Molecular signatures may become of use in clinical practice to assess the prognosis of breast cancers. However, although international consensus conferences sustain the use of these new markers in the near future, concerns remain about their degree of discordance and cost-effectiveness in different international settings. The present study aims to validate Ki67 as prognostic factor in a large cohort of early-stage (pT1–pT2, pN0) breast cancer patients.
456 patients treated in 1995–1996 were identified in the Institut Curie database. Ki67 (MIB1) was retrospectively assessed by immunohistochemistry for all cases. The prognostic value of this index was compared to that of histological grade (HG), Estrogen receptor (ER) and HER2 status. Distant disease free interval, loco-regional recurrence, time-lapse from first metastatic diagnosis to death were analyzed.
All 456 patients were treated by lumpectomy plus axillary dissection and radiotherapy. 27 patients (5.9%) received systemic treatment. Tumors were classified as HG1 in 35%, HG2 in 42% and HG3 in 23% of cases. ER was expressed in 86% of the tumors, HER2 in 5% and 14% were triple negative. The median follow-up was 151 [5–191] months. Distant and loco-regional disease recurrences were observed in 16% and 18%, respectively. High (>20%) Ki67 rate [HR = 3 (1.8–4.8), p<10e−06] and HG3 [HR = 4.4 (2.2–8.6), p = 0.00002] were associated with an increased rate of distant relapse. In multivariate analysis, the Ki67 remained the only significant prognostic factor in the subgroups of ER positive HER2 negative [HR = 2.6 (1.5–4.6), p = 0.0006] and ER positive HER2 negative HG2 tumors [HR = 2.2 (1.01–4.8), p = 0.04].
Citation: Reyal F, Hajage D, Savignoni A, Feron J-G, Bollet MA, Kirova Y, et al. (2013) Long-Term Prognostic Performance of Ki67 Rate in Early Stage, pT1-pT2, pN0, Invasive Breast Carcinoma. PLoS ONE 8(3): e55901. https://doi.org/10.1371/journal.pone.0055901
Editor: Ramon Andrade de Mello, University of Porto, Portugal
Received: June 26, 2012; Accepted: January 7, 2013; Published: March 19, 2013
Copyright: © 2013 Reyal et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no funding or support to report.
Competing interests: The authors have declared that no competing interests exist.
Breast cancer prognostic factors are essential to identify patients at risk of distant metastasis development and to decide whether adjuvant treatments are needed. The most validated biological marker in non-metastatic breast cancer are tumor size, histological grade, mitotic index, Ki67 rate, axillary lymph node involvement, Estrogen Receptor (ER), Progesterone Receptor (PR) and HER2 status. Tumor proliferation is one of the major factors associated with prognosis . It can be measured by two widely used markers mitotic index (MI) and Ki67 rate. MI, defined as the number of mitoses per 10 high power fields at the periphery of the tumor , , carries the main part of the prognostic value of the histological grade (Nottingham system). This index is linked to the percentage of tumor cells undergoing mitosis and to the duration of the cell-cycle, considering that the M phase is only a short part of the cell-cycle process. However MI does not reflect the doubling time of the tumor. In a large meta-analysis of 20 studies  corresponding to 7,021 patients, the independent prognostic value of MI for metastases or cancer specific deaths in breast cancer patients was confirmed using univariate and multivariate models. Nuclear Ki67 immuno-staining is the second proliferation marker most widely used in clinical practice. The Ki67 protein is present during G1, S, G2, M phases of the cell cycle and is strictly associated with cell proliferation. The Ki67 rate is most often measured on histological sections and is defined as the percentage of stained invasive carcinoma cells. The prognostic value of the Ki67 rate has been confirmed in several meta-analyses including univariate and multivariate models , , , . The Saint-Gallen guidelines , National Institute of Health guidelines  and Nottingham Prognosis Index guidelines  as well as the AdjuvantOnline! decision making tool  use a combination of these prognostic factors to assess the need for adjuvant treatments based. Owing to insufficiently accurate prognosis predictions, a substantial proportion of patients with breast cancer receive useless adjuvant systemic therapy . High-throughput technologies such as gene expression microarrays offer new opportunities to improve the ability to determine prognosis for individual patients. Molecular signatures (Proliferation signatures) such as Mammaprint© (Agendia, Amsterdam, Netherlands) , , OncotypeDX© (Genomic Health, Redwood, California, USA)  and MapquantDX© (Ipsogen, Marseille, France)  may become of use in clinical practice. International consensus conferences seem to sustain the use of these new markers in the near future despite great concerns about the real benefit, the large degree of discordance between them and the potential low cost-effectiveness of these classifiers. In a pilot study, and taking into account medico-economic aspects, we favored the use of Ki67, with a 20% cut-off, as a routine marker for the assessment of tumor cell proliferation (Reyal et al., Plos one 2012). The present study aims at analyzing the Ki67 prognostic value in a large cohort of early-stage, pN0, breast cancer patients treated in a reference comprehensive cancer center. We focused our analysis on the ER positive HER2 negative subgroup and on the ER positive HER2 negative Grade 2 subgroup as they represent two entities with a need to improve their prognostic determination and consequently their adjuvant treatment decision-making process. Conversely, the treatments of patients with HER2 positive or triple-negative tumour do not rely on the level of their proliferation markers due to the intrinsic aggressiveness of these two subgroups.
