Patients with resected non-small cell lung cancer (NSCLC) are at risk for recurrence of disease, but currently there are no tools to predict which patients are at highest risk. The authors set out to create a risk model incorporating both clinical data and biomarkers.
Patients with resected non—small cell lung cancer (NSCLC) are at risk for recurrence of disease, but currently there are no tools to predict which patients are at highest risk. The authors set out to create a risk model incorporating both clinical data and biomarkers.
The scientists assembled a comprehensive database with archival tissues and clinical follow-up from patients with NSCLC resected between 2002 and 2005. Twenty-one proteins identified from preclinical studies as related to lung carcinogenesis were investigated, including pathways related to metabolism, DNA repair, inflammation, and growth factors. Expression of proteins was quantified using immunohistochemistry. Immunohistochemistry was chosen because it is widely available and can be performed on formalin-fixed paraffin-embedded specimens. Cox models were fitted to estimate effects of clinical factors and biomarkers on recurrence-free survival (RFS) and overall survival (OS).
The result was the development of a comprehensive risk model predictive for recurrence in a large retrospective database, which is one of the largest reported series of resected NSCLC.
Read the original paper here:
Source: Clinical Cancer Research
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