Regression Program Research Articles

Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning

Background: Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis of PD’s mortality characterizes temporal shifts, examines demographic and regional differences, and provides machine-learning predictions. Methods: PD-related deaths in the United States were gathered from CDC WONDER. Age-adjusted mortality rates (AAMR) were collected, and trends were analyzed based on gender, race, region, age, and place of death. Annual percent change and average annual percent change were calculated using Joinpoint Regression program. Forecasts were obtained using the optimal Autoregressive Integrated Moving Average (ARIMA) model. Results: Overall mortality rate due to Parkinson’s increased from 1999 to 2022. Male gender, White race, Southern region, and older ages were associated with higher mortality compared to other groups. Deaths at home decreased and hospice deaths increased during the study period. Conclusions: This study highlights the increasing rate of PD AAMR and how it may become even more prevalent with time, emphasizing the value of increasing knowledge surrounding the disease and its trends to better prepare health systems and individual families for the burden of PD.

Evolving regional trends in U.S. opioid-related mortality: Disparities and the impact of COVID-19 (1999-2023)

Background The opioid crisis is a public health challenge in the United States, significantly impacting mortality rates. This has been further exacerbated by COVID-19, contributing to a surge in substance use and overdose deaths. Methods Data from the CDC Wonder Database was used to identify opioid use-related deaths in the United States from 1999 to 2023. Crude and age-adjusted mortality rates (AAMR) were calculated across different geographic and demographic groups. Temporal trends in mortality were analyzed using the Joinpoint Regression Program. Annual percentage change (APC) and average annual percentage change (AAPC) in mortality rates were calculated. Results Opioid-related mortality surged during the COVID-19 period, with significant regional, racial, and state-level disparities. The Midwest region exhibited the highest AAPC from 1999 to 2023. State-specific analyses showed that West Virginia experienced the highest increase in AAMR from 1999 to 2023. Among racial groups, non-Hispanic American Indians/Alaska Natives had the highest AAPC from 1999 to 2023. Gender-specific analyses revealed that males had a higher AAPC from 1999 to 2023 than females. Conclusion The United States opioid crisis continued to escalate during the COVID-19 period, with significant increases in mortality across the regions. The highest AAPCs were seen in the Midwest and among non-Hispanic American Indians/Alaska Natives. These findings underscore the need for targeted interventions to account for trends in racial and regional disparities in opioid-related mortality that have increased during and post-COVID-19.

Changing suicide trends: A shift in regional disparities across the UK

BackgroundIn 2023, suicide rates in England & Wales reached their highest levels since 1999. Despite changes in legal definitions and registration methods impacting trends, this increase reflects growing individual suffering. International comparisons suggest that while the UK saw a 12 % rise in suicide rates between 1999 and 2020, many other European countries experienced significant declines. MethodsWe used publicly available data from the Office for National Statistics on suicide rates from 1981 to 2023, by sex and geographical region in England & Wales. We conducted descriptive and statistical analyses with the Joinpoint regression programme to identify significant discontinuities in trends in suicide rates. ResultsIn 1981, London had the highest suicide rates, but by 2023, it reported the lowest for both sexes, with declines of 51 % for men and 69 % for women. In contrast, the North East and North West now have much higher rates, particularly in men. Several regions have seen little improvement. ConclusionsThere are substantial regional differences in suicide trends in England. These are consistent with known social and economic changes and point to a need for whole of government responses.

Improving Generalization of Genetic Programming for High-Dimensional Symbolic Regression with Shapley Value Based Feature Selection

AbstractSymbolic Regression (SR) on high-dimensional datasets often encounters significant challenges, resulting in models with poor generalization capabilities. While feature selection has the potential to enhance the generalization and learning performance in general, its application in Genetic Programming (GP) for high-dimensional SR remains a complex problem. Originating from game theory, the Shapley value is applied to additive feature attribution approaches where it distributes the difference between a model output and a baseline average across input variables. By providing an accurate assessment of each feature importance, the Shapley value offers a robust approach to select features. In this paper, we propose a novel feature selection method leveraging the Shapley value to identify and select important features in GP for high-dimensional SR. Through a series of experiments conducted on ten high-dimensional regression datasets, the results indicate that our algorithm surpasses standard GP and other GP-based feature selection methods in terms of learning and generalization performance on most datasets. Further analysis reveals that our algorithm generates more compact models, focusing on the inclusion of important features.

