Prognostic models to predict survival in non-small-cell lung cancer patients treated with first-line paclitaxel and carboplatin with or without bevacizumab

Tien Hoang, Suzanne E. Dahlberg, Alan B. Sandler, Julie R. Brahmer, Joan H. Schiller, David H. Johnson

Research output: Contribution to journalArticle

39 Scopus citations

Abstract

BACKGROUND:: To determine prognostic factors and build a model to predict 1-year overall survival (OS) and 6-month progression-free survival (PFS) in advanced non-small-cell lung cancer (NSCLC) patients treated with first-line paclitaxel and carboplatin with or without bevacizumab. MATERIALS AND METHODS:: We analyzed 26 pretreatment clinical variables in 850 NSCLC patients treated in the randomized Eastern Cooperative Oncology Group 4599 study. Univariate and multivariate analyses were performed to identify prognostic factors. Cox regression with 50% randomly sampled data was used to build nomograms with a prognostic score assigned to each factor. The model was validated with the remaining 50% of data. RESULTS:: Eleven poor factors for OS (hazard ratio) were as follows: skin metastasis (4.49), body mass index less than 18.5 (2.09), increased serum lactate dehydrogenase (1.74), adrenal metastasis (1.52), performance status greater than 0 (1.45), low serum albumin (1.45), men (1.39), bone metastasis (1.39), large cell/not otherwise specified histology (1.29), mediastinal nodal metastasis (1.23), and treatment without bevacizumab (1.18). Seven poor factors for PFS were as follows: skin metastasis (3.13), treatment without bevacizumab (1.52), bone metastasis (1.41), liver metastasis (1.40), low serum albumin (1.39), performance status greater than 0 (1.21), and mediastinal nodal metastasis (1.14). Based on these factors, we built and validated two nomograms predicting 1-year OS and 6-month PFS. CONCLUSION:: Using our proposed models, the probability of survival with first-line paclitaxel and carboplatin with or without bevacizumab in nonsquamous NSCLC patients can be estimated. These prognostic models provide a tool for research design and clinical decision making, such as patient stratification and therapy selection.

Original languageEnglish (US)
Pages (from-to)1361-1368
Number of pages8
JournalJournal of Thoracic Oncology
Volume7
Issue number9
DOIs
StatePublished - Sep 2012

Keywords

  • Bevacizumab
  • Chemotherapy
  • Nomograms
  • Non-small-cell lung cancer
  • Prognostic models

ASJC Scopus subject areas

  • Oncology
  • Pulmonary and Respiratory Medicine

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