Objective This study investigates racial disparity in life expectancies (LEs) and life years lost (LYL) associated with multiple obesity-related chronic conditions (OCCs). Methods Data from the Medical Expenditure Panel Survey, 2008–2012, were used. Four OCCs were studied: diabetes, hypertension, coronary heart disease (CHD), and stroke. LE for each subpopulation was simulated by Markov modelling. LYL associated with a disease for a subpopulation was computed by taking the difference between LEs for members of that subpopulation without disease and LEs for members of that subpopulation who had that disease. Racial disparities were measured in the absolute differences in LEs and LYL between black women/men and white women/men. Results Blacks had higher risks of developing diabetes, hypertension, and stroke. Disparity in LE between whites and blacks was largest in men age 40–49 with at least stroke: blacks lived 3.12 years shorter than whites. Disparity in LYL between whites and blacks was largest in women age 70–79 with at least CHD: blacks had 1.98 years greater LYL than whites. Conclusions Racial disparity exists in incident disease and mortality risks, LEs, and LYL associated with multiple OCCs. Efforts targeting subpopulations with large disparities are required to reduce disparities in the burden of multiple OCCs.

1557 Background: The Veterans Health Administration (VHA) provides extensive electronic health records (EHRs) on Veterans nationwide. Our prior studies utilized VHA data to study the risk of progression from monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma. These studies relied on International Classification of Disease (ICD) codes and manual abstraction on clinical notes to both identify and verify MGUS patients. Diagnosis confirmation is necessary because many providers place a diagnosis on the clinical notes to order lab tests, which is often left in the EHR despite a negative test result. However, manual abstraction is labor intensive and time consuming. With the advancement in natural language processing (NLP), we developed a model to make MGUS confirmation more efficient. Methods: We randomly selected 700 patients within patients diagnosed with MGUS from 1999-2021 in the VHA identified via ICD codes. A random sample of 500 patients were selected and split into the training (80%) and the testing (20%) sets. The remainder (n = 200) served as the validation set. There were 32,708 unstructured hematology/oncology Text Integration Utility reports and 9,237 lab reports (including 2,322 discrete results and 6,915 unstructured comments). All reports were manually reviewed to confirm MGUS diagnoses and served as the reference standard. We compiled three lists of keywords suggestive of MGUS diagnosis, subtypes of immunoglobulins, and negation modifiers. We trained a symbolic NLP model to identify diagnoses using combinations of the lists along with M-protein levels from lab reports. The optimized combination that gave the highest recall and precision from the training set was used and evaluated on the testing and validation sets. Results: Among patients with ICD codes for MGUS, manual abstraction confirmed 84% MGUS diagnoses in the testing set and 80% in the validation set. Our NLP model in the training set confirmed 75% and achieved recall, precision, accuracy, and F1 score of 88.1, 98.7, 89.0, and 93.1%, respectively; in the validation set, our rule confirmed 76% patients and the recall, precision, accuracy, and F1 score were 89.4, 94.7, 87.5, and 92.0%, respectively. On average data abstraction took five minutes per patient (excluding data loading time), whereas NLP model completed 13 patients per minute. Conclusions: The developed NLP model to confirm MGUS diagnosis improves accuracy in diagnosis, compared to ICD codes alone. While the performance is similar to that of manual abstraction, our NLP model is an efficient and viable method in MGUS diagnosis confirmation. [Table: see text]

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Introduction: Monoclonal gammopathy of undetermined significance (MGUS) is an asymptomatic premalignant plasma cell disorder with an annual risk of ~1% of progression to more advanced diseases, including multiple myeloma (MM). Few studies reported mortality risk in patients with MGUS, among which the diagnosis of MGUS was typically incidental due to unrelated symptoms or laboratory abnormalities. This study aims to compare the survival of MGUS patients with the U.S. general population using a nationally representative screening-based survey. Methods: Data were obtained from the third National Health and Nutrition Examination Survey (NHANES III) 1988-1994 and continuous NHANES 1999-2004, with follow-up all-cause mortality data through December 31, 2019. Participants were screened for MGUS by protein electrophoresis, immunofixation, and kappa and lambda free light chain assays in serum. Multivariable Cox-proportional regressions were performed, adjusting for demographic characteristics (age, gender, race/ethnicity, education, income, body mass index [BMI]), health behaviors (smoking, physical activity), baseline medical conditions (hypertension, diabetes, osteoporosis, myocardial infarction, stroke, congestive heart failure, coronary heart disease, peripheral vascular disease [PVD], arthritis, liver diseases, chronic obstructive pulmonary disease, renal diseases, cancer), and survey year. We also tested the interaction between race/ethnicity and MGUS diagnosis in the fully adjusted model. The NHANES complex sampling design was accounted for in all analyses to obtain population estimates. Results: The prevalence of MGUS among the U.S. population aged 50 years or older was 2.5% in 1988-1994 (sample size n=6,557; population size N=56,136,480) and 2.3% in 1999-2004 (n=5,847; N=68,835,295). MGUS patients were older and more likely to have PVD (13.1% vs. 7.7%, p = 0.03). No evidence was found showing a difference in gender distribution, education, income, BMI, and other comorbidities between the two populations. In NHANES 1999-2004, MGUS was associated with an increased risk of death (Hazard ratios [HR] 1.20, 95% CI: 1.02-1.41, p = 0.03) compared to the general population. NHANES III also showed a trend toward increased risk of mortality (HR 1.15, 95% CI: 0.89-1.48, p = 0.27). No interaction between race/ethnicity and MGUS diagnosis was found. It was notable that PVD was associated with an increased risk of death (HR 1.67, 95% CI: 1.43-1.94, p < 0.001). Conclusion: In the large cohort of NHANES participants, MGUS was associated with an increased risk of mortality. MGUS is typically viewed as a “benign” condition that has the potential to progress to cancer. These findings suggest that there may be alternate health implications to a diagnosis of MGUS. Future studies should focus on the causes of death in this population and the role of MGUS. Citation Format: Mengmeng Ji, John Huber, Mei Wang, Yi-Hsuan Shih, Yao-Chi Yu, Lawrence Liu, Theodore Thomas, Martin W. Schoen, Kristen M. Sanfilippo, Graham A. Colditz, Shi-Yi Wang, Su-Hsin Chang. Mortality in patients with monoclonal gammopathy of undetermined significance: an analysis of National Health and Nutrition Examination Survey [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6480.