Factors Affecting Long-Survival of Patients with Breast Cancer by Non-Mixture and Mixture Cure Models Using the Weibull,Log-logistic and Dagum Distributions: A Bayesian Approach

Background: Breast cancer is a top biomedical research priority, and it is a major health problem. Therefore, the present study aimed to determine the prognostic factors of breast cancer survival using cure models. Methods: In this retrospective cohort analytic study, data of 140 breast cancer patients were collected from Ali Ibn Abi Taleb hospital, Rafsanjan, Southeastern Iran. Since in this study, a part of the population had long-term survival, cure models were used and evaluated using DIC index. The data were analyzed using Openbugs Software. Results: In this study, of 140 breast cancer patients, 23 (16.4%) cases died of breast cancer. Based on the findings, the Bayesian nonmixture cure model, with type I Dagum distribution, was the best fitted model. The variables of BMI, number of children, number of natural deliveries, tumor size, metastasis, consumption of canned food, tobacco use, and breastfeeding affected patients’ survival based on type I Dagum distribution. Conclusion: The results of the present study demonstrated that the Bayesian nonmixture cure model, with type I Dagum distribution, can be a good model to determine factors affecting the survival of patients when there is the possibility of a fraction of cure. In this study, it was found that adapting a healthy lifestyle (eg, avoiding canned foods and smoking) can improve the survival of breast cancer patients.     

Application of a Non-Mixture Cure Rate Model for Analyzing Survival of Patients with Breast Cancer

Background: As a result of significant progress made in treatment of many types of cancers during the lastfew decades, there have been an increased number of patients who do not experience mortality. We refer to theseobservations as cure or immune and models for survival data which include cure fraction are known as cure ratemodels or long-term survival models. Materials and Methods: In this study we used the data collected from 438female patients with breast cancer registered in the Cancer Research Center in Shahid Beheshti University ofMedical Sciences, Tehran, Iran. The patients had been diagnosed from 1992 to 2012 and were followed up untilOctober 2014. We had to exclude some because of incomplete information. Phone calls were made to confirmwhether the patients were still alive or not. Deaths due to breast cancer were regarded as failure. To identifyclinical, pathological, and biological characteristics of patients that might have had an effect on survival of thepatients we used a non-mixture cure rate model; in addition, a Weibull distribution was proposed for the survivaltime. Analyses were performed using STATA version 14. The significance level was set at P ≤ 0.05. Results: Atotal of 75 patients (17.1%) died due to breast cancer during the study, up to the last follow-up. Numbers ofmetastatic lymph nodes and histologic grade were significant factors. The cure fraction was estimated to be58%. Conclusions: When a cure fraction is not available, the analysis will be changed to standard approachesof survival analysis; however when the data indicate that the cure fraction is available, we suggest analysis ofsurvival data via cure models.     

5-Year Survival Rates and Prognostic Factors in Patients with Synchronus and Metachronus Breast Cancer from 2010 to 2015

Introduction: Currently breast (BC) cancer is a serious medical problem in all countries of the world. Survivaldepends on many factors. The present study focused on 5-year survival and its related factors in patients with BC inIran. Material and methods. The present analytical retrospective study was performed (from March 2010 until March2015) on patients with BC followed for at least 6 months. The main variables assessed were tumor size, grade of lymphnode involvement, metastasis, stage, history, human epidermal growth factor receptor expression, and tumor origin.Analysis of survival was accomplished using the Kaplan- Meier method. Results: Some 351 (80.2%) of the total of438 individuals had unilateral and 87(19.8%) had bilateral cancer, 28 (35.6%) of the latter being synchronous and56(64.4%) metachronous. Mean duration of follow-up was 47.44±28.19 months, during which 61 (17.3%) patientswith unilateral and 18 with bilateral cancer eventually died. The 5-year survival rate in patients with unilateral BC wassignificantly higher than those with bilateral BC (Log-rank Test chi2= 3.11, p=0.032). In addition, with metachronouscases, the survival rate was 64.2% in comparison with 51.6% for synchronous BCs. Survival rate was significantly(p value =0.038) higher with metachronous than with synchronous cancers (Log-rank Test chi2=3.54, p=0.038). Thehighest survival rate was reported for BCs originating from lobule tissue and the lowest rate examples of interstitialtissue origin (Log-rank Test chi2=11.54, p=0.0001). Patients with earl stage lesions (M1) survived longer than withother stages (Log-rank Test chi2= 9.55, p=0.001). Conclusion: In this study, most women with BC had a positivefamily history and were married. The 5-year survival rate was lower with advanced stages of cancer. According to ourfindings, survival rates might improve if patients undergo screening and diagnosis is made at an early stage of the disease.     

