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Imaging, Diagnosis, Prognosis |
Authors' Affiliations: 1 Department of Experimental and Diagnostic Medicine, Section of Anatomic Pathology, University of Ferrara, Ferrara, Italy; 2 Unit of Medical Statistics and Biometry, National Cancer Institute of Milano; 3 Institute of Medical Statistics and Biometry, University of Milano, Milan, Italy; and 4 Department of Oncology and Neurosciences and Unit of Cancer Pathology, CeSI, "G. d'Annunzio" Chieti University Foundation, Chieti, Italy
Requests for reprints: Saverio Alberti, Unit of Cancer Pathology, Center of Excellence in Research on Aging, University "G. d' Annunzio," Via Colle dell' Ara, 66013 Chieti Scalo (Chieti), Italy. Phone: 39-0871-541-551; Fax: 39-0871-541-551; E-mail: s.alberti{at}unich.it.
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Abstract |
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 Top Abstract Patients and MethodsResultsDiscussionReferences |
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0.2 mm in diameter [pN0(i+), nanometastases] and analyzed their prognostic effect. Experimental Design: Single-institution, consecutive patients with 8 years of median follow-up (n = 702) were studied. To maximize chances of detecting micrometastases and nanometastases, whole-axilla dissections were analyzed. pN0 cases (n = 377) were systematically reevaluated by lymph node (n = 6676) step-sectioning and anticytokeratin immunohistochemical analysis. The risk of first adverse events and of distant relapse of bona fide pN0 patients was compared with that of pN0(i+), pN1mi, and pN1 cases.
Results: Minimal lymph node deposits were revealed in 13% of pN0 patients. The hazard ratio for all adverse events of pN0(i+) versus pN0(i–) was 2.51 (P = 0.00019). Hazards of pN1mi and pN0(i+) cases were not significantly different. A multivariate Cox model showed a hazard ratio of 2.16 for grouped pN0(i+)/pN1mi versus pN0(i–) (P = 0.0005). Crude cumulative incidence curves for metastatic relapse were also significantly different (Gray's test 
2 = 5.54, P = 0.019).
Conclusion: Nanometastases are a strong risk factor for disease-free survival and for metastatic relapse. These findings support the inclusion of procedures for nanometastasis detection in tumor-node-metastasis staging.
Serial sectioning coupled to immunohistochemical analysis has considerably improved the detection of small tumor cell clusters in lymph nodes (5–10). Occult metastases can indeed be identified in up to 30% of cases previously classified as pN0 (7–9), in 14% to 20% of the cases by single lymph node sections (9, 10). Studies based on these procedures have shown that axillary lymph node microinvasion is a prognostic factor for breast cancer patients, and is associated with poorer disease-free and overall survival (7, 8, 11–13). As a consequence, micrometastases (0.21-2 mm in diameter) have been identified as a relevant risk factor and their detection has been introduced in TNM staging procedures (2003 TNM edition; ref. 1).
Following these guidelines, isolated tumor cells or cell deposits smaller than 0.2 mm are currently required to be classified as pN0(i+) (1). This is because the associated risk is believed to be small or altogether nil. However, little clinical data are available to support this point of view, and the question of the lower size limit of lymph node metastases that may bear clinical significance remains open.
To tackle this issue, we systematically investigated the presence and prognostic effect of tumor cell deposits 0.2 mm in diameter in the axillary lymph nodes of breast cancer patients conventionally classified as pN0. As these tumor deposits are up to six orders of magnitude smaller in volume than micrometastases, we propose to indicate them as "nanometastases."
