• Asian Pacific Journal of Cancer Prevention
• /
• 제15권14호
• /
• pp.5571-5575
• /
• 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.

• 한국인공지능학회지
• /
• 제6권2호
• /
• pp.11-15
• /
• 2018

Breast cancer is one of the leading causes of cancer related death among women. So prediction of overall survival status is important into decided in adjuvant treatment. Deep belief network is a kind of artificial intelligence (AI). We intended to construct prediction model by deep belief network using associated clinicopathologic factors. 103881 cases were found in the Korean Breast Cancer Registry. After preprocessing of data, a total of 15733 cases were enrolled in this study. The median follow-up period was 82.4 months. In univariate analysis for overall survival (OS), the patients with advanced AJCC stage showed relatively high HR (HR=1.216 95% CI: 0.011-289.331, p=0.001). Based on results of univariate and multivariate analysis, input variables for learning model included 17 variables associated with overall survival rate. output was presented in one of two states: event or cencored. Individual sensitivity of training set and test set for predicting overall survival status were 89.6% and 91.2% respectively. And specificity of that were 49.4% and 48.9% respectively. So the accuracy of our study for predicting overall survival status was 82.78%. Prediction model based on Deep belief network appears to be effective in predicting overall survival status and, in particular, is expected to be applicable to decide on adjuvant treatment after surgical treatment.

• Asian Pacific Journal of Cancer Prevention
• /
• 제15권19호
• /
• pp.8483-8488
• /
• 2014

Background: Breast cancer is the most common cancer and the second most common cause of cancer-induced mortalities in Iranian women, following gastric carcinoma. The survival of these patients depends on several factors, which are very important to identify in order to understand the natural history of the disease. Materials and Methods: In this retrospective study, 313 consecutive women with pathologically-proven diagnosis of breast cancer who had been treated during a seven-year period (January 2006 until March 2014) at Towhid hospital, Sanandaj city, Kurdistan province of Iran, were recruited. The Kaplan-Meier method was used for data analysis, and finally those factors that showed significant association on univariate analysis were entered in a Cox regression model. Results: the mean age of patients was $46.10{\pm}10.81$ years. Based on Kaplan-Meier method median of survival time was 81 months and 5 year survival rate was $75%{\pm}0.43$. Tumor metastasis (HR=9.06, p=0.0001), relapse (HR=3.20, p=0.001), clinical stage of cancer (HR=2.30, p=0.03) and place of metastasis (p=0.0001) had significant associations with the survival rate variation. Patients with tumor metastasis had the lowest five-year survival rate (37%)and among them patients who had brain metastasis were in the worst condition (5 year survival rate= $11%{\pm}0.10$). Conclusions: Our findings support the observation that those women with higher stages of breast malignancies (especially with metastatic cancer) have less chance of surviving the disease. Furthermore, screening programs and early detection of breast cancer may help to increase the survival of those women who are at risk of breast cancer.

• Asian Pacific Journal of Cancer Prevention
• /
• 제15권3호
• /
• pp.1141-1144
• /
• 2014

Background: Even though many studies have examined the possible effect of low-fat diet on breast cancer survival, the relationship remains unclear. Objectives: To summarize the current evidence about the effect of post-diagnostic low-fat diet on recurrence and all-cause mortality of breast cancer. Methods: We conducted a search of Pubmed, Embase, Web of Science, and Cochrane Library and as a result two randomized controlled trials (RCT) and one large multi-center prospective cohort study with 9,966 breast cancer patients were included in this report. Results: Post-diagnostic low-fat diet reduced risk of recurrence of breast cancer by 23% (HR=0.77, 95%CI 0.63 to 0.94, P=0.009) and all cause mortality of breast cancer by 17% (HR=0.83, 95%CI 0.69 to 1.00, P=0.05). Conclusions: This meta-analysis suggested the post-diagnostic low-fat diet can improve breast cancer survival by reducing risk of recurrence. However, more trials of the relationship between low-fat diet and allcause mortality of breast cancer are still needed.

