Development and validation of a prognostic nomogram in lung cancer with obstructive sleep apnea syndrome

Abstract

Background To analyze the prognostic factors and survival rate of lung cancer patients with OSA by nomogram. Methods We developed and validated a nomogram to help improve prediction of overall survival in Lung cancer patients with OSA. The nomogram was established by a development cohort (n = 90), and the validation cohort included 38 patients. Factors in the nomogram were identified by Cox hazard analysis. We tested the accuracy of the nomograms by discrimination and calibration, and plotted decision curves to assess the benefits of nomogram-assisted decisions. At last we evaluated the risk in the two cohort. Results There were significant difference in sex, AHI, TNM stage, coronary heart disease, LSpO2, T90%, TS90% and ODI4 between lung cancer subgroup and lung cancer with OSA subgroup (P < 0.05). Lung cancer patients with OSA age(P = 0.021), AHI(P = 0.006), TNM stage(P = 0.005), cancer types(P = 0.038), BMI(P = 0.007) and were independent prognostic factor. Based on these six factors, a nomogram model was established. The c-index of internal verification was 0.802 (95% CI 0.767–0.885)。The ROC curve analysis for the nomogram show 1-year survival (AUC = 0.827), 3-year survival (AUC = 0.867), 5-year survival (AUC = 0.801) in the development cohort and 3-year survival(AUC = 0.863) in the validation cohort is with good accuracy. The calibration curve shows that the survival probability of this prediction model is in good agreement with the actual situation at 1, 3 and 5 years with good consistency. decision curve analysis(DCA)suggests that the net benefit of decision-making with this nomogram is higher, especially in the probability interval of < 20% threshold. Conclusions Age, AHI,TNM stage, cancer types, BMI and ODI4 are independent risk factors for prognosis of lung cancer patients with OSAS༌the nomogram can predict the prognosis of patients and guide individualized treatment.