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Patients and Methods |
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Clinical and pathologic status and follow-up data (radiotherapy, chemotherapy, or hormone therapy; site of relapse; last follow-up time or date/cause of death) were recorded (Tables 1 and 2 ; Supplementary Table S1). Histologic grade was reevaluated on the original pathology slides. Patients (Table 1) were selected according to the following criteria: T1 to T3; availability of at least 10 resected axillary lymph nodes (14); absence of synchronous bilateral tumors and of other malignancies before breast cancer diagnosis and up to 6 months after surgery; absence of distant metastases at diagnosis and up to 6 months after surgery; no neoadjuvant therapy. Three hundred and seventy-seven patients were classified as node negative (pN0) at diagnosis (median follow-up, 9 years), according to European guidelines for mammographic screening (15). The latter recommended the analysis of three macrosections for lymph nodes >5 mm and of two for those <5 mm. pN0 patients were reevaluated for the occurrence of lymph node microinvasion by the procedures outlined below. Patients with one [pN1(1+)] or two to three [pN1(2+3+)] macrometastatic axillary lymph nodes (184 cases; median follow-up, 9 years) were used for comparison of risk estimates with micrometastatic and nanometastatic cases. The protocol of this study was approved by the board of the Ministry of the University and Research ("Identification and validation of new markers of metastasizing phenotype of breast cancer," prot. MM06095812_006, year 2000).
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0.2 mm), pN0(i+); micrometastases (largest diameter 0.21-2 mm), pN1mi. Staining for estrogen receptor was done with the 6F11 mouse monoclonal antibody (Ventana). Staining for Her2/neu was done with the CB11 (Cell Marque, Hot Springs, AR). Statistical analysis. The occurrence of any adverse event over the follow-up period was considered as hard end point and was used to estimate the event-free survival of the patients under study. Cumulative incidence curves for a three-level classification [pN0(i–), pN0(i+), pN1mi] according to the reevaluated lymph node status were estimated by the Kaplan-Meier method. The difference between the hazard of pN0(i+) versus pN0(i–), and of pN1mi versus pN0(i+) was analyzed using a Cox model. The effect of the reevaluated lymph node status was adjusted for established prognostic factors [pathologic T stage (T2-T3 versus T1), grading (G2-G3 versus G1), and age (35 versus 55 years)] by a multivariate Cox model. Age was modeled using a spline function (19). The assumption of proportional hazards was checked using Schoenfeld residuals (20).
Among all adverse events, the occurrence of distant metastases was the end point of main interest. In the analysis of the latter, methodologies that account for the presence of competing risks (i.e., local relapses, contralateral tumors, other neoplasias, or death without evidence of neoplastic disease) were used. The reevaluated lymph node status was considered both in a three-level classification or grouping pN0(i+) and pN1mi cases. Nonparametric estimates of the probability of occurrence of metastases as the first observed event [crude cumulative incidence (CCI)] were obtained (20). CCI curves were compared by the Gray's test (21), which is the equivalent, in the presence of competing risks, to the log-rank test for the comparison of survival curves. A procedure based on the proportional subdistribution hazard regression model was used to assess the difference among CCI curves of pN0(i+) versus pN0(i–), and of pN1mi versus pN0(i+) (22). This model is the natural extension of the Gray's test and can be thought of as the equivalent of the Cox regression model in the presence of competing risks. To quantify the effect of the reevaluated lymph node status adjusted for the established prognostic factors described above, a multiple regression subdistribution hazard model was used. Model estimates of CCI curves for pN0(i+)/pN1mi versus pN0(i–) were plotted for high- and low-risk groups of patients, defined according to the above prognostic factors. Proportional subdistribution hazard assumptions were checked using Schoenfeld-type residuals (22). The risk attributable to "exposure" (23) to micrometastases and nanometastases was estimated for both end points.
CCIs for pN1(1+) and pN1(2+3+) patients were compared with those of pN0(i+)/pN1mi and pN0(i–) cases by plotting nonparametric estimates. SAS system5 and S-plus software were used throughout this study. The Cmprsk library for S-plus6 was applied for competing risk analysis.
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Results |
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TopAbstractPatients and MethodsResultsDiscussionReferences |
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The reinclusion and restaging of 6,676 axillary lymph nodes of the pN0 cases (median, 16.5 per patient) were systematically carried out. Including the H&E analysis at the time of surgery, a total of eight levels per lymph node was analyzed, six of which by both H&E staining and immunohistochemical analysis. On average, 250 lymph node sections were analyzed per patient (by H&E or immunohistochemistry), for a gross total of 90,000 data points. Noteworthy, all micrometastases detected by H&E were also identified by immunohistochemistry, but not vice versa, which is consistent with previous work (7–9). Thus, only immunohistochemical data underwent statistical analysis. After reevaluation, 328 patients (87%) were confirmed to be pN0(i–). Cancer cells were revealed in the axillary lymph nodes of 49 cases (13%). Twenty-four cases (6.4%) were classified as pN0(i+) (nanometastases); 11 of these presented with isolated tumor cells; 13 contained clusters of tumor cells that ranged between 0.036 and 0.2 mm in diameter (median value, 0.14 mm; Supplementary Table S2). Twenty-five cases (6.6%) were classified as pN1mi (micrometastases; diameter range. 0.21-2 mm; Fig. 1).
