| BackgroundBreast cancer is one of the most common cancers in women worldwide. It ranks first in both incidence and mortality among women globally. During past decades, with the implement of mass screening of breast cancer and advances in treatment, breast cancer survival has been sustainably increasing. However, long-term survival rates calculated by using traditional survival analysis approaches such as cohort method and complete method are usually quite out-of-date. Moreover, due to imcomplete information on pathological stages in Cancer Register data in China, it is difficult to distinguish the contribution of breast cancer screening in improved survival rate from that of advances in treatment.ObjectivesTo obtain more up-to-date long-term survival estimates of female breast cancer in Shanghai Cancer Hospital, Fudan University, by using multiple survival analysis methods.MethodsThis study included a total of 7,275 newly-diagnosed local female breast cancer patients in Shanghai Cancer Hospital, Fudan University, during the period of Jan 1, 1997 and Dec 31,2011. For each patient, demographic and clinical information such as patients’ name, id number, date of birth, pathological types, tumor stage, types of surgery, radiotherapy, chemotherapy and hormone therapy were obtained from electronic medical records. Follow-up surveys and record linkage with the Shanghai Vital Registry were conducted to obtain information of vital status and date of death for all patients up to Dec 31,2011. The Shanghai life expectancy table was used to estimate expected survival rates of general population. Cohort analysis, complete analysis and period analysis were applied, respectively, to estimate 5-year survival rate of breast cancer during the three interested periods of 1997～2001,2002～2006 and 2007～2011.Statistical analyses were conducted utilizing SAS statistical software 9.2 (SAS Institude Inc., Cary, NC). ANOVA and chi-square test were used to compare characteristics of patients at three time periods. p value< 0.05 was regarded as significance level. Period analysis was conducted using SAS macro "period". TNM stage distribution of cancers in 2007-2011 was used as reference to calculate stage-adjusted 5-year survival rate during 1997-2001 and 2002～2006. The projection method was applied to predict 5-year relative survival rate in the period of 2012～2016.ResultsWhile period analysis performed better in generating more up-to-date long-term survival estimates than did cohort analysis and complete analysis, it ranked second to complete analysis in robustness of the estimations. The 5-year crude and relative survival rates calculated using period analysis were 73.3% and 84.1% in 1997～2001, 80.3% and 91.4% in 2002～2006, and 82.1% and 93.6% in 2007～2011, respectively, higher than those estimated by cohort analysis.By using period method, the stage-adjusted 5-year relative survival rate was observed 0.9% lower than the unadjusted rate in 1997～2001 and 0.5% lower in 2002～2006, but increased 7.3% from 1997～2001 to 2002～2006, and 2.2% from 2002～2006 to 2007～2011, respectively. Stratified analysis showed that, from 1997～2001 to 2007～2011, the 5-year relative survival rates increased 3.3% in stage I patients,13.0% in stage II patients and 7.5% in Ⅲ～Ⅳ stage patients, respectively. Upward trends in stage-adjusted 5-year relative survival rates were observed in all patients regardless of therapy. However, the increases in survival rates were more evident in patients having breast conserving surgery, chemotherapy or hormone thrapy, but among those never engaging radiotherapy, particularly during the period from 1997～2001 to 2002～2006.Based on the survival status of breast cancer cases in 1997～2001,2002～2006 and 2007～2011, the relative 5-year survival rate during 2012～2016 was predicted as 95.2% by using projection method.ConclusionPeriod analysis performs better than cohort analysis and complete anlaysis in estimating 5-year survival rates; the survival rates of female breast cancer in the studied hospital has been significantly increasing in recent decades, which may mainly benefit from progress in cancer treatment. |
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