Univariate Models Research Articles

The association between microaggressions and mental health among UK trans people: a cross-sectional study.

Epidemiological studies investigating the mental health impacts of microaggressions in the trans population have tended to have methodological limitations, including a lack of validated measures, raising concerns about the validity of their findings. To address this evidence gap, we investigated the associations between microaggressions and poor mental health (depression; anxiety; non-suicidal self-harm [NSSH]; suicidal thoughts; suicide attempt) amongst trans people. We conducted a cross-sectional survey of 787 trans adults in the UK, measuring mental health and exposure to microaggressions using the Gender Identity Microaggressions Scale (GIMS). Using univariable and multivariable linear and logistic regression models we tested for an association of microaggressions with depressive symptoms (PHQ-9), anxiety symptoms (GAD-7), lifetime NSSH, lifetime suicidal thoughts, and lifetime suicide attempt. Of the 787 participants, 574 (73%) provided complete data. Microaggressions were a common experience, affecting 97.6% of participants over their lifetime. In adjusted analyses, using sociodemographic and clinical variables, increased microaggression scores were associated with increased depressive symptoms (adjusted coefficient: 1.86 (95%CI = 1.35 to 2.36)), anxiety symptoms (adjusted coefficient: 1.57 (95%CI = 1.09 -2.05)) and with increased odds of NSSH (Odds Ratio [OR]adj 1.83 (95%CI = 1.45 -2.30)), suicidal thoughts (ORadj 2.18, (95%CI = 1.52 -3.13)), and suicide attempt (ORadj, 1.59, (95%CI = 1.32 -1.92)). In exploratory analyses different GIMS subscales were associated with these various outcomes. There was evidence of associations between microaggressions and adverse mental health outcomes, as well as to support specific microaggressions being associated with specific outcomes, emphasizing the importance of public health interventions that target microaggressions directed at trans adults. Longitudinal studies are needed to investigate the temporality of the associations between microaggressions and mental health outcomes.

Wave-Former: Lag removing univariate long time series forecasting transformer for ocean waves

Long-Sequence Time Series Forecasting (LSTSF) of ocean waves using univariate modelling has always been a challenging task in the field of oceanography as it demands a high prediction capacity model capable to capture precise long-range dependency between input and output variables. Inherently, it exhibits the problem of “time lag or phase shift” in predictions which is due to high autocorrelation in between time dependent sequential values. Very few researchers had tried to remove this “phase shift” problem in the univariate modelling including the author of present work wherein preprocessing of time series data was done by different methods. Many failed in gaining high prediction accuracy at longer forecasting intervals. Overcoming these limitations, present work aims for LSTSF of ocean waves ranging from 24 to 144 hours (hrs) at the three locations of Gulf of Mexico using “WaveFormer” architecture based on the Informer. Probabilistic self-attention mechanism has proved to be efficient to remove the “time lag or phase shift” in ocean waves as well as in predicting the waves at large time intervals (144 hrs). Low Root Mean Squared Errors (RMSEs) (0.045–0.100) and high correlation coefficients (0.90–0.99), low values of test loss (0.002–0.012) of all the developed models demonstrated the competency of WaveFormer.

The role of wide local excision of a primary lesion in cutaneous malignant melanoma: a retrospective analysis of its usefulness in local and general control of disease.

Currently, wide local excision is recommended after the primary excision of cutaneous melanomas. The definition of margins for wide local excision indicated by the guidelines has remained unchanged over the years, although the reported indications are derived from fairly dated studies in which melanomas tended to be thicker or in advanced stages at diagnosis. This study aimed to retrospectively evaluate the usefulness of wide local excision for local and general control of the disease and to identify patients who had benefited from the wide local excision procedure in terms of prognosis improvement. This retrospective observational study was conducted on patients who had undergone surgery for melanoma at a single institution. The primary endpoint was progression-free survival after wide local excision in patients with or without residual melanoma. The secondary endpoint was to evaluate which patients' demographic features and melanoma histological data were associated with residual melanoma after wide local excision. In the univariate model, melanoma-positive wide local excision resulted in the worst progression-free survival; however, this association was not confirmed in the multivariate model. The results also showed that Breslow thickness was the only factor associated with an increased risk of metastasis to the wide local excision area. According to the receiver operating characteristic analysis, the optimum cutoff value of Breslow's thickness to predict a tumor-positive wide local excision was 2.31 mm for males and 2.4 mm for females.