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

• Asian Pacific Journal of Cancer Prevention
• /
• 제16권14호
• /
• pp.5853-5858
• /
• 2015

Background: The survival rate reflecting prognosis of breast cancer patients is usually estimated based on crude survival methods such as observed and cause-specific. In situations where data are based on population-cancer registries, this method may produce biased estimations. This study therefore aimed to estimate the net survival of breast cancer based on relative survival. Materials and Methods: Data for 622 breast cancer patients diagnosed at the Iran Cancer Institute during 1990-95 and tracked till the end of 2000 were analyzed. For estimation of relative survival, Ederer's second method and SAS (9.1) and STATA (11) software were used. Results: Threeyear relative survivals of 85%, 90%, 80% and 67% were observed for age groups 15-44, 55-59, 60-74, and 75+years-old, respectively. A relative survival of approximately one was observed for two subsequent years for age-group 45-59 years-old. A value greater than one for two subsequent years of follow-up was observed in the age-group 60-74 years-old. Conclusions: Tracking the diagnosis of breast cancer, the relative survival decreases as we go to higher age-groups. It is also perceived that through follow-up, relative survival first decreased and then increased a little. The statistical cure point is acceptable for age group 45-59 years-old while for age-groups 15-44 and 60-74 years old is a sign of low quality data for some follow-up intervals.

• Asian Pacific Journal of Cancer Prevention
• /
• 제14권10호
• /
• pp.5811-5816
• /
• 2013

Background: Breast cancer is the most common cancer among women. Molecular subtypes are important in determining prognosis. This study evaluated five-year disease-free survival among four molecular subtypes in patients with early stages of breast cancer. Materials and Methods: In this retrospective descriptive-analytical study, information on patients with breast cancer between 2001-2010 was evaluated. Five hundred ninety two patients in the early stages of breast cancer (stages 1 and 2) were selected to undergo anthracycline-based chemotherapy. Relapse, death or absence (censor) were considered as the end of the study. Patients based on ER, PR and HER-2 expression were divided into four subtypes (luminal A, luminal B, HER-2 enriched and triple negative). Information based upon questionnaire was analysed. To show the patients survival rate, life table and Kaplan-Meyer methods were used, and for comparing mean survival among different groups, the Log-Rank test was utilized. Results: Mean age at diagnosis was $47.9{\pm}9.6$. Out of the 592 patients, 586 were female (99%) and 6 were male (1%). Considering breast cancer molecular subtypes, 361 patients were in the luminal A group (61%), 49 patients in the luminal B group (8.3%), 48 patients in the HER-2 enriched group (8.1%) and 134 in the triple negative group (22.6%). Mean disease-free survival was 53.7 months overall, 55.4 months for the luminal A group, 48.3 months for the luminal B group, 43 months for the HER-2enriched group and 54.6 months for the triple negatives. Disease free survival differed significantly among the molecular subtypes (p value=0.0001). Conclusions: The best disease-free survival rate was among the luminal A subgroup and the worst disease-free survival rate was among the HER-2 enriched subgroup. Disease free survival rate in the HER-2 positive groups (luminal B and HER-2 enriched) was worse than the HER-2 negative groups (luminal A and triple negative).

