction in US breast cancer mortality compared with interventions in 1975. Simulations suggested that treatment for stage I to III breast cancer was associated with approximately 47% of the mortality reduction, whereas treatment for metastatic breast cancer was associated with 29% of the reduction and screening with 25% of the reduction.

Studying near-miss errors is essential to preventing errors from reaching patients. When an error is committed, it may be intercepted (near-miss) or it will reach the patient; estimates of the proportion that reach the patient vary widely. To better understand this relationship, we conducted a retrospective cohort study using two objective measures to identify wrong-patient imaging order errors involving radiation, estimating the proportion of errors that are intercepted and those that reach the patient. This study was conducted at a large integrated healthcare system using data from 1 January to 31 December 2019. The study used two outcome measures of wrong-patient orders: (1) wrong-patient orders that led to misadministration of radiation reported to the New York Patient Occurrence Reporting and Tracking System (NYPORTS) (misadministration events); and (2) wrong-patient orders identified by the Wrong-Patient Retract-and-Reorder (RAR) measure, a measure identifying orders placed for a patient, retracted and rapidly reordered by the same clinician on a different patient (near-miss events). All imaging orders that involved radiation were extracted retrospectively from the healthcare system data warehouse. Among 293 039 total eligible orders, 151 were wrong-patient orders (3 misadministration events, 148 near-miss events), for an overall rate of 51.5 per 100 000 imaging orders involving radiation placed on the wrong patient. Of all wrong-patient imaging order errors, 2% reached the patient, translating to 50 near-miss events for every 1 error that reached the patient. This proportion provides a more accurate and reliable estimate and reinforces the utility of systematic measure of near-miss errors as an outcome for preventative interventions.

Abstract Disclosure: M. Hashmi: None. C. Schechter: None. A. Herrera Chancay: None. H. Tabassum: None. N. Shiraliyeva: None. J. Daily: None. A.K. Myers: None. Objective Diabetes complications, especially diabetic foot ulcers (DFU), are a leading cause of health care expenditures. This study examined the total cost of amputations and subsequent procedures in Health First insured (HF) patients initially treated at Montefiore Medical Center (MMC) for DFU. Using the database of HF, a large-scale Medicaid managed insurance organization, we captured healthcare utilization beyond the scope of one hospital system, obtaining a more comprehensive understanding of expenditures. We also explored the associations of demographic and lab values with expenditures. Methods The HF data extraction covered calendar years 2021 and 2022 plus YTD 2023. Amputations were identified by CPT codes 27880, 27590, 28810, and 28820. One hundred twenty patients were included in the sample as they had HF insurance and their initial admission for DFU was at one of three hospitals at MMC. Demographic and laboratory data were extracted from the EHR. Demographics, lab values within 3 months of the index admission, and total costs were summarized, and paid amounts per capita per year were calculated. Expenditures included amputation, labs, wound care, surgery, hyperbaric therapy, interpreter services, emergency department visits, home care visits, and outpatient follow-up (in-person and telehealth). We explored demographic, comorbidity, and lab values as predictors of expenditure levels using a bivariate analysis. Results The mean age was 60.6 ± 12 years with majority being male (n=79, 65.3%) and having Type 2 Diabetes (n=103, 96.3%). A significant portion identified their race as other (n=58, 53.7%) or ethnicity as Hispanic-Latino (n=60, 56.1%). Common comorbidities in this group were current or former tobacco use (n=64, 59.2%), chronic kidney disease (n=62, 57.9%), and hypertension (n=94, 86.2%). Glycemic control was suboptimal with an average Hemoglobin A1c of 9.1% (SD 3.1%) and average admission glucose of 232.2 mg/dL. C-reactive protein 17.1 (SD 34.1) and erythrocyte sedimentation rate 88.8 (SD 36.3) were both elevated for most patients. The DFU-related amputation cost was higher for Hispanic-Latino individuals, RR 1.97 (CI 1.04, 3.71) and for those with chronic kidney disease, RR 1.36 (1, 1.86). Female sex, serum glucose and BMI were moderately associated with increased relative cost. The study was limited by not having access to subsequent visits outside our health system and the retrospective nature of the study. Conclusions Our study highlights disparities among patients who underwent a DFU related amputation, with higher costs for Hispanic-Latino individuals, those with chronic kidney disease , and women, emphasizing the need for tailored interventions for these populations to ameliorate the high cost of DFU-related care. Presentation: 6/2/2024