Genetic Parameter Estimates for Growth of Hāpuku (Groper, Polyprion oxygeneios) in Land-Based Aquaculture Using Random Regression Models

Hāpuku (Polyprion oxygeneios) is a promising candidate for aquaculture production in New Zealand. Methods for spawning, juvenile production, and growout to harvest entirely on land, where water quality, pathogens, environmental impacts, and genetic “pollution” can be tightly controlled, have been developed, and genetic improvement to optimise land-based production is the obvious next step. However, estimates of genetic parameters are required to design a rigorous, disciplined, and effective selective breeding program. By using existing data consisting of irregularly spaced repeated measurements of fork length and live body weight collected on wild-collected founders and two generations of captively reared progeny, we evaluated the species’ genetic potential for improvement in growth. We first tested a range of univariate random regression models to identify the best-fitting models for these data. Subsequently, using a bivariate model, we estimated variance components for growth trajectories of fork length and whole body weight. With one to six records available per fish, the best-fitting univariate models included only a fixed effect for contemporary groups and fixed and random genetic third-order Legendre polynomials. More complex models that included full-sib family and/or permanent environmental effects produced unacceptable constrained and/or non-positive-definite solutions. Both traits are moderately heritable at all stages of the growout phase (~0.4–0.5), and the genetic correlation patterns between daily breeding values estimated via the covariance function are different for length and weight. Genetic correlations for length between all pairs of age-specific breeding values are positive and strong (>0.7) and change gradually and smoothly with increasing temporal separation. For weight, these correlations deteriorate more rapidly with increasing time lags between measurements and become negative for some age pairings. We conclude that random regression analyses are a valuable tool for extracting genetic information from irregularly spaced repeated measurements of fish size, speculate that emerging technologies for high-throughput genotyping and phenotyping will add to the value of this approach in the near future, and reason that a breeding strategy that rigorously takes into account the potentially unfavourable genetic correlations between breeding values for weight at some ages will further adapt hāpuku to land-based systems and enhance the profitability commercial-scale production.

Myocardial Scarring and Sudden Cardiac Death in Young Patients With Hypertrophic Cardiomyopathy

The ability to predict sudden cardiac death (SCD) in children and adolescents with hypertrophic cardiomyopathy (HCM) is currently inadequate. Late gadolinium enhancement (LGE) by cardiovascular magnetic resonance (CMR) imaging is associated with SCD events in adults with HCM. To examine the prognostic significance of LGE in patients with HCM who are younger than 21 years. This multicenter, retrospective cohort study was conducted from April 8, 2015, to September 12, 2022, in patients with HCM who were younger than 21 years and had undergone CMR imaging across multiple sites in the US, Europe, and South America. Observers of CMR studies were masked toward outcomes and demographic characteristics. Natural history of HCM. The primary outcome was SCD and surrogate events, including resuscitated cardiac arrest and appropriate discharges from an implantable defibrillator. Continuous and categorical data are expressed as mean (SD), median (IQR), or number (percentage), respectively. Survivor curves comparing patients with and without LGE were constructed by the Kaplan-Meier method, and likelihood of subsequent clinical events was further evaluated using univariate and multivariable Cox proportional hazards models. Among 700 patients from 37 international centers, median (IQR) age was 14.8 (11.9-17.4) years, and 518 participants (74.0%) were male. During a median (IQR) [range] follow-up period of 1.9 (0.5-4.1) [0.1-14.8] years, 35 patients (5.0%) experienced SCD or equivalent events. LGE was present in 230 patients (32.9%), which constituted an mean (SD) burden of 5.9% (7.3%) of left ventricular myocardium. The LGE amount was higher in older patients and those with greater left ventricular mass and maximal wall thickness; patients with LGE had lower left ventricular ejection fractions and larger left atrial diameters. The presence and burden of LGE was associated with SCD, even after correcting for existing risk stratification tools. Patients with 10% or more LGE, relative to total myocardium, had a higher risk of SCD (unadjusted hazard ratio [HR], 2.19; 95% CI, 1.59-3.02; P < .001). Furthermore, the addition of LGE burden improved the performance of the HCM Risk-Kids score (before LGE addition: 0.66; 95% CI, 0.58-0.75; after LGE addition: 0.73; 95% CI, 0.66-0.81) and Precision Medicine in Cardiomyopathy score (before LGE addition: 0.68; 95% CI, 0.49-0.77; after LGE addition: 0.73; 95% CI, 0.64-0.82) SCD predictive models. In this retrospective cohort study, quantitative LGE was a risk factor for SCD in patients younger than 21 years with HCM and improved risk stratification.

Searching for a Novel HLA-Cw6-Linked Cardiometabolic Endotype in Psoriatic Disease.

