A Survival Analysis Study Of Patients With Locally Advanced Non-small Cell Lung Cancer Based On Pre-and Post-treatment Information

It has been demonstrated^[1]that the higher maximum standardized uptake value（SUVmax）of tumors after patient treatment is associated with poorer survival in patients with locally advanced non-small cell lung cancer and that when the tumor SUVmax takes a binary cutoff value of5.0,it is significantly associated with survival prognosis of patients correlation（p<0.05）.In clinical practice,treated patients do not always undergo repeat PET/CT.Therefore,prediction of post-treatment tumor SUVmax greater than 5.0 based on pre-treatment FDG-PET may be potentially valuable in predicting overall survival in patients with locally advanced non-small cell lung cancer.Since it is difficult to collect post-treatment data,most of the current survival analyses of patients with non-small cell lung cancer are based on some pre-treatment information,and few studies have examined analyses based on both pre-and post-treatment information,this paper further investigates the impact of pre-and post-treatment clinical information on the survival analysis of patients.Therefore,this article predicted whether the tumor post-treatment SUVmax was greater than 5.0 based on the patient’s pre-treatment information,and evaluated its impact on the overall survival of locally advanced non-small cell lung cancer patients.Furthermore,the study investigated the impact of pre-and post-treatment clinical information on patient survival analysis.This study focuses on the survival analysis of locally advanced non-small cell lung cancer patients based on the prediction of post-treatment SUVmax.The study consists of two parts:predicting whether the tumor SUVmax after treatment is greater than 5.0 and survival analysis.First,a 3D convolutional neural network（3D CNN）was used to extract features from the pre-treatment whole-body FDG-PET to predict whether the tumor SUVmax after treatment is greater than 5.0.Second,Cox proportional hazards model^[2]（Cox Model）was used to conduct survival analysis by selecting clinical features with Cox univariate and multivariate analysis and combining them with the predicted results.The results indicate that using pre-treatment FDG-PET images can predict the tumor SUVmax after treatment relatively accurately and improve the accuracy of survival analysis.This study focuses on the survival analysis of locally advanced non-small cell lung cancer patients based on clinical information.The study also consists of two parts:selecting clinical features and predicting patient survival.Cox univariate and multivariate analysis were used to select clinical features,and Cox Model was used to predict patient survival.The results indicate that using both pre-and post-treatment clinical information can accurately predict patient survival time,and the selected clinical features reflect the impact of clinical information on patient survival prognosis.This article predicted the impact of tumor SUVmax after treatment on patient survival analysis and found that the prediction results based on pre-treatment FDG-PET can significantly improve the accuracy of patient survival analysis,which is an important factor in the prognosis of locally advanced non-small cell lung cancer patients and has certain guiding significance for clinical decision-making.The study of patient survival analysis based on pre-and post-treatment clinical features can provide reference for doctors to develop more personalized treatment plans,and deepen the understanding of patients’condition and treatment effectiveness.This research has important clinical significance for improving the survival rate and treatment effectiveness of locally advanced non-small cell lung cancer patients.