Incidence Data Research Articles

The Clinical and Economic Burdens of Obesity and the Value of Weight Loss for an EMR-Derived US Cohort: A Modeling Study.

Obesity-related comorbidities (ORCs) cause significant economic and clinical burdens for people with obesity and the US health care system. A reduction in weight at the population level may reduce incident ORC diagnoses and associated costs of treatment. The aim of this work is to describe obesity burden in the United States through the prevalence and direct treatment costs of ORCs, as well as the clinical and economic value of 15% weight loss in a population of adults with obesity. The IQVIA Ambulatory US electronic medical record database was used to create a cohort (7,667,023 individuals 20-69 years of age, body mass index of 30-50 kg/m2), utilized to characterize the prevalence of 10 ORCs. Direct treatment costs were collected from literature reports. A risk model was leveraged to estimate the number and cost of additional ORC diagnoses over 5 years from baseline through two scenarios: stable weight and 15% lower body weight at baseline for all members of the population. Prevalence, incidence, and cost data were scaled down to a representative subset of 100,000 individuals. In 2022, the annual treatment costs for all 10 ORCs exceeded $918 million for the representative cohort. In a stable-weight scenario, these costs were estimated to increase to ≈$1.4 billion by 2027. With 15% lower body weight at baseline, $221 million in cumulative savings was estimated, corresponding to $2205 in savings/patient over 5 years. Consequently, weight loss in this population may correspond to significantly reduced numbers of incident ORC complications translating to substantial cost savings.

Budget impact analysis of participating in sponsored clinical trials in cancer within the Colombian healthcare system: A real-world evidence approach.

e23031 Background: Clinical trials (CTs) are a key element in researching and developing new technologies for cancer. Assessing the economic impact of CTs and the potential savings for healthcare systems in Low- and Middle-Income Countries (LMICs) is vital to guide healthcare decision-making. This research aims to quantify the budget impact for the Colombian Health System of including hematology and oncology patients in sponsored clinical trials. Methods: This study uses real-world data (RWD) from CTIC, a high-complexity cancer center from Bogotá, Colombia. We followed the Budget Impact Analysis methodology defined by the local HTA agency using data for five tumors retrieved from an institutional data lake resource using clinical information and related costs. Tumors were selected based on their prevalence and economic burden. CTIC’s clinical experts validated the cost-generating events for each disease. The eligible population for phase 3 clinical trials was estimated from the literature and CTIC oncology units’ leaders’ opinions. Prevalent and incident population data were obtained from the Colombian High-Cost Account (CAC). Results: There are 7,703 potential patients to be included in CTs, representing a total cost of 217,544,023 for 2023 USD (1 USD = 4,325 COP). If at least 25% of patients with these tumors were included in CTs in 2023, the approximate cost would be 54,386,006 USD. Advanced prostate cancer represented the highest cost, given its prevalence and CT inclusion opportunity. Conclusions: With approximately USD 24 billion spent on healthcare (USD 5 billion in drugs), Colombia could save around 4% of its drug expenditure if all potential candidates were to be included in cancer CTs. Furthermore, assuming similar average costs per patient, inclusion rates, and population growth for 5-years, this could represent savings of around USD 1.1 billion. These savings would ease the reimbursement and access to innovation for Colombian patients, improving health outcomes and enhancing long-term financial sustainability. [Table: see text]

Cancer in Southeast Asia: A comparative analysis of 2022 incidence and mortality data.