Materials and Methods
Our dataset consisted of 456 early-stage (pN0) breast cancer patients treated between 1995 and 1996 by breast conserving surgery with axillary lymph node dissection as primary treatment at the Institut Curie and identified through the Institut Curie prospective breast cancer database. The main inclusion criterion was the absence of pathologic axillary lymph node involvement. Patients who had received a neoadjuvant treatment (chemotherapy, hormonal therapy or radiotherapy) were excluded from the study.
The histological features (Histological Type, Elston Ellis Grade, Mitotic Index, Ki67 rate, Estrogen Receptor status, Progesterone Receptor status, HER2 over expression status) were re-assessed for each sample by senior pathologists. Tissue sections of 4 µm were prepared from a representative part of each tumor sample to score several markers.
Mitotic Index was assessed on histological sections stained by Hematein, Eosin and Saffron. The criteria of Van Diest and al were used to define mitotic figures , . It corresponded to the mitotic score defined in the Nottingham grade; the number of mitoses observed in 10 consecutive high power fields (HPF) using a microscope with 40× objectives and a 10× ocular. Cut-off, according to the field of our microscope, <10, 10–19 and ≥20 mitosis were used to define low, intermediate and high mitotic indexes.
Tissue sections were first digested in 0.1% trypsin and 0.1% calcium chloride in triphosphate buffer saline pH 7.6 for 5 minutes. Antigen retrieval was performed by incubating tissue sections for 20 minutes in citrate buffer 10 mM (ph 6.1) in a 850 W microwave oven. Tissue sections were then incubated for one hour with the anti-Ki67 monoclonal antibody (Clone MIB1, Dako A/S, Glostrup, Denmark) at 1/100 dilution. The revelation of the staining was performed using the Vectastain Elite ABC peroxydase mouse IgG kit (Vector Burlingame, CA, USA) and diamino-benzidine (Dako A/S) as chromogen. The semiquantitative assessment was performed by estimating at X200 magnification, the percentage of positive neoplastic nuclei within the area of highest positivity chosen after scanning the entire tumour surface at low power (x10 objective). All nuclei with homogeneous staining even with a light staining or only a nucleolar staining were interpreted as positive. A cut-off of >20% was used to define tumors with high KI67 rate.
Estrogen receptor (ER) and Progesterone receptor (PR) status
After rehydration and antigenic retrieval in citrate buffer (10 mM, pH 6.1), the tissue sections were stained for estrogen receptor (ER, clone 6F11, Novocastra, 1/200), and progesterone receptor (PR, clone 1A6, Novocastra, 1/200). Revelation of staining was performed using the Vectastain Elite ABC peroxidase mouse IgG kit (Vector Burlingame, CA) and diaminobenzidine (Dako A/S, Glostrup, Denmark) as chromogen. Positive and negative controls were included in each slide run. Cases were considered positive for ER and PR according to standardized guidelines using a cut-off of ≥10% stained tumour nuclei , .
After rehydration and antigenic retrieval in citrate buffer (10 mM, pH 6.1), the tissue sections were stained for HER-2 (clone CB11, Novocastra, 1/1000). Revelation of staining was performed using the Vectastain Elite ABC peroxidase mouse IgG kit (Vector Burlingame, CA) and diaminobenzidine (Dako A/S, Glostrup, Denmark) as chromogen. Positive and negative controls were included in each slide run. The determination of HER2 overexpression was determined according to GEFPICS guidelines with FISH performed in all cases of HER2 2+ result .
Statistical analyses were performed in both the whole population and in two restricted immune-phenotypic population defined as 1) ERpositive, HER2negative 2) ERpositive, HER2negative, Histological Grade 2.
