Chinese Medical Association guideline for clinical diagnosis and treatment of lung cancer (2023 edition): An interpretation_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

DONG Dong , HUANG Yiheng , ZHANG Yajie ,  LI Hecheng

Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, P. R. China;

Corresponding author：

LI Hecheng, Email: lihecheng2000@hotmail.com

Keywords：

Lung cancer; treatment; guideline interpretation

DOI：

10.7507/1007-4848.202309018

Video：

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Abstract Full text Figures/Tables Video References Cited by

Chinese Medical Association Guidelines for Clinical Diagnosis and Treatment of Lung Cancer (2023 Edition) has been released in July 2023. Based on the 2022 edition, the 2023 edition of the guideline has been updated in the aspects of lung cancer screening, pathology, surgical standards, neoadjuvant therapy, targeted therapy and treatment of advanced lung cancer. This article will give a brief introduction to these updated parts.

Citation： DONG Dong, HUANG Yiheng, ZHANG Yajie, LI Hecheng. Chinese Medical Association guideline for clinical diagnosis and treatment of lung cancer (2023 edition): An interpretation. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2023, 30(11): 1533-1538. doi: 10.7507/1007-4848.202309018 Copy

1.	中华医学会, 中华医学会肿瘤学分会, 中华医学会杂志社. 中华医学会肺癌临床诊疗指南(2018版). 中华肿瘤杂志, 2018, 40(12): 935-964.
2.	中华医学会肿瘤学分会, 中华医学会杂志社. 中华医学会肺癌临床诊疗指南(2023版). 中华医学杂志, 2023, 103(27): 2037-2074.
3.	Aberle DR, Adams AM, Berg CD, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med, 2011, 365(5): 395-409.
4.	de Koning HJ, van der Aalst CM, de Jong PA, et al. Reduced lung-cancer mortality with volume CT screening in a randomized trial. N Engl J Med, 2020, 382(6): 503-513.
5.	Potter AL, Rosenstein AL, Kiang MV, et al. Association of computed tomography screening with lung cancer stage shift and survival in the United States: Quasi-experimental study. BMJ, 2022, 376: e069008.
6.	Guisier F, Deslee G, Birembaut P, et al. Endoscopic follow-up of low-grade precancerous bronchial lesions in high-risk patients: Long-term results of the SELEPREBB randomised multicentre trial. Eur Respir J, 2022, 60(3): 2101946.
7.	Ziegelmayer S, Graf M, Makowski M, et al. Cost-effectiveness of artificial intelligence support in computed tomography-based lung cancer screening. Cancers, 2022, 14(7): 1729.
8.	Adams SJ, Mondal P, Penz E, et al. Development and cost analysis of a lung nodule management strategy combining artificial intelligence and lung-RADS for baseline lung cancer screening. J Am Coll Radiol, 2021, 18(5): 741-751.
9.	Ardila D, Kiraly AP, Bharadwaj S, et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med, 2019, 25(6): 954-961.
10.	Hata A, Yanagawa M, Yoshida Y, et al. Combination of deep learning-based denoising and iterative reconstruction for ultra-low-dose CT of the chest: Image quality and lung-RADS evaluation. AJR Am J Roentgenol, 2020, 215(6): 1321-1328.
11.	Obuchowski NA, Bullen JA. Statistical considerations for testing an AI algorithm used for prescreening lung CT images. Contemp Clin Trials Commun, 2019, 16: 100434.
12.	Setio AAA, Traverso A, de Bel T, et al. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal, 2017, 42: 1-13.
