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Annals of Oncology Advance Access published online on October 24, 2007
Annals of Oncology, doi:10.1093/annonc/mdm491
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© 2007 European Society for Medical Oncology

Population-based study of breast cancer survival in Cote d'Or (France): prognostic factors and relative survival

T. S. Dabakuyo1,5, F. Bonnetain1,5, P. Roignot2, M.-L. Poillot1,5, G. Chaplain1, T. Altwegg3, G. Hedelin4 and P. Arveux1,5,*

1 Breast and Gynaecologic Cancer Registry of Cote d'Or, Centre Georges François Leclerc, 1 rue Professeur Marion, Dijon
2 Centre de Pathologie, 33 rue Nicolas Bornier, Dijon
3 Centre Radiotherapie Du Parc, 18 cours du General de Gaulle, Dijon
4 Department of epidemiology and public health, Faculty of Medicine, Louis Pasteur University, 11 rue Humann, Strasbourg
5 EA 4184, Faculty of Medicine, University of Burgundy, 7 boulevard Jeanne d'Arc, Dijon, France

* Correspondence to: Dr P. Arveux, Centre Georges-François Leclerc, 1 rue Professeur Marion, Dijon 21000, France. Tel: +33-03-80-73-77-15; Fax: +33-03-80-73-77-34; E-mail: parveux{at}dijon.fnclcc.fr


   Abstract
Top
 Abstract
introduction
 patients and methods
 results
 discussion
 funding
 Acknowledgements
 References
 
Background: Few population-based studies have reported jointly analyses of relative survival according to the following prognostic factors: tumour-node-metastasis (TNM) stage, age, number of examined and positive nodes, hormonal status, histologic Scarff Bloom and Richardson (SBR) grade, tumour extension, hormone receptor status and tumour multifocal status.

Patients and methods: Data on female invasive breast cancer were provided by the Cote d'Or breast cancer registry. The Kaplan–Meier method and log-rank test were used to estimate and compare the survival probability at 1, 5, 10 and 15 years. The effect of prognostic factors on survival was assessed with crude and relative multivariate survival analyses.

Results: Crude survival seemed to be worse in patients aged >60 years compared with those aged (45–60) (P > 0.0001), whereas relative survival did not differ. TNM stage, histologic SBR grade, progesterone receptor status, tumour multifocal status, locoregional extension and the period of diagnosis were independent prognostic factors of crude and relative survival.

Conclusion: Breast cancer is influenced by many factors. Despite the absence of any association between the number of examined nodes and overall survival in this study, the number of nodes removed, in conjunction with other prognostic factors, may be useful in selecting node-negative patients for systemic therapy.

breast cancer, crude survival, epidemiology, population-based cancer registry, prognostic factors, relative survival


   introduction
Top
 Abstract
 introduction
patients and methods
 results
 discussion
 funding
 Acknowledgements
 References
 
Breast cancer is the most common cancer among women worldwide. It accounts for ~20% of all malignancy, and the proportion is higher in women from western developed countries [1, 2].

The main risk factors identified were related to the woman's reproductive history: early menarche, late first pregnancy, low parity, late menopause and endogenous hormones. The use of oral contraceptives and hormonal replacement therapy have both been linked to increased risk [3, 4, 5].

In France, cancer registries have been set up to collect population-based cancer survival data. These data are useful to assess the effectiveness of strategies to control the incidence of cancer [6]. The Cote d'Or breast and gynaecologic cancer registry is, in France, the only cancer registry which focuses on breast and gynaecologic cancer. It has been collecting comprehensive population-based data since 1982.

Some population-based studies have already provided some results related to prognostic factors for overall survival (OS) in breast cancer [7–10]. However, to our knowledge, few studies have reported jointly analyses of relative and crude survival according to the following prognostic factors: tumour-node-metastasis (TNM) stage, age, number of examined and positive nodes, hormone status, histologic Scarff Bloom and Richardson (SBR) grade, tumour extension, oestrogen and progesterone receptor status and tumour multifocal status. The use of relative survival allows indirect correction for deaths not attributable to breast cancer [11].