329例转移性乳腺癌的预后因素及生存分析

目的观察转移性乳腺癌患者的疗效及预后情况,分析影响转移性乳腺癌患者生存的预后因素。方法选取转移性乳腺癌患者329例进行回顾性研究。结果总生存率(OS)1年总生存率为62.9%,2年总生存率为41.9%,3年总生存率为25.8%及5年总生存率11.9%。接受治疗的患者中位生存时间为18.2个月,分别为:骨转移患者23.4个月,淋巴结转移患者31.3个月,肝转移患者17.6个月,肺转移患者15.3个月,脑转移患者7.2个月。通过单因素及多因素分析,获取了同生存获益相关的预后因素。结论对转移性乳腺癌生存有积极影响的独立因素包括:体力状况,年龄≤70岁以及没有内脏的转移。对于此类患者,在解救治疗中应采取较为积极的处理措施,争取更好的生存获益。     

Cure Models for Estimating Hospital-Based Breast CancerSurvival

Objective: Research on cancer survival is enriched by development and application of innovative analyticalapproaches in relation to standard methods. The aim of the present paper is to document the utility of a mixturemodel to estimate the cure fraction and compare it with other approaches. Methods: The data were for 1,107patients with locally advanced breast cancer, who completed the neo-adjuvant treatment protocol during 1990-99at the Cancer Institute (WIA), Chennai, India. Tumour stage, post-operative pathological node (PN) and tumourresidue (TR) status were studied. Event free survival probability was estimated using the Kaplan-Meier method.Cure models under proportional and non-proportional hazard assumptions following log normal distribution forsurvival time were used to estimate both the cure fraction and the survival function for the uncured. Results:Event free survival at 5 and 10 years were 64.2% and 52.6% respectively and cure fraction was 47.5% forall cases together. Follow up ranged between 0-15 years and survival probabilities showed minimal changesafter 7 years of follow up. TR and PN emerged as independent prognostic factors using Cox and proportionalhazard (PH) cure models. Proportionality condition was violated when tumour stage was considered and it wasstatistically significant only under PH and not under non PH cure models. However, TR and PN continued tobe independent prognostic factors after adjusting for tumour stage using the non PH cure model. A consistentordering of cure fractions with respect to factors of PN and TR was forthcoming across tumour stages using PHand non PH cure models, but perceptible differences in survival were observed between the two. Conclusion: IfPH conditions are violated, analysis using a non PH model is advocated and mixture cure models are useful inestimating the cure fraction and constructing survival curves for non-cures.     

Relative Survival of Breast Cancer Patients in Iran

Background: The survival rate reflecting prognosis of breast cancer patients is usually estimated based on crudesurvival methods such as observed and cause-specific. In situations where data are based on population-cancerregistries, this method may produce biased estimations. This study therefore aimed to estimate the net survival ofbreast cancer based on relative survival. Materials and Methods: Data for 622 breast cancer patients diagnosedat the Iran Cancer Institute during 1990-95 and tracked till the end of 2000 were analyzed. For estimation ofrelative survival, Ederer’s second method and SAS (9.1) and STATA (11) software were used. Results: Threeyearrelative 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 forage-group 45-59 years-old. A value greater than one for two subsequent years of follow-up was observed in theage-group 60-74 years-old. Conclusions: Tracking the diagnosis of breast cancer, the relative survival decreasesas we go to higher age-groups. It is also perceived that through follow-up, relative survival first decreased andthen increased a little. The statistical cure point is acceptable for age group 45-59 years-old while for age-groups15-44 and 60-74 years old is a sign of low quality data for some follow-up intervals.     