13.	Jiang B, Li N, Shi X, et al. Deep learning reconstruction shows better lung nodule detection for ultra-low-dose chest CT. Radiology, 2022, 303(1): 202-212.
14.	Pehrson LM, Nielsen MB, Ammitzbøl Lauridsen C. Automatic pulmonary nodule detection applying deep learning or machine learning algorithms to the LIDC-IDRI database: A systematic review. Diagnostics, 2019, 9(1): 29.
15.	Cui X, Zheng S, Heuvelmans MA, et al. Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program. Eur J Radiol, 2022, 146: 110068.
16.	Venkadesh KV, Setio AAA, Schreuder A, et al. Deep learning for malignancy risk estimation of pulmonary nodules detected at low-dose screening CT. Radiology, 2021, 300(2): 438-447.
17.	Baldwin DR, Gustafson J, Pickup L, et al. External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules. Thorax, 2020, 75(4): 306-312.
18.	Li D, Mikela Vilmun B, Frederik Carlsen J, et al. The performance of deep learning algorithms on automatic pulmonary nodule detection and classification tested on different datasets that are not derived from LIDC-IDRI: A systematic review. Diagnostics, 2019, 9(4): 207.
19.	Zhang Y, Liu W, Zhang H, et al. Extracellular vesicle long RNA markers of early-stage lung adenocarcinoma. Int J Cancer, 2023, 152(7): 1490-1500.
20.	Sozzi G, Boeri M, Rossi M, et al. Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: A correlative MILD trial study. J Clin Oncol, 2014, 32(8): 768-773.
21.	Sullivan FM, Mair FS, Anderson W, et al. Earlier diagnosis of lung cancer in a randomised trial of an autoantibody blood test followed by imaging. Eur Respir J, 2021, 57(1): 2000670.
22.	Nicholson AG, Tsao MS, Beasley MB, et al. The 2021 WHO classification of lung tumors: Impact of advances since 2015. J Thorac Oncol, 2022, 17(3): 362-387.
23.	Ruparel M, Quaife SL, Dickson JL, et al. Lung Screen Uptake Trial: Results from a single lung cancer screening round. Thorax, 2020, 75(10): 908-912.
24.	Van Hal G, Diab Garcia P. Lung cancer screening: Targeting the hard to reach—A review. Transl Lung Cancer Res, 2021, 10(5): 2309-2322.
25.	Van Meerbeeck JP, O'Dowd E, Ward B, et al. Lung cancer screening: New perspective and challenges in Europe. Cancers, 2022, 14(9): 2343.
26.	Baine MK, Hsieh M-S, Lai WV, et al. SCLC subtypes defined by ASCL1, NEUROD1, POU2F3, and YAP1: A comprehensive immunohistochemical and histopathologic characterization. J Thorac Oncol, 2020, 15(12): 1823-1835.
27.	Gandhi JS, Alnoor F, Sadiq Q, et al. SMARCA4 (BRG1) and SMARCB1 (INI1) expression in TTF-1 negative neuroendocrine carcinomas including merkel cell carcinoma. Pathol Res Pract, 2021, 219: 153341.
28.	La Fleur L, Falk-Sörqvist E, Smeds P, et al. Mutation patterns in a population-based non-small cell lung cancer cohort and prognostic impact of concomitant mutations in KRAS and TP53 or STK11. Lung Cancer, 2019, 130: 50-58.
29.	NSCLC Meta-analysis Collaborative Group. Preoperative chemotherapy for non-small-cell lung cancer: A systematic review and meta-analysis of individual participant data. Lancet, 2014, 383(9928): 1561-1571.
30.	Forde PM, Spicer J, Lu S, et al. Neoadjuvant nivolumab plus chemotherapy in resectable lung cancer. N Engl J Med, 2022, 386(21): 1973-1985.
31.	Provencio M, Serna-Blasco R, Nadal E, et al. Overall survival and biomarker analysis of neoadjuvant nivolumab plus chemotherapy in operable stage ⅢA non-small-cell lung cancer (NADIM phase Ⅱ trial). J Clin Oncol, 2022, 40(25): 2924-2933.
