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Neoadjuvant chemotherapy (NACT) outcomes vary according to breast cancer (BC) subtype. Since pathologic complete response is one of the most crucial target endpoints of NACT, further investigation of NACT outcomes in BC is vital. Thus, identifying sensitive and specific predictors of treatment response for each phenotype would enable early detection of chemoresistance and residual disease, decreasing exposures to ineffective therapies and enhancing overall survival rates. In addition, the combination of untargeted‐based metabolomics and longitudinal statistical approaches may represent a handy tool for the improvement of treatment and in administering a more personalized BC follow‐up in clinical practice.
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