Construction and internal verification of prediction model for patients with lung cancer complicated with pulmonary embolism
Objective To investigate the influencing factors of patients with lung cancer complicated with pulmonary embolism(PE)and the con-struction of clinical prediction model.Methods A total of 150 patients with lung cancer complicated with PE from the Affiliated Tumor Hospital of Xinjiang Medical University from January 2016 to December 2021 was selected as PE group,and 600 patients with lung cancer were matched as control group at the same time.General data and clinical data of two groups were collected,the influencing factors of patients with lung cancer com-plicated with PE were analyzed,a nomogram model was constructed,and the model was evaluated by receiver operating characteristic curve,cali-bration curve,and decision curve analysis.Results There were statistically significant differences in pathological type,stage,combined pneumonia,combined pleural effusion,history of diabetes,history of coronary artery disease,history of hyperlipidemia,history of central venous catheter,history of operation,blood type,dyspnea,smoking,and history of chemotherapy between two groups(P＜0.05).White blood cell count,blood platelet count(PLT),neutrophil count,neutrophil/lymphocyte ratio,platelet/lymphocyte ratio(PLR),D-dimer(D-D),prothrombin time(PT),fibrinogen(FIB),lactic dehydrogenase(LDH),triglyceride,total cholesterol,carcino-embryonic antigen(CEA),carbohydrate antigen 125(CA125),squamous cell carcinoma antigen,and pH value of PE group were higher than those of control group,while albumin(Alb),partial pressure of carbon dioxide(PCO2),and partial pressure of oxygen were lower than those of control group,and the differences were statistically significant(P＜0.05).The results of univariate logistic regression analysis showed that pathological type,combined pneumonia,history of coronary artery disease,history of hyperlipi-demia,history of operation,pH value,dyspnea,PLT,PLR,D-D,PT,FIB,type B natriuretic peptide,Alb,LDH,CEA,CA125,history of chemo-therapy,and PCO2 had an impact on patients with lung cancer complicated with PE(P＜0.05).LASSO regression analysis showed that PLT,PLR,D-D,PT,CA125,PCO2,dyspnea,combined pneumonia,history of central venous catheterization,smoking,and history of chemotherapy were the characteristic variables of screening.Multivariate logistic regression analysis showed that pneumonia,PLT,D-D,and history of chemotherapy were independent risk factors for lung cancer patients complicated with PE(OR=5.065,1.005,1.343,16.240,P＜0.05).The area under the curve of pa-tients with lung cancer complicated with PE predicted by nomogram model was 0.918,the sensitivity was 0.861,and the specificity was 0.840.The calibration curve results showed that the model had good calibration degree and good prediction ability.The results of decision curve analysis showed that when the threshold probability was＜76％,the net benefit was＞0,and the risk assessment model had clinical significance.Conclu-sion The constructed nomogram model can better predict the risk of patients with lung cancer complicated with PE,which is helpful for individual-ized treatment of patients and provides a basis for timely and effective treatment measures.
Lung cancerPulmonary embolismLASSO regressionPre-diction model
NETL
NSTL
万方数据
