• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5571-5575
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• 2014

Background: The ability to predict the survival time of breast cancer patients is important because of the potential high morbidity and mortality associated with the disease. To develop a predictive inference for determining the survival of breast cancer patients, we applied a novel Bayesian method. In this paper, we propose the development of a databased statistical probability model and application of the Bayesian method to predict future survival times for White Hispanic female breast cancer patients, diagnosed in the US during 1973-2009. Materials and Methods: A stratified random sample of White Hispanic female patient survival data was selected from the Surveillance Epidemiology and End Results (SEER) database to derive statistical probability models. Four were considered to identify the best-fit model. We used three standard model-building criteria, which included Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) to measure the goodness of fit. Furthermore, the Bayesian method was used to derive future survival inferences for survival times. Results: The highest number of White Hispanic female breast cancer patients in this sample was from New Mexico and the lowest from Hawaii. The mean (SD) age at diagnosis (years) was 58.2 (14.2). The mean (SD) of survival time (months) for White Hispanic females was 72.7 (32.2). We found that the exponentiated Weibull model best fit the survival times compared to other widely known statistical probability models. The predictive inference for future survival times is presented using the Bayesian method. Conclusions: The findings are significant for treatment planning and health-care cost allocation. They should also contribute to further research on breast cancer survival issues.

• The Journal of Korean Medicine
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• v.23 no.4
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• pp.91-97
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• 2002

Objective: This study was conducted to know the survival probability of the patients with cerebrovascular disease. Method: 1,341 patients who were suspected of having cerebrovascular disease clinically were investigated by telephone and NHIC (National Health Insurance Corporation) data. Conclusion: 1. The study population was grouped as 'Negative Brain CT findings' (11.8%), 'Hemorrhage' (12.4%) and 'Infarction' (75.7%). 2. The survival probabilities calculated by the Life Table method were statistically significant among brain CT finding groups (P<0.01). 3. The mean survival time calculated by the Kaplan-Meier method were also statistically significant among brain CT finding groups (P<0.01). 4. The result of Cox regression model was that sex (OR=0.7), age (OR=1.07), diabetes mellitus (OR=1.38), and heart disease (OR=1.69) affected the survival of the patients with cerebrovascular disease.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5381-5384
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• 2012

Background and Aim: Cholangiocarcinoma (CCA) is an uncommon malignancy of the bile duct, occurring in nearly 2 out of 100,000 people. It is a type of adenocarcinoma that originates in the mucous glands of the epithelium, or surface layers of the bile ducts. The aim of this study was to evaluate the clinical features, diagnostic results and factors associated with survival, morbidity and mortalityof cholangiocarcinoma cases in Iranian patients. Method: In this retrospective study the hospital medical records of 283 patients with a primary or final diagnosis of cholangiocarcinoma who had been admitted to gastroenterology ward of our hospital from 2004 to 2011 were retrospectively reviewed. Results: 283 patients (180 male, 63%, and 103 female, 38.6%) with a mean age of $59.7{\pm}14.4$ years were studied. The most frequent symptoms were painless jaundice (190, 66.9%), abdominal pain (77, 27%), pruritus 133 (46.8%) and weight loss (169, 59.5%). The most frequent associated risk factors and diseases were as follows: gallstones (72, 25.4%), diabetes (70, 24.6%), HBV infection (52 (18.3%), HCV infection 43 (15%), primary sclerosing cholangitis (16, 5.6%) and smoking (120, 42.3%). The most frequent type of cholangiocarcinoma in ERCP and MRCP was hilar. The mean survival time was $7.42{\pm}5.76$ months. Conclusion: The mean survival time in our study was lower than one year. Moreover the most frequent risk factors and associated diseases were smoking, gallstones and diabetes. Painless jaundice, abdominal pain and weight loss were the most clinical features related to cholangiocarcinoma. Additionally survival time did not correlate with risk factors, associated diseases and clinical presentations, but was linked to biliary metallic stenting and surgery.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

• Journal of Chest Surgery
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• v.27 no.4
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• pp.281-286
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• 1994

