Establishment and validation of a model for predicting infiltration of pulmonary subsolid nodules by circulating tumor cells combined with imaging features_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

MA Xiang ^1,2,3 , LIN Ruijiang ^2,3 , MA Minjie ^2,3 , CAO Xiong ^2,3 , LIANG Qiuhao ^1,2,3 , HAN Zhiwei ^1,2,3 , XU Shangqing ^2,3 ,  HAN Biao ^1,2,3

1. The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, P. R. China;
2. Department of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000, P. R. China;
3. Major in R & D and Application of Key Technologies in Thoracic Surgery Gansu International Science and Technology Cooperation Base, Lanzhou, 730000, P. R. China;

Corresponding?author：

HAN Biao, Email: hanbiao66@163.com

Keywords：

Pulmonary subsolid nodules; clinical radiological features; circulating tumor cells; tumor invasiveness

DOI：

10.7507/1007-4848.202204041

Video：

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Objective To evaluate the clinical radiological features combined with circulating tumor cells (CTCs) in the diagnosis of invasiveness evaluation of subsolid nodules in lung cancers. Methods Clinical data of 296 patients from the First Hospital of Lanzhou University between February 2019 and February 2021 were retrospectively included. There were 130 males and 166 females with a median age of 62.00 years. Patients were randomly divided into a training set and an internal validation set with a ratio of 3 : 1 by random number table method. The patients were divided into two groups: a preinvasive lesion group (atypical adenomatoid hyperplasia and adenocarcinoma in situ) and an invasive lesion group (microinvasive adenocarcinoma and invasive adenocarcinoma). Independent risk factors were selected by regression analysis of training set and a Nomogram prediction model was constructed. The accuracy and consistency of the model were verified by the receiver operating characteristic curve and calibration curve respectively. Subgroup analysis was conducted on nodules with different diameters to further verify the performance of the model. Specific performance metrics, including sensitivity, specificity, positive predictive value, negative predictive value and accuracy at the threshold were calculated. Results Independent risk factors selected by regression analysis for subsolid nodules were age, CTCs level, nodular nature, lobulation and spiculation. The Nomogram prediction mode provided an area under the curve (AUC) of 0.914 (0.872, 0.956), outperforming clinical radiological features model AUC [0.856 (0.794, 0.917), P=0.003] and CTCs AUC [0.750 (0.675, 0.825), P=0.001] in training set. C-index was 0.914, 0.894 and corrected C-index was 0.902, 0.843 in training set and internal validation set, respectively. The AUC of the prediction model in training set was 0.902 (0.848, 0.955), 0.913 (0.860, 0.966) and 0.873 (0.730, 1.000) for nodule diameter of 5-20 mm, 10-20 mm and 21-30 mm, respectively. Conclusion The prediction model in this study has better diagnostic value, and is more effective in clinical diagnosis of diseases.

Citation： MA Xiang, LIN Ruijiang, MA Minjie, CAO Xiong, LIANG Qiuhao, HAN Zhiwei, XU Shangqing, HAN Biao. Establishment and validation of a model for predicting infiltration of pulmonary subsolid nodules by circulating tumor cells combined with imaging features. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2023, 30(2): 198-204. doi: 10.7507/1007-4848.202204041 Copy

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14.	何花, 胡文滕, 藺瑞江, 等. CT特征聯合腫瘤標志物預測肺磨玻璃結節腫瘤浸潤性的回顧性隊列研究. 中國胸心血管外科臨床雜志, 2022, 29(9): 1113-1119.
15.	Zhai Y, Hui Z, Men Y, et al. Combined neat model for the prognosis of postoperative stage Ⅲ-N2 non-small cell lung cancer. Thorac Cancer, 2020, 11(9): 2610-2617.
16.	Yoshimura A, Uchino J, Hasegawa K, et al. Carcinoembryonic antigen and CYFRA 21-1 responses as prognostic factors in advanced non-small cell lung cancer. Transl Lung Cancer Res, 2019, 8(3): 227-234.
17.	Tomita M, Ayabe T, Maeda R, et al. Serum carcinoembryonic antigen level predicts cancer-specific outcomes of resected non-small cell lung cancer with interstitial pneumonia. World J Oncol, 2018, 9(5-6): 136-140.
18.	陳耿春, 李陽, 邱士軍. 肺部小結節與浸潤性肺癌的影像學相關性研究. 現代診斷與治療, 2018, 29(24): 4010-4012.
19.	單文莉, 周圍, 孔丹, 等. 肺腺癌CT征象與病理組織學亞型及分化程度的對照研究. 臨床放射學雜志, 2019, 38(12): 2312-2316.
20.	黃海峽, 徐國厚, 左翔, 等. CT特征聯合癌胚抗原對磨玻璃結節的浸潤前和浸潤性鑒別診斷價值的研究. 中國CT和MRI雜志, 2020, 18(10): 29-33.
21.	Miao Y, Zhang J, Zou J, et al. Correlation in histological subtypes with high resolution computed tomography signatures of early stage lung adenocarcinoma. Transl Lung Cancer Res, 2017, 6(1): 14-22.