32.	Provencio M, Nadal E, González-Larriba JL, et al. Perioperative nivolumab and chemotherapy in stage Ⅲ non-small-cell lung cancer. N Engl J Med, 2023, 389(6): 504-513.
33.	Mazieres J, Drilon A, Lusque A, et al. Immune checkpoint inhibitors for patients with advanced lung cancer and oncogenic driver alterations: Results from the IMMUNOTARGET registry. Ann Oncol, 2019, 30(8): 1321-1328.
34.	Soria J-C, Ohe Y, Vansteenkiste J, et al. Osimertinib in untreated EGFR-mutated advanced non-small-cell lung cancer. N Engl J Med, 2018, 378(2): 113-125.
35.	Lisberg A, Cummings A, Goldman JW, et al. A phase Ⅱ study of pembrolizumab in EGFR-Mutant, PD-L1+, tyrosine kinase inhibitor naïve patients with advanced NSCLC. J Thorac Oncol, 2018, 13(8): 1138-1145.
36.	Camidge DR, Dziadziuszko R, Peters S, et al. Updated efficacy and safety data and impact of the EML4-ALK fusion variant on the efficacy of alectinib in untreated ALK-positive advanced non-small cell lung cancer in the global phase ⅢALEX Study. J Thorac Oncol, 2019, 14(7): 1233-1243.
37.	Gainor JF, Dardaei L, Yoda S, et al. Molecular mechanisms of resistance to first- and second-generation ALK inhibitors in ALK-rearranged lung cancer. Cancer Discov, 2016, 6(10): 1118-1133.
38.	Zhao J, Zhao L, Guo W, et al. Efficacy, safety, and biomarker analysis of neoadjuvant camrelizumab and apatinib in patients with resectable NSCLC: A phase 2 clinical trial. J Thorac Oncol, 2023, 18(6): 780-791.
39.	Tsuboi M, Weder W, Escriu C, et al. Neoadjuvant osimertinib with/without chemotherapy versus chemotherapy alone for EGFR-mutated resectable non-small-cell lung cancer: NeoADAURA. Future Oncol, 2021, 17(31): 4045-4055.
40.	Lococo F, Cancellieri A, Chiappetta M, et al. Salvage surgery after first-line alectinib for locally-advanced/metastatic ALK-rearranged NSCLC: Pathological response and perioperative results. Clin Lung Cancer, 2023, 24(5): 467-473.
41.	Sentana-Lledo D, Viray H, Piper-Vallillo AJ, et al. Complete pathologic response to short-course neoadjuvant alectinib in mediastinal node positive (N2) ALK rearranged lung cancer. Lung Cancer, 2022, 172: 124-126.
42.	Altorki N, Wang X, Kozono D, et al. Lobar or sublobar resection for peripheral stage ⅠA non-small-cell lung cancer. N Engl J Med, 2023, 388(6): 489-498.
43.	Saji H, Okada M, Tsuboi M, et al. Segmentectomy versus lobectomy in small-sized peripheral non-small-cell lung cancer (JCOG0802/WJOG4607L): A multicentre, open-label, phase 3, randomised, controlled, non-inferiority trial. Lancet, 2022, 399(10335): 1607-1617.
44.	Aokage K, Suzuki K, Saji H, et al. Segmentectomy for ground-glass-dominant lung cancer with a tumour diameter of 3 cm or less including ground-glass opacity (JCOG1211): A multicentre, single-arm, confirmatory, phase 3 trial. Lancet Respir Med, 2023, 11(6): 540-549.
45.	Suzuki K, Watanabe S-I, Wakabayashi M, et al. A single-arm study of sublobar resection for ground-glass opacity dominant peripheral lung cancer. J Thorac Cardiovasc Surg, 2022, 163(1): 289-301.
46.	Tsuboi M, Herbst RS, John T, et al. Overall survival with osimertinib in resected EGFR-mutated NSCLC. N Engl J Med, 2023, 389(2): 137-147.
