摘要
Objective The study aimed to construct and validate a predictive model for pulmonary nodules(PN)nature based on clinicopa-thological features,imaging,and serum biomarkers,so as to provide scientificdecision-making for early diagnosis and treatment of lung cancer.Methods A retrospective was performed on 816 PN patients with definited pathological diagnosis who received surgical resection analysisor lung biopsy in the Department of Thoracic Surgery and Oncology of Shenzhen Traditional Chinese Medicine Hospital from January 2019 to February 2023.Among them,113 cases that did not meet the inclusion criteria were excluded,and the remaining 703 cases were included in the study.The study based on the clinicopathologic features(age,gender,smoking history,smoking cessation history and family history of cancer),chest imaging(maximum diameter of nodule,location of lesion,clear border,Lobulation,spiculation,vascular convergence sign,vacuole,calcification,air bronchial sign,emphysema,nodule type and pleural indentation,nodule number)and serum carcinoembryonic antigen(CEA),cytokeratin 19 fragment(CYFRA21-1),squamous cell carcinoma antigen(SCCA)in patients with PN.These cases were randomly divided into a modeling group(n=552,237 benign,315 malignant)and a validation group(n=151,85 benign,66 malignant).First,univariate analysis was performed to screen for statistically significant predictors of nodules nature.Then,multivariate regression analysis was performed to screen for independent predictors of nodules nature.Finally,the prediction model of PN nature was constructed by logistic regression analysis.Subsequently,the validation group data were entered into the proposed model and Mayo clinic(Mayo)model,veterans affairs(VA)model,Brock University(Brock)model,Peking University(PKU)model and Guangzhou Medical University(GZMU)model,respectively.PN malignancy probability was calculated.The receiver operating characteristic(ROC)curves were plotted.The diagnostic efficiency of each model was compared according to the area under the curve(AUC).Results There were statistically significant variables including age,family history of cancer,maximum nodule diameter,nodule type,upper lobe of lung,calcification,vascular convergence sign,lobulation,clear border,spiculation,and serum CEA,SCCA,CYFRA21-1 using univariate analysis.Multiple regression analysis showed that age,CEA,clear border,CYFRA21-1,SCCA,upper lobe of lung,maximum nodule diameter,family history of cancer,spiculation and nodule type were independent predictors of PN nature.The prediction model equation constructed in this study is as follows:f(x)= ex/(1+ex),X=(-6.318 8+0.020 8×Age+0.527 4×CEA-0.928 4×clear border+0.294 6×Cyfra21-1+0.294×maximum nodule diameter+1.220 1×family history of cancer +0.573 2×upper lobe of lung +0.064 8×SCCA +1.461 5×Spiculation +1.497 6×nodule type).The AUC(0.799 vs 0.659,0.650)of the proposed model was significantly higher compared with Mayo model and VA model,and there were statistically significant differences(Z=3.029,2.638,P=0.003,0.008).However,compared with Brock model,PKU model and GZMU model,the differences of AUC(0.799 vs 0.762,0.773,0.769)were not statistically significant(Z=1.063,0.686,0.757,P=0.288,0.493,0.449).Conclusion The prediction model for PN nature established in this study is accurate and reliable,which can help clinics with early diagnosis and early intervention,and this prediction model deserves to be popularized.
摘要
Objective To evaluate the effects of diagnostic and treatment manipulation of the urinary diseases on serum prostate specific antigen(PSA) levels .Methods 80 male patients were recruited from urology surgery department of Shenzhen Tranditional Chinese Medicine (TCM ) Hospital ,Which included 13 cases with digital rectal examination (DRE) ,10 cases with catheterization , 12 cases with rigid cystoscopy ,17 cases with prostate biopsy ,28 cases with transurethral resection of the prostate (TURP) .Blood samples of 80 patients were collected before diagnostic and treatment manipulation of the urinary diseases and 24 h ,3 d ,7 d ,14 d af‐ter that ,respectively .Then ,serum total prostate antigen(TPSA) and free prostate antigen (FPSA) was measured .Results There was no effects of DRE on serum TPSA and FPSA levels(P>0 .05) .On the contrary ,serum TPSA and FPSA levels increased sig‐nificantly in patients with catheterization and cystoscopy(P<0 .05) ,and the duration was longer(7-14 d) .Serum TPSA and FPSA levels increased significantly(P<0 .05)in patients with TURP and biopsy at the 24th hour after manipulation and it began to de‐crease on the third day .Also ,the serum TPSA and FPSA levels decreased to baseline after 14 days .Conclusion There′re no effects of DRE on serum TPSA and FPSA levels .However ,serum TPSA and FPSA levels increase differently in patients with catheteriza‐tion ,cystoscopy ,biopsy and TURP ,but the durations were different ,too .