In recent years, a possible connection between HLA-Cw6 and a distinctive cardiometabolic (CM) profile in patients with psoriatic disease (PsD) has been proposed, although there is still little support for this. Our aim was to further investigate this possible association by studying a large population of PsD patients. For this study, three different cohorts of patients with PsD were analyzed: two with a majority of cutaneous psoriasis, pooled n: 600, and a third with only psoriatic arthritis-PsA-cases, n: 340. Potential relationships between HLA-Cw6 and the different CM risk factors (hypertension, diabetes, obesity, dyslipidemia) were analyzed using univariate and multivariate regression models, while the final net effect was assessed using fixed- or random-effects meta-analyses, as appropriate. In the PsA cohort, no association was detected between HLA-Cw6 carriership and any of the CM comorbidity factors. In psoriasis cohorts, after correcting for age, sex, disease duration, and arthritis, HLA-Cw6 carriers had a reduced diabetes risk (OR 0.49, 95%CI: 0.26-0.91, p = 0.026). This latter effect was confirmed by a fixed-effects meta-analysis of the included cohorts (pooled OR: 0.50, 95%CI: 0.27-0.90). This work demonstrates a potential protective effect of the HLA-Cw6 allele on the risk of diabetes in PsD. Our findings together with those of others seem to confirm the existence of a novel HLA-Cw6-linked cardiometabolic endotype in this disease.

Impact of Serum Phosphate on Hemoglobin Level: A Longitudinal Analysis on a Large Cohort of Dialysis Patients

Background/Objectives: Phosphate is a macro-element involved in all cellular energetic processes. As about 90% of the phosphate filtered by the glomerulus is excreted by kidneys, the impairment of renal function and the consequent over-secretion of parathyroid hormone and fibroblast growth factor 23 results in the increase in the serum phosphate levels. The association between phosphate and hemoglobin is controversial, as both direct and indirect relationships have been reported. The present study aims to investigate the relationship between phosphate and hemoglobin in a large prospective, longitudinal cohort including dialysis patients from the Sicilian Registry of Nephrology, Dialysis, and Transplantation. Methods: In this prospective cohort study, we included 6263 hemodialysis patients to achieve a total of 120,462 repeated measurements of serum phosphate and hemoglobin over time. The longitudinal association between phosphate and hemoglobin was analyzed by univariate and multivariate Linear Mixed Models. Results: The mean age was 66 ± 16 years and the median dialysis vintage was 5 months [IQR: 2–16]. Mean and median values of hemoglobin and phosphate were 10.7 g/dL (SD 1.3 g/dL) and 4.6 mg/dL [IQR 3.9–5.5 mg/dL], respectively. The multivariate model, adjusted for potential confounders, confirmed the positive association between serum phosphate and hemoglobin [adjβ = 0.13, 95%CI 0.03–0.23, p = 0.01)]. These results were confirmed in analyses stratified for the use of phosphate binders. Conclusions: In our large cohort of dialysis patients, we found a linear, direct relationship between phosphate and hemoglobin levels. As a reduction in phosphate is associated with a parallel reduction in hemoglobin levels, hypophosphatemia can accentuate anemia in dialysis patients. Our results generate the hypothesis that monitoring serum phosphate in clinical practice might provide a better management of anemia.

Association Between Median Household Income and Perioperative Outcomes of Lumbar Spinal Fusion: An Analysis of the National Inpatient Sample (2009–2020)

Relationships between low socioeconomic status (SES) and surgical outcomes are well established for certain procedures. However, scant literature has focused on relationships between median household income and lumbar fusion outcomes. Patients who underwent fusion procedures between January 1, 2009 and December 31, 2020 were identified from the National Inpatient Sample (NIS) database. They were categorized into 4 quartiles, from lowest to highest, based on median household incomes in respective zip codes. We applied univariable and multivariable linear and logistic regression models to analyze perioperative data according to income quartiles. We included 2,826,396 patients. In multivariable regression, patients in the 3 lowest income quartiles exhibited higher rates of in-hospital cardiac events perioperatively, with odds ratios (OR) of 1.19 (95% confidence interval[CI]1.13-1.26, p<0.001), 1.10 (95%CI 1.05-1.16, p<0.001), and 1.06 (95%CI 1.01-1.12, p=0.011) for the first, second, and third quartiles, respectively. Patients in the lowest income (first) quartile had a higher occurrence of perioperative urinary complications (OR=1.07, 95%CI 1.03-1.12, p=0.001), systemic infectious complications (OR=1.17, 95% CI 1.04-1.32, p=0.006), neurological deficit (OR=1.17, 95%CI 1.06-1.30, p=0.002), and wound infections (OR=1.22, 95%CI 1.12-1.34, p<0.001). Those in the 3 lowest income quartiles were less likely to experience respiratory, gastrointestinal, and venous thrombotic complications (p<0.05). The lowest income quartile had protective associations for dural tears (OR 0.93, 95%CI 0.89-0.99, p=0.038) and postprocedure anemia across all 3 lower quartiles, with OR<1 and p<0.001. Reduced household income significantly affected perioperative outcomes after lumbar fusion and should be taken into consideration during the perioperative period.

Estimation of Genetic Parameters for Milk Production Rate and Its Stability in Holstein Population.