Metastasis Risk Reduction Related with Beta-Blocker Treatment in Mexican Women with Breast Cancer

Background: Breast Cancer (BCa) is the most common malignant tumour in Mexican women. In BCa, several studies have linked β2-adrenergic receptor activation with increased tumour growth and progression as related with Epinephrine-NorEpinephrine (E-NE) stimulation. The aim of this study was to describe Beta-Blocker (BB) treatment related with reduction of the risk of metastasis in Mexican patients with BCa. Materials and Methods: We collected data of 120 patients seen at the High-Specialty Naval General Hospital in Mexico City (HOSGENAES), all of these with a histopathological diagnosis of BCa. Four groups of patients were divided as follows: without Systemic Arterial Hypertension (SAH); with SAH treatment with non-selective BB; with SAH treatment with selective BB, and with SAH treatment with other antihypertensive drugs. Chi-square, Mantel- Haenszel, Student t, and ANOVA tests were performed for data analysis. Results: On average, patients were 54.8±11.8 years of age. Risk factors such as smoking and consuming alcohol exhibited a frequency of 33 and 36.5% respectively. Clinical stages III- IV were found in 50% of patients, while, 30% of patients had arterial hypertension (n=29 and N=96, respectively) and 17.5% used BB. One hundred percent of patients with arterial hypertension treated with BB for β1 - and β2 -adrenergic-receptors did not present metastasis globally, but patients treated with β1 BB presented 30% of metastasis while patients treated with no BB or without SAH had around 70% of metastasis. Conclusions: In Mexican patients with BCa and SAH treated with non-selective (β1- and β2-adrenergic receptors) BB, a decrease in the risk for metastasis was observed at the time of diagnosis.     

Bayesian Method for Modeling Male Breast Cancer Survival Data

Background: With recent progress in health science administration, a huge amount of data has been collectedfrom thousands of subjects. Statistical and computational techniques are very necessary to understand suchdata and to make valid scientific conclusions. The purpose of this paper was to develop a statistical probabilitymodel and to predict future survival times for male breast cancer patients who were diagnosed in the USA during1973-2009. Materials and Methods: A random sample of 500 male patients was selected from the SurveillanceEpidemiology and End Results (SEER) database. The survival times for the male patients were used to derivethe statistical probability model. To measure the goodness of fit tests, the model building criterions: AkaikeInformation Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC)were employed. A novel Bayesian method was used to derive the posterior density function for the parametersand the predictive inference for future survival times from the exponentiated Weibull model, assuming that theobserved breast cancer survival data follow such type of model. The Markov chain Monte Carlo method wasused to determine the inference for the parameters. Results: The summary results of certain demographic andsocio-economic variables are reported. It was found that the exponentiated Weibull model fits the male survivaldata. Statistical inferences of the posterior parameters are presented. Mean predictive survival times, 95%predictive intervals, predictive skewness and kurtosis were obtained. Conclusions: The findings will hopefullybe useful in treatment planning, healthcare resource allocation, and may motivate future research on breastcancer related survival issues.     

Predicting the Survival of Gastric Cancer Patients Using Artificial and Bayesian Neural Networks

Introduction and purpose: In recent years the use of neural networks without any premises for investigation of prognosis in analyzing survival data has increased. Artificial neural networks (ANN) use small processors with a continuous network to solve problems inspired by the human brain. Bayesian neural networks (BNN) constitute a neural-based approach to modeling and non-linearization of complex issues using special algorithms and statistical methods. Gastric cancer incidence is the first and third ranking for men and women in Iran, respectively. The aim of the present study was to assess the value of an artificial neural network and a Bayesian neural network for modeling and predicting of probability of gastric cancer patient death. Materials and Methods: In this study, we used information on 339 patients aged from 20 to 90 years old with positive gastric cancer, referred to Afzalipoor and Shahid Bahonar Hospitals in Kerman City from 2001 to 2015. The three layers perceptron neural network (ANN) and the Bayesian neural network (BNN) were used for predicting the probability of mortality using the available data. To investigate differences between the models, sensitivity, specificity, accuracy and the area under receiver operating characteristic curves (AUROCs) were generated. Results: In this study, the sensitivity and specificity of the artificial neural network and Bayesian neural network models were 0.882, 0.903 and 0.954, 0.909, respectively. Prediction accuracy and the area under curve ROC for the two models were 0.891, 0.944 and 0.935, 0.961. The age at diagnosis of gastric cancer was most important for predicting survival, followed by tumor grade, morphology, gender, smoking history, opium consumption, receiving chemotherapy, presence of metastasis, tumor stage, receiving radiotherapy, and being resident in a village. Conclusion: The findings of the present study indicated that the Bayesian neural network is preferable to an artificial neural network for predicting survival of gastric cancer patients in Iran.     