47.	Strauss GM, Herndon JE, Maddaus MA, et al. Adjuvant paclitaxel plus carboplatin compared with observation in stage ⅠB non-small-cell lung cancer: CALGB 9633 with the Cancer and Leukemia Group B, Radiation Therapy Oncology Group, and North Central Cancer Treatment Group Study Groups. J Clin Oncol, 2008, 26(31): 5043-5051.
48.	Butts CA, Ding K, Seymour L, et al. Randomized phase Ⅲtrial of vinorelbine plus cisplatin compared with observation in completely resected stageⅠB andⅡnon-small-cell lung cancer: Updated survival analysis of JBR-10. J Clin Oncol, 2010, 28(1): 29-34.
49.	Qian F, Yang W, Wang R, et al. Prognostic significance and adjuvant chemotherapy survival benefits of a solid or micropapillary pattern in patients with resected stage ⅠB lung adenocarcinoma. J Thorac Cardiovasc Surg, 2018, 155(3): 1227-1235.
50.	Hong L, Negrao MV, Dibaj SS, et al. Programmed death-ligand 1 heterogeneity and its impact on benefit from immune checkpoint inhibitors in NSCLC. J Thorac Oncol, 2020, 15(9): 1449-1459.
51.	Mok TSK, Wu YL, Kudaba I, et al. Pembrolizumab versus chemotherapy for previously untreated, PD-L1-expressing, locally advanced or metastatic non-small-cell lung cancer (KEYNOTE-042): A randomised, open-label, controlled, phase 3 trial. Lancet, 2019, 393(10183): 1819-1830.
52.	O'Brien M, Paz-Ares L, Marreaud S, et al. Pembrolizumab versus placebo as adjuvant therapy for completely resected stage ⅠB-ⅢA non-small-cell lung cancer (PEARLS/KEYNOTE-091): An interim analysis of a randomised, triple-blind, phase 3 trial. Lancet Oncol, 2022, 23(10): 1274-1286.
53.	Zhou Q, Chen M, Jiang O, et al. Sugemalimab versus placebo after concurrent or sequential chemoradiotherapy in patients with locally advanced, unresectable, stageⅢ non-small-cell lung cancer in China (GEMSTONE-301): Interim results of a randomised, double-blind, multicentre, phase 3 trial. Lancet Oncol, 2022, 23(2): 209-219.
54.	Reck M, Rodríguez-Abreu D, Robinson AG, et al. Updated analysis of KEYNOTE-024: Pembrolizumab versus platinum-based chemotherapy for advanced non-small-cell lung cancer with PD-L1 tumor proportion score of 50% or greater. J Clin Oncol, 2019, 37(7): 537-546.
55.	Drilon A, Oxnard G, Wirth L, et al. PL02.08 registrational results of LIBRETTO-001: A phase 1/2 trial of LOXO-292 in patients with RET fusion-positive lung cancers. J Thorac Oncol, 2019, 14(10): S6-S7.
56.	Tsao M-S, Sakurada A, Cutz J-C, et al. Erlotinib in lung cancer—Molecular and clinical predictors of outcome. N Engl J Med, 2005, 353(2): 133-144.
57.	Solomon BJ, Besse B, Bauer TM, et al. Lorlatinib in patients with ALK-positive non-small-cell lung cancer: Results from a global phase 2 study. Lancet Oncol, 2018, 19(12): 1654-1667.
58.	Peters S, Camidge DR, Shaw AT, et al. Alectinib versus crizotinib in untreated ALK-positive non-small-cell lung cancer. N Engl J Med, 2017, 377(9): 829-838.
59.	Wu S-G, Shih J-Y. Management of acquired resistance to EGFR TKI-targeted therapy in advanced non-small cell lung cancer. Mol Cancer, 2018, 17(1): 38.
60.	Qiao M, Jiang T, Liu X, et al. Immune checkpoint inhibitors in EGFR-mutated NSCLC: Dusk or dawn? J Thorac Oncol, 2021, 16(8): 1267-1288.
61.	Isomoto K, Haratani K, Hayashi H, et al. Impact of EGFR-TKI treatment on the tumor immune microenvironment in EGFR mutation-positive non-small cell lung cancer. Clin Cancer Res, 2020, 26(8): 2037-2046.