Cumulative incidence curves for the time to any adverse event are presented in Fig. 2 (left) . Of interest, the estimated cumulative incidence of pN1mi patients is greater than that of pN0(i+) patients until about the first 40 months, whereas, at later times, this effect is lost (see also below). The unadjusted hazard ratio of pN0(i+) versus pN0(i–) for the three-level classification was 2.51 (P = 0.00019; 95% confidence interval, 1.55-4.07). On the other hand, there was no significant difference between the hazard of pN1mi and pN0(i+) (hazard ratio, 0.728; confidence interval, 0.34-1.56; P = 0.41). No significant time-dependent effects were detected. Thus, pN0(i+) and pN1mi cases were grouped for further analyses.
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The distributions of the different causes of failure and of deaths (CCI at 36 and 96 months) and of the therapies administered to the three different patient classes are reported in Table 2. Notably, the estimated CCI of all events for pN0(i–) cases are consistently lower than the estimated CCI for the other two classes. The estimated CCI for all failure causes different from metastases is greater in pN1mi cases with respect to pN0(i+) at early follow-up times. CCI curves of metastatic relapse in pN0(i–), pN0(i+), and pN1mi cases are shown in Supplementary Fig. S1 (left). The difference among CCIs was statistically significant (Gray's test: 2 = 7.90, P = 0.019, degrees of freedom = 2). The percentages of treated pN0(i+) and pN0(i–) patients were fairly close (33% and 27%, respectively). The percentage of treated pN1mi patients (44%) was only slightly greater. Thus, differences in the CCI for pN0(i–) cases with respect to the other two classes are unlikely to have been caused by treatment imbalance.
The unadjusted subdistribution hazard ratio for distant metastases of pN0(i+) versus pN0(i–) for the three-level classification was 3.43 (P = 0.0054; 95% confidence interval, 1.44-8.19). On the other hand, there was no significant difference between the CCIs of pN1mi and pN0(i+) (hazard ratio, 0.40; confidence interval, 0.12-1.82; P = 0.27). The CCI curves for distant metastases in the two-level classification are shown in Supplementary Fig. S1 (right; Gray's test, 2 = 5.54, P = 0.019; degrees of freedom = 1). The presence of micrometastases and nanometastases had a heavy effect on the CCIs for distant metastases (unadjusted hazard ratio, 2.47; confidence interval, 1.16-5.26, P = 0.019; adjusted hazard ratio, 2.10; confidence interval, 0.96-4.58; P = 0.063; Supplementary Table S4). The model estimates of distant metastasis CCIs for patients at high risk (tumor grading G2 or G3, pathologic T2 or T3 stage, 35 years of age) or low risk (tumor grading G1, pathologic T1 stage, 55 years of age) are shown in Fig. 3
. A significant difference in the respective CCI curves was observed in both cases. The estimated risk attributable to exposure over time showed an approximately constant value of 0.52, i.e., 50% of the risk of distant relapse was accounted for by the presence of nanometastases and micrometastases in axillary lymph nodes.
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Discussion |
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TopAbstractPatients and MethodsResultsDiscussionReferences |
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Whole-axilla dissection was privileged in the current study for two major reasons. The first one was the requirement for a long median follow-up time. This was satisfied by the enrollment of patients who underwent surgery between 1989 and 1993, a time where sentinel lymph node analysis had not been introduced yet in clinical practice (26). The second reason was that an analysis of at least 10 lymph nodes per patient was shown to possess the highest sensitivity in the detection of micrometastases (14, 25). The detection of nanometastases was further optimized by using frequent, narrow-sectioning intervals, which were previously shown to provide a 90% to 95% sensitivity (9, 16–18). Several factors are likely to contribute to this accuracy level: Among them are the larger information volume of sections near the equatorial region of a lymph node, a possible preferential regional colonization (27), and the occurrence of multiple micrometastases in a given lymph node.
