International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer

Tuomo J Meretoja; Marjut H K Leidenius; Päivi S Heikkilä; Gabor Boross; István Sejben; Peter Regitnig; Gero Luschin-Ebengreuth; Janez Zgajnar; Andraz Perhavec; Barbara Gazic; György Lázár; Tibor Takács; Andras Vörös; Zuhair A Saidan; Rana M Nadeem; Isabella Castellano; Anna Sapino; Simonetta Bianchi; Vania Vezzosi; Emmanuel Barranger; Ruben Lousquy; Riccardo Arisio; Maria Pia Foschini; Shigeru Imoto; Hiroshi Kamma; Tove F Tvedskov; Niels Kroman; Maj-Brit Jensen; Riccardo A Audisio; Gabor Cserni

doi:10.1093/jnci/djs455

International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer

Tuomo J Meretoja, Marjut H K Leidenius, Päivi S Heikkilä, Gabor Boross, István Sejben, Peter Regitnig, Gero Luschin-Ebengreuth, Janez Zgajnar, Andraz Perhavec, Barbara Gazic, György Lázár, Tibor Takács, Andras Vörös, Zuhair A Saidan, Rana M Nadeem, Isabella Castellano, Anna Sapino, Simonetta Bianchi, Vania Vezzosi, Emmanuel BarrangerRuben Lousquy, Riccardo Arisio, Maria Pia Foschini, Shigeru Imoto, Hiroshi Kamma, Tove F Tvedskov, Niels Kroman, Maj-Brit Jensen, Riccardo A Audisio, Gabor Cserni

56 Citations (Scopus)

Abstract

Background Axillary treatment of breast cancer patients is undergoing a paradigm shift, as completion axillary lymph node dissections (ALNDs) are being questioned in the treatment of patients with tumor-positive sentinel nodes. This study aims to develop a novel multi-institutional predictive tool to calculate patient-specific risk of residual axillary disease after tumor-positive sentinel node biopsy. Methods Breast cancer patients with a tumor-positive sentinel node and a completion ALND from five European centers formed the original patient series (N = 1000). Statistically significant variables predicting nonsentinel node involvement were identified in logistic regression analysis. A multivariable predictive model was developed and validated by area under the receiver operating characteristics curve (AUC), first internally in 500 additional patients and then externally in 1068 patients from other centers. All statistical tests were two-sided. Results Nine tumor- and sentinel node-specific variables were identified as statistically significant factors predicting nonsentinel node involvement in logistic regression analysis. A resulting predictive model applied to the internal validation series resulted in an AUC of 0.714 (95% confidence interval [CI] = 0.665 to 0.763). For the external validation series, the AUC was 0.719 (95% CI = 0.689 to 0.750). The model was well calibrated in the external validation series. Conclusions We present a novel, international, multicenter, predictive tool to assess the risk of additional axillary metastases after tumor-positive sentinel node biopsy in breast cancer. The predictive model performed well in internal and external validation but needs to be further studied in each center before application to clinical use.

Original language	English
Journal	National Cancer Institute. Journal (Print)
Volume	104
Issue number	24
Pages (from-to)	1888-96
Number of pages	9
ISSN	0027-8874
DOIs	https://doi.org/10.1093/jnci/djs455
Publication status	Published - 19 Dec 2012

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10.1093/jnci/djs455

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Meretoja, T. J., Leidenius, M. H. K., Heikkilä, P. S., Boross, G., Sejben, I., Regitnig, P., Luschin-Ebengreuth, G., Zgajnar, J., Perhavec, A., Gazic, B., Lázár, G., Takács, T., Vörös, A., Saidan, Z. A., Nadeem, R. M., Castellano, I., Sapino, A., Bianchi, S., Vezzosi, V., ... Cserni, G. (2012). International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer. National Cancer Institute. Journal (Print), 104(24), 1888-96. https://doi.org/10.1093/jnci/djs455

