Acknowledgement
This study was supported by a 2020 grant from The Korean Academy of Tuberculosis and Respiratory Diseases.
References
- Global Burden of Disease Cancer Collaboration; Fitzmaurice C, Dicker D, Pain A, Hamavid H, Moradi-Lakeh M, et al. The global burden of cancer 2013. JAMA Oncol 2015;1:505-27.
- Young RP, Hopkins RJ, Christmas T, Black PN, Metcalf P, Gamble GD. COPD prevalence is increased in lung cancer, independent of age, sex and smoking history. Eur Respir J 2009;34:380-6. https://doi.org/10.1183/09031936.00144208
- Barta JA, Powell CA, Wisnivesky JP. Global epidemiology of lung cancer. Ann Glob Health 2019;85:8.
- Venuta F, Diso D, Onorati I, Anile M, Mantovani S, Rendina EA. Lung cancer in elderly patients. J Thorac Dis 2016;8(Suppl 11):S908-14. https://doi.org/10.21037/jtd.2016.05.20
- Donington J, Ferguson M, Mazzone P, Handy J Jr, Schuchert M, Fernando H, et al. American College of Chest Physicians and Society of Thoracic Surgeons consensus statement for evaluation and management for high-risk patients with stage I non-small cell lung cancer. Chest 2012;142:1620-35. https://doi.org/10.1378/chest.12-0790
- Oswald NK, Halle-Smith J, Mehdi R, Nightingale P, Naidu B, Turner AM. Predicting postoperative lung function following lung cancer resection: a systematic review and meta-analysis. EClinicalMedicine 2019;15:7-13. https://doi.org/10.1016/j.eclinm.2019.08.015
- Lim E, Baldwin D, Beckles M, Duffy J, Entwisle J, FaivreFinn C, et al. Guidelines on the radical management of patients with lung cancer. Thorax 2010;65 Suppl 3:iii1-27. https://doi.org/10.1136/thx.2010.145938
- Wyser C, Stulz P, Soler M, Tamm M, Muller-Brand J, Habicht J, et al. Prospective evaluation of an algorithm for the functional assessment of lung resection candidates. Am J Respir Crit Care Med 1999;159(5 Pt 1):1450-6. https://doi.org/10.1164/ajrccm.159.5.9809107
- Wu MT, Pan HB, Chiang AA, Hsu HK, Chang HC, Peng NJ, et al. Prediction of postoperative lung function in patients with lung cancer: comparison of quantitative CT with perfusion scintigraphy. AJR Am J Roentgenol 2002;178:667-72. https://doi.org/10.2214/ajr.178.3.1780667
- Cukic V. Preoperative prediction of lung function in pneumonectomy by spirometry and lung perfusion scintigraphy. Acta Inform Med 2012;20:221-5. https://doi.org/10.5455/aim.2012.20.221-225
- Batihan G, Ceylan KC, Usluer O, Kaya SO. Video-assisted thoracoscopic surgery vs thoracotomy for non-small cell lung cancer greater than 5 cm: is VATS a feasible approach for large tumors? J Cardiothorac Surg 2020;15:261.
- Landreneau RJ, Hazelrigg SR, Ferson PF, Johnson JA, Nawarawong W, Boley TM, et al. Thoracoscopic resection of 85 pulmonary lesions. Ann Thorac Surg 1992;54:415-20. https://doi.org/10.1016/0003-4975(92)90430-C
- Zeiher BG, Gross TJ, Kern JA, Lanza LA, Peterson MW. Predicting postoperative pulmonary function in patients undergoing lung resection. Chest 1995;108:68-72. https://doi.org/10.1378/chest.108.1.68
- Kushibe K, Kawaguchi T, Kimura M, Takahama M, Tojo T, Taniguchi S. Exercise capacity after lobectomy in patients with chronic obstructive pulmonary disease. Interact Cardiovasc Thorac Surg 2008;7:398-401. https://doi.org/10.1510/icvts.2007.165696
- Chen JH, Asch SM. Machine learning and prediction in medicine: beyond the peak of inflated expectations. N Engl J Med 2017;376:2507-9. https://doi.org/10.1056/NEJMp1702071
- Harford S, Darabi H, Del Rios M, Majumdar S, Karim F, Vanden Hoek T, et al. A machine learning based model for Out of Hospital cardiac arrest outcome classification and sensitivity analysis. Resuscitation 2019;138:134-40. https://doi.org/10.1016/j.resuscitation.2019.03.012
- Hirano Y, Kondo Y, Sueyoshi K, Okamoto K, Tanaka H. Early outcome prediction for out-of-hospital cardiac arrest with initial shockable rhythm using machine learning models. Resuscitation 2021;158:49-56. https://doi.org/10.1016/j.resuscitation.2020.11.020
- Toste PA, Lee JM. Limited resection versus lobectomy in early-stage non-small cell lung cancer. J Thorac Dis 2016;8:E1511-3. https://doi.org/10.21037/jtd.2016.11.71
- Kodama K, Doi O, Higashiyama M, Yokouchi H. Intentional limited resection for selected patients with T1 N0 M0 non-small-cell lung cancer: a single-institution study. J Thorac Cardiovasc Surg 1997;114:347-53. https://doi.org/10.1016/S0022-5223(97)70179-X
- Durham AL, Adcock IM. The relationship between COPD and lung cancer. Lung Cancer 2015;90:121-7. https://doi.org/10.1016/j.lungcan.2015.08.017
- Shin TR, Oh YM, Park JH, Lee KS, Oh S, Kang DR, et al. The prognostic value of residual volume/total lung capacity in patients with chronic obstructive pulmonary disease. J Korean Med Sci 2015;30:1459-65. https://doi.org/10.3346/jkms.2015.30.10.1459
- Matsumoto R, Takamori S, Yokoyama S, Hashiguchi T, Murakami D, Yoshiyama K, et al. Lung function in the late postoperative phase and influencing factors in patients undergoing pulmonary lobectomy. J Thorac Dis 2018;10:2916-23. https://doi.org/10.21037/jtd.2018.05.27
- Kwon OB, Yeo CD, Lee HY, Kang HS, Kim SK, Kim JS, et al. The value of residual volume/total lung capacity as an indicator for predicting postoperative lung function in non-small lung cancer. J Clin Med 2021;10:4159.
- Kwak SK, Kim JH. Statistical data preparation: management of missing values and outliers. Korean J Anesthesiol 2017;70:407-11. https://doi.org/10.4097/kjae.2017.70.4.407
- Khan SI, Hoque AS. SICE: an improved missing data imputation technique. J Big Data 2020;7:37.
- Zhang Z. Missing values in big data research: some basic skills. Ann Transl Med 2015;3:323.