• Asian Pacific Journal of Cancer Prevention
• /
• 제17권4호
• /
• pp.2223-2227
• /
• 2016

Background: Breast cancer is the most common cancer among Iranian women. Since development of the disease in Iranian women occurs relatively early, the survival rate matters considerably. In different countries, survival of breast cancer patients varies considerably. Therefore, the one-year, three-year, five-year, and ten-year survival rates for breast cancer in Iran were assessed using a meta-analysis. Materials and Methods: This systematic review and meta-analysis was based on valid Iranian sources including SID, MAGIRAN and IRANMEDEX, along with reliable English databases, namely, PUBMED and SCOPUS. In domestic databases, a search was conducted based on key words of breast cancer and survival rate, and in international databases, with "breast cancer" and the equivalent of "neoplasm" of Mesh Word, "survival rate" and "Iran." Then all reviewed papers and theses which met the inclusion criteria were selected for investigation. To conduct the analysis STATA 11.2 software and random-effects models were used. Results: In 24 studies, 22,745 participants were included. The one-year, three-year, five-year and ten-year survival rates were 0.956, 0.808, 0.695 and 0.559, respectively. The minimum and maximum survival rates for 5-years were 0.48 and 0.87. The average age of the onset of the disease was 48.3. Conclusions: As in Iran, since the onset of the disease is at low age, in spite of the relatively high survival rate as compared to other cancers, prevention and screening programs at early age for early stage diagnosis seems necessary.

• Asian Pacific Journal of Cancer Prevention
• /
• 제13권3호
• /
• pp.995-998
• /
• 2012

Aim: Isoflavones in soy foods are part of a larger class of flayonoid compounds that have have been demonstrated to be potent dietary anti-cancer agents, and the effect of soy intake on the survival of ovarian cancer is conflicting. Therefore, we aimed to explore the whether soy intake is related to the risk of death of breast cancer. Methods: A prospective study was conducted. A total of 256 patients included in this study had breast cancer and were recruited between January 2004 and January 2006. All of them were followed up from since January 2011. A univariate Cox's regression analysis was used to assess the association between soy intake and survival. Results: The education level, menopausal status, ER/PR status and TNM stage were significant difference in the survival of breast cancer. The highest soy isoflavone was associated with a decreased death risk of breast cancer (OR=0.25, 95% CI=0.09-0.54). Moreover, the higher consumption of soy protein also presented a trend decreased breast cancer risk, and the highest consumption significantly reduced the cancer risk compared with the lowest consumption (OR=0.38, 95% CI=0.17-0.86). Conclusion: The present study suggests soy intake is associated with a significant reduced death risk of breast cancer in Chinese population. Further large sample studies are warranted to confirm the inverse association of soy consumption and breast cancer survival by menopausal status.

• Asian Pacific Journal of Cancer Prevention
• /
• 제13권11호
• /
• pp.5525-5528
• /
• 2012

Introduction: Breast cancer is the most common cancer in women. Improvements of early diagnosis modalities have led to longer survival rates. This study aimed to determine the 5, 10 and 15 year mortality rates of breast cancer patients compared to the normal female population. Materials and Methods: The follow up data of a cohort of 615 breast cancer patients referred to Iranian Breast Cancer Research Center (BCRC) from 1986 to 1996 was considered as reference breast cancer dataset. The dataset was divided into 5 year age groups and the 5, 10 and 15 year probability of death for each group was estimated. The annual mortality rate of Iranian women was obtained from the Death Registry system. Standardized mortality ratios (SMRs) of breast cancer patients were calculated using the ratio of the mortality rate in breast cancer patients over the general female population. Results: The mean age of breast cancer patients at diagnosis time was 45.9 (${\pm}10.5$) years ranging from 24-74. A total of 73, 32 and 2 deaths were recorded at 5, 10 and 15 years, respectively, after diagnosis. The SMRs for breast cancer patients at 5, 10 and 15 year intervals after diagnosis were 6.74 (95% CI, 5.5-8.2), 6.55 (95%CI, 5-8.1) and 1.26 (95%CI, 0.65-2.9), respectively. Conclusion: Results showed that the observed mortality rate of breast cancer patients after 15 years from diagnosis was very similar to expected rates in general female population. This finding would be useful for clinicians and health policy makers to adopt a beneficial strategy to improve breast cancer survival. Further follow-up time with larger sample size and a pooled analysis of survival rates of different centres may shed more light on mortality patterns of breast cancer.