Meretoja, TJ, Leidenius, MHK, Heikkilä, PS, Boross, G, Sejben, I, Regitnig, P, Luschin-Ebengreuth, G, Zgajnar, J, Perhavec, A, Gazic, B, Lázár, G, Takács, T, Vörös, A, Saidan, ZA, Nadeem, RM, Castellano, I, Sapino, A, Bianchi, S, Vezzosi, V, Barranger, E, Lousquy, R, Arisio, R, Foschini, MP, Imoto, S, Kamma, H, Tvedskov, TF, Kroman, N, Jensen, M-B, Audisio, RA & Cserni, G 2012, 'International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer', National Cancer Institute. Journal (Print), vol. 104, no. 24, pp. 1888-96. https://doi.org/10.1093/jnci/djs455

@article{edf30c19e07c4b2baba1b833ff8e900a,

title = "International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer",

abstract = "Background Axillary treatment of breast cancer patients is undergoing a paradigm shift, as completion axillary lymph node dissections (ALNDs) are being questioned in the treatment of patients with tumor-positive sentinel nodes. This study aims to develop a novel multi-institutional predictive tool to calculate patient-specific risk of residual axillary disease after tumor-positive sentinel node biopsy. Methods Breast cancer patients with a tumor-positive sentinel node and a completion ALND from five European centers formed the original patient series (N = 1000). Statistically significant variables predicting nonsentinel node involvement were identified in logistic regression analysis. A multivariable predictive model was developed and validated by area under the receiver operating characteristics curve (AUC), first internally in 500 additional patients and then externally in 1068 patients from other centers. All statistical tests were two-sided. Results Nine tumor- and sentinel node-specific variables were identified as statistically significant factors predicting nonsentinel node involvement in logistic regression analysis. A resulting predictive model applied to the internal validation series resulted in an AUC of 0.714 (95% confidence interval [CI] = 0.665 to 0.763). For the external validation series, the AUC was 0.719 (95% CI = 0.689 to 0.750). The model was well calibrated in the external validation series. Conclusions We present a novel, international, multicenter, predictive tool to assess the risk of additional axillary metastases after tumor-positive sentinel node biopsy in breast cancer. The predictive model performed well in internal and external validation but needs to be further studied in each center before application to clinical use.",

author = "Meretoja, {Tuomo J} and Leidenius, {Marjut H K} and Heikkil{\"a}, {P{\"a}ivi S} and Gabor Boross and Istv{\'a}n Sejben and Peter Regitnig and Gero Luschin-Ebengreuth and Janez Zgajnar and Andraz Perhavec and Barbara Gazic and Gy{\"o}rgy L{\'a}z{\'a}r and Tibor Tak{\'a}cs and Andras V{\"o}r{\"o}s and Saidan, {Zuhair A} and Nadeem, {Rana M} and Isabella Castellano and Anna Sapino and Simonetta Bianchi and Vania Vezzosi and Emmanuel Barranger and Ruben Lousquy and Riccardo Arisio and Foschini, {Maria Pia} and Shigeru Imoto and Hiroshi Kamma and Tvedskov, {Tove F} and Niels Kroman and Maj-Brit Jensen and Audisio, {Riccardo A} and Gabor Cserni",

year = "2012",

month = dec,

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doi = "10.1093/jnci/djs455",

