Development of a Prognostic Prediction Model for Non-Smoking Lung Adenocarcinoma Based on Pathological Information and Laboratory Hematologic Indicators: A Multicenter Study

Run Xiang ^1,2 Peihong Hu ¹ Xiaoxiong Xiao ³ Wen Li ⁴ Xiaoqing Liao ⁵ Jun Li ⁶ WEN ZHU ² Xiaoqin Liu ^1* Qiang Li ^1*

• ¹ Department of Thoracic Surgery, Sichuan Cancer Hospital, Chengdu, China
• ² State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
• ³ Department of Thoracic Surgery, Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
• ⁴ Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
• ⁵ Department of Thoracic Surgery, Dazhu County People's Hospital, Dazhou, China
• ⁶ Department of Thoracic Surgery, Ziyang Yanjiang People’s Hospital, Ziyang, China

Objective: To develop a simple and practical model to predict the prognostic survival of non-smoking patients with lung adenocarcinoma by combining general pathological information with laboratory hematologic indicators. Methods: Cox univariate and multivariate analyses were used to identify the variable indicators. A Cox proportional hazards model was constructed based on the selected variables to compare survival outcomes between the high-and low-risk groups of non-smoking patients with lung adenocarcinoma and to validate the model's performance. Subsequently, a nomogram model was established to systematically evaluate the impact of selected variables on prognosis. Results: Data of non-smoking patients with lung adenocarcinoma from four hospitals were retrospectively collected. We enrolled 1,172 patients, this includes 372 external validation data. Multivariate analysis identified six significant variables (P < 0.05): tumor TNM stage, tumor size, white blood cell count, neutrophil percentage, lymphocyte percentage, and hemoglobin level. We combined these six variables to build a model. The C-index of the training set is 0.811 (0.780-0.842), this value is 0.786 (0.737-0.835) in,test set and 0.810 (0.772-0.847) in validation set. The area under the curve (AUC) results of the predicted 3-years overall survival (OS) of the three data sets were 0.850, 0.819, and 0.860, respectively. These values for 5-years were 0.811, 0.771, and 0.849. Stratified analysis based on tumor staging showed that the model effectively distinguished outcomes (P < 0.0001). High-risk groups demonstrated significantly poorer prognosis compared to low-risk groups (P < 0.001).The prognostic model based on tumor TNM stage, tumor size, white blood cell count, neutrophil percentage, lymphocyte percentage, and hemoglobin levels effectively predicted the prognosis of non-smoking patients with lung adenocarcinoma. Compared with the more studied blood markers at present, the indicators of our model do not need conversion, Our model provides a useful reference for personalized diagnosis and treatment in clinical practice.