The first aim of our study was to assess prognostic factors on crude and relative OS among patients with breast cancer and then to study survival according to the main patient and tumour characteristics.


   patients and methods
Top
 Abstract
 introduction
 patients and methods
results
 discussion
 funding
 Acknowledgements
 References
 
population
Data on female breast cancer were provided by the Cote d'Or breast and gynaecologic cancer registry. Cases were registered from January 1982 to December 1997. Women with in situ breast cancer, lost at diagnostic date or those for whom the only information was that given on the death certificate only (DCO) were excluded. For patients with synchronous bilateral breast cancer, the first site diagnosed was selected.

studied variables and end points
We reviewed a population-based series of 4223 patients. All patients were staged according to the TNM system [12]. Staging was based on pathological information; clinical information was used when pathological data were missing. Age at diagnosis, the tumour size, the number of examined or positive nodes were categorized. The hormone status premenopausal or postmenopausal, oestrogen and progesterone receptor status, histologic SBR grade and the tumour multifocal status were also collected and reported. To take into account progress in diagnosis and therapeutic options, the period was split according to time of diagnosis: 1982–1992 and 1993–1997.

Survival was calculated from the date of diagnosis until the date of death or the date of last follow-up. The cut-off date for survival analysis was set at 30 June 2005. Patients who were alive after the cut-off date were censored.

statistical method
Continuous and qualitative variables were, respectively, described by mean, standard deviation (SD), median and by percent. The percentage of missing values is also provided.

Crude survival probabilities were estimated using the Kaplan–Meier method, and were compared by the log-rank test.

Relative survival is an estimator of the excess risk of death or the excess mortality ratio (EMR). The EMR was calculated by dividing the observed number of deaths by the expected number of deaths estimated from the expected survival (ES) probability.

The ES was estimated with the Ederer II method [13] using age and period-matched mortality rates based on Cote d'Or female life expectancy tables. The EMR was estimated in a generalized linear model with a poisson error structure [14]. Follow-up time was stratified in annual intervals.

Multivariate Cox proportional hazards modelling was applied to assess the independent prognostic effect for crude survival. Variables with missing data >15% were excluded.

All reported P values are two sided. The statistical significance level was set at P < 0.05.

Analyses were done using SAS (Statistical Analysis system version 9.1) and or STATA (version 9.0).


   results
Top
 Abstract
 introduction
 patients and methods
 results
discussion
 funding
 Acknowledgements
 References
 
population
Four thousand two hundred and twenty-three (4223) women were registered from January 1982 to December 1997. Among them, 86 cases were diagnosed on the basis of DCO, 57 patients were lost at the date of diagnosis and 249 patients presented an in situ tumour. Finally, a total of 3831 patients were retained for the study (Figure 1).


Figure 1
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  		Figure 1. Summary of patients’ inclusion criteria.

 
Mean age at diagnosis was 61 (SD = 14). Seventy-two percent of patients were postmenopausal (Table 1). According to tumour characteristics, the mean tumour size was 22 mm (SD = 16), and 54% of patients presented T1 stage. The mean number of examined and positive nodes were, respectively, 9 (SD = 5) and 2 (SD = 3). Forty-one percent of patients with negative receptors were lymph node positive and 42 percent of them received chemotherapy. N0 and M0 stage, histologic SBR grade 2, oestrogen and progesterone-positive receptors were the most frequently found characteristics (Table 1). Three thousand seven hundred and forty-seven patients (98%) underwent surgery. Adjuvant systemic treatment was given to 2121 patients (55%), 3071 patients (80%) received radiotherapy and 1275 patients (33%) developed metastases during follow-up (Table 2).


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  		Table 1. Patient and tumour characteristics

 

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  		Table 2. Patient treatment and metastasis characteristics

 
crude survival
The median follow-up was 9 years (0.003–24). At the cut-off date, 1818 deaths had occurred (48%) and 92 patients were lost to follow-up (2%).