Cardiovascular mortality trends and disparities in U.S. breast cancer patients, 1999–2020: a population-based retrospective study

BackgroundBreast cancer survivors face a higher risk of cardiovascular disease (CVD) compared to non-breast cancer patients, yet contemporary data on CVD-related mortality within this group remains scarce.ObjectiveTo investigate trends and disparities in CVD mortality among breast cancer patients.MethodsWe queried the Centers for Disease Control and Prevention’s Wide-Ranging Online Data for Epidemiologic Research (CDC Wonder) and conducted serial cross-sectional analyses on national death certificate data for CVD mortality in breast cancer patients aged 25 and above from 1999 to 2020. We calculated age-adjusted mortality rates (AAMR) per 100,000 individuals and analyzed trends over time using the Joinpoint Regression Program, with further analyses stratified by age, race, census region, and urbanization level.ResultsA total of 74,733 CVDs with comorbid breast cancer in the United States were identified between 1999 and 2020. The AAMR from CVDs with comorbid breast cancer decreased from 2.57 (95% CI [2.50–2.65]) in 1999 to 1.20 (95% CI [1.15–1.24]) in 2020, with an average annual percent change (AAPC) of − 4.3. The three most common causes of CVDs were ischemic heart disease (47.8%), cerebrovascular disease (17.1%), and hypertensive disease (10.6%). Our analysis revealed a significant decrease in AAMR for all CVD subtypes, except for hypertensive diseases and arrhythmias. The decrease in annual percent change (APC) was more pronounced in individuals aged ≥ 65 years compared to those < 65 years (-4.4, 95%CI [-4.9, -3.9] vs. -2.9, 95%CI [-4.1, -1.7], respectively. Notably, non-Hispanic Blacks consistently exhibited the highest AAMR (1.95, 95%CI [1.90–1.99]), whereas Hispanic or Latina patients had the lowest AAMR (0.75, 95% CI [0.72–0.78]). The AAMR was also higher in rural regions than in urban areas (1.64, 95%CI [1.62–1.67] vs. 1.55, 95%CI [1.53–1.56]).ConclusionThe study highlights a significant decline in CVD mortality among breast cancer patients over two decades, with persistent disparities by race and region. Exceptionally, hypertensive diseases and arrhythmias did not follow this declining trend.

Prophylaxis of topical levofloxacin against endophthalmitis after cataract surgery in Taiwan, 2001-2019: an interrupted time series analysis.

Since May 2007, topical levofloxacin 0.5% ophthalmic solution for prophylaxis of postoperative endophthalmitis (POE) in cataract surgery has been reimbursable in Taiwan. We used the National Health Insurance Research Database to estimate the practice of levofloxacin in cataract surgery from 2001 to 2019 and compared the POE rates before and after the introduction of levofloxacin using interrupted time series (ITS) analysis. We did propensity score-based stabilized weights (PSSW) for each quarterly cohort and used the Joinpoint Regression Program to determine the significant change time point. 1,456,380 patients and 2,208,126 eyes were eligible. The Joinpoint Regression Program revealed a significant change in the second quarter of 2010. Levofloxacin use started from 0% in the second quarter of 2007, and increased to 6.3% and 30.2% in the second quarter of 2010 and the last quarter of 2019. The POE rate (per 1000 eyes) was 3.7 in the first quarter of 2001, reduced to 1.9, 1.7, and 1.4 in the first, second quarters of 2010, and the last quarter of 2019, respectively. ITS reveals a significant but smaller time trend of - 0.0088‰ during 2010Q2-2019 (post-interruption). The r-square between the levofloxacin use and the POE rate was 0.305. The results of ITS and r-square after PSSW are similar to those without PSSW. Although the POE reduction rate in cataract surgery aligns with the increased use of levofloxacin, the small r-square and low usage implied topical levofloxacin use is not the sole determinant of POE reduction.