PURPOSE:The purpose of the 12-month randomized controlled trial was to evaluate the effectiveness of a Telephonic Self-Management Support (T-SMS) program among adults with type 2 diabetes (T2D). METHODS:Eight hundred twelve adults with T2D participated in NYC Care Calls (mean age = 59.2, SD = 10.8; female = 57%; mean A1C = 9.3, SD = 1.8; Latino = 86%) and were randomly assigned to T-SMS or enhanced usual care (EUC). A1C (primary outcome), blood pressure, and body mass index (secondary outcomes) were extracted from electronic medical records. Secondary patient-reported outcomes, including depressive symptoms, diabetes distress, medication adherence, and self-management activities, were assessed by telephone in English or Spanish. For T-SMS, the number of assigned phone calls was based on baseline A1C, depressive symptoms, and/or diabetes distress. Analyses were conducted under the intention-to-treat principle. RESULTS:A1C decreased over 12 months in both T-SMS (0.72% percentage points; 95% CI, 0.53-0.91) and EUC (0.66% percentage points; 95% CI, 0.46-0.85; Ps < .001). Diabetes distress and self-management also improved over time in both arms (Ps < .05). Compared to EUC, participants in the T-SMS arm did not differ in outcomes. CONCLUSIONS:The T-SMS and EUC groups were found not to have an appreciable outcome difference. It is unclear whether improvements in A1C across both conditions represent a secular trend or indicate that print-based educational intervention may have a positive impact on self-management and well-being.

IMPORTANCE The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. OBJECTIVE To estimate outcomes of various mammography screening strategies. DESIGN, SETTING, AND POPULATION Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. EXPOSURES Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. MAIN OUTCOMES AND MEASURES Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, over diagnosis), and number of mammograms per 1000 women. RESULTS Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening)was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 over diagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and over diagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. CONCLUSIONS This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

OBJECTIVE:Underserved young adults (YA) with type 1 diabetes (T1D) experience the worst outcomes across the life span. We developed and integrated the Supporting Emerging Adults with Diabetes (SEAD) program into routine endocrinology care to address unmet social and medical challenges. RESEARCH DESIGN AND METHODS:This study was designed as a longitudinal cohort study, with prospective data collection over 4 years on YA in SEAD compared with usual endocrine care. We used propensity-weighted analysis to account for differences in baseline characteristics, and multivariate regression and Cox proportional hazard models to evaluate change in outcomes over time. Primary outcomes included incidence of hospitalizations, diabetes technology uptake, and annual change in HbA1c levels. RESULTS:We included 497 YA with T1D in SEAD (n = 332) and usual endocrine care (n = 165); mean age 25 years, 27% non-Hispanic Black, 46% Hispanic, 49% public insurance, mean HbA1c 9.2%. Comparing YA in SEAD versus usual care, 1) incidence of hospitalizations was reduced by 64% for baseline HbA1c >9% (HR 0.36 [0.13, 0.98]) and 74% for publicly insured (HR 0.26 [0.07, 0.90]); 2) automated insulin delivery uptake was 1.5-times higher (HR 1.51 [0.83, 2.77]); and 3) HbA1c improvement was greater (SEAD, -0.37% per year [-0.59, -0.15]; usual care, -0.26% per year [-0.58, 0.05]). CONCLUSIONS:SEAD meaningfully improves clinical outcomes in underserved YA with T1D, especially for publicly insured and high baseline HbA1c levels. Early intervention for at-risk YA with T1D as they enter adult care could reduce inequity in short and long-term outcomes.

Importance:The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective:To estimate outcomes of various mammography screening strategies. Design, Setting, and Population:Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures:Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures:Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results:Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions:This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Abstract Disclosure: T.L. Danehy: None. A. Manavalan: None. C. Schechter: None. Y. Tomer: None. Objective: Thyroid cancer is the second most common cancer diagnosed in pregnancy (1). Both HCG and estrogen have been implicated in this increased risk (2). While the classic variant of papillary thyroid cancer is the most common subtype in non-pregnant women, the effect of exposure to pregnancy on histological subtype remains unclear and could have clinical implications. Methods: This is a retrospective cohort study conducted at Montefiore Medical Center. All women of childbearing age (18-45) with a diagnosis of thyroid cancer between the years of 2015 -2020 (n=152) were identified. 43 participants were excluded due to missing data. The remaining 114 participants were divided into 2 groups; Group 1 or the exposed (n=25) included those diagnosed with thyroid cancer during pregnancy or in the 2 years postpartum and had carried their pregnancy to term, and Group 2 or the unexposed (n =89) included those who were nulliparous or diagnosed with thyroid cancer prior to pregnancy or more than 2 years post-partum. Charts were reviewed to obtain data on the initial histopathology and were classified into Follicular Thyroid Cancer (FTC), Hurthle cell carcinoma (HCC), Medullary Thyroid Cancer (MTC), and Papillary Thyroid Cancer (PTC). Results: Women in the unexposed group were significantly younger than those exposed to pregnancy (28.7 vs 32.7 p=0.005). The distribution of histological types in the two groups was as follows:Group 1: FTC (13.0%), HCC (0%), MTC (0%), and PTC (87%). Group 2: FTC (5.7%), HCC (2.3%), MTC (3.4%), PTC (88.5%). Thus, the incidence of follicular thyroid cancer in the exposed group was > 2-fold that observed in unexposed group, but this difference did not meet statistical significance (p=0.594). Conclusions: Our study showed a non-statistically significant increased incidence of FTC in women who were diagnosed with thyroid cancer during pregnancy or 2 years postpartum compared to unexposed women. While this did not meet statistical significance, our study sample was small and may have been underpowered. Therefore, our findings merit further investigation given their potential clinical implications. References: 1. Smith L.H., Danielsen B., Allen M.E., Cress R. Cancer associated with obstetric delivery: results of linkage with the California cancer registry. Am J Obstet Gynecol. 2003 2. Tafani M., De Santis E., Coppola L., Perrone G.A., Carnevale I., Russo A. Bridging hypoxia, inflammation, and estrogen receptors in thyroid cancer progression. Biomed Pharmacother. 2014;68(1):1-5 Presentation: 6/2/2024