1. 中华医学会, 中华医学会肿瘤学分会, 中华医学会杂志社. 中华医学会肺癌临床诊疗指南(2018版). 中华肿瘤杂志, 2018, 40(12): 935-964.
2. 中华医学会肿瘤学分会, 中华医学会杂志社. 中华医学会肺癌临床诊疗指南(2023版). 中华医学杂志, 2023, 103(27): 2037-2074.
3. Aberle DR, Adams AM, Berg CD, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med, 2011, 365(5): 395-409.
4. de Koning HJ, van der Aalst CM, de Jong PA, et al. Reduced lung-cancer mortality with volume CT screening in a randomized trial. N Engl J Med, 2020, 382(6): 503-513.
5. Potter AL, Rosenstein AL, Kiang MV, et al. Association of computed tomography screening with lung cancer stage shift and survival in the United States: Quasi-experimental study. BMJ, 2022, 376: e069008.
6. Guisier F, Deslee G, Birembaut P, et al. Endoscopic follow-up of low-grade precancerous bronchial lesions in high-risk patients: Long-term results of the SELEPREBB randomised multicentre trial. Eur Respir J, 2022, 60(3): 2101946.
7. Ziegelmayer S, Graf M, Makowski M, et al. Cost-effectiveness of artificial intelligence support in computed tomography-based lung cancer screening. Cancers, 2022, 14(7): 1729.
8. Adams SJ, Mondal P, Penz E, et al. Development and cost analysis of a lung nodule management strategy combining artificial intelligence and lung-RADS for baseline lung cancer screening. J Am Coll Radiol, 2021, 18(5): 741-751.
9. Ardila D, Kiraly AP, Bharadwaj S, et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med, 2019, 25(6): 954-961.
10. Hata A, Yanagawa M, Yoshida Y, et al. Combination of deep learning-based denoising and iterative reconstruction for ultra-low-dose CT of the chest: Image quality and lung-RADS evaluation. AJR Am J Roentgenol, 2020, 215(6): 1321-1328.
11. Obuchowski NA, Bullen JA. Statistical considerations for testing an AI algorithm used for prescreening lung CT images. Contemp Clin Trials Commun, 2019, 16: 100434.
12. Setio AAA, Traverso A, de Bel T, et al. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge. Med Image Anal, 2017, 42: 1-13.
13. Jiang B, Li N, Shi X, et al. Deep learning reconstruction shows better lung nodule detection for ultra-low-dose chest CT. Radiology, 2022, 303(1): 202-212.
14. Pehrson LM, Nielsen MB, Ammitzbøl Lauridsen C. Automatic pulmonary nodule detection applying deep learning or machine learning algorithms to the LIDC-IDRI database: A systematic review. Diagnostics, 2019, 9(1): 29.
15. Cui X, Zheng S, Heuvelmans MA, et al. Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program. Eur J Radiol, 2022, 146: 110068.
16. Venkadesh KV, Setio AAA, Schreuder A, et al. Deep learning for malignancy risk estimation of pulmonary nodules detected at low-dose screening CT. Radiology, 2021, 300(2): 438-447.
17. Baldwin DR, Gustafson J, Pickup L, et al. External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules. Thorax, 2020, 75(4): 306-312.
18. Li D, Mikela Vilmun B, Frederik Carlsen J, et al. The performance of deep learning algorithms on automatic pulmonary nodule detection and classification tested on different datasets that are not derived from LIDC-IDRI: A systematic review. Diagnostics, 2019, 9(4): 207.
19. Zhang Y, Liu W, Zhang H, et al. Extracellular vesicle long RNA markers of early-stage lung adenocarcinoma. Int J Cancer, 2023, 152(7): 1490-1500.
20. Sozzi G, Boeri M, Rossi M, et al. Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: A correlative MILD trial study. J Clin Oncol, 2014, 32(8): 768-773.
21. Sullivan FM, Mair FS, Anderson W, et al. Earlier diagnosis of lung cancer in a randomised trial of an autoantibody blood test followed by imaging. Eur Respir J, 2021, 57(1): 2000670.
22. Nicholson AG, Tsao MS, Beasley MB, et al. The 2021 WHO classification of lung tumors: Impact of advances since 2015. J Thorac Oncol, 2022, 17(3): 362-387.
23. Ruparel M, Quaife SL, Dickson JL, et al. Lung Screen Uptake Trial: Results from a single lung cancer screening round. Thorax, 2020, 75(10): 908-912.
24. Van Hal G, Diab Garcia P. Lung cancer screening: Targeting the hard to reach—A review. Transl Lung Cancer Res, 2021, 10(5): 2309-2322.