Trends in sepsis-associated cardiovascular disease mortality in the United States, 1999 to 2022

PurposeCardiovascular disease (CVD) is the leading cause of death in the United States, and sepsis significantly contributes to hospitalization and mortality. This study aims to assess the trends of sepsis-associated CVD mortality rates and variations in mortality based on demographics and regions in the US.MethodsThe Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) database was used to identify CVD and sepsis-related deaths from 1999 to 2022. Data on gender, race and ethnicity, age groups, region, and state classification were statistically analyzed to obtain crude and age-adjusted mortality rates (AAMR). The Joinpoint Regression Program was used to determine trends in mortality within the study period.ResultsDuring the study period, there were a total of 1,842,641 deaths with both CVD and sepsis listed as a cause of death. Sepsis-associated CVD mortality decreased between 1999 and 2013, from AAMR of 65.7 in 1999 to 58.8 in 2013 (APC −1.06*%, 95% CI: −2.12% to −0.26%), then rose to 74.3 in 2022 (APC 3.23*%, 95% CI: 2.18%–5.40%). Throughout the study period, mortality rates were highest in men, NH Black adults, and elderly adults (65+ years old). The Northeast region, which had the highest mortality rate in the initial part of the study period, was the only region to see a decline in mortality, while the Northwest, Midwest, and Southern regions experienced significant increases in mortality rates.ConclusionSepsis-associated CVD mortality has increased in the US over the past decade, and both this general trend and the demographic disparities have worsened since the onset of the COVID-19 pandemic.

Effects of reducing redundant parameters in parameter optimization for symbolic regression using genetic programming

Gradient-based local optimization has been shown to improve results of genetic programming (GP) for symbolic regression (SR) – a machine learning method for symbolic equation learning. Correspondingly, several state-of-the-art GP implementations use iterative nonlinear least squares (NLS) algorithms for local optimization of parameters. An issue that has however mostly been ignored in SR and GP literature is overparameterization of SR expressions, and as a consequence, bad conditioning of NLS optimization problem. The aim of this study is to analyze the effects of overparameterization on the NLS results and convergence speed, whereby we use Operon as an example GP/SR implementation. First, we demonstrate that numeric rank approximation can be used to detect overparameterization using a set of six selected benchmark problems. In the second part, we analyze whether the NLS results or convergence speed can be improved by simplifying expressions to remove redundant parameters with equality saturation. This analysis is done with the much larger Feynman symbolic regression benchmark set after collecting all expressions visited by GP, as the simplification procedure is not fast enough to use it within GP fitness evaluation. We observe that Operon frequently visits overparameterized solutions but the number of redundant parameters is small on average. We analyzed the Pareto-optimal expressions of the first and last generation of GP, and found that for 70% to 80% of the simplified expressions, the success rate of reaching the optimum was better or equal than for the overparameterized form. The effect was smaller for the number of NLS iterations until convergence, where we found fewer or equal iterations for 51% to 63% of the expressions after simplification.

Semantics-guided multi-task genetic programming for multi-output regression

Semantics-guided multi-task genetic programming for multi-output regression

Disruptions in Lung Cancer Detection During COVID-19.

Objective: To quantify the extent of the disruption and recovery of lung cancer detection during the first two years of the pandemic, focusing on disparities across demographic and community factors. Methods: This retrospective cohort study used the SEER database to identify lung cancer cases from 2001 to 2021. Expected incidence rates for 2020 and 2021 were projected based on pre-pandemic trends (2000-2019) using the NCI's Joinpoint Regression program. Percent differences between expected and observed incidence rates were calculated. Multivariate and propensity score analyses were conducted to quantify changes in the odds of being diagnosed with metastatic disease during the pandemic. Results: Lung cancer incidence fell by 10% in 2020 compared to pre-pandemic projections, with rural populations, non-Hispanic Black and Asian patients, and females disproportionately affected. By 2021, detection rates partially recovered but remained 5% below expected levels. Localized disease detection improved significantly, while rural communities not adjacent to metropolitan areas faced further declines. Adjusted analyses showed that patients with small-cell lung cancer (SCLC) and those of Hispanic, non-Hispanic Black, or Asian/Pacific Islander ethnicity had persistently higher rates of distant disease presentation through 2021. Conclusions: The pandemic significantly reduced lung cancer detection, with only partial recovery by 2021. Persistent gaps, particularly in rural and minoritized populations, highlight the need for targeted interventions to reengage these communities.

