P2.03a-033 Prediction of Response to First Line Treatment for Metastatic Non-Small Cell Lung Cancer: Topic: Clinical Trials

Abstract

Non-small cell lung cancer (NSCLC) is a worldwide problem and usually presents at an advanced stage. Despite widespread availability of multiple chemotherapies for stage IV NSCLC, response rates are generally low. We tried to identify pretreatment factors that may predict response to treatment, particularly relevant in countries with limited laboratory and imaging facilities and drug availability. we conducted a retrospective analysis of patients with stage IV NSCLC receiving systemic treatment from 2002 to 2012 at the University of Alabama at Birmingham (UAB), which is a NCCN member institute. Pretreatment risk factors including age, race, gender, presenting symptoms, and laboratory values, were evaluated. Patients who originally received adjuvant therapy and no further treatment upon recurrence and those receiving first line treatment on a clinical trial with no further therapy were excluded. 409 patients received more than 10 different regimens as first line treatment in metastatic non-small-cell lung cancer. The most commonly used regimens were paclitaxel and carboplatin with or without bevacizumab; Carboplatin and pemetrexed with or without bevacizumab; pemetrexed single agent; Carboplatin and Gemcitabine; and a tyrosine kinase inhibitor. 76.4%of patients had a performance status of 0-1 and 21.6% of them has a performance status of 2. More than 50 pretreatment factors were analyzed, of which smoking (p = 0.049), pleural metastases or effusion (p = 0.004), abdominal metastases (p = 0.033), hypoalbuminemia (p = 0.043) and hyponatremia (p = 0.002) are associated with poor responses to treatment. Smoking status, presence or absence of pleural metastases or effusion, abdominal metastases, presence of hypoalbuminemia or hyponatremia can help identify patients who are less likely to respond to treatment. We are developing a mathematical model incorporating these factors. This may help in the selection of patients for systemic therapy and may improve stratification in clinical trials.