Estimation of the Cure Rate in Iranian Breast Cancer Patients

Background: Although the Cox’s proportional hazard model is the popular approach for survival analysis to investigate significant risk factors of cancer patient survival, it is not appropriate in the case of log-term disease free survival. Recently, cure rate models have been introduced to distinguish between clinical determinants of cure and variables associated with the time to event of interest. The aim of this study was to use a cure rate model to determine the clinical associated factors for cure rates of patients with breast cancer (BC). Materialsand Methods: This prospective cohort study covered 305 patients with BC, admitted at Shahid Faiazbakhsh Hospital, Tehran, during 2006 to 2008 and followed until April 2012. Cases of patient death were confirmed by telephone contact. For data analysis, a non-mixed cure rate model with Poisson distribution and negative binomial distribution were employed. All analyses were carried out using a developed Macro in WinBugs. Deviance information criteria (DIC) were employed to find the best model. Results: The overall 1-year, 3-year and 5-year relative survival rates were 97%, 89% and 74%. Metastasis and stage of BC were the significant factors, but age was significant only in negative binomial model. The DIC also showed that the negative binomial model had a better fit. Conclusions: This study indicated that, metastasis and stage of BC were identified as the clinical criteria for cure rates. There are limited studies on BC survival which employed these cure rate models to identify the clinical factors associated with cure. These models are better than Cox, in the case of long-termsurvival.     

Chemotherapy Negates the Effect of SDF1 mRNA to Distant Metastasis and Poor Overall Survival in Breast Cancer Patients

Objective: Investigate the effect of SDF1a, nuclear, and cytoplasmic CXCR4 breast cancer tissue on metastasis and overall survival in patients with complete-chemotherapy and no-chemotherapy. Methods: Cohort ambidirectional design was employed with survival analysis that followed the patient’s diagnosis until obtaining the outcome, distant metastasis, or death. We analyzed samples in three groups (all-patient, no-chemotherapy, and complete-chemotherapy groups).  Breast cancer cell nuclear and cytoplasm expressions of CXCR4 protein were examined using immunohistochemistry. Amplification of mRNA SDF1a of breast cancer tissue was examined using rtPCR on 131 samples from the same initial paraffin block. Results: In the distant metastasis and Overall Survival (OS) analysis, there was no correlation between cytoplasmic and nuclear CXCR4 in all-patient, no-chemotherapy, and complete-chemotherapy groups. SDF1a was significantly correlated to shorter distant metastasis and poor OS in the all-patient (p=0.004 and p=0.04, respectively) and no-chemotherapy group (p=0.008 and p=0.026, respectively). However, in the complete-chemotherapy group, SDF1a was not correlated to either metastasis (p=0.527) or OS (p=0.993), advanced stage demonstrated a strong association on shorter distant metastatic in no-chemotherapy (p=0.021) and complete-chemotherapy group (p=0.004) and also poor OS in both groups (p=0.006 and p=0.002, respectively). The hormone receptor showed a protective effect on the no-chemotherapy group’s OS (p= 0.019). Meanwhile, not undergoing chemotherapy was associated with poor OS in the all-patient group (p= 0.011). Conclusion: SDF1a mRNA amplification has a significant correlation with the occurrence of metastasis and OS in all-patient and no-chemotherapy group. Undergoing chemotherapy negates the effect of SDF1a for distant metastasis and OS.     

Eight Year Survival Analysis of Patients with Triple Negative Breast Cancer in India

