TY - JOUR
T1 - Clinical model to predict survival in chemonaive patients with advanced non-small-cell lung cancer treated with third-generation chemotherapy regimens based on Eastern Cooperative Oncology Group data
AU - Hoang, Tien
AU - Xu, Ronghui
AU - Schiller, Joan H.
AU - Bonomi, Philip
AU - Johnson, David H.
PY - 2005/1/1
Y1 - 2005/1/1
N2 - Purpose: (1) Identify clinical factors that can be used to predict survival in chemotherapy-naive patients with advanced non-small-cell lung cancer (NSCLC) treated with third-generation chemotherapy regimens, and (2) build a clinical model to predict survival in this patient population. Patients and Methods: Using data from two randomized, phase III Eastern Cooperative Oncology Group (ECOG) trials (E5592/E1594), we performed univariate and multivariate stepwise Cox regression analyses to identify survival prognostic factors. We used 75% of randomly sampled data to build a prediction model for survival, and the remaining 25% of data to validate the model. Results: From 1993 to 1999, 1,436 patients with stage IV or IIIB NSCLC with effusion were treated with platinum-based doublets (involving either paclitaxel, docetaxel, or gemcitabine). The response rate and median survival time were 20% and 8.2 months, respectively. One- and 2-year survivals were 33% and 11%, respectively. In multivariate analysis, six independent poor prognostic factors were identified: skin metastasis (hazard ratio [HR], 1.88), lower performance status (ECOG 1 or 2; HR, 1.46), loss of appetite (HR, 1.62), liver metastasis (HR, 1.32), > four metastatic sites (HR, 1.20), and no prior surgery (HR, 1.16). A nomogram using six pretreatment prognostic factors was built to predict 1- and 2-year survival. Conclusion: Six pretreatment factors can be used to predict survival in chemotherapy-naive NSCLC patients treated with standard chemotherapy. Using our prognostic nomogram, 1- and 2-year survival probability of NSCLC patients can be estimated before treatment. This prognostic model may help clinicians and patients in clinical decision making, as well as investigators in research planning.
AB - Purpose: (1) Identify clinical factors that can be used to predict survival in chemotherapy-naive patients with advanced non-small-cell lung cancer (NSCLC) treated with third-generation chemotherapy regimens, and (2) build a clinical model to predict survival in this patient population. Patients and Methods: Using data from two randomized, phase III Eastern Cooperative Oncology Group (ECOG) trials (E5592/E1594), we performed univariate and multivariate stepwise Cox regression analyses to identify survival prognostic factors. We used 75% of randomly sampled data to build a prediction model for survival, and the remaining 25% of data to validate the model. Results: From 1993 to 1999, 1,436 patients with stage IV or IIIB NSCLC with effusion were treated with platinum-based doublets (involving either paclitaxel, docetaxel, or gemcitabine). The response rate and median survival time were 20% and 8.2 months, respectively. One- and 2-year survivals were 33% and 11%, respectively. In multivariate analysis, six independent poor prognostic factors were identified: skin metastasis (hazard ratio [HR], 1.88), lower performance status (ECOG 1 or 2; HR, 1.46), loss of appetite (HR, 1.62), liver metastasis (HR, 1.32), > four metastatic sites (HR, 1.20), and no prior surgery (HR, 1.16). A nomogram using six pretreatment prognostic factors was built to predict 1- and 2-year survival. Conclusion: Six pretreatment factors can be used to predict survival in chemotherapy-naive NSCLC patients treated with standard chemotherapy. Using our prognostic nomogram, 1- and 2-year survival probability of NSCLC patients can be estimated before treatment. This prognostic model may help clinicians and patients in clinical decision making, as well as investigators in research planning.
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U2 - 10.1200/JCO.2005.04.177
DO - 10.1200/JCO.2005.04.177
M3 - Article
C2 - 15625371
AN - SCOPUS:15044352688
SN - 0732-183X
VL - 23
SP - 175
EP - 183
JO - Journal of Clinical Oncology
JF - Journal of Clinical Oncology
IS - 1
ER -