Time to distant metastases and time to loco-regional recurrences were defined as the time from the breast cancer primary tumour diagnosis to the occurrence of the event. Time to death was defined as the time from the diagnosis of the metastases to the occurrence of the death. Survival analyses were performed using the Kaplan-Meier estimate of the survival function. Comparison between survival curves was performed using the logrank test. Hazard ratios were estimated using the Cox proportional hazard model. P-values were considered significant when below 0.05. Only variables with a significant p-value in univariate analyses were included in a multivariate ascending stepwise procedure using the Cox model.
The multivariate model performance was quantified with respect to discrimination (i.e., whether the relative ranking of individual predictions is in the correct order when compared to observation), quantified with the Concordance index (C-index) [Harrell et al Ref. 1, 1996] and its 95% confidence interval. The analyses were performed using R software (http://cran.r-project.org).
The registration of patients of the Institut Curie (Paris and Saint-Cloud) in this cohort received a favorable agreement of the french National Committee on Computers and Liberties (CNIL, Commission nationale de l'informatique et des libertés). Patients gave informed written consent prior to be registered in the cohort. The study was approved by the breast cancer study group and the comity of clinical research study of the Institut Curie (Paris and Saint-Cloud).
A continuous retrospective series of 456 patients with pN0, pT1–pT2, invasive breast carcinoma, treated at the Institut Curie between 1995–1996 was identified using a prospective database (Table 1). All patients were all treated by lumpectomy plus axillary lymph node dissection. 27 (5.9%) patients received an adjuvant chemotherapy and 32 (8.5%) adjuvant hormonal therapy for 5 years. All of the patients received an irradiation of the whole breast with a median dose of 50 Gy [45–55] (International Comission on Radiation Units; ICRU) in 25 daily fractions and 5 weeks. 347 patients (76%) had a boost to the tumor bed with a median dose of 15 Gy – in 8 daily fractions, and 231 patients (50.6%) received irradiation of the internal mammary chain (combination of photons and electrons) to 45 Gy in 23 daily fractions and 4.6 weeks. The clinical and pathological features of patients are summarized in tables Table 1. Tumors corresponded mainly to ductal (76%) or lobular (14%) infiltrating carcinomas. All cases were free of axillary lymph node metastases. Tumors were classified as histological grade I (HG1) in 35% (161/456), HG2 in 42% (192/456) and HG3 in 23% (103/456) (Notthingham histological grade). Immunophenotyping showed that ER was expressed in 86% (386/456) of the tumors, PR in 70% (319/456), HER2 in 5% (23/456) whereas 14% (62/456) remained negative for all three markers. The median follow-up period was 151 [5–191] months. 73 patients developed a distant relapse (16%) and 81 patients developed a loco-regional recurrence (17.7%). 19 patients (26%) had bone as the only site of metastases when first diagnosed with metastatic disease. Other locations were lung, liver, brain, lymph-node, bowel and skin.
ER positive and HER2 negative tumors constituted a subgroup of 371 (81.4%) cases (Table 2). In this group, tumors corresponded mainly to ductal (74%) or lobular (16%) carcinoma. It was classified as HG1 in 41% (153/371), HG2 in 46% (169/371) and HG3 in 13% (49/371) of cases. 50 patients (13.5%) developed a distant relapse and 61 patients (16.4%) developed a loco-regional recurrence. Another subgroup (169 cases, 37%) corresponded to ER positive HER2 negative HG2 tumors (Table 3). In this subgroup, 28 patients (16.5%) developed a distant relapse and 30 (17.7%) a loco-regional recurrence.
Histological Grade, Mitotic Index and Ki67 Rate
The kernel density plots of the Mitotic Index (MI) in each grade categories showed a low mitotic index (≤20) for 100% of the HG1 tumors and for 96% of the HG2 tumors. Only HG3 tumors had a Mitotic Index higher than 20 in 80%. Ki67 distribution was a much more discriminatory factor with extreme values in HG1 (90% with Ki67≤20) and HG3 (85% with Ki67>20) tumors. In contrast, a wide spectrum of the Ki67 rate was observed in HG2 tumors: it was ≤20% in 59% of the cases and >20 in 41%. We identified a subgroup of 262 (57%) samples with a low MI (<20) and a low Ki67 rate (≤20), 112 (24%) samples with a low MI and a high Ki67 rate, 77 (15%) samples with high MI and a high Ki67 rate and 12 (3%) samples with high MI and low Ki67 rate.