From 1973 through June 1993, 25 patients underwent pulmonary resection for pulmonary metastases from carcinoma or sarcoma at our institution. There were 11 carcinomas and 14 sarcomas. 24 patients[96% complete] could follow-up and the median follow-up time was 20 months with a range of 4 months to 271 months and total follow-up period was 1105 months-patients. In our patients, actuarial 5-year survival rate was 49%, mean survival time was 66.6$\pm$12.6 months and median survival time was 84 months. Patients with sarcoma, more than 24 months of the tumor-free interval, postoperative adjuvant therapy had a better survival than did those with carcinoma, less than 24 months of the tumor-free interval, no postoperative adjuvant therapy. But there were no statistical differences between two groups[P>0.05]. This results recommend more aggressive surgical treatment for pulmonary metastases.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2567-2570
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• 2013

Background: This study analyzed Surveillance, Epidemiology and End Results (SEER) data to assess if socio-economic factors (SEFs) impact on endometrial cancer survival. Materials and Methods: Endometrial cancer patients treated from 2004-2007 were included in this study. SEER cause specific survival (CSS) data were used as end points. The areas under the receiver operating characteristic (ROC) curve were computed for predictors. Time to event data were analyzed with Kaplan-Meier method. Univariate and multivariate analyses were used to identify independent risk factors. Results: This study included 64,710 patients. The mean follow up time (S.D.) was 28.2 (20.8) months. SEER staging (ROC area of 0.81) was the best pretreatment predictor of CSS. Histology, grade, race/ethnicity and county level family income were also significant pretreatment predictors. African American race and low income neighborhoods decreased the CSS by 20% and 3% respectively at 5 years. Conclusions: This study has found significant endometrial survival disparities due to SEFs. Future studies should focus on eliminating socio-economic barriers to good outcomes.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.4049-4054
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• 2014

Background: Race and ethnicity are significant factors in predicting survival time of breast cancer patients. In this study, we applied advanced statistical methods to predict the survival of White non-Hispanic female breast cancer patients, who were diagnosed between the years 1973 and 2009 in the United States (U.S.). Materials and Methods: Demographic data from the Surveillance Epidemiology and End Results (SEER) database were used for the purpose of this study. Nine states were randomly selected from 12 U.S. cancer registries. A stratified random sampling method was used to select 2,000 female breast cancer patients from these nine states. We compared four types of advanced statistical probability models to identify the best-fit model for the White non-Hispanic female breast cancer survival data. Three model building criterion were used to measure and compare goodness of fit of the models. These include Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC). In addition, we used a novel Bayesian method and the Markov Chain Monte Carlo technique to determine the posterior density function of the parameters. After evaluating the model parameters, we selected the model having the lowest DIC value. Using this Bayesian method, we derived the predictive survival density for future survival time and its related inferences. Results: The analytical sample of White non-Hispanic women included 2,000 breast cancer cases from the SEER database (1973-2009). The majority of cases were married (55.2%), the mean age of diagnosis was 63.61 years (SD = 14.24) and the mean survival time was 84 months (SD = 35.01). After comparing the four statistical models, results suggested that the exponentiated Weibull model (DIC= 19818.220) was a better fit for White non-Hispanic females' breast cancer survival data. This model predicted the survival times (in months) for White non-Hispanic women after implementation of precise estimates of the model parameters. Conclusions: By using modern model building criteria, we determined that the data best fit the exponentiated Weibull model. We incorporated precise estimates of the parameter into the predictive model and evaluated the survival inference for the White non-Hispanic female population. This method of analysis will assist researchers in making scientific and clinical conclusions when assessing survival time of breast cancer patients.

