Elsevier

Journal of Thoracic Oncology

Volume 7, Issue 9, September 2012, Pages 1361-1368
Journal of Thoracic Oncology

Original Article
Prognostic Models to Predict Survival in Non–Small-Cell Lung Cancer Patients Treated with First-Line Paclitaxel and Carboplatin with or without Bevacizumab

https://doi.org/10.1097/JTO.0b013e318260e106Get rights and content
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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.

Key Words

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

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Disclosure: The authors declare no conflict of interest.

This study was coordinated by the Eastern Cooperative Oncology Group (Robert L. Comis, MD, Chair). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Cancer Institute.