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Three models were suggested to predict response values based on the mentioned variables.
Many imaging modalities have been suggested to predict response to neoadjuvant chemotherapy and oncological outcomes.
Although skin rash has been suggested to predict response to gefitinib, available data do not support this hypothesis.
Likewise, skin rash has been suggested to predict response to gefitinib as we have shown in our multivariate analysis; however, available data do not definitively support this hypothesis (van Zandwijk, 2003).
Other factors such as, EGFR amplification [ 9- 11], epiregulin and amphiregulin expression [ 12], nuclear factor-kB tumor expression [ 13], PTEN [ 14], BRAF [ 15] or PIK3CA [ 16] were also suggested to predict response to cetuximab but these additional biomarkers require further validation before incorporation into clinical practice.
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We sought mutations in the EGFR gene in TNBCs, because EGFR mutations were found in a subset of Japanese non-small lung cancers, despite being very rare in Caucasians [ 23], and because these mutations were suggested to predict responses to gefitinib therapy [ 23, 24].
Anthropometric measures at initiation of therapy have been suggested to predict positive response to rGH; namely lower baseline height and higher BMI [ 32].
This signature was assessed in a series of 167 patients with tumours >5 cm or clinically positive nodes and has also been suggested to predict the response to neoadjuvant CT [112].
In this fashion, the capacity of the TOP2A index to predict response to docetaxel would suggest that the predictive capacity of the TOP2A index is not target specific and may measure a more general phenomenom related to chemotherapy sensitivity, such as proliferation.
These data suggested that combined evaluation of other gene expressions is needed to predict response more accurately.
Preliminary studies suggested that the determination of p53 status and angiogenesis may be useful to predict response to chemotherapy.
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