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Neoadjuvant chemotherapy has been used for breast cancer aiming atdowngrading before surgery. In this article we propose a new quantitativeanalysis of the effects of the neoadjuvant therapy to obtain numerical,personalized, predictions on the shrinkage of the tumor size after the drugdoses, by data assimilation of the individual patient. The algorithm has beenvalidated by a sample of 37 patients with histological diagnosis of locallyadvanced primary breast carcinoma. The biopsy specimen, the initial tumor sizeand its reduction after each treatment were known for all patients. We findthat: a) the measure of tumor size at the diagnosis and after the first dosepermits to predict the size reduction for the follow up; b) the results are inagreement with our data sample, within 10-20 %, for about 90% of the patients.The quantitative indications suggest the best time for surgery. The analysis ispatient oriented, weakly model dependent and can be applied to other cancerphenotypes.

Quantitative predictions of neoadjuvant chemotherapy effects in breast cancer by individual patient data assimililation