10564 Background: Southeast Asia (SEA), home to over 680 million people representing almost 9% of the global population, is amongst the most diverse and fastest-growing regions in the world. This study evaluates cancer incidence and mortality in Association of Southeast Asian Nations (ASEAN) countries with the goal of informing future research, health services, and cancer policy in the region. Methods: The number of new cases of and deaths from the leading cancers in the ASEAN region, colorectum including anus (ICD-10 C18-C21), liver including intrahepatic bile ducts (C22), lung including trachea and bronchus (C33-34), female breast (C50), cervix uteri (C53) and prostate (C61), were extracted from the International Agency for Research on Cancer GLOBOCAN 2022 database for the 10 ASEAN countries by sex and age groups. Age-standardized incidence and mortality rates (ASIR and ASMR) per 100,000 person-years are presented. Results: In 2022, breast cancer was the most common cancer among women in all ten ASEAN countries (ASIR: Singapore 72.6, Philippines 60.3, Brunei 50.2, Malaysia 46.1, Indonesia 41.8, Vietnam 38.0, Thailand 37.4, Laos 31.6, Cambodia 25.1, Myanmar 23.4). Breast cancer was also the most common cause of cancer mortality among women in five ASEAN countries (ASMR: Philippines 21.5, Malaysia 19.3, Singapore 17.8, Vietnam 14.7, Indonesia 14.4). In Thailand for which time trends are available, ASIR has risen from 19 per 100,000 in 2000 to 37.4 per 100,000 in 2022. Lung cancer was the most common cancer among men in the Philippines (ASIR 37.7), Malaysia (ASIR 23.3), Myanmar (ASIR 21.6), and Indonesia (ASIR 21.3). Lung cancer is also the leading cause of cancer death among men in the Philippines (ASMR 33.6), Singapore (ASMR 31.9), Brunei Darussalam (ASMR 23.8), Malaysia (ASMR 20.4), Myanmar (ASMR 19.9), and Indonesia (ASMR 19.0). Lung cancer is also the leading cause of cancer death among women in Brunei Darussalam (ASMR 18.4). Liver cancer contributes the greatest incidence and mortality among men in Cambodia (ASIR 39.4, ASMR 37.2), Laos (ASIR 36.5, ASMR 36.4), Vietnam (ASIR 34.9, ASMR 33.3), and Thailand (ASIR 34.4, ASMR 33.4). Liver cancer was also the leading cause of cancer death among women in Laos (ASMR 13.5), Cambodia (ASMR 13.3), and Thailand (ASMR 12.1). Cervical cancer is the leading cause of cancer death amongst women in Myanmar (ASMR 13.4). Colorectum cancer is the most common cancer in men in Singapore (ASIR 39.4) and Brunei Darussalam (ASIR 37.7). Conclusions: In 2022, cancer incidence and mortality in SEA were driven primarily by breast cancer among women and lung cancer among men. Liver cancer drives incidence and mortality in Cambodia, Laos, Thailand, and Vietnam. Cervical cancer and colorectal cancer are also significant contributors to incidence and mortality in SEA. Regional and global collaboration is needed to improve cancer prevention, access to diagnosis and care, and research in Southeast Asia.

Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic health records in 420 448 individuals

IntroductionNone of the studies of type 2 diabetes (T2D) subtyping to date have used linked population-level data for incident and prevalent T2D, incorporating a diverse set of variables, explainable methods...

Dengue hemorrhagic fever prediction in coastal area using geographically weighted regression

Dengue hemorrhagic fever (DHF) is still a health problem globally, including in Indonesia. Geographical and climatic conditions in coastal areas are different from other areas, which may impact differences in environmental risk factors for dengue. This study aims to create a prediction model for the incidence of DHF in coastal areas. The research was conducted in Bantul Regency, Indonesia, involving data from 2015-2019. Dengue incidence data were collected from the health office. Climatic data were from climatology station. Data on altitude and shoreline distance were obtained by geographic information system (GIS) processing. Population density and wide settlement area are obtained from the Bureau of Statistics. The geographically weighted regression (GWR) analysis was carried out using GWR4. The results showed that GWR with a weighting of Fixed Bi-Square Kernel obtained an R2 value of 0.7768, better than the global model (R2 0.5254). It indicates that DHF (Y) in Bantul Regency is 77.68% determined by population density (X1), altitude (X2), settlement area (X3), shoreline distance (X4) and rainfall (X5) and the remaining 22.32% are influenced by other variables which are not investigated. Geographically, the predictor variables explain the DHF incidence with a strong category in the central region, and weak in coastal area.

Epidemiological characteristics of syphilis in mainland China, 2004 to 2019.