Milk production rate (MPR) refers to the rate of milk secretion per hour (kg/h), calculated from the harvested milk yield and milking interval, and it is considered an appropriate measure to evaluate the production potential of cows. The objective of this study was to estimate the phenotypic and genetic parameters of milk production rate traits. In this study, the milking records of 4760 Holstein cows were collected, and four milk yield traits and six milk production rate traits were defined. The MIXED procedure was used to detect the impacts of non-genetic effects on milk yield and milk production rate traits, including parity, measured season and lactation stage. Variance and covariance components for milk yield and milk production rate traits were estimated using a univariate linear repeatability model. Parity, measurement season and lactation stage had significant effects (p < 0.01) on milk yield, milk production rate and its stability. Milk yield and milk production traits had high heritability, and ranged from 0.25 to 0.39. The stability of milk production rate had low heritability (0.04~0.05). Milk production rate is beneficial for the devolving novel trait in dairy breeding and provides new insights for herd management and genetic selection of production performance of dairy cattle.

Forecasting intraoperative hypotension during hepatobiliary surgery.

Prediction and avoidance of intraoperative hypotension (IOH) can lead to less postoperative morbidity. Machine learning (ML) is increasingly being applied to predict IOH. We hypothesize that incorporating demographic and physiological features in an ML model will improve the performance of IOH prediction. In addition, we added a "dial" feature to alter prediction performance. An ML prediction model was built based on a multivariate random forest (RF) trained algorithm using 13 physiologic time series and patient demographic data (age, sex, and BMI) for adult patients undergoing hepatobiliary surgery. A novel implementation was developed with an adjustable, multi-model voting (MMV) approach to improve performance in the challenging context of a dynamic, sliding window for which the propensity of data is normal (negative for IOH). The study cohort included 85% of subjects exhibiting at least one IOH event. Males constituted 70% of the cohort, median age was 55.8years, and median BMI was 27.7. The multivariate model yielded average AUC = 0.97 in the static context of a single prediction made up to 8min before a possible IOH event, and it outperformed a univariate model based on MAP-only (average AUC = 0.83). The MMV model demonstrated AUC = 0.96, PPV = 0.89, and NPV = 0.98 within the challenging context of a dynamic sliding window across 40min prior to a possible IOH event. We present a novel ML model to predict IOH with a distinctive "dial" on sensitivity and specificity to predict first IOH episode during liver resection surgeries.

Is second 131I treatment necessary for differentiated thyroid cancer patients and who could not benefit from it? A real-world retrospective study in China.

The efficacy of a second radioactive iodine-131 (131I) treatment in patients with differentiated thyroid cancer (DTC) who did not achieve an excellent response (ER) following initial 131I therapy remains controversy and the population that would derive limited benefit from it is currently unclear. The aim of this retrospective study was to assess the efficacy of the second 131I treatment in DTC patients with non-ER after the initial 131I therapy, and to identify potential risk factors associated with non-benefit of the second 131I treatment. 127 DTC patients who underwent two 131I treatments following thyroidectomy were included in this study, and the therapeutic response was evaluated after each 131I treatment. Beneficial treatment was defined as an improvement in therapy response grade (e.g. from indeterminate response to ER) after the second 131I treatment, while unbeneficial treatment was defined as no change or a downgrade in therapy response grade. The potential risk factors associated with the non-benefit of the second 131I treatment were identified using univariate and multivariate logistic regression models. Following the second 131I treatment, therapy responses of 55.12% (70/127) of patients were reclassified to a better grade indicating treatment benefit, while 44.88% (57/127) showed no change or were reclassified to a worse grade suggesting no benefit from treatment. The non-benefit of the second 131I treatment was significantly associated with potential risk factors including stimulated thyroglobulin (sTg) level ≥ 11.46ng/mL before the second 131I treatment, primary tumor size > 2cm, status T2 or higher, N1b status and ATA high risk. The study results demonstrated that more than half of DTC patients could potentially benefit from a second 131I therapy. However, over 40% of patients exhibited no benefit in response to the second 131I treatment, suggesting potential overtreatment for this subgroup. Therefore, clinicians should exercise meticulous and precise decision-making based on identified risk factors when considering the necessity of a second 131I treatment.