Loco Regional Recurrence
Univariate analyses (Table 1) showed that young age, pre-menopausal status or hormone replacement therapy and non-clear surgical margins (less than 3 mm) were associated with an increased rate of loco-regional recurrences. We performed a subgroup analysis in 371 ER+ HER2− patients (81.4%) and showed that age at diagnosis and surgical margins were still significant factors correlated to an increasing risk of loco-regional recurrence (Table 2). No factors were identified in ER+, HER2−, HG2 tumor samples (Table 3). Variables selected in the multivariate model are summarized in table 4 (in terms of Hazard Ratio, confidence Intervals and p value). Only menopausal status and surgical margins were finally selected (Table 4, figure S1 and S2). The C-index of this model was 0.62 [CI95% = 0.56–0.68]. A nomogram was built (Figure 1).
Univariate analyses (Table 1) showed that pathological tumor size (p = 0.03), histological type (p = 0.03), lympho-vascular invasion (p = 0.01), histological grade (p = 0.00002), immunophenotypic subtypes (ER+ HER2− and ER−; p = 0.0006), and Ki67 rate (p<10e−6) were associated with an increased rate of distant metastases.
We designed a multivariate ascending stepwise procedure using the Cox model to determine the probability of distant metastasis. In the whole population, Ki67 rate and histological grade remained significant variables (figure S3 and S4). Ki67 rate was the only significant variable when the multivariate analysis was performed in the whole population or in the two subgroups of ER+ HER2− and ER+ HER2− HG2 (Table 2, Table 3, Table 5). C-index of this model was 0.68 [CI95% = 0.62–0.74]. A nomogram was built (Figure 2).
From First Metastatic Event to Death
Development of distant relapse was observed in 73 patients (16%). Median delay from metastasis diagnosis to death was 36 months [1–144]. 19 patients (26%) had metastasis in bone only as first diagnostic of secondary tumor location. Other sites were lung, liver, brain, lymph node, bowel and skin. Primary tumors features (lympho-vascular invasion, histological grade, hormone receptor status), time lapse between primary tumor and first metastasis and first metastasis location (bone versus other locations) were all correlated to the time-lapse from first metastatic event to death from breast cancer (figure S5, S6 and S7). Variables selected in the multivariate model were time-lapse from primary tumor to first metastasis diagnosis, lympho-vascular invasion and hormone receptor status (Table 6). The C-index of the model was 0.66 [CI95% = 0.59–0.74]. A nomogram was built (Figure 3).
This study aimed to analyze the Ki67 rate prognostic value in a large cohort of 456 consecutive early-stage (pT1–pT2), pN0 breast cancer patients. These patients were all treated by primary breast-conserving surgery followed by whole-breast radiotherapy. A few patients received either adjuvant chemotherapy (5.9%) or a 5-year adjuvant hormonal therapy (8.5%). The median follow-up length was 12 years.
In the whole population, the Ki67 rate (threshold 20%) was the most significant factor associated to the distant disease free interval, in univariate and in multivariate analyses, outperforming the values of both Mitotic Index and HG. Ki67 rate was the only significant variable in the subgroups of ER+ HER2− and of ER+ HER2− HG2 tumors. As the concordance between the HG and Ki67 rate was high for HG1 and HG3 tumors and as the prognostic value of the Ki67 was significant in the ER+ HER2− HG2 subgroup (37% of the cases), we conclude that the Ki67 is a cost-effective decision marker for the indication of adjuvant therapy in more than one third of early-stage, pT1–pT2, pN0, breast cancer patients.
Proliferation is a key determinant of both prognosis , – and response to adjuvant systemic treatments whether on chemotherapy  or aromatase inhibitors . In a series of 2847 HR+ breast cancer patients, Cheang et al showed how Ki67 was able to discriminate luminal B from luminal A tumors and that this marker was significantly associated with poor disease recurrence-free and disease-specific survival in all adjuvant systemic treatment categories . However the determination of the Ki67 threshold remains controversial, ranging from 3 to 35% . The one used in our previous analysis was 20%. The integration of gene expression arrays data and Ki67 immuno-staining allowed us to identify that Ki67 rate higher than 20% was correlated to a strong activation (over-expression) of the genes involved in the tumor proliferation process. It is however still crucial to underline the absolute need to set-up a multi-center, international, standardization process of the determination of Ki67 status. In their letter, Colozza et al  expressed their concern that setting Ki67 cut-offs in order to determine the systemic adjuvant therapy, as the St Gallen experts had done at the 2009 Consensus (<15%, 16–30%, >30%) was a little hasty as long as a standardization of the Ki67 status, and particularly of the pre-analytical handling of the tumors was not done .