Syphilis is a globally prevalent sexually transmitted infection. This study aimed to elucidate the epidemiological characteristics of syphilis in China from 2004 to 2019. Incidence data for syphilis across 31 provinces in mainland China were obtained from the Data Center of China Public Health Science for the period from 2004 to 2019. Epidemiological methods and the Chi-squared test were used to analyze the temporal, regional, and disease stage distributions of syphilis. In total, 5,527,399 syphilis cases were reported in China from 2004 to 2019, with an average annual prevalence of 25.7063 per 100,000 population and overall increasing trend. In terms of regional distribution, high-incidence provinces included Shanghai, Zhejiang, Fujian, Guangxi, Guangdong, Xinjiang, Ningxia, and Qinghai. The proportion of latent syphilis increased from 20.41% in 2004 to 82.95% in 2019, with an upward trend each year. Syphilis incidence exhibited an overall increasing trend in China, and latent syphilis was predominant. Syphilis incidences considerably varied among regions, and syphilis was detected from coastal to inland provinces. Thus, syphilis prevention and control programs should be tailored according to the specific epidemiological characteristics of each region.

Racial/ethnic representation and disparities in preclinical cancer models.

1601 Background: Patient-derived xenograft models (PDXs) recapitulate tumor characteristics credibly and have become a standard for preclinical inquiries that form the basis of clinical trials of novel therapies in oncology. While ample evidence reveals racial/ethnic disparities in cancer care delivery and clinical research, limited data exists regarding racial composition of available PDXs. We sought to define the extent of racial/ethnic representation and disparities among existing PDXs. Methods: Data regarding available PDXs was gathered from the publicly accessible CancerModels.org website ( https://www.cancermodels.org/overview ). Seven members of the research team were involved in data extraction. Information on race/ethnicity (White, Black, Hispanic, Asian), sex, age, and cancer type were recorded. The primary objective was to determine the racial/ethnic composition of PDX models and compare this to racial/ethnic demographics of cancer patients, for which we used US population-based cancer estimates calculated using National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER Incidence Data, 11/2022 Submission (1975 - 2020), SEER 22 registries). Descriptive statistics were used. Proportions were compared using Fischer’s exact test or Chi-squared tests with Yates' correction (odds-ratio [OR] and 95% confidence intervals [95%CI] or Woolf logit interval) were reported. Results: We reviewed 4597 unique PDXs across 33 SEER cancer sites spanning 11 oncology sub-specialties. Of these, 55% models were derived from males and age groups were (years): < 20: 6%; 20-70: 69% and ≥ 70: 25%. Most common cancer sites represented were colorectal (26%), lung (12%), breast (9%), melanoma (9%) and leukemia (7%). Race/ethnicity was not reported in 3395 (73.9%) cases. Racial/ethnic composition of the remaining models was Whites (80.9%), Blacks (7.3%), Hispanics (6.4%) and Asians (5.4%). Compared with their respective proportion of US cancer incidence (69.9%, 10.9%, 13.2% and 5.9%, respectively), these models were over-representative for Whites (OR: 1.82, 95%CI: 1.6-2.1, P < 0.001) and under-represented Blacks (OR: 0.64, 95%CI: 0.5-0.8, P < 0.001) and Hispanics (OR: 0.45, 95%CI: 0.4-0.6, P < 0.001) but not Asians (OR: 0.89, 95%CI: 0.7-1.2, P = 0.43). Similar trends were seen in subgroups focused by cancer site. Among colorectal (N = 1201) models, race/ethnicity was reported for 17.2% of cases and Blacks (OR: 0.52; 55.7% of expected; P = 0.014) and Hispanics (OR: 0.57; 60.8% of expected; P = 0.015) were underrepresented compared to Whites (OR: 1.82; 116% of expected; P < 0.001). Conclusions: Race/ethnicity are infrequently reported for PDX models. Minority races/ethnicities (Blacks and Hispanics) are underrepresented in preclinical models compared to their burden of cancer incidence. There is a need to develop a diverse repertoire of preclinical models to ensure inclusivity and guide equitable research.