Perceived Chronic Traumatic Encephalopathy and Suicidality in Former Professional Football Players

ImportanceParticipation in American-style football (ASF) has been linked to chronic traumatic encephalopathy neuropathological change (CTE-NC), a specific neuropathologic finding that can only be established at autopsy. Despite being a postmortem diagnosis, living former ASF players may perceive themselves to have CTE-NC. At present, the proportion and clinical correlates of living former professional ASF athletes with perceived CTE who report suicidality are unknown.ObjectiveTo determine the proportion, clinical correlates, and suicidality of living former professional ASF players with perceived CTE.Design, Setting, and ParticipantsA cross-sectional study within the Football Players Health Study at Harvard University was conducted from 2017 to 2020. Using electronic and paper surveys, this population-based study included former ASF players who contracted with a professional league from 1960 to 2020 and volunteered to fill out a baseline survey. Data for this study were analyzed from June 2023 through March 2024.ExposuresData included demographics, football-related exposures (eg, position, career duration), and current health problems (anxiety, attention-deficit/hyperactivity disorder, depression, diabetes, emotional and behavioral dyscontrol symptoms, headache, hyperlipidemia, hypertension, low testosterone level, pain, sleep apnea, and subjective cognitive function).Main Outcomes and MeasuresThe proportion of participants reporting perceived CTE. Univariable and multivariable models were used to determine clinical and suicidality correlates of perceived CTE.ResultsAmong 4180 former professional ASF players who volunteered to fill out a baseline survey, 1980 (47.4%) provided follow-up data (mean [SD] age, 57.7 [13.9] years). A total of 681 participants (34.4%) reported perceived CTE. Subjective cognitive difficulties, low testosterone level, headache, concussion signs and symptoms accrued during playing years, depressive/emotional and behavioral dyscontrol symptoms, pain, and younger age were significantly associated with perceived CTE. Suicidality was reported by 171 of 681 participants with perceived CTE (25.4%) and 64 of 1299 without perceived CTE (5.0%). After adjusting for established suicidality predictors (eg, depression), men with perceived CTE remained twice as likely to report suicidality (odds ratio, 2.06; 95% CI, 1.36-3.12; P &amp;amp;lt; .001).Conclusions and RelevanceThis study found that approximately one-third of living former professional ASF players reported perceived CTE. Men with perceived CTE had an increased prevalence of suicidality and were more likely to have health problems associated with cognitive impairment compared with men without perceived CTE. Perceived CTE represents a novel risk factor for suicidality and, if present, should motivate the diagnostic assessment and treatment of medical and behavioral conditions that may be misattributed to CTE-NC.

Abstract C034: Impact of survivorship care plans on self-reported health and functional well-being

Abstract Introduction: Cancer survivors have varying physical, psychosocial, and informational needs. Organizations such as American Society of Clinical Oncology have developed survivorship care plans (SCP) for cancer screening, treatment side effect management, and care coordination. There is a need to better understand SCP utilization among underserved and diverse patient communities. Methods: Adults ages 18+ years with breast or colorectal cancer diagnosed between 2019 and 2021 were recruited from the Greater Bay Area Cancer Registry. Participants completed a 30-minute survey about their survivorship plans, quality of life, health behaviors, and social support. Analysis: Overall comparisons between groups were evaluated with chi-square tests. Associations between demographic characteristics and receipt of any type of survivorship plan were evaluated with univariate binomial logistic regression models, and associations between receipt of any type of survivorship plan and health/well-being outcomes were assessed using univariate ordinal regression models. Multivariable models will be built using relevant variables. Results: Participants (n=872) were on average 59 years (range=24-95) and mostly female (70.2%). Participants had either breast (41.3%) or colorectal cancer (58.7%). Participants were American Indian/Alaska Native (AIAN) (1.0%), Asian American (18.2%), NH Black (12.8%), NH White (38.0%), LatinX (29.0%), and Native Hawaiian or Pacific Islander (0.8%). Receipt of a SCP was reported by 258 (29.6%) participants, 328 (37.6%) had another type of post-treatment guide provided to them, and 224 (25.7%) were not offered any kind of survivorship plan. There were no differences in race/ethnicity, nativity status, non-English language spoken at home, marital status, or educational attainment between those who received any kind of survivorship plan vs. no plan. Being female was associated with 40% lower odds of receiving any kind of survivorship plan (OR=0.60, 95%CI=0.42-0.87). Being on public insurance was also associated with lower odds of receiving a survivorship plan than being on private insurance (OR=0.59, 95%CI=0.43-0.81). Receipt of a survivorship plan was associated with 52% higher odds of reporting a higher level of overall current health (OR=1.52, 95%CI=1.14-2.02) compared to those who did not receive any plan. Receiving a survivorship plan was also associated with higher odds of reporting a higher level of ability to work (OR=1.58, 95%CI=1.18-2.11), more fulfilling work (OR=1.69, 95%CI=1.27-2.23), ability to enjoy life (OR=1.55, 95%CI=1.17-2.06), ability to sleep well (OR=1.35, 95%CI=1.03-1.79), and contentment with their current quality of life (OR=1.51, 95%CI=1.14-1.99). Conclusion: Receipt of any survivorship plan was associated with higher levels of self-reported current overall health and measures of functional well-being. Women, as well as people on public insurance, are less likely to receive a survivorship plan, highlighting disparities in survivorship care planning for these populations. Citation Format: Aly M. Cortella, Katarina Wang, Debby Oh, Niharika Dixit, Zinnia Loya, Kathie Lau, Michelle Wadhwa, Chris Duffy, Salma Shariff-Marco, Kristan Olazo, Vlad Honcharov, Marika Dy, Urmimala Sarkar, Scarlett Lin Gomez. Impact of survivorship care plans on self-reported health and functional well-being [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C034.

