BACKGROUND Axillary sentinel lymph node biopsy(SLNB)is standard treatment for patients with clinically and pathological negative lymph nodes.However,the role of completion axillary lymph node dissection(cALND)followin...BACKGROUND Axillary sentinel lymph node biopsy(SLNB)is standard treatment for patients with clinically and pathological negative lymph nodes.However,the role of completion axillary lymph node dissection(cALND)following positive sentinel lymph node biopsy(SLNB)is debated.AIM To identify a subgroup of women with high axillary tumor burden undergoing SLNB in whom cALND can be safely omitted in order to reduce the risk of longterm complications and create a Preoperative Clinical Risk Index(PCRI)that helps us in our clinical practice to optimize the selection of these patients.METHODS Patients with positive SLNB who underwent a cALND were included in this study.Univariate and multivariate analysis of prognostic and predictive factors were used to create a PCRI for safely omitting cALND.RESULTS From May 2007 to April 2014,we performed 1140 SLN biopsies,of which 125 were positive for tumor and justified to practice a posterior cALND.Pathologic findings at SLNB were micrometastases(mic)in 29 cases(23.4%)and macrometastasis(MAC)in 95 cases(76.6%).On univariate analysis of the 95 patients with MAC,statistically significant factors included:age,grade,phenotype,histology,lymphovascular invasion,lymph-node tumor size,and number of positive SLN.On multivariate analysis,only lymph-node tumor size(≤20 mm)and number of positive SLN(>1)retained significance.A numerical tool was created giving each of the parameters a value to predict preoperatively which patients would not benefit from cALND.Patients with a PCRI≤15 has low probability(<10%)of having additional lymph node involvement,a PRCI between 15-17.6 has a probability of 43%,and the probability increases to 69%in patients with a PCRI>17.6.CONCLUSION The PCRI seems to be a useful tool to prospectively estimate the risk of nodal involvement after positive SLN and to identify those patients who could omit cALND.Further prospective studies are necessary to validate PCRI clinical generalization.展开更多
Background:Pathological complete response(pCR)of axillary lymph nodes(ALNs)is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy(NAC),and ALN status is an import...Background:Pathological complete response(pCR)of axillary lymph nodes(ALNs)is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy(NAC),and ALN status is an important prognostic factor for breast cancer patients.This study aims to develop a new predictive clinical model to assess the ALN pCR rate after NAC.Methods:This was a retrospective series of 467 patients who had biopsy-proven positive ALNs at diagnosis and underwent ALN dissection from 2007 to 2014 at the National Cancer Center/Cancer Hospital of the Chinese Academy of Medical Sciences.We analyzed the clinicopathologic features of the patients and developed a nomogram to predict the probability of ALN pCR.A multivariable logistic regression stepwise model was used to construct a nomogram to predict ALN pCR in node-positive patients.The adjusted area under the receiver operating characteristic curve(AUC)was calculated to quantify the ability to rank patients by risk.Internal validation was performed using the 50/50 hold-out validation method.The nomogram was externally validated with prospective cohorts of 167 patients from 2016 to 2018 at the Cancer Hospital of the Chinese Academy of Medical Sciences and 114 patients from 2018 to 2020 at Beijing Tiantan Hospital.Results:In this retrospective study,115(24.6%)patients achieved ALN pCR after NAC.Multivariate analysis showed that clinical tumor stage(Odds ratio[OR]:0.321,95%confidence interval[CI]:0.121-0.856;P=0.023);primary tumor response(OR:0.189;95%CI:0.123-0.292;P<0.001),and estrogen receptor status(OR:0.530,95%CI:0.304-0.925;P=0.025)were independent predictors of ALN pCR.The nomogram was constructed based on the result of multivariate analysis.In the internal validation of performance of nomogram,the AUCs for the training and test sets were 0.719 and 0.753,respectively.The nomogram was validated in external cohorts with AUCs of 0.720,which demonstrated good discriminatory power in these data sets.Conclusion:We developed a nomogram to predict the likelihood of axillary pCR in node-positive breast cancer patients after NAC.The predictive model performed well in multicenter prospective external validation.This practical tool could provide information to surgeons regarding whether to perform additional ALN dissection after NAC.Trial registration:ChiCTR.org.cn,ChiCTR1800014968.展开更多