1. Imielinski M, Berger AH, Hammerman PS, et al. Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell, 2012, 150(6): 1107-1120.
2. 方三高, 陳真偉, 魏建國. 2021年第5版WHO胸部腫瘤分類. 診斷病理學雜志, 2021, 28(7): 591-593, 607.
3. Li Q, Dai J, Zhang P, et al. Management of pulmonary ground glass nodules: Less is more. Ann Thorac Surg, 2021, 112(1): 1-2.
4. 鄭慧, 李建玉, 王珊, 等. 基于肺磨玻璃結節CT征象的診斷模型列線圖評估肺癌浸潤性. 放射學實踐, 2021, 36(4): 470-474.
5. Godoy MC, Sabloff B, Naidich DP. Subsolid pulmonary nodules: Imaging evaluation and strategic management. Curr Opin Pulm Med, 2012, 18(4): 304-312.
6. Seidelman JL, Myers JL, Quint LE. Incidental, subsolid pulmonary nodules at CT: Etiology and management. Cancer Imaging, 2013, 13(3): 365-373.
7. 孟慶成, 賈丙鑫, 張建偉, 等. 微浸潤型肺腺癌的高分辨率CT表現. 中國醫學影像學雜志, 2013, 21(7): 536-538, 542.
8. 劉佳, 李文武, 黃勇, 等. 表現為磨玻璃密度結節的肺腺癌浸潤前病變與微浸潤腺癌的多排螺旋CT影像學征象及其鑒別診斷價值. 中華腫瘤雜志, 2015, 37(8): 611-616.
9. Syrigos K, Fiste O, Charpidou A, et al. Circulating tumor cells count as a predictor of survival in lung cancer. Crit Rev Oncol Hematol, 2018, 125: 60-68.
10. Wang J, Wang K, Xu J, et al. Prognostic significance of circulating tumor cells in non-small-cell lung cancer patients: A meta-analysis. PLoS One, 2013, 8(11): e78070.
11. Gao Y, Ni X, Guo H, et al. Single-cell sequencing deciphers a convergent evolution of copy number alterations from primary to circulating tumor cells. Genome Res, 2017, 27(8): 1312-1322.
12. Yin W, Zhu J, Ma B, et al. Overcoming obstacles in pathological diagnosis of pulmonary nodules through circulating tumor cell enrichment. Small, 2020, 16(25): e2001695.
13. Wilshire CL, Louie BE, Horton MP, et al. Comparison of outcomes for patients with lepidic pulmonary adenocarcinoma defined by 2 staging systems: A North American experience. J Thorac Cardiovasc Surg, 2016, 151(6): 1561-1568.
14. 何花, 胡文滕, 藺瑞江, 等. CT特征聯合腫瘤標志物預測肺磨玻璃結節腫瘤浸潤性的回顧性隊列研究. 中國胸心血管外科臨床雜志, 2022, 29(9): 1113-1119.
15. Zhai Y, Hui Z, Men Y, et al. Combined neat model for the prognosis of postoperative stage Ⅲ-N2 non-small cell lung cancer. Thorac Cancer, 2020, 11(9): 2610-2617.
16. Yoshimura A, Uchino J, Hasegawa K, et al. Carcinoembryonic antigen and CYFRA 21-1 responses as prognostic factors in advanced non-small cell lung cancer. Transl Lung Cancer Res, 2019, 8(3): 227-234.
17. Tomita M, Ayabe T, Maeda R, et al. Serum carcinoembryonic antigen level predicts cancer-specific outcomes of resected non-small cell lung cancer with interstitial pneumonia. World J Oncol, 2018, 9(5-6): 136-140.
18. 陳耿春, 李陽, 邱士軍. 肺部小結節與浸潤性肺癌的影像學相關性研究. 現代診斷與治療, 2018, 29(24): 4010-4012.
19. 單文莉, 周圍, 孔丹, 等. 肺腺癌CT征象與病理組織學亞型及分化程度的對照研究. 臨床放射學雜志, 2019, 38(12): 2312-2316.
20. 黃海峽, 徐國厚, 左翔, 等. CT特征聯合癌胚抗原對磨玻璃結節的浸潤前和浸潤性鑒別診斷價值的研究. 中國CT和MRI雜志, 2020, 18(10): 29-33.
21. Miao Y, Zhang J, Zou J, et al. Correlation in histological subtypes with high resolution computed tomography signatures of early stage lung adenocarcinoma. Transl Lung Cancer Res, 2017, 6(1): 14-22.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Establishment and validation of a model for predicting infiltration of pulmonary subsolid nodules by circulating tumor cells combined with imaging features

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