25. Van Meerbeeck JP, O'Dowd E, Ward B, et al. Lung cancer screening: New perspective and challenges in Europe. Cancers, 2022, 14(9): 2343.
26. Baine MK, Hsieh M-S, Lai WV, et al. SCLC subtypes defined by ASCL1, NEUROD1, POU2F3, and YAP1: A comprehensive immunohistochemical and histopathologic characterization. J Thorac Oncol, 2020, 15(12): 1823-1835.
27. Gandhi JS, Alnoor F, Sadiq Q, et al. SMARCA4 (BRG1) and SMARCB1 (INI1) expression in TTF-1 negative neuroendocrine carcinomas including merkel cell carcinoma. Pathol Res Pract, 2021, 219: 153341.
28. La Fleur L, Falk-Sörqvist E, Smeds P, et al. Mutation patterns in a population-based non-small cell lung cancer cohort and prognostic impact of concomitant mutations in KRAS and TP53 or STK11. Lung Cancer, 2019, 130: 50-58.
29. NSCLC Meta-analysis Collaborative Group. Preoperative chemotherapy for non-small-cell lung cancer: A systematic review and meta-analysis of individual participant data. Lancet, 2014, 383(9928): 1561-1571.
30. Forde PM, Spicer J, Lu S, et al. Neoadjuvant nivolumab plus chemotherapy in resectable lung cancer. N Engl J Med, 2022, 386(21): 1973-1985.
31. Provencio M, Serna-Blasco R, Nadal E, et al. Overall survival and biomarker analysis of neoadjuvant nivolumab plus chemotherapy in operable stage ⅢA non-small-cell lung cancer (NADIM phase Ⅱ trial). J Clin Oncol, 2022, 40(25): 2924-2933.
32. Provencio M, Nadal E, González-Larriba JL, et al. Perioperative nivolumab and chemotherapy in stage Ⅲ non-small-cell lung cancer. N Engl J Med, 2023, 389(6): 504-513.
33. Mazieres J, Drilon A, Lusque A, et al. Immune checkpoint inhibitors for patients with advanced lung cancer and oncogenic driver alterations: Results from the IMMUNOTARGET registry. Ann Oncol, 2019, 30(8): 1321-1328.
34. Soria J-C, Ohe Y, Vansteenkiste J, et al. Osimertinib in untreated EGFR-mutated advanced non-small-cell lung cancer. N Engl J Med, 2018, 378(2): 113-125.
35. Lisberg A, Cummings A, Goldman JW, et al. A phase Ⅱ study of pembrolizumab in EGFR-Mutant, PD-L1+, tyrosine kinase inhibitor naïve patients with advanced NSCLC. J Thorac Oncol, 2018, 13(8): 1138-1145.
36. Camidge DR, Dziadziuszko R, Peters S, et al. Updated efficacy and safety data and impact of the EML4-ALK fusion variant on the efficacy of alectinib in untreated ALK-positive advanced non-small cell lung cancer in the global phase ⅢALEX Study. J Thorac Oncol, 2019, 14(7): 1233-1243.
37. Gainor JF, Dardaei L, Yoda S, et al. Molecular mechanisms of resistance to first- and second-generation ALK inhibitors in ALK-rearranged lung cancer. Cancer Discov, 2016, 6(10): 1118-1133.
38. Zhao J, Zhao L, Guo W, et al. Efficacy, safety, and biomarker analysis of neoadjuvant camrelizumab and apatinib in patients with resectable NSCLC: A phase 2 clinical trial. J Thorac Oncol, 2023, 18(6): 780-791.
39. Tsuboi M, Weder W, Escriu C, et al. Neoadjuvant osimertinib with/without chemotherapy versus chemotherapy alone for EGFR-mutated resectable non-small-cell lung cancer: NeoADAURA. Future Oncol, 2021, 17(31): 4045-4055.
40. Lococo F, Cancellieri A, Chiappetta M, et al. Salvage surgery after first-line alectinib for locally-advanced/metastatic ALK-rearranged NSCLC: Pathological response and perioperative results. Clin Lung Cancer, 2023, 24(5): 467-473.
41. Sentana-Lledo D, Viray H, Piper-Vallillo AJ, et al. Complete pathologic response to short-course neoadjuvant alectinib in mediastinal node positive (N2) ALK rearranged lung cancer. Lung Cancer, 2022, 172: 124-126.
42. Altorki N, Wang X, Kozono D, et al. Lobar or sublobar resection for peripheral stage ⅠA non-small-cell lung cancer. N Engl J Med, 2023, 388(6): 489-498.
43. Saji H, Okada M, Tsuboi M, et al. Segmentectomy versus lobectomy in small-sized peripheral non-small-cell lung cancer (JCOG0802/WJOG4607L): A multicentre, open-label, phase 3, randomised, controlled, non-inferiority trial. Lancet, 2022, 399(10335): 1607-1617.
44. Aokage K, Suzuki K, Saji H, et al. Segmentectomy for ground-glass-dominant lung cancer with a tumour diameter of 3 cm or less including ground-glass opacity (JCOG1211): A multicentre, single-arm, confirmatory, phase 3 trial. Lancet Respir Med, 2023, 11(6): 540-549.
