A predictive index of axillary nodal involvement in operable breast cancer
Open Access
- 1 May 1996
- journal article
- Published by Springer Nature in British Journal of Cancer
- Vol. 73 (10) , 1241-1247
- https://doi.org/10.1038/bjc.1996.238
Abstract
We investigated the association between pathological characteristics of primary breast cancer and degree of axillary nodal involvement and obtained a predictive index of the latter from the former. In 2076 cases, 17 histological features, including primary tumour and local invasion variables, were recorded. The whole sample was randomly split in a training (75% of cases) and a test sample. Simple and multiple correspondence analysis were used to select the variables to enter in a multinomial logit model to build an index predictive of the degree of nodal involvement. The response variable was axillary nodal status coded in four classes (N0, N1-3, N4-9, N > or = 10). The predictive index was then evaluated by testing goodness-of-fit and classification accuracy. Covariates significantly associated with nodal status were tumour size (P < 0.0001), tumour type (P < 0.0001), type of border (P = 0.048), multicentricity (P = 0.003), invasion of lymphatic and blood vessels (P < 0.0001) and nipple invasion (P = 0.006). Goodness-of-fit was validated by high concordance between observed and expected number of cases in each decile of predicted probability in both training and test samples. Classification accuracy analysis showed that true node-positive cases were well recognised (84.5%), but there was no clear distinction among the classes of node-positive cases. However, 10 year survival analysis showed a superimposible prognostic behaviour between predicted and observed nodal classes. Moreover, misclassified node-negative patients (i.e. those who are predicted positive) showed an outcome closer to patients with 1-3 metastatic nodes than to node-negative ones. In conclusion, the index cannot completely substitute for axillary node information, but it is a predictor of prognosis as accurate as nodal involvement and identifies a subgroup of node-negative patients with unfavourable prognosis.Keywords
This publication has 48 references indexed in Scilit:
- A technique for using neural network analysis to perform survival analysis of censored dataCancer Letters, 1994
- The need to reexamine axillary lymph node dissection in invasive breast cancerCancer, 1994
- Axillary surgery in breast cancer: What debate?European Journal Of Cancer, 1993
- Axillary surgery in breast cancer—there still is a debateEuropean Journal Of Cancer, 1993
- A practical application of neural network analysis for predicting outcome of individual breast cancer patientsBreast Cancer Research and Treatment, 1992
- Axillary surgery in breast cancer—Is there still a debate?European Journal Of Cancer, 1992
- Role and extent of lymphadenectomy for early breast cancerSeminars in Surgical Oncology, 1992
- A demonstration that breast cancer recurrence can be predicted by Neural Network analysisBreast Cancer Research and Treatment, 1992
- Axillary dissection of level I and II lymph nodes is important in breast cancer classificationEuropean Journal Of Cancer, 1992
- Ten-Year Results of a Randomized Clinical Trial Comparing Radical Mastectomy and Total Mastectomy with or without RadiationNew England Journal of Medicine, 1985