Variability and uncertainty of variance components in fixed-effects and mixed-effects ground-motion models

It has become common in the development of ground-motion models (GMMs), especially using mixed-effects regression with crossed random effects, to calculate standard deviations, referred to as variance components, from sample statistics of the residuals (i.e. random effects and within-group errors) rather than using the variance components reported by a mixed-effects regression program, calculated using the same algorithms used in the mixed-effects regression, or estimated using Bayesian inference. This practice leads to underestimating the standard deviations because it does not account for the uncertainty (i.e. standard errors) associated with fitting the random effects and within-group errors during the regression analysis. In this study, we used a series of ground-motion models for Fourier amplitude spectra developed using mixed-effects regression of an Next Generation Attenuation (NGA)-West2 database to show that residual-based standard deviations can be significantly smaller than regression-based standard deviations. These differences are exacerbated for those variance components with the fewest number of observations or when the residuals are partitioned (e.g. by earthquake magnitude). Using residual-based variance components not only results in smaller standard deviations but can lead to biased inferences when attempting to compare the efficacy of a model based solely on a comparison of the values of the variance components or their related mean square errors. It can also lead to biased fixed-effects coefficients if the variance components are derived from the residuals of a mixed-effects regression rather than estimated during a regression. We show that variance components can be decomposed into various random-effect grouping factors and partitioned into subsets of predictor variables, such as magnitude, from the total residuals of a non-Bayesian mixed-effects regression program using Bayesian inference. This process does not require the development of an entire GMM using Bayesian mixed-effects regression.

Trends of extreme hyperbilirubinemia related infant mortality in select European countries (1990-2019).

Limited data exist on population-level mortality outcomes related to extreme neonatal hyperbilirubinemia (EHB) and this study examines trends in annual infant mortality rate (IMR) attributed to hemolytic and perinatal jaundice among Germany, France, Italy, Portugal, Greece and Spain from 1990 to 2019. Data on annual incident cases and disability-adjusted life years were collected from the 2019 Global Burden of Disease study. Live birth cohort data were sourced from UN World Population Prospects. We quantified temporal trends, with relative percent changes. Average annual percent changes (AAPCs) were evaluated using the Joinpoint Regression Program. EHB-related infant mortality decreased from 21.4 (95%CI: 16.1, 27.1) in 1990 to 4.2 (95%CI: 1.9, 7.6) per million live births in 2019. Germany demonstrated lowest AAPC of -3.2% (95% CI: -3.8, -2.5), while Portugal had the highest AAPC of -8.6% (95% CI -11.9, -5.1) in reducing infant mortality due to EHB. There were distinct divergences in the trajectories of declining EHB mortality among the studied countries. This study highlights a significant decline in infant mortality due to extreme hyperbilirubinemia, emphasizing the need for national surveillance and tailored guidelines to prevent bilirubin induced neurological damage. This cross-sectional analysis revealed a marked decline in infant mortality rates attributed to extreme hyperbilirubinemia across the selected European countries. The rates of decline varied significantly between countries, demonstrating notable heterogeneity in mortality trends when stratified by age at death. Implementing data-driven surveillance systems can optimize the alignment of equitable healthcare services, strengthen accountability measures, and identify critical operational inefficiencies. In the European Union, country-specific hyperbilirubinemia guidelines should be reinforced to ensure effective screening and post-discharge follow-up protocols that are tailored to risk burden and available healthcare resources.

