• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.887-890
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• 2014

This study was undertaken to compare surgical outcomes and survival rates of patients with the 2009 International Federation of Gynecology and Obstetrics (FIGO) stage IIA1 versus IIA2 cervical cancer treated with radical hysterectomy and pelvic lymphadenectomy (RHPL). Patients with stage IIA cervical cancer undergoing primary RHPL between January 2003 and December 2012 at Chiang Mai University Hospital were retrospectively reviewed. The analysis included clinicopathologic variables, i.e. nodal metastasis, parametrial involvement, positive surgical margins, deep stromal invasion (DSI)), lymph-vascular space invasion (LVSI), adjuvant treatment, and 5-year survival. The chi square test, Kaplan-Meier method and log-rank test were used for statistical analysis. During the study period, 133 women with stage IIA cervical cancer, 101 (75.9 %) stage IIA1, and 32 (24.1 %) stage IIA2 underwent RHPL. The clinicopathologic variables of stage IIA1 compared with stage IIA2 were as follows: nodal metastasis (38.6% vs 40.6%, p=0.84), parametrial involvement (10.9% vs 15.6%, p=0.47), positive surgical margins (31.7% vs 31.3%, p=1.0), DSI (39.6% vs 53.1%, p=0.18), LVSI (52.5% vs 71.9%, p=0.05) and adjuvant radiation (72.3% vs 84.4%, p=0.33). With a median follow-up of 60 months, the 5-year disease-free survival (84.6% vs 88.7%, p=0.67) and the 5-year overall survival (83.4% vs 90.0%, P=0.49) did not significantly differ between stage IIA1 and stage IIA2 cervical cancer. In conclusion, patients with stage IIA1 and stage IIA2 cervical cancer have comparable rates of locoregional spread and survival. The need for receiving adjuvant radiation was very high in both substages. The revised 2009 FIGO system did not demonstrate significant survival differences in stage IIA cervical cancer treated with radical hysterectomy. Concurrent chemoradiation should be considered a more suitable treatment for patients with stage IIA cervical cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2893-2900
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• 2014

Background: Statistical methods are very important to precisely measure breast cancer patient survival times for healthcare management. Previous studies considered basic statistics to measure survival times without incorporating statistical modeling strategies. The objective of this study was to develop a data-based statistical probability model from the female breast cancer patients' survival times by using the Bayesian approach to predict future inferences of survival times. Materials and Methods: A random sample of 500 female patients was selected from the Surveillance Epidemiology and End Results cancer registry database. For goodness of fit, the standard model building criteria were used. The Bayesian approach is used to obtain the predictive survival times from the data-based Exponentiated Exponential Model. Markov Chain Monte Carlo method was used to obtain the summary results for predictive inference. Results: The highest number of female breast cancer patients was found in California and the lowest in New Mexico. The majority of them were married. The mean (SD) age at diagnosis (in years) was 60.92 (14.92). The mean (SD) survival time (in months) for female patients was 90.33 (83.10). The Exponentiated Exponential Model found better fits for the female survival times compared to the Exponentiated Weibull Model. The Bayesian method is used to obtain predictive inference for future survival times. Conclusions: The findings with the proposed modeling strategy will assist healthcare researchers and providers to precisely predict future survival estimates as the recent growing challenges of analyzing healthcare data have created new demand for model-based survival estimates. The application of Bayesian will produce precise estimates of future survival times.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8513-8517
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• 2016

Background: GLOBOCAN12 recently reported high cancer mortality in Malaysia suggesting its cancer health services are under-performing. Cancer survival is a key index of the overall effectiveness of health services in the management of patients. This report focuses on Subang Jaya Medical Centre (SJMC) care performance as measured by patient survival outcome for up to 5 years. Materials and Methods: All women with breast cancer treated at SJMC between 2008 and 2012 were enrolled for this observational cohort study. Mortality outcome was ascertained through record linkage with national death register, linkage with hospital registration system and finally through direct contact by phone or home visits. Results: A total of 675 patients treated between 2008 and 2012 were included in the present survival analysis, 65% with early breast cancer, 20% with locally advanced breast cancer (LABC) and 4% with metastatic breast cancer (MBC). The overall relative survival (RS) at 5 years was 88%. RS for stage I was 100% and for stage II, III and IV disease was 95%, 69% and 36% respectively. Conclusions: SJMC is among the first hospitals in Malaysia to embark on routine measurement of the performance of its cancer care services and its results are comparable to any leading centers in developed countries.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.159-163
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• 2013

Background: This study used Surveillance, Epidemiology and End Results (SEER) pancreatic cancer data to identify predictive models and potential socio-economic disparities in pancreatic cancer outcome. Materials and Methods: For risk modeling, Kaplan Meier method was used for cause specific survival analysis. The Kolmogorov-Smirnov's test was used to compare survival curves. The Cox proportional hazard method was applied for multivariate analysis. The area under the ROC curve was computed for predictors of absolute risk of death, optimized to improve efficiency. Results: This study included 58,747 patients. The mean follow up time (S.D.) was 7.6 (10.6) months. SEER stage and grade were strongly predictive univariates. Sex, race, and three socio-economic factors (county level family income, rural-urban residence status, and county level education attainment) were independent multivariate predictors. Racial and socio-economic factors were associated with about 2% difference in absolute cause specific survival. Conclusions: This study s found significant effects of socio-economic factors on pancreas cancer outcome. These data may generate hypotheses for trials to eliminate these outcome disparities.