language = "English",

volume = "104",

pages = "1888--96",

journal = "National Cancer Institute. Journal (Print)",

issn = "0027-8874",

publisher = "Oxford University Press",

number = "24",

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TY - JOUR

T1 - International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer

AU - Meretoja, Tuomo J

AU - Leidenius, Marjut H K

AU - Heikkilä, Päivi S

AU - Boross, Gabor

AU - Sejben, István

AU - Regitnig, Peter

AU - Luschin-Ebengreuth, Gero

AU - Zgajnar, Janez

AU - Perhavec, Andraz

AU - Gazic, Barbara

AU - Lázár, György

AU - Takács, Tibor

AU - Vörös, Andras

AU - Saidan, Zuhair A

AU - Nadeem, Rana M

AU - Castellano, Isabella

AU - Sapino, Anna

AU - Bianchi, Simonetta

AU - Vezzosi, Vania

AU - Barranger, Emmanuel

AU - Lousquy, Ruben

AU - Arisio, Riccardo

AU - Foschini, Maria Pia

AU - Imoto, Shigeru

AU - Kamma, Hiroshi

AU - Tvedskov, Tove F

AU - Kroman, Niels

AU - Jensen, Maj-Brit

AU - Audisio, Riccardo A

AU - Cserni, Gabor

PY - 2012/12/19

Y1 - 2012/12/19

N2 - Background Axillary treatment of breast cancer patients is undergoing a paradigm shift, as completion axillary lymph node dissections (ALNDs) are being questioned in the treatment of patients with tumor-positive sentinel nodes. This study aims to develop a novel multi-institutional predictive tool to calculate patient-specific risk of residual axillary disease after tumor-positive sentinel node biopsy. Methods Breast cancer patients with a tumor-positive sentinel node and a completion ALND from five European centers formed the original patient series (N = 1000). Statistically significant variables predicting nonsentinel node involvement were identified in logistic regression analysis. A multivariable predictive model was developed and validated by area under the receiver operating characteristics curve (AUC), first internally in 500 additional patients and then externally in 1068 patients from other centers. All statistical tests were two-sided. Results Nine tumor- and sentinel node-specific variables were identified as statistically significant factors predicting nonsentinel node involvement in logistic regression analysis. A resulting predictive model applied to the internal validation series resulted in an AUC of 0.714 (95% confidence interval [CI] = 0.665 to 0.763). For the external validation series, the AUC was 0.719 (95% CI = 0.689 to 0.750). The model was well calibrated in the external validation series. Conclusions We present a novel, international, multicenter, predictive tool to assess the risk of additional axillary metastases after tumor-positive sentinel node biopsy in breast cancer. The predictive model performed well in internal and external validation but needs to be further studied in each center before application to clinical use.

AB - Background Axillary treatment of breast cancer patients is undergoing a paradigm shift, as completion axillary lymph node dissections (ALNDs) are being questioned in the treatment of patients with tumor-positive sentinel nodes. This study aims to develop a novel multi-institutional predictive tool to calculate patient-specific risk of residual axillary disease after tumor-positive sentinel node biopsy. Methods Breast cancer patients with a tumor-positive sentinel node and a completion ALND from five European centers formed the original patient series (N = 1000). Statistically significant variables predicting nonsentinel node involvement were identified in logistic regression analysis. A multivariable predictive model was developed and validated by area under the receiver operating characteristics curve (AUC), first internally in 500 additional patients and then externally in 1068 patients from other centers. All statistical tests were two-sided. Results Nine tumor- and sentinel node-specific variables were identified as statistically significant factors predicting nonsentinel node involvement in logistic regression analysis. A resulting predictive model applied to the internal validation series resulted in an AUC of 0.714 (95% confidence interval [CI] = 0.665 to 0.763). For the external validation series, the AUC was 0.719 (95% CI = 0.689 to 0.750). The model was well calibrated in the external validation series. Conclusions We present a novel, international, multicenter, predictive tool to assess the risk of additional axillary metastases after tumor-positive sentinel node biopsy in breast cancer. The predictive model performed well in internal and external validation but needs to be further studied in each center before application to clinical use.

U2 - 10.1093/jnci/djs455

DO - 10.1093/jnci/djs455

M3 - Journal article

C2 - 23117131

SN - 0027-8874

VL - 104

SP - 1888

EP - 1896

JO - National Cancer Institute. Journal (Print)

JF - National Cancer Institute. Journal (Print)

IS - 24

ER -

International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer

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