Lung and bronchus cancer in young females: Exploring sex disparities across diverse racial and ethnic groups in the U.S. (2000-2020).

e20048 Background: Lung and bronchus cancer incidence rates have been reported to be higher among females than males under the age of 50, particularly after 2004. The first e-cigarette device emerged in 2003, raising questions about its potential impact on cancer incidence in females compared to males and its connection to the sudden rise in female cases. This study aims to investigate sex differences in cancer incidence across diverse racial and ethnic groups, aiming to determine whether these variations stem from biological factors or unexplored environmental exposures. Methods: Cancer incidence data from the Surveillance, Epidemiology, and End Result (SEER) program (2000-2020) were utilized to analyze female-to-male incidence rate ratios (FM IRR) for young-onset lung and bronchus cancer diagnosed before the age of 50. The data was stratified by race and ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic Asian/Pacific Islander, American Indian/Alaskan Native, and Hispanic) and age-standardized to the 2000 U.S. population. Results: In the period from 2000 to 2020, 41,066 patients with lung and bronchus cancer under the age of 50 were identified. Incidence trends showed a consistent decrease each year, reaching the lowest rates in 2020 (2.1 per 100,000 cases) and the highest in 2000 (4.9 per 100,000 cases). Males accounted for 49.4% (20,303), while females constituted 50.6% (20,763). Despite the overall declining trend, FM IRR steadily increased post-2004, exhibiting a constant rise between 2005 and 2020. Non-Hispanic White comprised 65.9% of the cases, with the second and third largest groups being Non-Hispanic Black (15.3%) and Hispanic (9.62%). Incidence rates were highest among non-Hispanic Black (4.9 per 100,000 cases), followed by non-Hispanic White (4.2 per 100,000 cases), and lowest in the Hispanic population (1.6 per 100,000 cases). Young-onset lung and bronchus cancer diagnosed before age 50 showed a female predominance after 2004, with the Hispanic population having the highest FM IRR between 2000 and 2020 (1.13), followed by Non-Hispanic American Indian/Alaska Native (1.09) and Non-Hispanic White (1.02). There was a lower FM IRR among Non-Hispanic Black and Non-Hispanic Asian/Pacific Islander (0.83) and (0.96), respectively. Conclusions: The FM IRR for young-onset lung and bronchus cancer exhibited variations among racial and ethnic groups, with the highest rates observed among the Hispanic population. This study was limited by the absence of data on smoking habits and other environmental factors. Further research is needed to investigate the influence of e-cigarettes and other environmental factors on the incidence of lung and bronchus cancer, considering variations by sex.

Exploring young-onset colorectal cancer sex difference incidence rates by race and ethnicity: A SEER database analysis (2000-2020).

e15529 Background: Since 1994, there has been a 51% increase in young onset colorectal cancer incidence rates, as reported by the National Cancer Institute. Recently, the U.S. Preventative Task Force revised its guidelines, recommending colorectal cancer screening to commence at age 45 rather than 50. This study aimed to explore sex differences in cancer incidence across various race and ethnicities, aiming to discern whether these differences are rooted in biological factors or environmental exposures. Methods: Cancer incidence data from the Surveillance, Epidemiology and End Result (SEER) program (2000-2020) was used to calculate male-to-female incidence rate ratios (MF IRR) for colon and rectal cancer, stratified by race and ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic Asian/Pacific Islander, American Indian/Alaskan Native, and Hispanic), and age-standardized to the 2000 U.S. population for individuals under the age of 50 diagnosed with colon or rectal cancer. Results: A total of 82,238 patients with colorectal cancer under the age of 50 were identified in the study period. Of these, 43,255 (52.6%) were males and 38,983 (47.4%) were females. The incidence trends over the years were analyzed, revealing a steady increase, with the highest incidence found in 2019 (4,819, 5.8%) and the lowest in 2000 (3,189, 3.8%). Non-Hispanic Whites comprised 57.2% of the cases, while the second and third largest groups were Non-Hispanic Black (13.2%) and Hispanic (17.9%). Incidence rates were highest among the non-Hispanic American Indian/Alaskan Native population (8.6 per 100,000 cases), followed by the non-Hispanic Black population (8.4 per 100,000 cases), and lowest in the Hispanic population (5.7 per 100,000 cases). Young-onset colorectal cancer incidence rates exhibited a male predominance, with the MF IRR consistently > 1 every year across race and ethnicity. Non-Hispanic Asian/Pacific Islander had the highest MF IRRs (7 per 100,000 cases in males vs. 5.8 per 100,000 cases in females), while Non-Hispanic American Indian/Alaskan Native had the lowest MF IRRs throughout the years, with the lowest being in 2019 (5.1 per 100,000 cases in males vs. 12.6 per 100,000 cases in females). Conclusions: The MF IRR for young onset colorectal cancer showed no significant variation by race, implying a potential influence of biological factors. Notably, disparities in incidence rates were observed among different racial and ethnic groups, with the highest rates among non-Hispanic Black and non-Hispanic American Indian/Alaskan Native populations. Further research is warranted to pinpoint specific factors driving young onset colorectal cancer, facilitating targeted interventions for at-risk populations.