Background: Triple-negative breast cancer (TNBC) often presents as an interval cancer with short survival upon metastasis and thus represents an important clinical challenge. The present study investigated the clinicopathologic characteristics and long term survival outcome of early and locally advanced TNBC. Materials and Methods: Medical records were reviewed retrospectively for 148 consecutive confirmed cases of TNBC treated in a single unit at our centre. Demographic profile, tumor type, histopathology details, treatment and follow-up information was recorded and immunohistochemistry was performed. Results: Age group >50 years was associated with tumors of clinical stage 3 (53.8%), pathological stage 3 (46.2%), pathological grade 3 (45.7%), presence of extracapsular extension (ECE, 48.5%) and lymphovascular invasion (LVI, 64.9%). Locally advanced breast cancers (LABCs) were characterized by pathological stage 3 (96.2%), presence of ECE (100%) and absence of LVI (46.7%) as compared to early breast cancers (EBCs) which had higher incidence of lower stage tumors (100%), absence of ECE (82%) and presence of LVI (91.9%; p-value Conclusions: TNBCs are aggressive tumors which show poor long term survival. Patients with TNBC benefit from chemotherapy, thus better and less toxic treatment options are needed. Identification of newer targets and development of targeted therapies are the need of the hour.     

Metastasis and its Related Factors in Female Breast Cancer Patients in Kerman,Iran

Background: Metastasis is important in survival and the quality of life of female breast cancer patients. This study was run in order to investigate metastasis and its related factors in female breast cancer patients in Kerman province from 2005 to 2015. The aim of this study was to investigate the factors associated with secondary metastasis in female breast cancer patients in the largest province of Iran (Kerman). Materials and Methods: In this case-control study, medical records of women diagnosed with breast cancer between the years of 2005 to 2015 were studied. Among them, 200 breast cancer patients with secondary metastasis were randomly selected as cases and 400 patients without metastasis were selected as the control group. Backward logistic regression, chi-square test, t-test and Mann-Whitney-U test were performed for comparing the two groups in SPSS 22. Results: Disease stage at diagnosis was significantly associated with secondary metastasis (p<0.001). Female patients with stage III breast cancer at the time of diagnosis had a higher chance OR=9.11 (CI 95%=2.99-27.76) of metastasis than women with stage 0 and 1 at diagnosis. Also, patients from rural areas had a higher chance for metastasis OR=1.89 (CI 95%=1.04-3.41). Other factors such as age, tumor size, tumor grade at diagnosis, hormone receptor status of estrogen and progesterone and Her-2 showed no significant association with metastasis (p>0.05). Conclusion: Stage at diagnosis and the residential location of patients were the most important factors related to secondary metastasis. These results emphasize the importance of early diagnosis, adequate education and awareness for breast cancer screening.     

乳腺癌前哨淋巴结转移的相关因素分析及病理学研究

目的探究乳腺癌前哨淋巴结转移的相关因素。方法回顾性分析162例前哨淋巴结活检技术的乳腺癌患者的临床资料,对乳腺癌临床病理指标与前哨淋巴结转移之间的关系进行因素分析。结果前哨淋巴结阳性共83例,前哨淋巴结阴性共79例。2组间的年龄、性别组成、体重指数、吸烟史和饮酒史等的差异均无统计学意义(P>0.05)。原发肿瘤位置、活检方式与前哨淋巴结转移无关(P>0.05),但病理类型与前哨淋巴结转移有关。随着肿瘤的变大,灵敏度、特异性也随之升高。多元Logistic回归分析显示,肿瘤直径和病理类型是影响前哨淋巴结转移的独立危险因素(P<0.05)。结论乳腺癌前哨淋巴结转移考虑与肿瘤大小及病理类型相关,但具体病例需具体分析后考虑是否可行前哨淋巴结活检术。     

Determination of Cut Point in the Age of Colorectal Cancer Diagnosis Using a Survival Cure Model

Background and Objectives: Colorectal Cancer (CRC) is the fourth cancer-related cause of death worldwide.CRC is a multi-stage cancer, which is curable during the early stages of the disease. Therefore, determining the time ofcut-point existence could improve treatment planning and help directly allocate resources. This study aims to determinethe cut point in the age of CRC diagnosis. Methods: This study, covering the course 1985 to 2012, consisted of 345colorectal cancer patients registered in Taleghani Hospital, Tehran, Iran and followed up to 2013. The cut-point in theage of CRC diagnosis was obtained using a mixture cure model. The data were analyzed using SPSS and R, V. 20 and2.15.0, respectively. Results: The results showed that the cut point in the age of CRC diagnosis was 50 years. Basedon our estimation, 65% of the patients diagnosed with CRC at or younger than 50 were cured, while 31% of themdiagnosed older than 50 were cured, and the younger group had a better survival over the older group. Conclusion:Since access to a cut-point and analysis of created prognostic groups are important in screening and treatment planning,our results suggested that it is better to estimate the cut-point in the age of curable cancers in early stages via survivalcure models, and the cure rate would increase by CRC timely screening.     