Nottingham histological grade (HG) was the second independent prognostic factor for distant metastases in the whole subpopulation but this marker did not reach statistical significance in the subpopulation of luminal cancers. This confirms data showing that HG is a valuable prognostic factor , , , particularly in early breast cancer without lymph node involvement .
We built a nomogram based on Ki67 rate and HG to determine the 5 and 10 years probability of distant metastasis event. The maximum distant metastasis free probability [HG1, low Ki67 rate] was 96% and 92% at 5 and 10 years respectively. The minimum distant metastasis free probability was 84% and 70% at 5 and 10 years respectively.
Loco Regional Recurrence
In the whole series of 456 patients, we showed that young age, pre-menopausal status or hormone replacement therapy and non-clear surgical margins (less than 3 mm) were associated with an increased rate of loco-regional recurrences. Ki67 rate was not a factor associated to the loco-regional recurrence free interval. We built a multivariate model and corresponding nomogram based on menopause status and surgical margins to predict the 5 and 10 years loco-regional recurrence probability. The maximum loco-regional free probability [margin> = 3 mm, post-menopause status] was 95% and 92% at 5 and 10 years respectively. The minimum loco-regional free probability [margin<3 mm, pre-menopause status] was 85% and 72% at 5 and 10 years respectively. Many authors have already reported that young age, defined in either three classes or according to the menopause status, and a satisfactory surgical margin (3 mm) were major prognostic factors associated with loco-regional recurrence , , . Macroscopic involvement of the margin has been associated, since the eighties, with an increased risk of developing local recurrences despite the use of radiotherapy , . The impact of inadequate surgical margins seem to be lessened by postoperative radiotherapy  even though it is not eradicated , . Fourquet et al  showed in a series of 518 patients, of whom 68% were premenopausal, treated by breast conserving surgery followed by whole-breast radiotherapy for breast cancers without clinical axillary lymph node involvement that macroscopic involvement of the margin was, after age, the second most important independent factor for local recurrence. The effect of microscopically involved margin by invasive tumours is, on the other hand, more controversial. Many large series of breast conserving surgery with whole-breast radiotherapy have revealed that it was significantly associated, in univariate or multivariate analyses, with a higher rate of local relapses , , –, , , , , , , . Two retrospective studies, performed at the MD Anderson Cancer Center and at the Institut Curie Cancer Center showed that young age remains a major prognostic factor of local recurrence in a population of patients younger than 40 treated by breast conserving surgery and radiotherapy performed as either their initial treatments , or after neoadjuvant chemotherapy . The fact that young age is the most significant prognostic factor is not yet understood despite numerous studies. We could find its explanation in tumor biology and/or the hormonal environment specific to pre-menopausal women , , . The fact that we identified menopausal patients receiving Hormone Replacement Therapy as at the same risk of loco-regional recurrence as pre-menopausal patients seems to strengthen the hormonal environment hypothesis.
From First Metastatic Event to Death
Finally, we identified that hormonal receptor status, lympho vascular invasion, bone metastasis and the late discovery of the first metastases were significant variables correlated to the time lapse from a first metastatic event to death from breast cancer. We built a multivariate Cox model and corresponding nomogram based on time-lapse from primary tumour to first metastatic diagnosis, and two primary tumor features (lympho vascular invasion and hormone receptor status) to predict the 1, 5 and 10 years probabilities of death from breast cancer. The minimum death probability [time-lapse >24 months, no lympho vascular invasion, hormone receptor positive status] was 5%, 50% and 85% at 1, 5 and 10 years respectively. The maximum death probability [time-lapse <24 months, lympho vascular invasion, hormone receptor negative status] was 70% and 100% at 1 and 5 years respectively. Several groups have previously identified these factors. Chang et al , Rowlings et al , Rizzieri et al , Hortobagyi et al  showed that a short disease free interval, ER, PR and HER2 status were correlated to the survival outcome.
In conclusion, our study confirms the validity of the Ki67 proliferation marker to better evaluate the risk of distant metastases in early stage, pT1–pT2, pN0 breast cancers. Ki67 was not a relevant prognostic factor of loco-regional recurrence or of the time-lapse between the diagnosis of first metastasis and death. Since the concordance between the HG and Ki67 rate was high for HG1 and HG3 tumors and since the prognostic value regarding distant relapse of Ki67 rate was significant in the ER+ HER2− HG2 subgroup, we concluded that the Ki67 rate is a potential cost-effective prognostic proliferation marker in this later subgroup which represents 37% of early stage pN0 breast cancer patients. Three nomograms were built from this study to determine the probability of metastatic relapse, loco-regional recurrence and death from breast cancer at the time of first metastases diagnosis.