Crude survival rates at 1, 5, 10 and 15 years were, respectively, 94%, 74%, 59% and 48%. Table 3 describes crude survival rates according to main patient and tumour characteristics. Survival was longer in patients aged from 45 to 59 years (P < 0.0001) and in patients with oestrogen or progesterone-positive receptors (P < 0.0002 and P < 0.0001, respectively). Survival rates decreased with tumour size, the number of positive nodes and metastasis (P < 0.0001). A greater number of examined nodes was linked to better survival (P < 0.0001). Regarding T stage, crude survival was significantly better among T1 patients (P < 0.0001). With regard to the period of diagnosis, breast cancer patients diagnosed from 1993 to 1997 had better survival than those diagnosed from 1982 to 1992 (P < 0.0001); 10-year survival rates were 63% and 57%, respectively (Table 3).


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  		Table 3. Crude survival according to patient and tumour characteristics

 
prognostic factor analyses
The Cox multivariate model adjusted for the date of diagnosis was tested. Tumour size, number of positive nodes and hormonal status, respectively, correlated to T stage (r = 0.9), N stage (r = 0.8) and age (r = –0.7), were excluded. These analyses showed that age (P < 0.0001), T stage (P < 0.0001), N stage (P < 0.0001), M stage (P < 0.0001), SBR grade (P < 0.0001), progesterone receptor status (P < 0.0001), locoregional extension (P = 0.0009) and tumour multifocal status (P = 0.003) were independent significant prognostic factors of crude survival (Table 4).


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  		Table 4. Multivariate analyses of crude and relative survivals

 
relative survival
Relative survival for the whole population at 1, 5, 10 and 15 years were 97%, 82 %, 72% and 68%, respectively.

Table 5 describes relative survival rates at 1, 5, 10 and 15 years according to main patient and tumour characteristics. The relative survival rate was highest in patients aged from 45 to 59 years. The 10-year relative survival rates for <45, 45–59, 60–74 and ≥75 age were, respectively, 70%, 76%, 72% and 64%. Oestrogen or progesterone-positive receptors were significantly associated with better relative survival. Relative survival rates decreased with tumour size and the number of positive nodes. Regarding T stage, relative survival was significantly better among T1 patients. For T1, T2, T3 and T4 patients, 10-year relative survival rates were 87%, 61%, 41% and 20%, respectively.


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  		Table 5. RS according to patient and tumour characteristics

 
Multivariate analyses of relative survival (Table 4) confirmed that T, N and M stage, SBR grade, oestrogen and progesterone receptor status, locoregional extension, tumour multifocal status and period of diagnosis were independent prognostic factors. Compared with tumour stage T1, tumour stages T2 [HR = 2.3 (1.8–2.8)], T3 [HR = 3.0 (2.2–4.1)] and T4 [HR = 3.1 (2.1–4.4)] were associated with lower survival. An increased risk of death was also observed in patients with metastasis [HR = 5.9 (4.4–7.9)] and positive nodes [HR = 2.1 (1.7–2.6)]. Age at diagnosis did not influence relative survival (P = 0.14) (Table 4).


   discussion
Top
 Abstract
 introduction
 patients and methods
 results
 discussion
funding
 Acknowledgements
 References
 
Unlike clinical trials, in which patients are highly selected, population-based survival studies are based on heterogeneous groups and can be used to determine cancer prognostic factors without any selective bias [5].

Our study included all cases of invasive breast cancer diagnosed from 1982 to 1997 in a well-defined population; using a cancer registry specialized in breast cancer. Furthermore, the follow-up for vital status was nearly complete with a low lost-to-follow-up rate (2%). With this large panel, the results of our study could be considered representative of French patient survival during this period.

The Eurocare-3 study which analyzed survival of cancer patients diagnosed from 1990 to 1994 showed that 1- and 5-year relative survival in France was, respectively, 96.4% and 81.3% [15]. In the same way, a study conducted by FRANCIM (French registries network), which focused on survival in 1564 cases of breast cancer diagnosed in 1990 in seven departments covered by a registry, reported that 5-year relative survival was 81.7% [16]. Our relative survival estimates at 1 and 5 years were, respectively, 97% and 82% and were in agreement with these studies [15, 16]