• Journal of Korean Neurosurgical Society
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• v.59 no.4
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• pp.392-399
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• 2016

Objective : Brain metastases in gynecologic cancer (ovarian, endometrial, and cervical cancer) patients are rare, and the efficacy of Gamma Knife Radiosurgery (GKRS) to treat these had not been evaluated. We assessed the efficacy of GKRS and prognostic factors for tumor control and survival in brain metastasis from gynecologic cancers. Methods : This retrospective study was approved by the institutional review board. From May 1995 to October 2012, 26 women (mean age 51.3 years, range 27-70 years) with metastatic brain tumors from gynecologic cancer were treated with GKRS. We reviewed their outcomes, radiological responses, and clinical status. Results : In total 24 patients (59 lesions) were available for follow-up imaging. The median follow-up time was 9 months. The mean treated tumor volume at the time of GKRS was $8185mm^3$ (range $10-19500mm^3$), and the median dose delivered to the tumor margin was 25 Gy (range, 10-30 Gy). A local tumor control rate was 89.8% (53 of 59 tumors). The median overall survival was 9.5 months after GKRS (range, 1-102 months). Age-associated multivariate analysis indicated that the Karnofsky performance status (KPS), the recursive partitioning analysis (RPA) classification, and the number of treated lesions were significant prognostic factors for overall survival (HR=0.162, p=0.008, HR=0.107, p=0.038, and HR=2.897, p=0.045, respectively). Conclusion : GKRS is safe and effective for the management of brain metastasis from gynecologic cancers. The clinical status of the patient is important in determining the overall survival time.

• Journal of Korean Neurosurgical Society
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• v.61 no.6
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• pp.737-746
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• 2018

Objective : The purpose of this study was to compare the cosmetic outcome and complications after cranioplasty (CP) due to three different implant materials, and analyze the mean implant survival and cumulative survival rate based on these results. Methods : We reviewed 108 patients retrospectively who underwent CP between January 2014 and November 2016. Autologous bone (AB; 45 patients) and synthetic materials with porous polyethylene (PP; 32 patients) and custom-made 3-dimensional printed titanium mesh (CT; 31 patients) were used as implants. Results : Regardless of implanted materials, more than 89.8% of the CP patients were satisfied with the cosmetic outcome. No statistically significant difference was observed among the three groups. The overall postoperative complication rates of each group were 31.1% in the AB group, 15.6% in the PP group and 3.2% in the CT group. The CT group showed lower complication rates compared with AB and PP groups (${\chi}^2$-test : AB vs. PP, p=0.34; AB vs. CT, p=0.00; PP vs. CT, p=0.03). The AB and PP groups demonstrated a higher post-CP infection rate (11.1% and 6.3%) than the CT group (3.2%). However, no significant difference in the incidence of post-CP infection was observed among the three groups. The PP and CT groups demonstrated a higher mean implant survival time and cumulative survival rate than the AB group at the last follow-up (p<0.05). Conclusion : In comparison with AB and PP, cranioplasty with CT shows benefits in terms of lower post-CP complication, less intraoperative bleeding loss, shorter operation time and in-hospital stay. The PP and CT groups showed higher implant survival time and cumulative survival rate compared with the AB group.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.42
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• pp.29.1-29.7
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• 2020

Background: Microvascular reconstruction is the treatment of choice after oral cancer ablation surgery. There are few published studies of free flap survival among Korean populations. This study aimed to determine the survival rate after 121 consecutive cases of maxillofacial microvascular reconstruction and to analyze the complications associated with microsurgery. Methods: This study included consecutive patients who underwent microsurgical reconstruction with free flaps, from January 2006 through September 2019, performed by a single surgeon at the oral and maxillofacial surgery department of a tertiary medical center. A total of 121 cases were reviewed retrospectively. The flap survival rate, flap type, radiotherapy history, complications, and treatment results were analyzed. Results: Four different flap types were used for microvascular reconstruction: radial forearm (n = 65), fibula (n = 34), latissimus dorsi (n = 21), and serratus anterior muscle with rib bone free flap (n = 1). Total necrosis of the flap was found in four cases (two latissimus dorsi flaps and two fibular flaps). The free flap survival rate was 97.5%. Nineteen patients received radiotherapy before surgery, and none of them experienced flap failure. The mean operation time was 334 ± 83.1 min, and the mean ischemic time was 48.9 ± 12.7 min. Conclusions: The success rate was reliable and comparable with previous studies. The success rate was not affected by radiation therapy. Free flaps can be safely used even after radiation treatment.