Impact of Collegiate Football Games on Emergency Response Intervals: A Case Study of College Station, Texas (USA).

Little is known about how mass gatherings affect emergency response intervals. Previous research suggests that college football games increase ambulance transport intervals, but their impact on emergency response intervals is unexplored. This study examines how collegiate home football games in College Station, Texas (USA) affect emergency vehicle response intervals. The study determined the impact of collegiate football games on emergency response intervals using incident data provided by the College Station Fire Department (CSFD). Home games during the 2021-2023 Texas A&M University (TAMU) football seasons were the period of interest. Responses for a 72-hour period (Friday-Sunday) on home game weekends (HGWs) and non-home game weekends (NHGWs) were included (n = 5,095). Response intervals on football HGWs were an average of 30 seconds faster than on NHGWs. Emergency vehicles were 16.5% less likely to respond from fire station locations on HGWs compared to NHGWs. There was also a 12.1% increase in the number of calls to campus locations and a 9.7% increase in calls to the local entertainment district on HGWs compared to NHGWs. Home collegiate football games do not delay response intervals for emergency response vehicles. Further research is needed to determine if these findings can be reproduced in other communities.

Patient Safety Incidents in Operating Rooms Reported in the Past Five Years (2017-2021) in Korea.

Patient safety incidents in the operating room require special attention because they can cause catastrophic and irreversible conditions in patients. Although patient safety incidents have different characteristics, there may be similarities and patterns of risk factors that may be common. Therefore, this study analyzed factors associated with the PSIs by analyzing data from the Korean Patient Safety Reports from 2017 to 2019. The "Patient Safety Incidents Data from 2017 to 2021" systematically collected by the Korea Institute for Healthcare Accreditation, include patient safety incident reports from medical institutions. Data on 1140 patient safety incidents in the operating room were analyzed. They included patients' gender and age, Hospital size, Incident seasons, incident time, Incident reporter, incident type, Medical department, and Incident severity. The Incident severity was analyzed by dividing it into three stages: near miss, adverse event, sentinel event, which are applied by domestic medical institutions. The highest number of OR patient safety incidents were related to surgery and anesthesia. On analyzing the probability of adverse events based on near misses, the significant variables were patient gender, incident reporter, incident type, and Medical department. Additionally, the factors that were likely to precipitate sentinel events based on near misses were patient gender, incident time, reporter, and incident type. To prevent sentinel events in Patient safety incidents, female and during night shifts are required to pay close attention. Moreover, it is necessary to establish a patient safety reporting system in which not only all medical personnel, but also patients, generally, can actively participate in patient safety activities.

Improving tuberculosis control: assessing the value of medical masks and case detection-a multi-country study with cost-effectiveness analysis.