Abstract A100: Addressing financial toxicity and associated social determinants among Hispanic cancer patients in Puerto Rico

Abstract Introduction: Cancer is one of the most expensive medical conditions to treat due to the cost and duration of treatment. Financial toxicity (FT) describes the problems that a cancer patient has related to the cost of medical care, including subjective financial concerns. Despite the high burden of cancer, significant levels of poverty, and a fragile healthcare system in Puerto Rico (PR), no previous studies have evaluated FT among cancer patients in PR. Thus, we aimed to assess FT and associated social determinants among Hispanic cancer patients in PR. Methods: We are conducting a cross-sectional study through an online survey among cancer patients aged 21+ years who have received active cancer treatment over the last year. We use the COST-FACIT questionnaire, a validated survey composed of 12 questions; to measure low (score ≥ 21) and high (score &amp;lt; 21) FT. We also collect information on social determinants, including demographics, clinical characteristics, access to healthcare services, quality of life, social support, and patient navigation services, among others. Cronbach's alpha was used to assess the internal consistency of the FT score. Univariate (ULRM) and multivariate logistic regression models (MLRM) were used to determine the social determinants associated with FT. MLRM included significant variables in the ULRM (p &amp;lt; 0.10) and predictors supported by scientific literature. Results: As of April 8th, 2024, 387 people accessed the survey, with 294 (80.0%) completing it, including the FT section. The final sample size for this preliminary data analysis included 226 participants due to the exclusion of missing information on important covariates. Most of the participants were 51 to 64 years of age (46.9%), female (72.6%), had annual income &amp;lt; $25,000 (59.7%), and had a bachelor’s degree or higher (51.8%). COST-FACIT demonstrated good internal consistency (alpha=0.83). Approximately 46.0% of the participants had a high FT (overall FT mean score = 21.0±8.9). MLRM show that retired participants (OR: 0.22, 95%CI: 0.22-0.59) had less odds of high FT, while those who have public health insurance (OR: 2.38, 95%CI: 1.02-5.54), have comorbidities (OR: 2.27, 95%CI: 1.08-4.79), and have had a cancer diagnosis for more than 1 year (OR: 1.90, 95%CI: 1.02-3.53) have significantly higher odds of experiencing high FT. Conclusion: FT is higher among cancer patients with public health insurance, comorbidities, and more than one year since cancer diagnosis, but FT is lower in retired cancer patients. More research is needed to identify and evaluate interventions to address the FT of cancer treatment and the social determinants associated among Hispanic/Latino patients. IRB: This project was approved by the Institutional Review Board of the University of Puerto Rico Comprehensive Cancer Center (IRB # 2023-11-123). Citation Format: Marievelisse Soto-Salgado, Sofía Contreras-Fernández, Lorena González-Sepúlveda, Karina Torres-Mojica, Rocío Avilés-Mercado, Juan Paulo González-Mayoral, Nancy Cardona-Cordero. Addressing financial toxicity and associated social determinants among Hispanic cancer patients in Puerto Rico [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A100.

A nomogram for predicting survival based on hemoglobin A1c and circulating tumor cells in advanced gastric cancer patients receiving immunotherapy

BackgroundOur study aimed to investigate the correlation between hemoglobin A1c (HbA1c), circulating tumor cells (CTCs) and prognosis in advanced gastric cancer (GC) patients who received immunotherapy and explore the potential prognostic predictors to develop a nomogram. MethodsWe retrospectively enrolled 259 patients with advanced GC treated at Beijing Friendship Hospital between September 2014 and March 2024. Patients were divided into the immunochemotherapy cohort (ICT) and the chemotherapy (CT) cohort. Survival rate was calculated by Kaplan-Meier survival curve, and the differences were evaluated by log-rank test. The univariate and multivariate Cox proportional hazards regression model was used to identify factors independently associated with survival. A nomogram was developed to estimate 6-, 12-, and 18-month progression-free survival (PFS) probability based on the ICT cohort. ResultsPatients achieved higher PFS in the ICT cohort than the CT cohort. We focused on the ICT cohort and constructed a nomogram based on the multivariate analysis, including five variables: age, PD-L1 expression, HbA1c, CTCs and CEA*. The concordance index value was 0.82 in the training cohort and 0.75 in the validation cohort. Furthermore, we proved the nomogram was clinically useful and performed better than PD-L1 expression staging system. Notably, we found high HbA1c level but not diabetes mellitus significantly affected the efficacy of ICT. ConclusionICT showed better PFS than CT. In addition, HbA1c and CTCs were novel biomarkers to predict PFS in patients treated with ICT. The nomogram could predict PFS of advanced GC patients receiving ICT with increased accuracy and favorable clinical utility.

