Purpose: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) ependymoma data to identify predictive models and potential disparity in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ependymoma. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome ('brain and other nervous systems' specific death in yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of ependymoma death was computed for the predictors for comparison. Results: A total of 3,500 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 79.8 (82.3) months. Some 46% of the patients were female. The mean (S.D.) age was 34.4 (22.8) years. Age was the most predictive factor of outcome. Unknown grade demonstrated a 15% risk of cause specific death compared to 9% for grades I and II, and 36% for grades III and IV. A 5-tiered grade model (with a ROC area 0.48) was optimized to a 3-tiered model (with ROC area of 0.53). This ROC area tied for the second with that for surgery. African-American patients had 21.5% risk of death compared with 16.6% for the others. Some 72.7% of patient who did not get RT had cerebellar or spinal ependymoma. Patients undergoing surgery had 16.3% risk of death, as compared to 23.7% among those who did not have surgery. Conclusion: Grading ependymoma may dramatically improve modeling of data. RT is under used for cerebellum and spinal cord ependymoma and it may be a potential way to improve outcome.
Introduction: Capture-recapture methods have been suggested for reducing costs of disease registration as well as reducing bias in incidence estimations. This study aimed to estimate the gastric cancer incidence in the Tehran metropolis population during 2002-2006. Materials and Methods: We investigated new cases of gastric cancer reported by three sources; death certificates, pathology reports, and medical records to Tehran population-based cancer registry during 2002-2006. $G^2$ statistics and the two-source capture-recapture method were used to select the best-fitted log-linear model and to estimate incidence, respectively. EXCEL software version 2007 and SPSS software version 16 were used for this research. Results: The number of reported cases was 4,463, with an average age of 68.5 (${\pm}12.9$) years. We found the model that combined two sources of data including pathology reports and medical records and furthermore complemented by death certificates as the best model. The reported and the estimated incidences were 11.0 and 27.1 per 100,000 respectively. Conclusions: The incidence estimated by two-source capture-recapture method is about three times higher than the incidence reported by the sources under investigation. It is recommended to move towards the implementation of population-based cancer registration using various sources of data collection to achieve more accurate data.
Mathew, Aleyamma;George, Preethi Sara;Arjunan, Asha;Augustine, Paul;Kalavathy, MC;Padmakumari, G;Mathew, Beela Sarah
Asian Pacific Journal of Cancer Prevention
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제17권6호
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pp.2895-2899
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2016
Background: Increasing breast cancer (BC) incidence rates have been reported from India; causal factors for this increased incidence are not understood and diagnosis is mostly in advanced stages. Trivandrum exhibits the highest BC incidence rates in India. This study aimed to estimate trends in incidence by age from 2005-2014, to predict rates through 2020 and to assess the stage at diagnosis of BC in Trivandrum. Materials and Methods: BC cases were obtained from the Population Based Cancer Registry, Trivandrum. Distribution of stage at diagnosis and incidence rates of BC [Age-specific (ASpR), crude (CR) and age-standardized (ASR)] are described and employed with a joinpoint regression model to estimate average annual percent changes (AAPC) and a Bayesian model to estimate predictive rates. Results: BC accounts for 31% (2681/8737) of all female cancers in Trivandrum. Thirty-five percent (944/2681) are <50 years of age and only 9% present with stage I disease. Average age increased from 53 to 56.4 years (p=0.0001), CR (per $10^5$ women) increased from 39 (ASR: 35.2) to 55.4 (ASR: 43.4), AAPC for CR was 5.0 (p=0.001) and ASR was 3.1 (p=0.001). Rates increased from 50 years. Predicted ASpR is 174 in 50-59 years, 231 in > 60 years and overall CR is 80 (ASR: 57) for 2019-20. Conclusions: BC, mostly diagnosed in advanced stages, is rising rapidly in South India with large increases likely in the future; particularly among post-menopausal women. This increase might be due to aging and/or changes in lifestyle factors. Reasons for the increased incidence and late stage diagnosis need to be studied.
Background: This study used the receiver operating characteristic curve (ROC) to analyze Surveillance, Epidemiology and End Results (SEER) bronchioaveolar carcinoma data to identify predictive models and potential disparity in outcomes. Materials and Methods: Socio-economic, staging and treatment factors were assessed. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict cause specific survival. The area under the ROC was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate modeling errors. Risk of cause specific death was computed for the predictors for comparison. Results: There were 7,309 patients included in this study. The mean follow up time (S.D.) was 24.2 (20) months. Female patients outnumbered male ones 3:2. The mean (S.D.) age was 70.1 (10.6) years. Stage was the most predictive factor of outcome (ROC area of 0.76). After optimization, several strata were fused, with a comparable ROC area of 0.75. There was a 4% additional risk of death associated with lower county family income, African American race, rural residency and lower than 25% county college graduate. Radiotherapy had not been used in 2/3 of patients with stage III disease. Conclusions: There are socio-economic disparities in cause specific survival. Under-use of radiotherapy may have contributed to poor outcome. Improving education, access and rates of radiotherapy use may improve outcome.