Loco Regional Free Interval. Kaplan Meier Curves. Menopausal status.
Loco Regional Free Interval. Kaplan Meier Curves. Surgical Margin.
Distant Disease Free Interval. Kaplan Meier Curves. Ki67 rate.
Distant Disease Free Interval. Kaplan Meier Curves. Histological Grade
First Metastatic Event to Death. Kaplan Meier Curves. Hormone Receptors
First Metastatic Event to Death. Kaplan Meier Curves. Lympho-Vascular Invasion
First Metastatic Event to Death. Kaplan Meier Curves. Delay.
Conceived and designed the experiments: FR AVS BSZ XSG. Performed the experiments: FR DH AS BA. Analyzed the data: FR DH AS BA AVS BSZ XS. Contributed reagents/materials/analysis tools: JGF MAB YK AF JYP PC VD VF FL SA. Wrote the paper: FR DH AS BA AVS BSZ XS.
- 1. Anders CK, Hsu DS, Broadwater G, Acharya CR, Foekens JA, et al. (2008) Young age at diagnosis correlates with worse prognosis and defines a subset of breast cancers with shared patterns of gene expression. J Clin Oncol 26: 3324–3330.
- 2. Baak JP, van Diest PJ, Voorhorst FJ, van der Wall E, Beex LV, et al. (2005) Prospective multicenter validation of the independent prognostic value of the mitotic activity index in lymph node-negative breast cancer patients younger than 55 years. J Clin Oncol 23: 5993–6001.
- 3. Balaton AJ, Baviera EE, Galet B, Vaury P, Vuong PN (1995) [Immunohistochemical evaluation of estrogen and progesterone receptors on paraffin sections of breast carcinomas. Practical thoughts based on the study of 368 cases]. Arch Anat Cytol Pathol 43: 93–100.
- 4. Balaton AL, Coindre JM, Collin F, Ettore F, Fiche M, et al. (1996) [Recommendations for the immunohistochemical evaluation of hormone receptors on paraffin sections of breast cancer. Study Group on Hormone Receptors using Immunohistochemistry FNCLCC/AFAQAP. National Federation of Centres to Combat Cancer/French Association for Quality Assurance in Pathology]. Ann Pathol 16: 144–148.
- 5. Blamey RW, Ellis IO, Pinder SE, Lee AH, Macmillan RD, et al. (2007) Survival of invasive breast cancer according to the Nottingham Prognostic Index in cases diagnosed in 1990–1999. Eur J Cancer 43: 1548–1555.
- 6. Bollet MA, Savignoni A, De Koning L, Tran-Perennou C, Barbaroux C, et al. (2009) Tumor aromatase expression as a prognostic factor for local control in young breast cancer patients after breast-conserving treatment. Breast Cancer Res 11: R54.
- 7. Bollet MA, Sigal-Zafrani B, Mazeau V, Savignoni A, de la Rochefordiere A, et al. (2007) Age remains the first prognostic factor for loco-regional breast cancer recurrence in young (<40 years) women treated with breast conserving surgery first. Radiother Oncol 82: 272–280.
- 8. Chang J, Clark GM, Allred DC, Mohsin S, Chamness G, et al. (2003) Survival of patients with metastatic breast carcinoma: importance of prognostic markers of the primary tumor. Cancer 97: 545–553.
- 9. Cheang MC, Chia SK, Voduc D, Gao D, Leung S, et al. (2009) Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 101: 736–750.
- 10. Chia S, Norris B, Speers C, Cheang M, Gilks B, et al. (2008) Human epidermal growth factor receptor 2 overexpression as a prognostic factor in a large tissue microarray series of node-negative breast cancers. J Clin Oncol 26: 5697–5704.
- 11. Colozza M, Azambuja E, Cardoso F, Sotiriou C, Larsimont D, et al. (2005) Proliferative markers as prognostic and predictive tools in early breast cancer: where are we now? Ann Oncol 16: 1723–1739.
- 12. Colozza M, Sidoni A, Piccart-Gebhart M (2010) Value of Ki67 in breast cancer: the debate is still open. Lancet Oncol 11: 414–415.
- 13. de Azambuja E, Cardoso F, de Castro GJ, Colozza M, Mano MS, et al. (2007) Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br J Cancer 96: 1504–1513.
- 14. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365: 1687–1717.
- 15. Eifel P, Axelson JA, Costa J, Crowley J, Curran WJJ, et al. (2001) National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer, November 1–3, 2000. J Natl Cancer Inst 93: 979–989.
- 16. Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19: 403–410.