Prevalence of Unwanted Loneliness and Associated Factors in People over 65 Years of Age in a Health Area of the Region of Murcia, Spain: HELPeN Project.

Background/Objectives: Population aging poses many challenges to public health, highlighting loneliness and social isolation as severe problems that affect the physical and mental health of older adults. During the COVID-19 pandemic, these became aggravated. The objective of the present study was to assess the prevalence of loneliness and its relationship with social isolation, depression, cognitive deterioration, sleep quality, and the level of physical mobility and functioning of older adults in Health Area 3 of the Region of Murcia. Methods: A descriptive, observational, and cross-sectional study was performed. The inclusion criteria were age ≥ 65, living in Health Area 3 of the Region of Murcia, and not being institutionalized. The following variables were evaluated: sociodemographic variables, loneliness (UCLA scale), social isolation (DUFSS), depression (GDS), cognitive deterioration (Pfeiffer), sleep quality (PSQI), and mobility (Barthel index). A univariate and multivariate regression model was created to examine how the dependent variable was related to the independent variables. Results: A total of 102 older adults participated in the study. Of these, 31.4% perceived unwanted loneliness and 14.7% low social support. The multivariate regression analysis showed that social isolation, geriatric depression, and cognitive deterioration were significant predictors of loneliness. Conclusions: The findings highlight the importance of developing multifaceted interventions that address not only social isolation but also other interrelated factors such as depression, cognitive deterioration, and sleep quality. The strategies should be centered on community programs and support networks. It is fundamental to perform longitudinal studies to better understand the causal relationships between these variables.

Abstract B149: Investigating Disparities in Cost-Associated Barriers to Medication Adherence in Breast Cancer Survivors in the National Institutes of Health All of Us Research Program

Abstract Purpose: Medication adherence (e.g., endocrine therapy, antihypertensives) during survivorship remains suboptimal. Racial disparities in medication adherence continue to persist, yet reasons for this disparity are not fully understood. This study aimed to assess racial differences in cost-associated barriers to medication adherence. Methods: This cross-sectional analysis utilized data from the National Institutes of Health All of Us Research Program. Cohort eligibility included identifying as Black/African American or White, being at least 18 years old, and having a diagnosis of breast cancer. Survivors must have completed the Healthcare Access and Utilization survey, a validated assessment of factors impacting healthcare behaviors. Comparisons between patient characteristics (e.g., age, annual income, marital status, employment, education, etc.) and survey responses were analyzed by race using Pearson’s chi-square tests. Univariable and multivariable logistic regression models were fitted to investigate the unadjusted and adjusted associations of cost-related barriers to medication adherence and race. Results: Among the 1,840 breast cancer survivors included in this cohort, the mean age was 63.8 (standard deviation (sd) = 10.4). The majority of survivors were White (94.3%) (5.7% Black), married (58.9%) and unemployed (57.4%). The mean score for racial discrimination in healthcare was 10.3 (sd = 3.8) (range = 7 - 35). Most survivors did not report any cost-related barriers to adherence (74.9%); however, 19.5% of survivors asked their doctor for lower cost medication to save money. When compared with White survivors, a higher proportion of Black survivors reported that they could not afford prescription medicines (6.5% vs. 12.4%). In the multivariable model, no significant association by race was observed (p=0.387). Survivors who reported annual household income levels above $50k were less likely to report cost-reported barriers when compared to survivors who reported a household income of &amp;lt;$25k (p&amp;lt;0.001). Each one-point increase in perceived discrimination in healthcare increased the odds of reporting a cost-related barrier to adherence by a factor of 1.10 (95% confidence interval: 1.07, 1.13). Conclusions: Although racial differences were not noted for overall cost-related barriers, results highlight a need to understand nuanced differences in perceived cost-related barriers to adherence and how survivors navigate those differences. Further research is needed to understand providers’ roles in encouraging medication adherence and how discrimination in healthcare may serve as a barrier to adherence. Citation Format: Arnethea L. Sutton, Jian He, Lakeshia Cousin, Keesha Powell-Roach, Mandy J. Hill, Wendy Bottinor. Investigating Disparities in Cost-Associated Barriers to Medication Adherence in Breast Cancer Survivors in the National Institutes of Health All of Us Research Program [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B149.