Memorial Sloan-Kettering Cancer Center (MSKCC) has developed 2 nomograms: the Sentinel Lymph Node Nomogram (SLNN), which is used to predict the likelihood of sentinel lymph node (SLN) metastases in patients with invas...Memorial Sloan-Kettering Cancer Center (MSKCC) has developed 2 nomograms: the Sentinel Lymph Node Nomogram (SLNN), which is used to predict the likelihood of sentinel lymph node (SLN) metastases in patients with invasive breast cancer, and the Non-Sentinel Lymph Node Nomogram (NSLNN), which is used to predict the likelihood of residual axillary disease after a positive SLN biopsy. Our purpose was to compare the accuracy of MSKCC nomogram predictions with those made by breast surgeons. Two questionnaires were built with characteristics of two sets of 33 randomly selected patients from the MSKCC Sentinel Node Database. The first included only patients with invasive breast cancer, and the second included only patients with invasive breast cancer and positive SLN biopsy. 26 randomly selected Brazilian breast surgeons were asked about the probability of each patient in the first set having SLN metastases and each patient in the second set having additional non-SLN metastases. The predictions of the nomograms and breast surgeons were compared. There was no correlation between nomogram risk predictions and breast surgeon risk prediction estimates for either the SLNN or the NSLNN. The area under the receiver operating characteristics curves (AUCs) were 0.871 and 0.657 for SLNN and breast surgeons, respectively (p 0.0001), and 0.889 and 0.575 for the NSLNN and breast surgeons, respectively (p 0.0001). The nomograms were significantly more accurate as prediction tools than the risk predictions of breast surgeons in Brazil. This study demonstrates the potential utility of both nomograms in the decision-making process for patients with invasive breast cancer.展开更多
文摘BACKGROUND Axillary sentinel lymph node biopsy(SLNB)is standard treatment for patients with clinically and pathological negative lymph nodes.However,the role of completion axillary lymph node dissection(cALND)following positive sentinel lymph node biopsy(SLNB)is debated.AIM To identify a subgroup of women with high axillary tumor burden undergoing SLNB in whom cALND can be safely omitted in order to reduce the risk of longterm complications and create a Preoperative Clinical Risk Index(PCRI)that helps us in our clinical practice to optimize the selection of these patients.METHODS Patients with positive SLNB who underwent a cALND were included in this study.Univariate and multivariate analysis of prognostic and predictive factors were used to create a PCRI for safely omitting cALND.RESULTS From May 2007 to April 2014,we performed 1140 SLN biopsies,of which 125 were positive for tumor and justified to practice a posterior cALND.Pathologic findings at SLNB were micrometastases(mic)in 29 cases(23.4%)and macrometastasis(MAC)in 95 cases(76.6%).On univariate analysis of the 95 patients with MAC,statistically significant factors included:age,grade,phenotype,histology,lymphovascular invasion,lymph-node tumor size,and number of positive SLN.On multivariate analysis,only lymph-node tumor size(≤20 mm)and number of positive SLN(>1)retained significance.A numerical tool was created giving each of the parameters a value to predict preoperatively which patients would not benefit from cALND.Patients with a PCRI≤15 has low probability(<10%)of having additional lymph node involvement,a PRCI between 15-17.6 has a probability of 43%,and the probability increases to 69%in patients with a PCRI>17.6.CONCLUSION The PCRI seems to be a useful tool to prospectively estimate the risk of nodal involvement after positive SLN and to identify those patients who could omit cALND.Further prospective studies are necessary to validate PCRI clinical generalization.