Influence of Ethnicity on Survival of Breast Cancer Patients in Turkey

Background: Kurdish women with breast cancer have more unfavorable prognostic factors than theirTurkish and Arab counterparts. However, the effects of these factors on breast cancer survival among theseethnic groups remain unclear. We therefore investigated the impact of ethnicity on survival in breast cancerpatients in Turkey. Materials and Methods: Ethnicity, age, stage at diagnosis, tumor characteristics, treatmentsgiven (surgery, chemotherapy, radiotherapy and hormone therapy), and survival times were recorded. Kaplan-Meier analysis was used to estimate the overall survival times and survival plots. Log-rank test was used tocompare the survival curves.Results: Of the 723 breast cancer patients included in the study, 496 (68.7%) wereTurkish, 189 (26.2%) were Kurdish, 37 (5.1%) were Arabic and 1 was Armenian. Kurdish women with breastcancer had larger tumor sizes and higher rates of hormone receptor negative tumors than Turkish and Arabpatients. Mean follow-up time was 118.4 [95% Confidence Interval (CI): 95.4-141.3] months, and it was 129.9(95% CI: 93.7-166.2), 124.2 (95% CI: 108.4-140.1) and 103.1 (95% CI: 85.9-120.4) months for Turkish, Arabicand Kurdish patients, respectively. Conclusions: Kurdish ethnicity is associated with higher rates of hormonereceptor negative and triple-negative tumors and with worse survival. Clinical and epidemiological research iswarranted to elucidate reasons underlying overall survival, variations in tumor biology, differences in treatmentresponsiveness, and effects of social factors among ethnic groups in Turkey.     

Survival Analysis for White Non-Hispanic Female Breast Cancer Patients

Background: Race and ethnicity are significant factors in predicting survival time of breast cancer patients. Inthis study, we applied advanced statistical methods to predict the survival of White non-Hispanic female breastcancer patients, who were diagnosed between the years 1973 and 2009 in the United States (U.S.). Materialsand Methods: Demographic data from the Surveillance Epidemiology and End Results (SEER) database wereused for the purpose of this study. Nine states were randomly selected from 12 U.S. cancer registries. A stratifiedrandom sampling method was used to select 2,000 female breast cancer patients from these nine states. Wecompared 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 comparegoodness 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 MarkovChain Monte Carlo technique to determine the posterior density function of the parameters. After evaluatingthe model parameters, we selected the model having the lowest DIC value. Using this Bayesian method, wederived the predictive survival density for future survival time and its related inferences. Results: The analyticalsample 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 themean survival time was 84 months (SD = 35.01). After comparing the four statistical models, results suggestedthat the exponentiated Weibull model (DIC= 19818.220) was a better fit for White non-Hispanic females’ breastcancer survival data. This model predicted the survival times (in months) for White non-Hispanic women afterimplementation of precise estimates of the model parameters. Conclusions: By using modern model buildingcriteria, we determined that the data best fit the exponentiated Weibull model. We incorporated precise estimatesof the parameter into the predictive model and evaluated the survival inference for the White non-Hispanicfemale population. This method of analysis will assist researchers in making scientific and clinical conclusionswhen assessing survival time of breast cancer patients.     

Effecst of Patho- Biological Factors on the Survival of Recurrent Breast Cancer Cases

Background: Recurrence of breast cancer after treatment is generally due to loco-regional invasion or distantmetastasis. Although patients with metastasis are considered incurable, existing treatments might prolong a patient’s lifewhile also improving its quality. Choice of approach for individual patients requires identification of relevant survivalfactors. This study concerns factors influencing survival after recurrence in Iranian breast cancer patients. Methods: Thisstudy was performed on 442 recurrent breast cancer patients referred to the Cancer Research Center of Shahid BeheshtiUniversity between 1985 and 2015. After confirming recurrence as a distant metastasis or loco-regional invasion, theeffects of demographic, clinic-pathologic, biological, type of surgery and type of adjuvant treatment on survival wereevaluated using univariate and multivariate stratified Cox models. Results: The mean survival after recurrence was18 months (5 days to 13 years), 219 patients (70.42%) survived two years, 75 patients (24.12%) survived from 2 to 5years, and 17 patients (5.47%) survived more than 5 years. In this study, it was found through univariate analysis that thefactors of age, lymph node status, DFI, place of recurrence and nodal ratio demonstrated greatest influence on survivalafter recurrence. On multivariate analysis, the most important factors influencing survival were the place of recurrenceand the lymph node status. Conclusion: The results of this study enhance our knowledge of effects of different factorson survival of patients after breast cancer recurrence. Thus, they may be used to inform treatment choice.     

