The preoperative platelet distribution width: A predictive factor of the prognosis in patients with non‐small cell lung cancer

• Main Authors: Chang Liu, Hua Zhang, Qi Qi, Bin Zhang, Dongsheng Yue, Changli Wang
• Format: Article
• Language: English
• Published: Wiley 2020-04-01
• Series: Thoracic Cancer
• Subjects: Non‐small cell lung cancer; platelet distribution width; prognosis
• Online Access: https://doi.org/10.1111/1759-7714.13340

Abstract Background The prognostic value of platelet distribution width (PDW) is different in various malignancies. The purpose of this study was to identify the relationship between preoperative PDW and survival in patients with non‐small cell lung cancer (NSCLC). Methods Optimal cutoff values of PDW were confirmed using a receiver operating characteristic (ROC) curve. The Kaplan‐Meier method and log‐rank test were used to estimate disease‐free survival (DFS) and overall survival (OS). Univariate and multivariate Cox regression models were used for prognostic analysis. The likelihood ratio test (LRT) and Akaike information criterion (AIC) were used to compare two models of the TNM staging system and the PDW‐TNM staging system (combination of PDW and the TNM staging system). Results Survival analysis indicated that the disease‐free survival (DFS) and overall survival (OS) of patients with PDW > 12.65 were both significantly longer than those of patients with PDW ≤ 12.65. Multivariate analysis showed that PDW was an independent prognostic factor for DFS and OS. After the two prediction models were established, further LRT analysis showed that the PDW‐TNM model had a better ability to assess patient prognosis. Conclusions PDW might act as an independent risk factor to predict progression and prognosis. Preoperative PDW combined with the TNM staging system showed a better ability to assess the prognosis of NSCLC patients. Key points Our study focused on the prognostic value of preoperative PDW in 750 patients with NSCLC. We also analyzed preoperative PDW in different stages and histological subtypes systematically. A model built by preoperative PDW combined with the TNM staging system had a better prognostic ability. LRT was used to calculate values of the goodness of fit between the model and the TNM staging system.