A nomogram for predicting survival outcomes in locally advanced breast cancer

Author: 
Jignasa Sathwara., Saurabh Bobdey and Ganesh Balasubramaniam

Background: To construct and validate a nomogram to predict overall survival of patients with locally advanced breast cancer (LABC) using parameters that are measured during routine clinical management.
Patients and methods: Data from 531 patients treated for LABC at a single institution Tata Memorial Hospital, Mumbai from Jan 2008 to Dec 2008 were analyzed. The eligible patients were randomized 4:1 and divided into a training set (nomogram construction) and a validation set (nomogram validation). We used bootstrap resampling for the internal validation and we tested the nomogram on an independent validation set of patients for the external validation.
Results: The nomogram were based on a Cox proportional hazards regression model. Covariates for the overall survival model included tumor grade, molecular subtype, presence of lymphovascular invasion, presence of extensive intraductal component and pathological lymph nodal status. The nomogram was found to have a c-index of 0.7196 for predicting the five year OS. The calibration curve suggested that the model was well calibrated for all predictors. The nomogram for LABC based on these variables had good discrimination in training as well in validation set (AUC, 0.743 and 0.753).
Conclusion: A nomogram based on parameters that are measured on a routine basis was developed. The nomogram can be used to predict five-year OS with reasonable accuracy. This information will be useful for estimating prognosis and in guiding treatment selection

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DOI: 
DOI: http://dx.doi.org/10.24327/ijcar.2017.4203.0462
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