Tuberculosis (TB) remains a significant global health concern, necessitating effective control strategies. This article presents a mathematical model to evaluate the comparative effectiveness of medical mask usage and case detection in TB control. The model is constructed as a system of ordinary differential equations and incorporates crucial aspects of TB dynamics, including slow-fast progression, medical mask use, case detection, treatment interventions and differentiation between symptomatic and asymptomatic cases. A key objective of TB control is to ensure that the reproduction number, , remains below unity to achieve TB elimination or persistence if exceeds 1. Our mathematical analysis reveals the presence of a transcritical bifurcation when the signifies a critical juncture in TB control strategies. These results confirm that the effectiveness of case detection in diminishing the endemic population of symptomatic individuals within a TB-endemic equilibrium depends on exceeding a critical threshold value. Furthermore, our model is calibrated using TB yearly case incidence data per 100 000 population from Indonesia, India, Lesotho and Angola. We employed the bootstrap resampling residual approach to assess the uncertainty inherent in our parameter estimates which provides a comprehensive distribution of the parameter values. Despite a declining trend in new incidence, these four countries exhibit a reproduction number greater than 1, indicating persistent TB cases in the presence of ongoing TB control programmes. We employ the partial rank correlation coefficient in conjunction with the Latin hypercube sampling method to conduct a global sensitivity analysis of the parameter for each fitted parameter in every country. We find that the medical mask use is more sensitive to reduce compared with the case detection implementation. To further gain insight into the necessary control strategy, we formulated an optimal control and studied the cost-effectiveness analysis of our model to investigate the impact of case detection and medical mask use as control measures in TB spread. Cost-effectiveness analysis demonstrates that combining these interventions emerges as the most cost-effective strategy for TB control. Our findings highlight the critical importance of medical masks and their efficacy coupled with case detection in shaping TB control dynamics, elucidating the primary parameter of concern for managing the control reproduction number. We envisage our findings to have implications and be vital for TB control if implemented by policymakers and healthcare practitioners involved in TB control efforts.

Incidence trends and spatial distribution of thyroid cancer in the Chinese female population from 1990 to 2019

ObjectiveThis study aimed to analyze the incidence trends and spatial distribution characteristics of thyroid cancer among Chinese females from 1990 to 2019, thereby providing a scientific foundation and data support for the development of prevention and control policies. MethodsThyroid cancer incidence data from the Global Burden of Disease (GBD) research and the annual report from the Chinese Tumor Registration were utilized. The standardized thyroid cancer incidence rate among Chinese females 1990 to 2019 was described to understand the changes in developmental trends. The JoinPoint Regression Model was employed using Excel 2019, GraphPad Prism 8, JoinPoint Regression Program 4.8.0.1, and ArcGIS 10.2. ResultsThyroid cancer's standardized incidence among female Chinese continued to increase at 1.7% per year (annual average percentage change [AAPC] = 1.7, P < 0.001), and the spatial distribution was clustered. The main high-incidence areas were North, East, and Northwest China. ConclusionsThyroid cancer incidence in Chinese women is rapidly increasing, and its spatial distribution is concentrated. Strengthening monitoring, prevention, and control efforts in the relevant areas is warranted.

Fast Bayesian Functional Regression for Non-Gaussian Spatial Data

Functional generalized linear models (FGLM) have been widely used to study the relations between non-Gaussian response and functional covariates. However, most existing works for FGLM assume independence among observations and therefore they are of limited applicability for correlated data. A particularly important example is spatial functional data, where we observe functions over spatial domains, such as the age population curve or temperature curve at each areal unit. In this paper, we extend FGLM by incorporating spatial random effects. Especially, we study the relationship between the non-Gaussian response variable and functional covariates that are spatially observed. However, such model has computational and inferential challenges. The high-dimensional spatial random effects cause the slow mixing of Markov chain Monte Carlo (MCMC) algorithms. Furthermore, spatial confounding can lead to bias in parameter estimates and inflate their variances. To address these issues, we propose an efficient Bayesian method using a sparse reparameterization of high-dimensional random effects. We also study the average coverage probabilities of the credible intervals of functional parameters. We apply our methods to simulated and real data examples, including malaria incidence data and US COVID-19 data. The proposed method is fast while providing accurate functional estimates.

Factors Associated with Primary Liver Cancer Survival in a Southern Italian Setting in a Changing Epidemiological Scenario.

