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https://scidar.kg.ac.rs/handle/123456789/10018
Title: | Neuroendocrine differentiation as an indicator of chemosensitivity and prognosis in nonsmall cell lung cancer |
Authors: | Petrovic, Marina Baskic, Dejan Banković, Dragić Ilić Nevenka |
Issue Date: | 2011 |
Abstract: | Context: Nonsmall cell lung cancers with neuroendocrine differentiation (NSCLC-ND) may demonstrate biologic behavior intermediate between NSCLC and small cell lung cancer (SCLC) with impact on prognosis. Methods: We analyzed 116 consecutive patients with Stage III and IV NSCLC who were diagnosed and treated between 2001 and 2006. Using immuno-histochemical staining for neuron-specific enolase (NSE), chromogranin A (ChrA), and synaptophysin (Syn), 29 (25%) NSCLC-ND were identified. Results: Expression of NSE was present in 22.4%, ChrA in 15.5% and Syn in 14.8% of patients with NSCLC. Therapeutic response was significantly better in the NSCLC-ND group and specimens with > 30% neuroendocrine (NE)-differentiated tumor cells showed favourable therapeutic response (P<0.05). Multivariate binary logistic regression showed that percentage of NE positive tumor cells was a significant independent prognostic factor associated with a favourable outcome. Receiver operating characteristic (ROC) curves and areas under ROC curves confirmed that percentage of NE-differentiated tumor cells could be useful prediction factor of therapeutic response. Moreover, according to percentage of NE-differentiated tumor cells, optimal cutoffs and related sensitivities and specificities were determined for each markers. Conclusion: Advanced-stage NSCLC with NE tumor cells are clinically less aggressive tumors. Percentage of NE-differentiated tumor cells identifies patients with favourable therapy response to paclitaxel-cisplatin © 2011 Informa UK, Ltd. |
URI: | https://scidar.kg.ac.rs/handle/123456789/10018 |
Type: | article |
DOI: | 10.3109/1354750X.2011.560281 |
ISSN: | 1354-750X |
SCOPUS: | 2-s2.0-79957528306 |
Appears in Collections: | Faculty of Medical Sciences, Kragujevac |
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