Abstract 4120332: RISING TRENDS IN ISCHEMIC HEART DISEASE RELATED MORTALITY AMONG OLDER ADULTS WITH SLEEP APNEA IN THE UNITED STATES FROM 1999 TO 2021

Introduction: Sleep apnea (SA) is often underrecognized and undertreated despite its high prevalence in the adult population and its association with adverse cardiovascular outcomes. There are limited estimates of national trends on cardiovascular mortality in older patients with sleep apnea. We aimed to assess the sex and race-related trends of ischemic heart disease (IHD) mortality in the older adults with SA using a large population-based database. Methods: We utilized the Centers for Disease Control and Prevention Wide-Ranging, Online Data for Epidemiologic Research (CDC WONDER) database which provides information from death certificates of all US residents according to the International Classification of Diseases, Tenth Revision (ICD-10). The demographic and mortality data were obtained for the United States population &gt;65 years from 1999 to 2021. Ischemic heart disease (ICD-10 codes I20-I25) was listed as the underlying cause of death, and SA (G47.3) as a contributing cause of death. Age adjusted mortality rates (AAMRs) per 1,000,000 population were calculated by standardizing deaths to the year 2000 US population. We used Jointpoint Regression Program to analyze temporal trends in mortality from 2000 to 2021. Average annual percentage change (AAPC) with 95% CI were calculated to examine trends in AAMR over time. Results: Overall, AAMR of IHD mortality for patients with SA increased from 7.9 per 1,000,000 (95% CI, 6.9-8.8) in 1999 to 53.4 per 1,000,000 (95% CI, 51.4-55.4) in 2021 with an AAPC of 9.1% per year (95% CI, 8.8-9.5). Men had consistently higher AAMR than women throughout the study period (overall AAMR men: 45.51 (95% CI, 44.8-46.2); women: 12.5 (95% CI, 12.2-12.8). Both the groups had a similar increasing trend in AAMR, with men having a steeper increase. [AAPC men: 9.3% (95% CI, 8.5-10.8) versus AAPC women: 8.6%, 95% CI, 8.1-9.7]. Non Hispanic (NH) White population had the greatest AAMR throughout the study period, followed by NH Black and Hispanic or Latino. The NH White population had the largest increase in AAMR from 1999 to 2021 (AAPC 9.4%, 95% CI:8.9-10.1). Conclusion: In the United States, there has been a general increase in IHD mortality related to sleep apnea over the last two decades. This rising trend as noted in our analysis is concerning and underscores the need for more robust cardiovascular surveillance in these patients.

Abstract 4132212: Trends in Atrial Fibrillation or Flutter Related Mortality Among Adults in the United States: Insights from CDC WONDER Database from 1999-2020

Background: Atrial fibrillation or flutter (Afib/AFL) incidence rates continue to rise and are linked to significant mortality, particularly in older populations. Our analysis examines Afib/AFL mortality trends across different demographics and regions in the U.S. from 1999 to 2020, highlighting the importance of understanding these patterns. Aim: To guide preventive measures that alleviate the impact of Afib/AFL and identify high-risk populations and regions, we sought to quantify trends associated with Afib/AFL related mortality in the U.S. Methods: We conducted a comprehensive search of death certificates from 1999-2020 using Centers for Disease Control and Prevention Wide-Ranging OnLine Data for Epidemiologic Research (CDC WONDER) database focusing on Afib/AFL mortality in adults with ICD-10 codes I48. Gender, race, geographical and urban-rural parameters were investigated by calculating annual percent change (APC) and age-adjusted mortality rates (AAMRs) per 100,000 persons using the Joinpoint Regression Program (Joinpoint V 4.9.0.0, National Cancer Institute). Results: A total of 2,581,488 deaths occurred in patients with Afib/AFL from 1999 to 2020. The AAMR displayed an abrupt rise from 2018 to 2020 (APC: 8.51; 95% CI: 4.84-10.47). Men consistently exhibited a higher AAMR (overall AAMR male: 79.4, 95% CI 79.3-79.6; female: 60.8, 95% CI 60.7-60.9). Non-metropolitan areas showed higher AAMRs than metropolitan areas (overall AAMR non-metropolitan areas: 74.9, 95% CI 74.7-75.1; metropolitan: 67.2, 95% CI 67.1-67.2). Disparities were also observed in AAMRs by region with the West region showing the highest mortality rate with a notable rise between 2010 and 2020 (APC: 3.70, 95% CI 3.30-5.37). Non-hispanic (NH) White population showed the highest mortality (overall AAMR: 74.2, 95% CI 74.1-74.3), followed by NH American Indian (AAMR: 50.3), NH Black (AAMR: 45.8), NH Asian (AAMR: 35.0) and Hispanic (AAMR: 37.9) populations. Conclusion: Mortality from Afib/AFL has risen from 1999 to 2020. Men, NH white populations, and residents in non-metropolitan areas and Western U.S. are at higher risk. Targeted interventions and strategic healthcare resource allocation are needed to address these disparities and improve outcomes.

