Modeling the overall survival of patients with advanced-stage non-small cell lung cancer using data of routine laboratory tests

Abstract

Cancer patients undergo routine clinical monitoring with an array of blood tests that may carry long-term prognostic information. We aimed to develop a new prognostic model predicting survival for patients with advanced non-small cell lung cancer (NSCLC), based on laboratory tests commonly performed in clinical practice. A cohort of 1,161 stage IIIB or IV NSCLC patients was divided into training (n 5 773) and testing (n 5 388) cohorts. We analyzed the associations of 32 commonly tested laboratory variables with patient survival in the training cohort. We developed a model based on those significant laboratory variables, together with important clinical variables. The model was then evaluated in the testing cohort. Five variables, including albumin, total protein, alkaline phosphatase, blood urea nitrogen and international normalized ratio, were significantly associated with patient survival after stepwise selection. A model incorporating these variables classified patients into low-, medium-and high-risk groups with median survival of 16.9, 7.2 and 2.1 months, respectively (p < 0.0001). Compared with low-risk group, patients in the medium-and high-risk groups had a significantly higher risk of death at 1 year, with hazard ratio (HR) of 1.95 (95% CI 1.62-2.36) and 5.22 (4.30-6.34), respectively. These results were validated in the testing cohort. Overall, we developed a prognostic model relying entirely on readily available variables, with similar predictive power to those which depend on more specialized and expensive molecular assays. Further study is necessary to validate and further refine this model, and compare its performance to models based on more specialized and expensive testing.Lung cancer is the third most common malignancy in the United States, after prostate cancer in men and breast cancer in women.1 Lung cancer is the deadliest form of cancer in both men and women, accounting for more deaths than the other three most common cancers (breast, prostate and colon) combined.1,2 Non-small cell lung cancer (NSCLC) represents about 80% of all lung cancer cases. Expected 1-year survival for patients with NSCLC is low, partly because the majority of patients are diagnosed at advanced stages for which curative treatments are not feasible options.3 Despite the overall grim prognosis, advanced NSCLC patients can be stratified into sub-groups with relatively better or worse prognosis. A statistical model incorporating such prognostic information would allow physicians to set realistic expectations for survival time and guide end-of-life decision making, even if such information would not alter decision-making regarding specific therapeutic interventions.Physicians mostly rely on a set of basic demographic features (e.g., age, gender and ethnicity), histopathological information (e.g., tumor stage and grade) and other clinical information (e.g., tobacco use, alcohol use and performance status) to make therapeutic decisions and prognostic projections. [4][5][6][7] Several recent studies incorporated various genet...

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