Our analysis shows a heavy effect of occult metastases on the event-free survival of the bearing patients (unadjusted hazard ratio of 2.51 for pN0(i+) versus pN0(i–), P = 0.00019; multivariate Cox model hazard ratio of 2.16, P = 0.0005). A corresponding effect was shown on metastatic relapse. This unfavorable prognostic value was maintained in multivariate analyses accounting for competing risks and adjusted for grading, pathologic T stage, and age, although the smaller number of events limits the accuracy of the estimate. Notably, occult lymph node metastases were shown to account for 50% of metastatic recurrences in bearing patients. Hence, extremely small lymph node tumor cell clusters, for which we propose the term nanometastases, possess a strong negative prognostic effect on the event-free and relapse-free survival of bearing patients. Thus, we suggest these cases to be upstaged from the pN0(i+) class to a novel pathologic category, for which we propose the name pN1na.
Potential reasons for bias in our findings were investigated. Consistent with previous studies (28), histologic tumor types were found to correlate with the likelihood of macroscopic lymph node metastases. Ductal carcinomas carried a higher risk. On the other hand, lobular carcinomas and better prognosis tumor types (cribriform, medullary, mucinous, and tubular) showed a lower incidence of metastatic lymph nodes (28). Small occult metastases were detected in 13% of the cases, consistently with earlier reports (5, 6, 8–11, 24), and were more frequent in lobular than in ductal carcinomas (Table 1), consistent with previous reports (10, 13). An unbiased case distribution is also supported by corresponding estrogen receptor and Her-2/neu expression profiles in pN0 and pN1 cases, and by the younger age and worse average grading and pathologic T stage of pN1 cases.
Planned therapy essentially coincided with actual therapeutic procedures, and the percentages of treated pN0(i+) and pN0(i–) patients were very similar. Thus, bias due to treatment imbalance seems unlikely. It should also be noted that tamoxifen is expected to reduce the risk of relapse by 35% at 8 years of follow-up (29). Polychemotherapy is correspondingly expected to reduce the risk by 29% to 32% (29). Only a minority of pN0 patients was treated (8% with chemotherapy, 22% with tamoxifen). Hence, a strong effect of therapy on the number of events recorded in this category seems unlikely. Treatment of pN1 patients was much more frequent (80% of the cases) and a correspondingly larger effect is expected. This might have contributed to the flattening of the CCI curves of pN1 patients at long follow-up times, which is consistent with previous observations (7).
In this context, it is interesting to note that the CCI curves for "true" pN0 and pN0(i+) cases clearly diverge at 
36 months after surgery. Although a precise measurement of this effect was beyond the scope of this work, this observation raises several issues. Among them is the intuitive suggestion that distant metastases require time to grow to a detectable size (8). As these would be missed by studies with inadequate follow-up, the need for long observation times in breast cancer studies is emphasized, and the strategy chosen in this study is supported.
The results of this study seem to be important for a better understanding of metastasis development in breast cancer (30, 31). Indeed, the lack of a size threshold for lymph node metastases to bear an increased risk of distant relapse supports a model where microscopic lymph node tumor cell deposits are bona fide metastases at extremely early stages of disease. The constant risk of relapse over time also supports an unvaried metastatic ability over several years of tumor life. These results are consistent with recent comparative genomic hybridization (32) and transcriptomic (33) data. On the other hand, they raise questions on models where the development of metastases depends on the accumulation of successive, stochastic events (31).
In summary, our findings show that nanometastases are a risk factor for breast cancer patients. This supports the conduction of prospective clinical studies on the prognostic effect of occult metastases. These will provide an independent test of our conclusions and may lend decisive support to the inclusion of procedures for nanometastasis detection in TNM pathologic staging. In this context, an efficient compromise between the accurate but labor-intensive systematic detection of micrometastases and nanometastases by immunohistochemistry and reductionist approaches, e.g., sentinel lymph node analysis (25, 34, 35), should be investigated.
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Acknowledgments |
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Footnotes |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).
6 http://biowww.dfci.harvard.edu/~gray/. 
Received 3/ 9/06; revised 7/21/06; accepted 8/28/06.
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