A Method for Inferring Polymers Based on Linear Regression and Integer Programming.

A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear programming. In this paper, we design a new method for inferring a polymer based on the framework. For this, we introduce a new way of representing a polymer as a form of monomer and define new descriptors that feature the structure of polymers. We also use linear regression as a building block of constructing a prediction function in the framework. The results of our computational experiments reveal a set of chemical properties on polymers to which a prediction function constructed with linear regression performs well. We also observe that the proposed method can infer polymers with up to 50 nonhydrogen atoms in a monomer form.

Regional analysis and stage-specific incidence of breast cancer in Kazakhstan: A comprehensive study

BackgroundBreast cancer is the most prevalent oncological pathology in Kazakhstan, ranking among the top three causes of cancer-related deaths in women. The objective of this study is to analyze the incidence of breast cancer, considering factors such as stage, age, sex, and morphological verification in the regional context in Kazakhstan. MethodsThe retrospective study employed descriptive and analytical oncoepidemiological methods. Breast cancer incidence data (2005–2019) were obtained from the Unified Nationwide Electronic Health System (ICD-10 code C50). Demographic data came from the Bureau of National Statistics. Statistical analyses included age-standardized, crude, and age-specific incidence rates, with trend analyses performed using linear regression and the Joinpoint Regression Program to assess average percentage change over time. ResultsThe analysis of breast cancer incidence in Kazakhstan shows significant regional variations and an overall upward trend. Nationally, the age-standardized incidence rate is 40.9 per 100,000, with an annual increase of +1.96 %. Early-stage (I-II) breast cancer incidence is rising, particularly in Pavlodar, North Kazakhstan, and Almaty City. In contrast, advanced-stage (III-IV) incidence has generally declined, except in regions like Kostanay, North Kazakhstan, and Atyrau, where late-stage cases are increasing. High morphological verification rates across all regions ensure reliable and accurate diagnostic data. ConclusionThe study reveals a significant increase in early-stage breast cancer diagnoses in Kazakhstan, highlighting the effectiveness of the national screening program. However, regional disparities in late-stage cancer incidence suggest a need for targeted interventions and improved regional healthcare.

Planetary Health Booms: Unpacking the Surge in Research Across the Globe Through Joint-Point Analysis.

Planetary Health (PH) is a relatively new field that studies the sciences behind the interaction between the environment, living organisms, and human health. The number of publications in this field has increased exponentially in the past few years. This study analyzed the trend of using the term "PH" in literature. We searched PubMed for all publications (APP) and those mentioning Planetary Health (APmPH) without limitations on text availability, dates, or species. The publication trend was estimated using the average annual percent change (AAPC). Joinpoint Regression Program 4.9.1.0 identified periods with statistically distinct log-linear trends in publication numbers over time. Bonferroni adjustment determined significant trend shifts. The time frame of the retrieved APP and APmPH results ranged from 2002 to 2022 with a publication boom since 2017. The most common study designs were reviews, followed by comments and editorials. The APP, APmPH, and the proportion of APmPH to APP steadily increased from 2002 to 2022, with an AAPC of 6.0% (95% CI: 4.4%-7.6%, p<0.001), 35.7 (95% CI: 21.3%-51.9%, p<0.001), and 28.1% (95% CI: 15.2-42.5, p<0.001), respectively. The term "PH" is increasingly prominent in academic literature, underscoring the need for interdisciplinary efforts. Its growing usage also highlights the need for recognition in Medical Subject Headings by the National Library of Medicine.

Trends in high-risk human papillomavirus infection and cervical cytology of women in Karamay City, 2012-2021.

