• Asian Pacific Journal of Cancer Prevention
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• 제15권9호
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• pp.4091-4094
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• 2014

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.

• Asian Pacific Journal of Cancer Prevention
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• 제14권12호
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• pp.7133-7136
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• 2013

Background: We studied Surveillance, Epidemiology and End Results (SEER) breast cancer data of Georgia USA to analyze the impact of socio-economic factors on the disparity of breast cancer treatment outcome. Materials and Methods: This study explored socio-economic, staging and treatment factors that were available in the SEER database for breast cancer from Georgia registry diagnosed in 2004-2009. An area under the receiver operating characteristic curve (ROC) was computed for each predictor to measure its discriminatory power. The best biological predictors were selected to be analyzed with socio-economic factors. Survival analysis, Kolmogorov-Smirnov 2-sample tests and Cox proportional hazard modeling were used for univariate and multivariate analyses of time to breast cancer specific survival data. Results: There were 34,671 patients included in this study, 99.3% being females with breast cancer. This study identified race and education attainment of county of residence as predictors of poor outcome. On multivariate analysis, these socio-economic factors remained independently prognostic. Overall, race and education status of the place of residence predicted up to 10% decrease in cause specific survival at 5 years. Conclusions: Socio-economic factors are important determinants of breast cancer outcome and ensuring access to breast cancer treatment may eliminate disparities.

• Journal of Species Research
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• 제5권3호
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• pp.547-550
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• 2016

Hemicycliophora litoralis is newly collected from Korea. Korean population is well matched and within a range of original description and additional record from Solomon island in de Man's of L, b, c, V, R, Rex, Ran, Roes, RV (ant), annule, excretory pore, stylet length, and tail length. Differences are observed in RV and RVan. RV and RVan of original description was 55 (48-69) and 14 (10-19) but Korean population is 68 (61-76) and 22 (19-24), respectively. H. litoralis described from Solomon island has RVan of 19.6 (17-23) and is similar to Korean population. H. litoralis from Solomon island has slight higher Rst value of 39 (35-59) compared to Korean population of 33.5 (29-38). The measurements of MB (%), s, G1, G2 values are newly given.

• Bulletin of the Korean Chemical Society
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• 제32권9호
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• pp.3395-3399
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• 2011

Copper oxide thin films were synthesized by reactive radio frequency magnetron sputtering at different oxygen gas ratios. The chemical and physical properties of the thin films were investigated by X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD). XPS results revealed that the dominant oxidation states of Cu were $Cu^0$ and $Cu^+$ at 0% oxygen ratio. When the oxygen ratios increased above 5%, Cu was oxidized as CuO as detected by X-ray induced Auger electron spectroscopy and the $Cu(OH)_2$ phase was confirmed independent of the oxygen ratio. The valence band maxima were $1.19{\pm}0.09$ eV and an increase in the density of states was confirmed after formation of CuO. The thickness and roughness of copper oxide thin films decreased with increasing oxygen ratio. The crystallinity of the copper oxide films changed from cubic Cu through cubic $Cu_2O$ to monoclinic CuO with mean crystallite sizes of 8.8 nm (Cu) and 16.9 nm (CuO) at the 10% oxygen ratio level.

• Asian Pacific Journal of Cancer Prevention
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• 제15권1호
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• pp.25-28
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• 2014

Background: This study analyzed whether socio-economic factors affect the cause specific survival of soft tissue sarcoma (STS). Methods: Surveillance, Epidemiology and End Results (SEER) soft tissue sarcoma (STS) data were used to identify potential socio-economic disparities in outcome. Time to cause specific death was computed with Kaplan-Meier analysis. Kolmogorov-Smirnov tests and Cox proportional hazard analysis were used for univariate and multivariate tests, respectively. The areas under the receiver operating curve were computed for predictors for comparison. Results: There were 42,016 patients diagnosed STS from 1973 to 2009. The mean follow up time (S.D.) was 66.6 (81.3) months. Stage, site, grade were significant predictors by univariate tests. Race and rural-urban residence were also important predictors of outcome. These five factors were all statistically significant with Cox analysis. Rural and African-American patients had a 3-4% disadvantage in cause specific survival. Conclusions: Socio-economic factors influence cause specific survival of soft tissue sarcoma. Ensuring access to cancer care may eliminate the outcome disparities.