A retrospective observational study utilising cancer incidence data from a population-based registry investigated determinants affecting primary liver cancer survival in a southern Italian region with high hepatitis viral infection rates and obesity prevalence. Among 2687 patients diagnosed between 2006 and 2019 (65.3% male), a flexible hazard-based regression model revealed factors influencing 5-year survival rates. High deprivation levels [HR = 1.41 (95%CI = 1.15-1.76); p < 0.001], poor access to care [HR = 1.99 (95%IC = 1.70-2.35); p < 0.0001], age between 65 and 75 [HR = 1.48 (95%IC = 1.09-2.01); p < 0.05] or >75 [HR = 2.21 (95%CI = 1.62-3.01); p < 0.0001] and residing in non-urban areas [HR = 1.35 (95%CI = 1.08-1.69); p < 0.01] were associated with poorer survival estimates. While deprivation appeared to be a risk factor for primary liver cancer patients residing within the urban area, the geographic distance from specialised treatment centres emerged as a potential determinant of lower survival estimates for residents in the non-urban areas. After balancing the groups of easy and poor access to care using a propensity score approach, poor access to care and a lower socioeconomic status resulted in potentially having a negative impact on primary liver cancer survival, particularly among urban residents. We emphasise the need to interoperate cancer registries with other data sources and to deploy innovative digital solutions to improve cancer prevention.

Analysis and forecasting of syphilis trends in mainland China based on hybrid time series models.

Syphilis remains a serious public health problem in mainland China that requires attention, modelling to describe and predict its prevalence patterns can help the government to develop more scientific interventions. The seasonal autoregressive integrated moving average (SARIMA) model, long short-term memory network (LSTM) model, hybrid SARIMA-LSTM model, and hybrid SARIMA-nonlinear auto-regressive models with exogenous inputs (SARIMA-NARX) model were used to simulate the time series data of the syphilis incidence from January 2004 to November 2023 respectively. Compared to the SARIMA, LSTM, and SARIMA-LSTM models, the median absolute deviation (MAD) value of the SARIMA-NARX model decreases by 352.69%, 4.98%, and 3.73%, respectively. The mean absolute percentage error (MAPE) value decreases by 73.7%, 23.46%, and 13.06%, respectively. The root mean square error (RMSE) value decreases by 68.02%, 26.68%, and 23.78%, respectively. The mean absolute error (MAE) value decreases by 70.90%, 23.00%, and 21.80%, respectively. The hybrid SARIMA-NARX and SARIMA-LSTM methods predict syphilis cases more accurately than the basic SARIMA and LSTM methods, so that can be used for governments to develop long-term syphilis prevention and control programs. In addition, the predicted cases still maintain a fairly high level of incidence, so there is an urgent need to develop more comprehensive prevention strategies.

Quality check: concordance between two monitoring systems for postoperative organ/space-surgical site infections in rectal cancer surgery. Linkage of data from the Catalan Cancer Plan and the VINCat infection surveillance programme

BackgroundThe Catalan Cancer Plan (CCP) undertakes periodic audits of cancer treatment outcomes, including organ/space surgical site infections (O/S-SSI) rates, while the Catalan Healthcare-associated Infections Surveillance Programme (VINCat) carries out standardized prospective surveillance of surgical site infections (SSI) in colorectal surgery. This cohort study aimed to assess the concordance between these two monitoring systems for O/S-SSI following primary rectal cancer surgery.MethodsThe study compared O/S-SSI incidence data from CCP clinical audits versus the VINCat Programme in patients undergoing surgery for primary rectal cancer, in 2011-12 and 2015-16, in publicly funded centres in Spain. The main outcome variable was the incidence of O/S-SSI in the first 30 days after surgery. Concordance between the two registers was analysed using Cohen’s kappa. Discordant cases were reviewed by an expert, and the main reasons for discrepancies evaluated.ResultsPooling data from both databases generated a sample of 2867 patients. Of these, O/S-SSI was detected in 414 patients—235 were common to both registry systems, with satisfactory concordance (κ = 0.69, 95% confidence interval 0.65–0.73). The rate of discordance from the CCP (positive cases in VINCat and negative in CCP) was 2.7%, and from VINCat (positive in CCP and negative in VINCat) was 3.6%. External review confirmed O/S-SSI in 66.2% of the cases in the CCP registry and 52.9% in VINCat.ConclusionsThis type of synergy shows the potential of pooling data from two different information sources with a satisfactory level of agreement as a means to improving O/S-SSI detection. ClinicalTrials.gov Identifier: NCT06104579. Registered 30 November 2023.

The Role of Social Deprivation and Cannabis Use in Explaining Variation in the Incidence of Psychotic Disorders: Findings From the EU-GEI Study.