Background To describe the changes in cervical lesions prevalence and high-risk human papillomavirus (HR-HPV) infections from 2012 to 2021, which have never been reported before, to provide direction for the effective implementation of cervical cancer prevention measures. Methods This retrospective study included women aged >25years who received either organised or opportunistic cervical HR-HPV screening from January 2012 to December 2021 in Karamay Central Hospital, Karamay, China. The patients were split into four groups according to age 25-35, 36-45, 46-55 and >55years, respectively. The Joinpoint Regression Program was used to analyse the trends of HR-HPV infection and the detection of cervical lesions. Results Data from 85,429 women revealed a decline in HR-HPV infection rates across all age groups from 2012 to 2021. Although HR-HPV infection rates decreased, cervical lesion detection rates increased, although the proportion of cervical cancer in these lesions declined, likely due to enhanced awareness and HPV vaccination in Karamay. From 2012 to 2021, the prevalence of low-grade squamous intraepithelial lesions was 9.70%, and high-grade squamous intraepithelial lesions was 5.85%. HR-HPV infections were highest in the ≥55years age group, with HPV52 (20.96%) being the most prevalent type. Conclusions In the past 10years, the prevalence of HR-HPV infection has shown a decreasing trend, whereas the detection prevalence of cervical lesions has shown an upward trend among women in Karamay City. Importantly, particular emphasis should be placed on cervical cancer screening in women aged >55years.

Analisis Determinan Faktor pada Earning Per Share Perusahaan

Research aimed to analyze the effect of profitability and solvency to earnings per share. EPS describes the firm’s performance. Whether the firm’s performance is good or not, one of which is measured by its ability to generate profit per share. Also the presence of research gaps from previous research. This makes this research interesting and urgent to do. This research is used purposive sampling method. The samples criteria are included in the LQ45 Index, have positive EPS, have positive profitability and have complete data needed in this research. Research data were analyzed through the Linear Regression program. Regression analysis is carried out by conducting the t test and F test. T test is carried out to analyze the effect of each independent variable on the dependent variable and F test is carried out to analyze the effect of the independent variables simultaneously on the dependent variable. Based on the t test, the results show that Return on Equity or profitability at a significance of 0.000 &lt;0.05 and the Solvency variable at a significance of 0.001 &lt;0.05 proves to have a significant effect on Earnings Per Share (EPS). Based on the F test, it shows the results of profitability and solvency have simultaneous significant effect on Earnings Per Share (EPS) at a significance of 0.001 &lt;0.05.

[Artículo traducido] Efecto de la edad, cohorte y periodo en la incidencia de psoriasis en España: un análisis de 30 años (1990-2019)

AimThis study aimed to investigate the effects of age, period, and cohort on the incidence of psoriasis in Spain from 1990 through 2019 using the Global Burden of Disease (GBD) database and age-period-cohort (A-P-C) analysis. MethodsWe conducted an ecological trend study to analyze the incidence rates of psoriasis in Spain from 1990 through 2019. Joinpoint Regression Program, Version 5.0.2 - May 2023; Surveillance Research Program, National Cancer Institute and National Cancer Institute A-P-C tools were used to identify trends and assess the effects of age, period, and cohort. ResultsFrom 1990 through 2019, an estimated 2.99 million cases of psoriasis were diagnosed in Spain, with a mean annual increase of 0.49%. Significant decreases in age-standardized incidence rates (ASIR) were reported for both sexes, with women consistently maintaining a slightly higher ASIR. Joinpoint analysis revealed multiple turning points in the downward trend, indicating periods of stabilization. A-P-C analysis demonstrated significant declines in both net (overall trend) and local drift (age-specific trends), indicating a broad decrease in the incidence of psoriasis across most age groups. While the risk of psoriasis increased with age, peaking in the 50–54 age group, it declined thereafter. Furthermore, the analysis revealed a continuous decline in risk from 1990 through 2019 for both sexes, with individuals born in the early 21st century exhibiting a significantly lower risk vs those born in the early 20th century. ConclusionThis study observed a slight decline in the reported psoriasis ASIR in Spain, potentially due to reduced exposure to risk factors. However, limitations in data and the complexity of factors influencing the incidence of psoriasis require further research.