Literature DB >> 19177485

Prognostic model to predict outcomes in nonsmall cell lung cancer patients treated with gefitinib as a salvage treatment.

Min Jae Park1, Min Jae Park1, Jeeyun Lee, Jung Yong Hong, Moon Ki Choi, Joon Ho Yi, Su Jin Lee, Suk Joong Oh, Jin Seok Ahn, Keunchil Park, Myung Ju Ahn.   

Abstract

BACKGROUND: A prognostic model based on clinical parameters for nonsmall cell lung cancer (NSCLC) patients treated with gefitinib (250 mg/day) as a salvage therapy was devised.
METHODS: Clinical data regarding a total of 316 metastatic or recurrent NSCLC patients who were treated with gefitinib were analyzed.
RESULTS: Poor prognostic factors for overall survival (OS) by multivariate analysis were an Eastern Cooperative Oncology Group (ECOG) performance status of 2 to 3 (hazards ratio [HR] of 2.07; 95% confidence interval [CI], 1.57-2.73 [P < .001]), the presence of intra-abdominal metastasis (HR of 1.76; 95% CI, 1.33-2.34 [P < .001]), elevated serum alkaline phosphatase (HR of 1.50; 95% CI, 1.13-2.00 [P = .005]), time interval from diagnosis to gefitinib therapy of < or =12 months (HR of 1.48; 95% CI, 1.12-1.95 [P = .005]), low serum albumin (HR of 1.45; 95% CI, 1.09-1.92 [P = .009]), progression-free interval for previous chemotherapy of < or =12 weeks (HR of 1.40; 95% CI, 1.0-1.84 [P = .015]), white blood cell > 10,000/microL (HR of 1.38; 95% CI, 1.02-1.85 [P = .032]), and ever-smoker (HR of 1.33; 95% CI, 1.02-1.75 [P = .033]). Of the 272 patients applicable to this prognostic model, 41 patients (15%) were categorized as a good prognosis group (0-1 risk factors), 100 patients (37%) as an intermediate prognosis group (2-3 risk factors), 81 patients (30%) as a poor prognosis group (4-5 risk factors), and 50 patients (16%) as a very poor prognosis group (> or = 6 risk factors). The median OS from the time of gefitinib treatment for the good, intermediate, poor, and very poor prognosis groups were 18.0 months, 11.2 months, 4.0 months, and 1.3 months, respectively (P < .001).
CONCLUSIONS: This prognostic model based on easily available clinical variables would be useful to identify patients who might derive more benefit from gefitinib treatment and to make decisions in clinical practice. (c) 2009 American Cancer Society

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Year:  2009        PMID: 19177485     DOI: 10.1002/cncr.24151

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


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