Recent findings suggest the incidence of first-episode psychotic disorders (FEP) varies according to setting-level deprivation and cannabis use, but these factors have not been investigated together. We hypothesized deprivation would be more strongly associated with variation in FEP incidence than the prevalence of daily or high-potency cannabis use between settings. We used incidence data in people aged 18-64 years from 14 settings of the EU-GEI study. We estimated the prevalence of daily and high-potency cannabis use in controls as a proxy for usage in the population at-risk; multiple imputations by chained equations and poststratification weighting handled missing data and control representativeness, respectively. We modeled FEP incidence in random intercepts negative binomial regression models to investigate associations with the prevalence of cannabis use in controls, unemployment, and owner-occupancy in each setting, controlling for population density, age, sex, and migrant/ethnic group. Lower owner-occupancy was independently associated with increased FEP (adjusted incidence rate ratio [aIRR]: 0.76, 95% CI: 0.61-0.95) and non-affective psychosis incidence (aIRR: 0.68, 95% CI: 0.55-0.83), after multivariable adjustment. Prevalence of daily cannabis use in controls was associated with the incidence of affective psychoses (aIRR: 1.53, 95% CI: 1.02-2.31). We found no association between FEP incidence and unemployment or high-potency cannabis use prevalence. Sensitivity analyses supported these findings. Lower setting-level owner-occupancy and increased prevalence of daily cannabis use in controls independently contributed to setting-level variance in the incidence of different psychotic disorders. Public health interventions that reduce exposure to these harmful environmental factors could lower the population-level burden of psychotic disorders.

Development of an Italian National Epidemiological Register on Endometriosis Based on Administrative Data.

Background/Objectives: Endometriosis is a female chronic inflammatory disease in which endometrial tissue develops outside the uterine cavity. It is a complex pathology, which significantly contributes to morbidity in premenopausal women, leading to chronic pain, infertility, and subfertility negatively impacting physical and emotional well-being and the overall quality of life. The public health burden of endometriosis remains elusive and challenging to determine, and this uncertainty can lead to inadequate healthcare services and treatments. The objective was to estimate the incidence and prevalence of endometriosis in Italy using the hospital discharge records database via a population-based retrospective study, nationwide between 2011 and 2020. Methods: From the National Hospital Discharge Database, we selected all admissions with a diagnosis of endometriosis (ICD-9-CM, codes 617.x), supported by the presence of a procedure code of laparoscopy or any other surgical procedure allowing for direct visualisation of the lesions. The main outcomes measured: incidence and prevalence of endometriosis were estimated for the entire 2011-2020 period and by individual year, analysing the time trend and variability in different geographical areas of Italy. Results: There were a total of 134,667,646 women aged 15-50 years with one or more hospitalisations for endometriosis in all Italian hospitals. The incidence of endometriosis in Italy during this period was 0.839 per 1000 women (CI95% 0.834-0.844), exhibiting a statistically significant decreasing trend over the years. A discernible north-south gradient was observed, with higher rates documented in the northern regions. The prevalence rate stood at 14.0 per 1000 during the same period, and a similar north-south geographical gradient was identifiable in the prevalence rates as well. Conclusions: The utilization of national-level hospital data enables the generation of incidence and prevalence data for endometriosis without variations in methods and definitions, facilitating the evaluation of temporal trends and regional comparisons. Understanding and quantifying this phenomenon is essential for appropriate healthcare planning in various Italian regions.

Semisupervised Machine Learning Approach for Ddos Detection

Analyzing cyber incident data sets is an important method for deepening our understanding of the evolution of the threat situation. In present generation we come to know about many cyber breaches and hacking taking place. In this project work, we research about the various cyber- attacks and breaches and study the way these attacks are done and find an alternative for the same. We show that rather than by distributing these attacks as because they exhibit autocorrelations, we should model by stochastic process both the hacking breach incident inter- arrival times and breach sizes. We draw a set of cyber securities insights, including that the threat of cyber hacks is indeed getting worse in terms of their frequency. In our project we will be using the algorithms such as Convolution Neural Network (CNN) as existing and Recurrent Neural Network (RNN) as proposed for analyzing our results. From the results obtained its proved that proposed RNN works better than existing CNN.