ImportanceInformation on long-term benefits and harms of screening with digital breast tomosynthesis (DBT) with or without supplemental breast magnetic resonance imaging (MRI) is needed for clinical and policy discussions, particularly for patients with dense breasts.ObjectiveTo project long-term population-based outcomes for breast cancer mammography screening strategies (DBT or digital mammography) with or without supplemental MRI by breast density.Design, Setting, and ParticipantsCollaborative modeling using 3 Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer simulation models informed by US Breast Cancer Surveillance Consortium data. Simulated women born in 1980 with average breast cancer risk were included. Modeling analyses were conducted from January 2020 to December 2023.InterventionAnnual or biennial mammography screening with or without supplemental MRI by breast density starting at ages 40, 45, or 50 years through age 74 years.Main outcomes and MeasuresLifetime breast cancer deaths averted, false-positive recall and false-positive biopsy recommendations per 1000 simulated women followed-up from age 40 years to death summarized as means and ranges across models.ResultsBiennial DBT screening for all simulated women started at age 50 vs 40 years averted 7.4 vs 8.5 breast cancer deaths, respectively, and led to 884 vs 1392 false-positive recalls and 151 vs 221 false-positive biopsy recommendations, respectively. Biennial digital mammography had similar deaths averted and slightly more false-positive test results than DBT screening. Adding MRI for women with extremely dense breasts to biennial DBT screening for women aged 50 to 74 years increased deaths averted (7.6 vs 7.4), false-positive recalls (919 vs 884), and false-positive biopsy recommendations (180 vs 151). Extending supplemental MRI to women with heterogeneously or extremely dense breasts further increased deaths averted (8.0 vs 7.4), false-positive recalls (1088 vs 884), and false-positive biopsy recommendations (343 vs 151). The same strategy for women aged 40 to 74 years averted 9.5 deaths but led to 1850 false-positive recalls and 628 false-positive biopsy recommendations. Annual screening modestly increased estimated deaths averted but markedly increased estimated false-positive results.Conclusions and relevanceIn this model-based comparative effectiveness analysis, supplemental MRI for women with dense breasts added to DBT screening led to greater benefits and increased harms. The balance of this trade-off for supplemental MRI use was more favorable when MRI was targeted to women with extremely dense breasts who comprise approximately 10% of the population.

Objective: Diabetic foot ulcers (DFUs) are a leading cause of morbidity and mortality, which disproportionately impacts underserved populations. This study aimed to provide data regarding the rates and outcomes of amputation in patients admitted with DFU in our health system, which cares for an ethnically diverse and underserved population. Methods: This retrospective study examined the electronic medical records of adult patients hospitalized with DFU at 3 hospitals in our health system between June 1, 2016, and May 31, 2021. Results: Among 650 patients admitted with DFU, 88% self-identified as non-White race. Male sex (odds ratio [OR], 0.62), low body mass index (OR, 0.98), and history of smoking (OR, 1.45) were significantly associated with amputation during the study period. A higher erythrocyte sedimentation rate (OR, 1.01), C-reactive protein level (OR, 1.05), and white blood cell count (OR, 1.11) and low albumin level (OR, 0.41) were found to be significantly associated with amputation versus no amputation during admission. The amputation risk during the index admission for DFU was 44%. Conclusion: Our study identified a high DFU-related amputation risk (44%) among adult patients who were mostly Black and/or Hispanic. The significant risk factors associated with DFU amputation included male sex, low body mass index, smoking, and high levels inflammation or low levels of albumin during admission. Many of these patients required multidisciplinary care and intravenous antibiotic therapy, necessitating a longer length of stay and high readmission rate. (c) 2024 AACE. Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

Stata has an if qualifier and an if command. Here we discuss generally when you should use either and specifically flag a common pitfall in using the if command. In a nutshell, the pitfall arises from confusing the two constructs: the if command does not loop over the data but, at most, looks in the first observation of a dataset. There has long been a StataCorp FAQ on this topic (Wernow 2005), but we and others have usually tried to explain matters otherwise. This tip is intended as a more durable version of the story that should be easier to find than occasional Statalist postings that are vivid when read but hard to find later.