Nomogram prediction of overall survival for patients with non-small-cell lung cancer incorporating pretreatment peripheral blood markers. (27th December 2017) - Xie, Dong; Allen, Mark S; Marks, Randolph; Jiang, Gening; Sun, Zhifu; Nichols, Frances; Zhang, Mingrui; Chen, Chang; Aubry, Marie-Christine; Jatoi, Aminah; Garces, Yolanda I; Mansfield, Aaron; et al.
Abstract: OBJECTIVES: The objective of this study is to build a novel prognostic nomogram in non-small-cell lung cancer (NSCLC) incorporating pre-treatment peripheral blood markers beyond known pathoclinical predictors. METHODS: We analysed 7158 patients with NSCLC diagnosed between 1 January 1997 and 31 December 2012 from a single institution with a uniform medical record and routine follow-up information. Besides common clinicopathological factors, we investigated the prognostic value of the neutrophil to lymphocyte ratio, monocytes and haemoglobin level in peripheral blood before treatment. Patients were randomly assigned to training (4772 patients, 66.7%) or validation cohorts (2386 patients, 33.3%). Cox proportional hazards models determined the effects of multiple factors on overall survival (OS). A nomogram was developed to predict median survival and 1-, 3-, 5- and 10-year OS for NSCLC. The performance of the nomogram was assessed by a concordance index and calibration curve. RESULTS: In the training cohort, the multivariate Cox model identified the neutrophil to lymphocyte ratio, monocytes and haemoglobin level before treatment as significant prognostic factors for OS independent of patient age, gender, smoking history of intensity and cessation, performance status, disease stage, tumour cell type and differentiation grade and therapies. All the significant prognostic variables were incorporated into a nomogram. In the validation cohort, the nomogram showed notable accuracy in predicting OS, with a concordance index of 0.81, and was well calibrated for predictions of OS. CONCLUSIONS: The proposed nomogram incorporating peripheral blood markers and known prognostic factors could accurately predict individualized survival probability of patients with NSCLC. It could be used in treatment planning and stratification in clinical trials.