Regarding the assessment of prognostic factors, our results could be mitigated by the level of missing values related to clinical variables. Of the 3831 patients, only 2615 (68%) patients with complete data were retained in multivariate survival analyses. This level of missing data could have independently influenced significant values of prognostic factors retained for our multivariate analyses. Nevertheless, some of our results were in agreement with those of other studies. Multivariate analyses of relative survival confirmed that tumour, node and metastasis staging at the time of diagnosis, SBR grade, hormone receptor status, locoregional extension, tumour multifocal status and the period of diagnosis were independent predictors of the length of survival [10, 17, 18]. Furthermore, women aged 45–59 years at diagnosis had the best prognosis of all age groups, with a 5-year relative survival rate of 85%. Five-year relative survival rates for <45, 60–74 and ≥75 age subgroups were 80%, 81% and 74%, respectively. A study conducted by Holli et al. [19] on the effect of age on the survival of breast cancer patients showed that 5- and 10-year relative survivals were highest in women aged 46–50 at diagnosis, whereas there was no significant difference between younger and older age groups. Our relative multivariate analyses did not confirm the influence of age. Crude analyses showed that patients aged >60 years had worse survival than those aged from 45 to 59, even though age was not an independent prognostic factor of relative survival. This excess mortality after 60 years may be due to the normal reduction in life expectancy with age. This controversy between crude and relative survival analyses highlights the interest of relative survival models when the effect of age is analyzed [13, 20].

Like in other studies [10, 17, 21, 22], tumour stage at diagnosis was the major predictor of survival. The three components of TNM staging were considered independently as prognosis factors in our study.

As in other studies [23, 24], the hormone receptor status influenced survival. According to the guidelines of the French health authorities [25], patients with positive hormone receptors are eligible for hormone therapy. Thus, the influence of hormone receptors could be mainly attributable to the efficacy of the chosen hormone therapy.

Our striking finding was that the number of nodes removed had no independent influence on OS. Conflicting results have already been reported from other studies concerning the relationship between the number of examined lymph nodes and survival [6, 26–30]. In a study conducted by Moorman et al. [27], the authors indicated that there was no relationship between specific mortality due to breast cancer and the number of lymph nodes examined. Others studies [6, 28, 29] reported that the number of removed nodes was associated with survival. However, these studies used crude survival as the primary outcome. As age is obviously inversely related to crude survival, these analyses may have been biased if age was associated with the number of examined nodes and other clinical characteristics. As demonstrated by Schaapveld et al. [10], the number of examined lymph nodes did not influence relative survival after adjustment for other prognostic variables. The use of relative survival makes it possible to correct for non-breast cancer-related deaths while circumventing the problems associated with establishing the cause of death. Moreover, for patients without systemic therapy, regional relapse is significantly increased with smaller numbers of removed nodes [30]. Recovery of a small number of negative lymph nodes at axillary dissection is likely to result in the understaging of patients and lead to undertreatment, giving rise to increased regional relapse and finally to poorer OS. The use of systemic therapy may overcome this effect. The number of nodes removed, in conjunction with other prognostic factors, may be useful in selecting node-negative patients for systemic therapy.

Breast cancer remains a major problem for public health authorities. Clinical research has proposed different approaches resulting in increased survival and improved quality of life for patients (mass screening, new biomarkers and new drugs). However, it is necessary to evaluate the impact of these approaches in a large population. Population-based registry studies are needed to assess and to monitor the true benefits of these improvements.


   funding
Top
 Abstract
 introduction
 patients and methods
 results
 discussion
 funding
Acknowledgements
 References
 
Ligue Nationale Contre le Cancer; Comité de Cote d'Or.


   Acknowledgements
Top
 Abstract
 introduction
 patients and methods
 results
 discussion
 funding
 Acknowledgements
References
 
We thank Coralie DEVILLE (Unité de Biostatistiques et d’épidémiologie, DIM, CGFL), Valérie JOOSTE (Institut National de la Santé et de la Recherche Médicale U866) and Ahmed HAMADOUCHE (Laboratoire d’épidémiologie et de santé publique, Faculté de Médecine, Strasbourg) for statistical assistance. We also thank Philip BASTABLE for correcting the manuscript.

Received for publication May 31, 2007. Revision received September 19, 2007. Accepted for publication September 19, 2007.


   References
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 Abstract
 introduction
 patients and methods
 results
 discussion
 funding
 Acknowledgements
 References
 
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