- 17. Elston CW, Ellis IO (2002) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. C. W. Elston & I. O. Ellis Histopathology 19: 403–410 Histopathology 41: 151–2, discussion 152–3.
- 18. Fourquet A, Campana F, Zafrani B, Mosseri V, Vielh P, et al. (1989) Prognostic factors of breast recurrence in the conservative management of early breast cancer: a 25-year follow-up. Int J Radiat Oncol Biol Phys 17: 719–725.
- 19. Freedman G, Fowble B, Hanlon A, Nicolaou N, Fein D, et al. (1999) Patients with early stage invasive cancer with close or positive margins treated with conservative surgery and radiation have an increased risk of breast recurrence that is delayed by adjuvant systemic therapy. Int J Radiat Oncol Biol Phys 44: 1005–1015.
- 20. Goldhirsch A, Ingle JN, Gelber RD, Coates AS, Thurlimann B, et al. (2009) Thresholds for therapies: highlights of the St Gallen International Expert Consensus on the primary therapy of early breast cancer 2009. Ann Oncol 20: 1319–1329.
- 21. Goldhirsch A, Wood WC, Gelber RD, Coates AS, Thurlimann B, et al. (2007) Progress and promise: highlights of the international expert consensus on the primary therapy of early breast cancer 2007. Ann Oncol 18: 1133–1144.
- 22. Goldstein NS, Kestin L, Vicini F (2003) Factors associated with ipsilateral breast failure and distant metastases in patients with invasive breast carcinoma treated with breast-conserving therapy. A clinicopathologic study of 607 neoplasms from 583 patients. Am J Clin Pathol 120: 500–527.
- 23. Hortobagyi GN, Smith TL, Legha SS, Swenerton KD, Gehan EA, et al. (1983) Multivariate analysis of prognostic factors in metastatic breast cancer. J Clin Oncol 1: 776–786.
- 24. Ikeda T, Akiyama F, Hiraoka M, Inaji H, Ohuchi N, et al. (1999) Surgical Margin Status as a Cause of Local Failure after Breast Conserving Therapy. Breast Cancer 6: 93–97.
- 25. Jobsen JJ, van der Palen J, Ong F, Meerwaldt JH (2003) The value of a positive margin for invasive carcinoma in breast-conservative treatment in relation to local recurrence is limited to young women only. Int J Radiat Oncol Biol Phys 57: 724–731.
- 26. Kini VR, Vicini FA, Frazier R, Victor SJ, Wimbish K, et al. (1999) Mammographic, pathologic, and treatment-related factors associated with local recurrence in patients with early-stage breast cancer treated with breast conserving therapy. Int J Radiat Oncol Biol Phys 43: 341–346.
- 27. Komoike Y, Akiyama F, Iino Y, Ikeda T, Akashi-Tanaka S, et al. (2006) Ipsilateral breast tumor recurrence (IBTR) after breast-conserving treatment for early breast cancer: risk factors and impact on distant metastases. Cancer 106: 35–41.
- 28. Kreike B, Halfwerk H, Armstrong N, Bult P, Foekens JA, et al. (2009) Local recurrence after breast-conserving therapy in relation to gene expression patterns in a large series of patients. Clin Cancer Res 15: 4181–4190.
- 29. Kreike B, Hart AA, van de Velde T, Borger J, Peterse H, et al. (2008) Continuing risk of ipsilateral breast relapse after breast-conserving therapy at long-term follow-up. Int J Radiat Oncol Biol Phys 71: 1014–1021.
- 30. Kurtz JM, Jacquemier J, Amalric R, Brandone H, Ayme Y, et al. (1990) Why are local recurrences after breast-conserving therapy more frequent in younger patients? J Clin Oncol 8: 591–598.
- 31. Livi L, Paiar F, Saieva C, Scoccianti S, Dicosmo D, et al. (2007) Survival and breast relapse in 3834 patients with T1-T2 breast cancer after conserving surgery and adjuvant treatment. Radiother Oncol 82: 287–293.
- 32. McGrath S, Antonucci J, Goldstein N, Wallace M, Mitchell C, et al. (2010) Long-term patterns of in-breast failure in patients with early stage breast cancer treated with breast-conserving therapy: a molecular based clonality evaluation. Am J Clin Oncol 33: 17–22.
- 33. Neuschatz AC, DiPetrillo T, Safaii H, Price LL, Schmidt-Ullrich RK, et al. (2003) Long-term follow-up of a prospective policy of margin-directed radiation dose escalation in breast-conserving therapy. Cancer 97: 30–39.