• Asian Pacific Journal of Cancer Prevention
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• 제15권1호
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• pp.483-488
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• 2014

Aim: This study employed public use National Health and Nutrition Examination Survey (NHANES III) data to investigate the association between urinary cadmium (UDPSI) and all cause, all cancer and prostate cancer mortalities in men. Patients and Methods: NHANES III household adult, laboratory and mortality data were merged. The sampling weight used was WTPFEX6, with SDPPSU6 applied for the probability sampling unit and SDPSTRA6 to designate the strata for the survey analysis. Results: For prostate cancer death, the significant univariates were UDPSI, age, weight, and drinking. Under multivariate logistic regression, the significant covariates were age and weight. For all cause mortality in men, the significant covariates were UDPSI, age, and poverty income ratio. For all cancer mortality in men, the significant covariates were UDPSI, age, black and Mexican race. Conclusions: UDPSI was a predictor of all cause and all cancer mortalities in men as well as prostate cancer mortality.

• Asian Pacific Journal of Cancer Prevention
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• 제14권12호
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• pp.7117-7120
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• 2013

Background: This study hypothesized living in a poor neighborhood decreased the cause specific survival in individuals suffering from carcinoid carcinomas. Surveillance, Epidemiology and End Results (SEER) carcinoid carcinoma data were used to identify potential socioeconomic disparities in outcome. Materials and Methods: This study analyzed socioeconomic, staging and treatment factors available in the SEER database for carcinoid carcinomas. The Kaplan-Meier method was used to analyze time to events and the Kolmogorov-Smirnov test to compare survival curves. The Cox proportional hazard method was employed for multivariate analysis. Areas under the receiver operating characteristic curves (ROCs) were computed to screen the predictors for further analysis. Results: There were 38,546 patients diagnosed from 1973 to 2009 included in this study. The mean follow up time (S.D.) was 68.1 (70.7) months. SEER stage was the most predictive factor of outcome (ROC area of 0.79). 16.4% of patients were un-staged. Race/ethnicity, rural urban residence and county level family income were significant predictors of cause specific survival on multivariate analysis, these accounting for about 5% of the difference in actuarial cause specific survival at 20 years of follow up. Conclusions: This study found poorer cause specific survival of carcinoid carcinomas of individuals living in poor and rural neighborhoods.

• Asian Pacific Journal of Cancer Prevention
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• 제17권1호
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• pp.347-352
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• 2016

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.

• Asian Pacific Journal of Cancer Prevention
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• 제17권1호
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• pp.353-356
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• 2016

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.

• Asian Pacific Journal of Cancer Prevention
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• 제14권5호
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• pp.3219-3221
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• 2013

Background: This study used receiver operating characteristic (ROC) curves to screen Surveillance, Epidemiology and End Results (SEER) skin melanoma data to identify and quantify the effects of socioeconomic factors on cause specific survival. Methods: 'SEER cause-specific death classification' used as the outcome variable. The area under the ROC curve was to select best pretreatment predictors for further multivariate analysis with socioeconomic factors. Race and other socioeconomic factors including rural-urban residence, county level % college graduate and county level family income were used as predictors. Univariate and multivariate analyses were performed to identify and quantify the independent socioeconomic predictors. Results: This study included 49,999 parients. The mean follow up time (SD) was 59.4 (17.1) months. SEER staging (ROC area of 0.08) was the most predictive foctor. Race, lower county family income, rural residence, and lower county education attainment were significant univariates, but rural residence was not significant under multivariate analysis. Living in poor neighborhoods was associated with a 2-4% disadvantage in actuarial cause specific survival. Conclusions: Racial and socioeconomic factors have a significant impact on the survival of melanoma patients. This generates the hypothesis that ensuring access to cancer care may eliminate these outcome disparities.