SALEH, Choirul;HAYAT, Hayat;SUMARTONO, Sumartono;PRATIWI, Ratih Nur
The Journal of Asian Finance, Economics and Business
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제7권6호
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pp.287-296
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2020
The study investigates the relationship and influence between religiosity, reward, and engagement in the public administration sector, both directly and causally via moderation. This study involved one hundred and twenty-three respondents in three local government organizations in Malang City, East Java Province, Indonesia, namely, the Malang City General Hospital, the Population and Civil Registry Office, and the Investment Office. The sampling method uses stratified random sampling from the total population of civil servants in Malang in the three institutions. The data analysis model of this study uses a quantitative approach with a unit of data analysis using the path analysis method. The analytical tools used are smart-PLS and SPSS. The results reveal that the direct combined effect of reward and religiosity has a positive and significant influence on the engagement. However, moderation between reward and commitment, which is bridged by religiosity, does not show positive and significant results. The non-positive relationship shown by testing moderation concludes that there is a separation of purpose between the portion of religiosity in the world of work, where religiosity in this study is only described as part of the concept of worship, and the relationship between the person and his God.
Malware propagated via the World Wide Web is one of the most dangerous tools in the realm of cyber-attacks. Its methodologies are effective, relatively easy to use, and are developing constantly in an unexpected manner. As a result, rapidly detecting malware propagation websites from a myriad of webpages is a difficult task. In this paper, we present LoGos, an automated high-interaction dynamic analyzer optimized for a browser-based Windows virtual machine environment. LoGos utilizes Internet Explorer injection and API hooks, and scrutinizes malicious behaviors such as new network connections, unused open ports, registry modifications, and file creation. Based on the obtained results, LoGos can determine the maliciousness level. This model forms a very lightweight system. Thus, it is approximately 10 to 18 times faster than systems proposed in previous work. In addition, it provides high detection rates that are equal to those of state-of-the-art tools. LoGos is a closed tool that can detect an extensive array of malicious webpages. We prove the efficiency and effectiveness of the tool by analyzing almost 0.36 M domains and 3.2 M webpages on a daily basis.
Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Conclusions: Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.
Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) for glassy cell carcinoma data to identify predictive models and potential disparities in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors. For risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. Area under the receiver operating characteristic curves (ROCs) were computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate modeling errors. Risk of glassy cell carcinoma death was computed for the predictors for comparison. Results: There were 79 patients included in this study. The mean follow up time (S.D.) was 37 (32.8) months. Female patients outnumbered males 4:1. The mean (S.D.) age was 54.4 (19.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.69). The risks of cause specific death were, respectively, 9.4% for localized, 16.7% for regional, 35% for the un-staged/others category, and 60% for distant disease. After optimization, separation between the regional and unstaged/others category was removed with a higher ROC area of 0.72. Several socio-economic factors had small but measurable effects on outcome. Radiotherapy had not been used in 90% of patients with regional disease. Conclusions: Optimized SEER stage was predictive and useful in treatment selection. Underuse of radiotherapy may have contributed to poor outcome.
Background: This is a part of a larger effort to characterize the effects on socio-economic factors (SEFs) on cancer outcome. Surveillance, Epidemiology and End Result (SEER) bone and joint sarcoma (BJS) data were used to identify potential disparities in cause specific survival (CSS). Materials and Methods: This study analyzed SEFs in conjunction with biologic and treatment factors. Absolute BJS specific risks were calculated and the areas under the receiver operating characteristic (ROC) curve were computed for predictors. Actuarial survival analysis was performed with Kaplan-Meier method. Kolmogorov-Smirnov's 2-sample test was used to for comparing two survival curves. Cox proportional hazard model was used for multivariate analysis. Results: There were 13501 patients diagnosed BJS from 1973 to 2009. The mean follow up time (SD) was 75.6 (90.1) months. Staging was the highest predictive factor of outcome (ROC area of 0.68). SEER stage, histology, primary site and sex were highly significant pre-treatment predictors of CSS. Under multivariate analysis, patients living in low income neighborhoods and rural areas had a 2% and 5% disadvantage in cause specific survival respectively. Conclusions: This study has found 2-5% decrement of CSS of BJS due to SEFs. These data may be used to generate testable hypothesis for future clinical trials to eliminate BJS outcome disparities.
The paper discusses a novel educational initiative in e-commerce pedagogy where students work on an e-government project. The paper describes a two-semester joint e-government project conducted by the town of Amherst, NY, and the State University of New York at Buffalo. During the first semester, students in a graduate e-commerce course in the School of Management were instructed to identify and analyze management issues valuable for small or middle size local government. In the second semster graduate students from the Department of Computer Science and Engineering designed and implemented prototypes of three e-government portals: an on-line action site for governmental procurement (E-Procurement), a portal for reservation of community recreation facilities (E-Recreation), and a portal for online dog registration (E-DogRegistration) combining a central registry of dog owners with distributed veterinarian databases. The objective of this initiative is twofold. First, it saves the local government resources by eliminating duplication of services and by using students as developers. Second, it provides students with real life hands-on experience. The paper discusses both the technical issues involved in the implementation of the project, and the management issues that need to be taken into account to enhance the e-commerce experience for the ordinary citizen and local governments.
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