- 34. Oh JL, Bonnen M, Outlaw ED, Schechter NR, Perkins GH, et al. (2006) The impact of young age on locoregional recurrence after doxorubicin-based breast conservation therapy in patients 40 years old or younger: How young is “young”? Int J Radiat Oncol Biol Phys 65: 1345–1352.
- 35. Paik S, Shak S, Tang G, Kim C, Baker J, et al. (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351: 2817–2826.
- 36. Park CC, Mitsumori M, Nixon A, Recht A, Connolly J, et al. (2000) Outcome at 8 years after breast-conserving surgery and radiation therapy for invasive breast cancer: influence of margin status and systemic therapy on local recurrence. J Clin Oncol 18: 1668–1675.
- 37. Penault-Llorca F, Andre F, Sagan C, Lacroix-Triki M, Denoux Y, et al. (2009) Ki67 expression and docetaxel efficacy in patients with estrogen receptor-positive breast cancer. J Clin Oncol 27: 2809–2815.
- 38. Penault-Llorca F, Vincent-Salomon A, Bellocq JP, Matthieu MC, Grogan GM, et al. (2010) [Update of the GEFPICS' recommendations for HER2 status determination in breast cancers in France]. Ann Pathol 30: 357–373.
- 39. Ravdin PM, Siminoff LA, Davis GJ, Mercer MB, Hewlett J, et al. (2001) Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 19: 980–991.
- 40. Rizzieri DA, Vredenburgh JJ, Jones R, Ross M, Shpall EJ, et al. (1999) Prognostic and predictive factors for patients with metastatic breast cancer undergoing aggressive induction therapy followed by high-dose chemotherapy with autologous stem-cell support. J Clin Oncol 17: 3064–3074.
- 41. Rowlings PA, Williams SF, Antman KH, Fields KK, Fay JW, et al. (1999) Factors correlated with progression-free survival after high-dose chemotherapy and hematopoietic stem cell transplantation for metastatic breast cancer. JAMA 282: 1335–1343.
- 42. Schnitt SJ, Abner A, Gelman R, Connolly JL, Recht A, et al. (1994) The relationship between microscopic margins of resection and the risk of local recurrence in patients with breast cancer treated with breast-conserving surgery and radiation therapy. Cancer 74: 1746–1751.
- 43. Smitt MC, Nowels KW, Zdeblick MJ, Jeffrey S, Carlson RW, et al. (1995) The importance of the lumpectomy surgical margin status in long-term results of breast conservation. Cancer 76: 259–267.
- 44. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, et al. (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98: 262–272.
- 45. Stuart-Harris R, Caldas C, Pinder SE, Pharoah P (2008) Proliferation markers and survival in early breast cancer: a systematic review and meta-analysis of 85 studies in 32,825 patients. Breast 17: 323–334.
- 46. van 't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415: 530–536.
- 47. van de Vijver MJ, He YD, van't Veer LJ, Dai H, Hart AA, et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347: 1999–2009.
- 48. van Diest PJ, Baak JP, Matze-Cok P, Wisse-Brekelmans EC, van Galen CM, et al. (1992) Reproducibility of mitosis counting in 2,469 breast cancer specimens: results from the Multicenter Morphometric Mammary Carcinoma Project. Hum Pathol 23: 603–607.
- 49. van Diest PJ, Belien JA, Baak JP (1992) An expert system for histological typing and grading of invasive breast cancer. First set up. Pathol Res Pract 188: 405–409.
- 50. Viale G, Giobbie-Hurder A, Regan MM, Coates AS, Mastropasqua MG, et al. (2008) Prognostic and predictive value of centrally reviewed Ki-67 labeling index in postmenopausal women with endocrine-responsive breast cancer: results from Breast International Group Trial 1–98 comparing adjuvant tamoxifen with letrozole. J Clin Oncol 26: 5569–5575.
- 51. Voogd AC, Nielsen M, Peterse JL, Blichert-Toft M, Bartelink H, et al. (2001) Differences in risk factors for local and distant recurrence after breast-conserving therapy or mastectomy for stage I and II breast cancer: pooled results of two large European randomized trials. J Clin Oncol 19: 1688–1697.
- 52. Wazer DE, Schmidt-Ullrich RK, Ruthazer R, Schmid CH, Graham R, et al. (1998) Factors determining outcome for breast-conserving irradiation with margin-directed dose escalation to the tumor bed. Int J Radiat Oncol Biol Phys 40: 851–858.
- 53. Yerushalmi R, Woods R, Ravdin PM, Hayes MM, Gelmon KA (2010) Ki67 in breast cancer: prognostic and predictive potential. Lancet Oncol 11: 174–183.