45. Suzuki K, Watanabe S-I, Wakabayashi M, et al. A single-arm study of sublobar resection for ground-glass opacity dominant peripheral lung cancer. J Thorac Cardiovasc Surg, 2022, 163(1): 289-301.
46. Tsuboi M, Herbst RS, John T, et al. Overall survival with osimertinib in resected EGFR-mutated NSCLC. N Engl J Med, 2023, 389(2): 137-147.
47. Strauss GM, Herndon JE, Maddaus MA, et al. Adjuvant paclitaxel plus carboplatin compared with observation in stage ⅠB non-small-cell lung cancer: CALGB 9633 with the Cancer and Leukemia Group B, Radiation Therapy Oncology Group, and North Central Cancer Treatment Group Study Groups. J Clin Oncol, 2008, 26(31): 5043-5051.
48. Butts CA, Ding K, Seymour L, et al. Randomized phase Ⅲtrial of vinorelbine plus cisplatin compared with observation in completely resected stageⅠB andⅡnon-small-cell lung cancer: Updated survival analysis of JBR-10. J Clin Oncol, 2010, 28(1): 29-34.
49. Qian F, Yang W, Wang R, et al. Prognostic significance and adjuvant chemotherapy survival benefits of a solid or micropapillary pattern in patients with resected stage ⅠB lung adenocarcinoma. J Thorac Cardiovasc Surg, 2018, 155(3): 1227-1235.
50. Hong L, Negrao MV, Dibaj SS, et al. Programmed death-ligand 1 heterogeneity and its impact on benefit from immune checkpoint inhibitors in NSCLC. J Thorac Oncol, 2020, 15(9): 1449-1459.
51. Mok TSK, Wu YL, Kudaba I, et al. Pembrolizumab versus chemotherapy for previously untreated, PD-L1-expressing, locally advanced or metastatic non-small-cell lung cancer (KEYNOTE-042): A randomised, open-label, controlled, phase 3 trial. Lancet, 2019, 393(10183): 1819-1830.
52. O'Brien M, Paz-Ares L, Marreaud S, et al. Pembrolizumab versus placebo as adjuvant therapy for completely resected stage ⅠB-ⅢA non-small-cell lung cancer (PEARLS/KEYNOTE-091): An interim analysis of a randomised, triple-blind, phase 3 trial. Lancet Oncol, 2022, 23(10): 1274-1286.
53. Zhou Q, Chen M, Jiang O, et al. Sugemalimab versus placebo after concurrent or sequential chemoradiotherapy in patients with locally advanced, unresectable, stageⅢ non-small-cell lung cancer in China (GEMSTONE-301): Interim results of a randomised, double-blind, multicentre, phase 3 trial. Lancet Oncol, 2022, 23(2): 209-219.
54. Reck M, Rodríguez-Abreu D, Robinson AG, et al. Updated analysis of KEYNOTE-024: Pembrolizumab versus platinum-based chemotherapy for advanced non-small-cell lung cancer with PD-L1 tumor proportion score of 50% or greater. J Clin Oncol, 2019, 37(7): 537-546.
55. Drilon A, Oxnard G, Wirth L, et al. PL02.08 registrational results of LIBRETTO-001: A phase 1/2 trial of LOXO-292 in patients with RET fusion-positive lung cancers. J Thorac Oncol, 2019, 14(10): S6-S7.
56. Tsao M-S, Sakurada A, Cutz J-C, et al. Erlotinib in lung cancer—Molecular and clinical predictors of outcome. N Engl J Med, 2005, 353(2): 133-144.
57. Solomon BJ, Besse B, Bauer TM, et al. Lorlatinib in patients with ALK-positive non-small-cell lung cancer: Results from a global phase 2 study. Lancet Oncol, 2018, 19(12): 1654-1667.
58. Peters S, Camidge DR, Shaw AT, et al. Alectinib versus crizotinib in untreated ALK-positive non-small-cell lung cancer. N Engl J Med, 2017, 377(9): 829-838.
59. Wu S-G, Shih J-Y. Management of acquired resistance to EGFR TKI-targeted therapy in advanced non-small cell lung cancer. Mol Cancer, 2018, 17(1): 38.
60. Qiao M, Jiang T, Liu X, et al. Immune checkpoint inhibitors in EGFR-mutated NSCLC: Dusk or dawn? J Thorac Oncol, 2021, 16(8): 1267-1288.
61. Isomoto K, Haratani K, Hayashi H, et al. Impact of EGFR-TKI treatment on the tumor immune microenvironment in EGFR mutation-positive non-small cell lung cancer. Clin Cancer Res, 2020, 26(8): 2037-2046.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Chinese Medical Association guideline for clinical diagnosis and treatment of lung cancer (2023 edition): An interpretation

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