Establishment of logistic regression diagnosis model predicting malignant solitary pulmonary nodules
YU Wei1, YE Bo2, XU Liyun3, Wang Zhaoyu4, Wang Shanjun5, Cao Hanbo5, Chen Zhijun1, ZHANG Yongkui1.
1.Department of Cardiothoracic Surgery, Zhoushan Hospital Affiliated to Wenzhou Medical University, Zhoushan, 316021; 2.Department of Thoracic Surgery, Chest Hospital Affiliated to Shanghai Jiaotong University, Shanghai, 200030; 3.Lung Cancer Research Center of Zhoushan City, Zhoushan Hospital Affiliated to Wenzhou Medical University, Zhoushan, 316021; 4.Pathology Diagnosis Center, Zhoushan Hospital Affiliated to Wenzhou Medical University, Zhoushan, 316021; 5.Radiology Diagnosis Center, Zhoushan Hospital Affiliated to Wenzhou Medical University, Zhoushan, 316021
YU Wei,YE Bo,XU Liyun, et al. Establishment of logistic regression diagnosis model predicting malignant solitary pulmonary nodules[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2017, 47(9): 660-665.
Abstract：Objective: To establish a logistic regression model for predicting the probability of malignancy in solitary pulmonary nodules (SPNs) and provide guidance for the diagnosis. Methods: The clinical data and computed tomography (CT) images of 212 patients with a clear pathological diagnosis of SPNs were retrospectively analyzed from Zhoushan Hospital Affiliated to Wenzhou Medical University were analyzed retrospectively, among which, benign SPNs were collected from January 2012 to December 2015, and malignant SPNs were collected from January 2013 to December 2013. To estimate the independent predictors of malignancy of SPNs, multivariate analysis was used. A logistic regression prediction model was subsequently created. Data from an additional 242 patients with pathologic diagnosis of SPNs were used to validate this logistic regression prediction model. Results: Fifty-eight percent of the nodules from 212 SPNs patients were malignant and 42% were benign. Logistic regression analysis showed that there were significant differences in nodule type, clear border, lobulation, spiculaion, pleural retraction sign between subgroups with benign and malignant SPNs (P<0.05). These factors were identified as independent predictors of malignancy in SPNs. In our model, sensitivity was 81.8%, specificity was 85.7%, positive predictive value was 88.2%, and negative predictive value was 78.3%. Conclusion: The prediction model established in this study can be used to assess the probability of malignancy in SPNs, thereby providing help for the diagnosis of SPNs.
[1] 林洁, 唐坤, 殷薇薇, 等. PET/CT及其数学预测模型对孤立性肺结节诊断价值的研究[J]. 温州医科大学学报, 2015, 45(5): 354-358.
[2] TRUONG M T, KO J P, ROSSI S E, et al. Update in the evaluation of the solitary pulmonary nodule[J]. Radiographics, 2014, 34(6): 1658-1679.
[3] KROCHMAL R, ARIAS S, YARMUS L, et al. Diagnosis and management of pulmonary nodules[J]. Expert Rev Respir Med, 2014, 8(6): 677-691.
[4] FERLAY J, SHIN H R, BRAY F, et al. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008[J]. Int J Cancer, 2010, 127(12): 2893-2917.
[5] JEMAL A, SIEGEL R, XU J, et al. Cancer Statistics, 2010 [J]. CA Cancer J Clin, 2010, 60(5): 277-300.
[6] GODTFREDSEN N S, PRESCOTT E, OSLER M. Effect of smoking reduction on lung cancer risk[J]. JAMA, 2005, 294(12): 1505-1510.
[7] FIELD J K, OUDKERK M, PEDERSEN J H, et al. Prospects for population screening and diagnosis of lung cancer[J]. Lancet, 2013, 382(9893): 732-741.
[8] ZHOU C, WU Y L, CHEN G, et al. Erlotinib versus chemotherapy as first-line treatment for patients with advanced EGFR mutation-positive non-small-cell lung cancer (OPTI-MAL, CTONG-0802): a multicentre, open-label, randomised, phase 3 study[J]. Lancet Oncol, 2011, 12(8): 735-742.
[9] RAMI-PORTA R, BOLEJACK V, GOLDSTRAW P. The new tumor, node, and metastasis staging system[J]. Semin Respir Crit Care Med, 2011, 32(1): 44-51.
[10] TANOUE L T, DETTERBECK F C. New TNM classification for non-small-cell lung cancer[J]. Expert Rev Anticancer Ther, 2009, 9(4): 413-423.
[11] LI Y, CHEN K Z, WANG J. Development and validation of a clinical prediction model to estimate the probability of malignancy in solitary pulmonary nodules in Chinese People[J]. Clin Lung Cancer, 2011, 12(5): 313-319.
[12] KHAN A, HERMAN P G, VORWERK P, et al. Solitary pulmonary nodules: comparison of classification with standard, thin-section, and reference phantom CT[J]. Radiology, 1991, 179(2): 477-481.
[13] SWENSEN S J, SILVERSTEIN M D, ILSTRUP D M, et al. The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules[J]. Arch Intern Med, 1997, 157(8): 849-855.
[14] GOULD M K, ANANTH L, BARNETT P G, et al. A clinical model to estimate the pretest probability of lung cancer inpatients with solitary pulmonary nodules[J]. Chest, 2007, 131(2): 383-388.