• Journal of Gastric Cancer
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• v.17 no.4
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• pp.319-330
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• 2017

Introduction: The extent of lymphadenectomy in the surgical treatment of gastric cancer is a topic of controversy among surgeons. This study was conducted to analyze the American National Cancer Database (NCDB) and conclude the optimal extent of lymphadenectomy for gastric adenocarcinoma. Methods: The NCDB for gastric cancer was utilized. Patients who received at least a partial gastrectomy were included. Patients with metastatic disease, unknown TNM stages, R1/R2 resection, or treated with a palliative intent were excluded. Joinpoint regression was used to identify the extent of lymphadenectomy that reflects the optimal survival. Cox regression analysis and Bayesian information criterion were used to identify significant survival predictors. Kaplan-Meier was applied to study overall survival and stage migration. Results: 40,281 patients of 168,377 met the inclusion criteria. Joinpoint analysis showed that dissection of 29 nodes provides the optimal median survival for the overall population. Regression analysis reported the cutoff ${\geq}29$ to have a better fit in the prognostic model than that of ${\geq}15$. Dissection of ${\geq}29$ nodes in the higher stages provides a comparable overall survival to the immediately lower stage. Nonetheless, the retrieval of ${\geq}15$ nodes proved to be adequate for staging without a significant stage migration compared to ${\geq}29$ nodes. Conclusion: The extent of lymphadenectomy in gastric adenocarcinoma is a marker of improved resection which reflects in a longer overall survival. Our analysis concludes that the dissection of ${\geq}15$ nodes is adequate for staging. However, the dissection of 29 nodes might be needed to provide a significantly improved survival.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.185-190
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• 2014

Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high-lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness-associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.3
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• pp.1053-1057
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• 2012

Objective: Identifying cancer-related genes or proteins is critical in preventing and controlling colorectal cancer (CRC). This study was to investigate the clinicopathological and prognostic value of activating transcription factor 1 (ATF1) in CRC. Methods: Protein expression of ATF1 was detected using immunohistochemistry in 66 CRC tissues. Clinicopathological association of ATF1 in CRC was analyzed with chi-square test or Fisher's exact test. The prognostic value of ATF1 in CRC is estimated using the Kaplan-Meier analysis and Cox regression models. Results: The ATF1 protein expression was significantly lower in tumor tissues than corresponding normal tissues (51.5% and 71.1%, respectively, P = 0.038). No correlation was found between ATF1 expression and the investigated clinicopathological parameters, including gender, age, depth of invasion, lymph node status, metastasis, pathological stage, vascular tumoral emboli, peritumoral deposits, chemotherapy and original tumor site (all with P > 0.05). Patients with higher ATF1 expression levels have a significantly higher survival rate than that with lower expression (P = 0.026 for overall survival, P = 0.008 for progress free survival). Multivariate Cox regression model revealed that ATF1 expression and depth of invasion were the predictors of the overall survival (P = 0.008 and P = 0.028) and progress free survival (P = 0.002 and P = 0.005) in CRC. Conclusions: Higher ATF1 expression is a predictor of a favorable outcome for the overall survival and progress free survival in CRC.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3541-3544
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• 2016

Background: As the treatment modalities for oral cancer have been relatively consistent during the last two-decades, this study was conducted to compare survivals of oral cancer patients in Khon Kaen Province before and after the universal coverage scheme (UC) was launched in Thailand. Materials and Methods: The data were retrieved from the population-based cancer registry of Khon Kaen for oral cancer patients diagnosed during 1992-2001 (pre-UC), and 2004-2012 (post-UC). To compare survival of the two cohorts, Kaplan Meier and log rank tests were employed. Results: Of 1,196 patients, 65% were females and the median age was 65 years. The most common primary sites were lip (31.0%), tongue (29.9%), and buccal mucosa (14.6%). The proportion of early stage cancer increased from 20.4 % in pre-UC to 41.3% in post-UC. The overall 5-year survival rate was 36.5% (95% CI =32.6-40.9) for pre-UC and 32.4% (95% CI = 28.8-36.4) for post-UC. The declining survival was mainly due to an increasing proportion of tongue cancer. However, no survival improvement was demonstrated on subgroup analysis of the tongue cancer patients. Conclusions: After the universal coverage scheme had been launched, early diagnosis increased, but no significant gain in survival for oral cancer patients was achieved.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.8
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• pp.4591-4594
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• 2013

Breast cancer is the most common cancer among Malaysian women. Other than hospital-based results, there are no documented population-based survival rates of Malaysian women for breast cancers. This populationbased retrospective cohort study was therefore conducted. Data were obtained from Health Informatics Centre, Ministry of Health Malaysia, National Cancer Registry and National Registration Department for the period from $1^{st}$ January 2000 to $31^{st}$ December 2005. Cases were captured by ICD-10 and linked to death certificates to identify the status. Only complete data were analysed. Survival time was calculated from the estimated date of diagnosis to the date of death or date of loss to follow-up. Observed survival rates were estimated by Kaplan-Meier method using SPSS Statistical Software version 17. A total of 10,230 complete data sets were analysed. The mean age at diagnosis was 50.6 years old. The overall 5-year survival rate was 49% with median survival time of 68.1 months. Indian women had a higher survival rate of 54% compared to Chinese women (49%) and Malays (45%). The overall 5-year survival rate of breast cancer patient among Malaysian women was still low for the cohort of 2000 to 2005 as compared to survival rates in developed nations. Therefore, it is necessary to enhance the strategies for early detection and intervention.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9453-9458
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• 2014

Background: Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model. Materials and Methods: The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH. Results: A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model. Conclusions: The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.