基金This research was supported by grants from the National Key Research and Development Program of China(No.2019YFE0110000)the CAMS Innovation Fund for Medical Sciences(CIFMS)(Nos.2016-I2M-1-001,2017-I2M-3-004)+3 种基金the National Natural Science Foundation of China(No.82072097)the Youth Research Fund of Beijing Tiantan Hospital(No.2017-YQN-09)the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences(Nos.2018PT32013,2017PT32001,and 2016ZX310178)the Beijing Hope Run Special Fund of Cancer Foundation of China(No.LC2020A18)。
文摘Background:Pathological complete response(pCR)of axillary lymph nodes(ALNs)is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy(NAC),and ALN status is an important prognostic factor for breast cancer patients.This study aims to develop a new predictive clinical model to assess the ALN pCR rate after NAC.Methods:This was a retrospective series of 467 patients who had biopsy-proven positive ALNs at diagnosis and underwent ALN dissection from 2007 to 2014 at the National Cancer Center/Cancer Hospital of the Chinese Academy of Medical Sciences.We analyzed the clinicopathologic features of the patients and developed a nomogram to predict the probability of ALN pCR.A multivariable logistic regression stepwise model was used to construct a nomogram to predict ALN pCR in node-positive patients.The adjusted area under the receiver operating characteristic curve(AUC)was calculated to quantify the ability to rank patients by risk.Internal validation was performed using the 50/50 hold-out validation method.The nomogram was externally validated with prospective cohorts of 167 patients from 2016 to 2018 at the Cancer Hospital of the Chinese Academy of Medical Sciences and 114 patients from 2018 to 2020 at Beijing Tiantan Hospital.Results:In this retrospective study,115(24.6%)patients achieved ALN pCR after NAC.Multivariate analysis showed that clinical tumor stage(Odds ratio[OR]:0.321,95%confidence interval[CI]:0.121-0.856;P=0.023);primary tumor response(OR:0.189;95%CI:0.123-0.292;P<0.001),and estrogen receptor status(OR:0.530,95%CI:0.304-0.925;P=0.025)were independent predictors of ALN pCR.The nomogram was constructed based on the result of multivariate analysis.In the internal validation of performance of nomogram,the AUCs for the training and test sets were 0.719 and 0.753,respectively.The nomogram was validated in external cohorts with AUCs of 0.720,which demonstrated good discriminatory power in these data sets.Conclusion:We developed a nomogram to predict the likelihood of axillary pCR in node-positive breast cancer patients after NAC.The predictive model performed well in multicenter prospective external validation.This practical tool could provide information to surgeons regarding whether to perform additional ALN dissection after NAC.Trial registration:ChiCTR.org.cn,ChiCTR1800014968.
文摘Memorial Sloan-Kettering Cancer Center (MSKCC) has developed 2 nomograms: the Sentinel Lymph Node Nomogram (SLNN), which is used to predict the likelihood of sentinel lymph node (SLN) metastases in patients with invasive breast cancer, and the Non-Sentinel Lymph Node Nomogram (NSLNN), which is used to predict the likelihood of residual axillary disease after a positive SLN biopsy. Our purpose was to compare the accuracy of MSKCC nomogram predictions with those made by breast surgeons. Two questionnaires were built with characteristics of two sets of 33 randomly selected patients from the MSKCC Sentinel Node Database. The first included only patients with invasive breast cancer, and the second included only patients with invasive breast cancer and positive SLN biopsy. 26 randomly selected Brazilian breast surgeons were asked about the probability of each patient in the first set having SLN metastases and each patient in the second set having additional non-SLN metastases. The predictions of the nomograms and breast surgeons were compared. There was no correlation between nomogram risk predictions and breast surgeon risk prediction estimates for either the SLNN or the NSLNN. The area under the receiver operating characteristics curves (AUCs) were 0.871 and 0.657 for SLNN and breast surgeons, respectively (p 0.0001), and 0.889 and 0.575 for the NSLNN and breast surgeons, respectively (p 0.0001). The nomograms were significantly more accurate as prediction tools than the risk predictions of breast surgeons in Brazil. This study demonstrates the potential utility of both nomograms in the decision-making process for patients with invasive breast cancer.