Side Population Cell Level in Human Breast Cancer and Factors Related to Disease-free Survival

Side population (SP) cells have stem cell-like properties with a capacity for self-renewal and are resistantto chemotherapy and radiotherapy. Therefore the presence of SP cells in human breast cancer probably hasprognostic value. Objective: To investigate the characteristics of SP cells and identify the relationship betweenthe SP cells levels and clinico-pathological parameters of the breast tumor and disease-free survival (DFS) inbreast cancer patients. Materials and Methods: A total of 122 eligible breast cancer patients were consecutivelyrecruited from January 1, 2006 to December 31, 2007 at Yunnan Tumor Hospital. All eligible subjects receivedconventional treatment and were followed up for seven years. Predictors of recurrence and/or metastasis andDFS were analyzed using Cox regression analysis. Human breast cancer cells were also obtained from freshhuman breast cancer tissue and cultured by the nucleic acid dye Hoechst33342 with Verapami. Flow cytometry(FCM) was employed to isolate the cells of SP and non-SP types. Results: In this study, SP cells were identifiedusing flow cytometric analysis with Hoechst 33342 dye efflux. Adjusted for age, tumor size, lymph nodal status,histological grade, the Cox model showed a higher risk of recurrence and/or metastasis positively associatedwith the SP cell level (1.75, 1.02-2.98), as well as with axillary lymph node metastasis (2.99, 1.76-5.09), pathologyinvasiveness type (1.7, 1.14-2.55), and tumor volume doubling time (TVDT) (1.54, 1.01-2.36). Conclusions: TheSP cell level is independently associated with tumor progression and clinical outcome after controlling for otherpathological factors. The axillary lymph node status, TVDT and the status of non-invasive or invasive tumorindependently predict the prognosis of breast cancer.     

Age and Survival Estimates in Patients Who Have Node-Negative T1ab Breast Cancer by Breast Cancer Subtype

Aim

This article evaluates the risk of recurrence for patients who have small node-negative breast cancer by age and tumor subtype.

Methods

One thousand twelve patients with a T1a,bN0 breast cancer diagnosed between 1990 and 2002 who did not receive chemotherapy or trastuzumab were included. Patients and tumor characteristics were compared using the χ² or Wilcoxon's rank sum tests. Survival outcomes were estimated with the Kaplan-Meier method and compared using the log-rank statistic. Cox proportional hazards models were used to determine association of breast cancer subtypes and age at diagnosis with other covariates.

Results

Median age was 51.5 years. There were 771 hormone receptor (HR)-positive, 98 HER2-positive, and 143 triple-negative breast cancers (TNBC). Six hundred ninety-three patients were > 50 years, and 33 patients were ≤ 35 years. For 5-year survival estimates, there were 118 deaths and overall survival was 94.6% (95% confidence interval [CI] = 93.2%, 96.1%). After adjusting for breast cancer subtype and other tumor characteristics, patients ≤ 35 had 2.51 (95% CI = 1.21-5.22) times greater risk of worse recurrence-free survival (RFS), and 2.60 (95% CI = 1.05-6.46) times greater risk of worse distant RFS (DRFS) compared to patients > 50 years old. Compared to patients with HR-positive disease, patients with HER2-positive breast cancer had 4.98 (95% CI = 2.91-8.53) times the risk of worse RFS and 4.70 (95% CI = 2.51-8.79) times greater risk of worse DRFS, and patients with TNBC had 2.71 (95% CI = 1.59-4.59) times greater risk of worse RFS and 2.08 (95% CI = 1.04-4.17) times greater risk of worse DRFS.

Conclusions

In this cohort, patients with T1a,bN0 breast cancer, young age and breast cancer subtype were significantly associated with RFS and DRFS.