Download AIMS - BC Total Tumour Load

P 116
Nomogram with total tumoral load as a novel factor to predict
axillary metastasis in breast cancer
1,9
MD *,
1
MD ,
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MD ,
Isabel T Rubio,
Martín Espinosa-Bravo,
Begoña Vieites,
Felip
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Vilardell, MD , José R. Antúnez , MD , Magdalena Sancho de Salas, MD , Julio J.
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Delgado-Sánchez, MD , Willy Pinto, MD , Francisco Gozalbo, MD , V. Peg, MD
1Breast
2Pathology
Cancer Center at Vall d´Hebron University Hospital, Barcelona,
Department Hospital Virgen del Rocío, Sevilla,
3Pathology Department Hospital Arnau de Vilanova, Lérida, 4Pathology Department Complejo Hospitalario Universitario de Santiago de
Compostela, 5Pathology Department Hospital Clínico de Salamanca, 6Pathology Department Hospital 12 de Octubre, Madrid, 7Pathology
Department Hospital Dr. Negrín, Gran Canaria, 8Instituto Valenciano de Oncología, Barcelona, 9SOLTI Breast Cancer Research Group,
Barcelona, Spain.
RESULTS
AIMS
AIMS
AIMS
Several models have been developed to predict non sentinel
node (SLN) metastasis in patients with a positive SLN.
However, the lack of accepted guidelines for SLN analysis
results in a great heterogeneity in disease assessment.
Intraoperative SLN assessed by one step nucleic acid
amplification (OSNA) has been validated as an accurate
method for detection of SLN metastasis compared to
conventional histological examination. It have been reported
that the total tumoral load in the SLNs assessed by OSNA is
a predictive factor for additional non SLN metastasis in the
axillary lymph node dissection (ALND). Based on the data
generated on this multicenter study, we developed a
nomogram that would allow predicting patient´s risk of
additionalnon SLN metastasis including parameters not
previously considered.
On multivariate logistic regression analysis, tumor size,
number of affected SLN, Her2 overexpression, LIV, and
total tumoral load were each associated with the
likelihood of additional non SLN metastasis (p < 0.05). A
nomogram was created with these variables and the
overall predictive accuracy of the nomogram, as
measured by the AUC was 0.7552 (IC95% de 0,7159 a
0.7945). The nomogram was well calibrated with no
evidence of a difference between the predicted and the
observed probabilities (p > 0.999).
METHODS
AIMS
Six hundred and ninety seven consecutive patients with
clinically and ultrasonographically node-negative cT1-3
invasive breast cancer who had undergone intraoperative
SLN evaluation by OSNA were recruited. Pathologic features
of the primary tumor and SLN metastases, including total
tumoral load (TTL) were collected. TTL was defined as the
amount of CK19 mRNA copies (copies/μL) in all positive
SLNs obtained by OSNA, The performance of the model was
evaluated in the training set in terms of discrimination and
calibration.
AIMS
CONCLUSIONS
TTL assessed by OSNA is a new predictive factor of non SLN metastasis in breast cancer patients with positive
SLNs. This novel, accurate, and discriminating nomogram may significantly help clinicians to make decisions about
ALND. Moreover, the standarization of pathologic assessment by OSNA may help to achieve interinstitutional
reproductibility among nomograms.