Research On The Related Factors Influencing The Diagnosis Of Pulmonary Nodules

Objectives This study aimed to develop and validate a preoperative CT-based nomogram combined with clinical and radiological features for distinguishing invasive from noninvasive pulmonary adenocarcinoma.Methods A total of 167 patients with solitary pulmonary nodules and pathologically confirmed adenocarcinoma treated between January 2020 and December 2020 at Hebei General Hospital were retrospectively assessed.Those issues as gender;age;body mass index;smoking history;history of cancer;family history of cancer;the diameter of solitary pulmonary nodule;highest attenuation of non-enhanced CT images;mean attenuation of non-enhanced CT images;margin;speculation;lobulation;pleural indentation;vacuole;vascular convergence;the location of solitary pulmonary nodule;carcinoembryonic antigen;squamous cell carcinoma antigen;neuron specific enolase;cytokeratin 19fragment;etc.were recorded.To evaluate the probability of invasive pulmonary adenocarcinoma,we developed three models,the multivariate logistic regression model,the stepwise logistic regression model,and the cross-validation model.The Akaike information criterion(AIC)was used to compare the relative strength of different models,and the area under the curve(AUC)was used to quantify the predictive accuracy.The best performing model was presented as a nomogram,calibrated and evaluated for clinical utility.Results The stepwise logistic regression model revealed highest(P=0.0046)and mean attenuations of non-enhanced CT images(P=0.0196),and lobulation(P=0.0069)and vacuole presence(P=0.0599)were predictive factors of invasive pulmonary adenocarcinoma.This model(AIC=67.528)with the lowest AIC value compared with that of the multivariate logistic regression model(AIC=69.301)or the cross-validation model(AIC=81.216)was identified as the best model,and its AUC value(0.9967;95%CI :0.9887～1)was higher than those of the other two models.The calibration curve showed optimal agreement in invasive pulmonary adenocarcinoma probability as predicted by the nomogram and the actual value.Conclusions This study developed and validated a nomogram that could estimate the preoperative probability of invasive pulmonary adenocarcinoma in patients with solitary pulmonary nodules,which may be useful in clinical decision-making associated with personalized surgical intervention and therapeutic regimen selection.Figure 7;Table 5;Reference 193...