Virtual Library
Start Your Search
W. Biao
Author of
-
+
P1.03 - Poster Session with Presenters Present (ID 455)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Radiology/Staging/Screening
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)
-
+
P1.03-029 - A Useful Algorithmatic Model in Predicting the Likelihood of Lung Cancer in Solitary Pulmonary Nodules (ID 5785)
14:30 - 14:30 | Author(s): W. Biao
- Abstract
Background:
The aim of this study was to establish a mathematic model to predict the likelihood of lung cancer in surgically resected solitary pulmonary nodules (SPNs) and investigate the value of multidisciplinary treatment (MDT) consultation in diagnosis of SPNs.
Methods:
From January 2011 to June 2016, 666 patients with a clear pathological diagnosis of SPN by surgical resection in Fujian Provicial Cancer Hospital were involved. Their clinicopathologic data were collected and retrospectively analyzed. All patients were divided into testing and validating cohorts，testing cohort consisted of patients from January 2011 to June 2015, whose data were used to create a mathematical model via multivariate logistic regression analysis. Patients from July 2015 to June 2016 were included in validating cohort, whose data were used to verify the accuracy of the prediction model. The positive rate of malignancy between cases discussed at MDT meeting and evaluated by surgeon were compared.
Results:
The number of testing and validating cohorts was 446 and 220, respectively. In testing cohort, there were 8 case (1.8%) diagnosed as atypical adenohyperplasia (AAH) and 313 cases (70.2%) as malignant SPNs, mainly invasive adenocarcinoma (IA, 234 cases/ 52.5%), small cell lung cancer (SCLC, 28 cases/6.3%), minimally invasive adenocarcinoma (MIA, 22 cases/4.9%) and adenocarcinoma in situ(AIS,10 cases/2.2%). Other were benign SPNs (125 cases, 28%), mainly including inflammation or fibrosis(95 cases, 21.3%), hamartoma (17 cases, 3.8%) and inflammatory pseudotumor (11 cases, 2.4%).Univariate analysis showed that there were significant differences between benign and malignant SPNs regarding age, sex, nodule type, maximum nodule diameter, CT value, nodule shape, spiculation, lobulation, pleural retraction sign, cavitation, bronchiole truncation and vascular convergence (P<0.05). Sex, age, nodule type, spiculation, vascular convergence, bronchiole truncation and nodule shape were identified as independent predictors of malignancy in multivariate logistic regression analysis.The area under curve (AUC) was 0.883 (95% CI, 0.885-0.915) in the model. An appropriate cut-off point was determined as P=0.77, sensitivity and specificity of the model was 77.6% and 80.0%, respectively. The positive rate of malignancy was 81.3%(104/128) in cases discussed at MDT meeting, comparing with 72.0% in all patients(P<0.05).The positive rate of malignancy reach to 90.4% in 97 patients with model predicting positive and discussed by MDT. The validation data set is on-going.
Conclusion:
The prediction model established in this study could be useful in assessing the likelihood of lung cancer in SPNs. And MDT consultation can improve the accuracy of prediction.