Abstract B087: Inflammation and breast cancer: Understanding the interplay and implications for prevention and treatment

Abstract Breast cancer continues to be a major global health issue, affecting millions and posing challenges for researchers and healthcare workers. Recent research has revealed the importance of inflammation in the development and progression of a variety of malignancies, including breast cancer. The aim of this study is to investigate the complex association between inflammation and breast cancer in order to improve treatment and preventative techniques. A mixed-methods approach was used, with both quantitative and qualitative studies. The study included 580 breast cancer patients and 2,573 control participants. Patient records, hospital databases, and publicly available datasets were all used as data sources. Statistical methods, including univariate and multivariate logistic regression models, were employed to discover breast cancer predictors associated with inflammation. Breast cancer growth is strongly linked to chronic inflammation and specific inflammatory markers (CRP, IL-6, and TNF-α). Breast cancer incidence is correlated with geographical, demographic, and lifestyle characteristics such as region, age, gender, race, education level, and overall health condition. Comorbidities like hypertension, diabetes, and arthritis, as well as BMI, smoking, and physical activity levels, all have a role in risk. Anti-inflammatory drugs and lifestyle changes show promise for lowering the risk of breast cancer and improving patient outcomes. The study reveals significant relationships between breast cancer incidence and a variety of demographic, lifestyle, and health-related variables. Chronic inflammation is important in the development of breast cancer; therefore, inflammatory indicators could be used as diagnostic or therapeutic tools. The study suggests that tailored anti-inflammatory medications and lifestyle changes could have a significant impact on breast cancer prevention and therapy. This study emphasizes the necessity of knowing the relationship between inflammation and breast cancer. The insights revealed can lead to novel methods for breast cancer management, stressing the importance of ongoing research to fully understand the connection between inflammation and breast cancer and to implement these discoveries in clinical practice. Citation Format: Opeyemi O. Ogungbola, Samuel O. Ejeh, Jane Odeh, Olajumoke R. Omoniyi, Abayomi A. Akomolafe, Emmanuel K. Abudu. Inflammation and breast cancer: Understanding the interplay and implications for prevention and treatment [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B087.

Comparison of Several Univariate Time Series Methods for Inflation Rate Forecasting

Forecasting inflation is very crucial for a country because inflation is one of indicator to measure development of the country. This study aims to evaluate the effectiveness of three univariate time series methods i.e., ARIMA (Autoregressive Integrated Moving Average), Double Exponential Smoothing (DES), and Trend Projection (TP), in forecasting Indonesia’s monthly inflation rates using data from 2018 to 2022. The analysis identifies DES as the most accurate method, evidenced by its lowest Root Mean Square Error (RMSE) value of 2.9296, outperforming ARIMA and TP, which have RMSE values of 13.1479 and 3.47053, respectively. Consequently, DES was selected as the preferred model for forecasting inflation over the next 36 month, with the forecasts indicating a consistent downward trend in inflation throughout the year. While these findings highlight DES's effectiveness, the study also acknowledges limitations, including its reliance on univariate models that do not incorporate other economic variables, and the potential limitations of the dataset’s specific time frame. To address these limitations, future research should consider multivariate models, integrate machine learning techniques, and conduct scenario analyses to improve forecast accuracy and robustness. Despite these constraints, the study provides valuable insights into inflation forecasting in Indonesia, offering a practical tool for policymakers and contributing to more informed economic decision-making.

An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors

BackgroundKidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both the graft and the pediatric recipient. However, there is limited research on DGF in pediatric kidney transplant recipients. This study aims to develop a predictive model for the risk of DGF occurrence after pediatric kidney transplantation by integrating donor and recipient characteristics and utilizing machine learning algorithms, ultimately providing guidance for clinical decision-making.MethodsThis single-center retrospective cohort study includes all recipients under 18 years of age who underwent single-donor kidney transplantation at our hospital between 2016 and 2023, along with their corresponding donors. Demographic, clinical, and laboratory examination data were collected from both donors and recipients. Univariate logistic regression models and differential analysis were employed to identify features associated with DGF. Subsequently, a risk score for predicting DGF occurrence (DGF-RS) was constructed based on machine learning combinations. Model performance was evaluated using the receiver operating characteristic curves, decision curve analysis (DCA), and other methods.ResultsThe study included a total of 140 pediatric kidney transplant recipients, among whom 37 (26.4%) developed DGF. Univariate analysis revealed that high-density lipoprotein cholesterol (HDLC), donor after circulatory death (DCD), warm ischemia time (WIT), cold ischemia time (CIT), gender match, and donor creatinine were significantly associated with DGF (P < 0.05). Based on these six features, the random forest model (mtry = 5, 75%p) exhibited the best predictive performance among 97 machine learning models, with the area under the curve values reaching 0.983, 1, and 0.905 for the entire cohort, training set, and validation set, respectively. This model significantly outperformed single indicators. The DCA curve confirmed the clinical utility of this model.ConclusionsIn this study, we developed a machine learning-based predictive model for DGF following pediatric kidney transplantation, termed DGF-RS, which integrates both donor and recipient characteristics. The model demonstrated excellent predictive accuracy and provides essential guidance for clinical decision-making. These findings contribute to our understanding of the pathogenesis of DGF.