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中华肺部疾病杂志(电子版) ›› 2022, Vol. 15 ›› Issue (01) : 11 -14. doi: 10.3877/cma.j.issn.1674-6902.2022.01.003

论著

肺结节与肺癌全程智能管理云平台的构建及临床应用
杨丽1, 王婷1, 敖敏1, 李维益1, 刘迅2, 秦明2, 郭述良1,()   
  1. 1. 400016 重庆,重庆医科大学附属第一医院呼吸与危重症医学科
    2. 401120 重庆,自由呼吸(重庆)科技有限公司
  • 收稿日期:2021-10-05 出版日期:2022-02-25
  • 通信作者: 郭述良
  • 基金资助:
    重庆市科学技术局技术创新与应用发展专项面上项目(cstc2019jscx-msxmX0184); 重庆医科大学附属第一医院学科创新基金学科培育项目(XKST134)

Construction and clinical application of cloud platform for intelligent management of lung nodules and lung cancer

Li Yang1, Ting Wang1, Min Ao1, Weiyi Li1, Xun Liu2, Ming Qin2, Shuliang Guo1,()   

  1. 1. Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
    2. Breathfree (Chongqing) Technology Company, Chongqing 400000, China
  • Received:2021-10-05 Published:2022-02-25
  • Corresponding author: Shuliang Guo
引用本文:

杨丽, 王婷, 敖敏, 李维益, 刘迅, 秦明, 郭述良. 肺结节与肺癌全程智能管理云平台的构建及临床应用[J/OL]. 中华肺部疾病杂志(电子版), 2022, 15(01): 11-14.

Li Yang, Ting Wang, Min Ao, Weiyi Li, Xun Liu, Ming Qin, Shuliang Guo. Construction and clinical application of cloud platform for intelligent management of lung nodules and lung cancer[J/OL]. Chinese Journal of Lung Diseases(Electronic Edition), 2022, 15(01): 11-14.

目的

我国肺癌患病率、病死率稳居恶性肿瘤第一位。创建肺结节与肺癌全程管理模式,将肺结节纳入规范诊疗体系,以期实现肺癌早诊早治,提高患者复诊依从性。

方法

构建肺结节与肺癌全程智能管理云平台,建立恶性肺结节队列、良性肺结节队列和未确诊肺结节规律随访队列。收集人口统计学、影像、病理、疗效等信息,通过全程管理后分析人群特征、诊治精准性与复诊率。

结果

创建了基于重庆市肺结节管理工作室的肺结节与肺癌全程智能管理云平台。2019年1月至2021年12月期间,纳入全程管理的肺结节与肺癌患者共5 144例,确诊肺结节1 546例(30.05%),其中恶性1 194例,良性352例;Ia期肺癌占确诊肺癌的(80.80%);随访中肺结节3 598例(69.95%)。2019年进入平台登记管理后未确诊的肺结节,有≥1次复诊记录的患者652例(74.86%);2020年667例(65.67%);2021年245例(13.94%)。

结论

建立肺结节与肺癌全程智能管理云平台有利于提高恶性肺结节早诊早治率与患者依从性,促进患者自我健康管理模式养成,改善肺癌预后,值得尝试。

Objective

Lung cancer is the most common cause of death with malignant tumor in China. The whole-process management mode of lung nodules and lung cancer was established, and lung nodules were included in the standardized diagnosis and treatment system, aim to improve the rate of early diagnosis and treatment for lung cancer, compliance of patients with following up.

Methods

A cloud platform for the whole-process intelligent management of pulmonary nodules and lung cancer was constructed. Malignant pulmonary nodules, benign pulmonary nodules and undiagnosed pulmonary nodules queues were established. Demographic, imaging, pathological, curative effect and other information were collected, and population characteristics, diagnosis and treatment accuracy and return visit rate were analyzed after the whole process of management.

Results

A cloud platform for whole-process intelligent management of pulmonary nodules and lung cancer was established based on Chongqing Pulmonary Nodules Management Studio. From January 2019 to December 2021, a total of 5 144 patients with pulmonary nodules and lung cancer were included in the whole-course management. 1 546 patients (30.05%) were confirmed including 1 194 malignant cases and 352 benign cases. Lung cancer with Stage Ia was accounted for 80.80%. 3 598 patients(69.95%)with lung nodules in follow up. Among undiagnosed pulmonary nodules after entering the platform registration management in 2019, the proportion of patients with ≥1 following-up was 74.86%. 667 patients (65.67%) in 2020. 245 patients (13.94%) in 2021.

Conclusion

The establishment of the cloud platform for the whole-process intelligent management of pulmonary nodules and lung cancer is beneficial to improve the rate of early diagnosis and treatment of malignant pulmonary nodules and patient compliance, promote the development of self-health management mode of patients and the prognosis of lung cancer, which is worthy of further promotion.

图1 肺结节与肺癌全程智能管理云平台登记流程图
图2 确诊肺结节的良恶性病理类型分布结果
表1 肺结节与肺癌云平台全程管理患者诊治结果(%)
1
Bray Freddie, Ferlay Jacques, Soerjomataram Isabelle, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2018, 68(6): 394-424.
2
Murakami Shuji, Ito Hiroyuki, Tsubokawa Norifumi, et al. Prognostic value of the new IASLC/ATS/ERS classification of clinical stage IA lung adenocarcinoma[J]. Lung Cancer, 2015, 90(2): 199-204.
3
中华医学会呼吸病学分会肺癌学组,中国肺癌防治联盟专家组. 肺部结节诊治中国专家共识 [J]. 中华结核和呼吸杂志2015, 38(4): 249-255.
4
National Lung Screening Trial Research Team, Aberle Denise R, Adams Amanda M, et al. National lung screening trial research team. reduced lung-cancer mortality with low-dose computed tomographic screening[J]. N Engl J Med, 2011, 365(5): 395-409.
5
Field JK, , Duffy SW, Baldwin DR, et al. UK Lung Cancer RCT Pilot Screening Trial: baseline findings from the screening arm provide evidence for the potential implementation of lung cancer screening[J]. Thorax, 2016, 71(2): 161-70.
6
van Klaveren Rob J, Oudkerk Matthijs, Prokop Mathias, et al. Management of lung nodules detected by volume CT scanning[J]. N Engl J Med, 2009, 361(23): 2221-2229.
7
Zeng Hongmei, Chen Wanqing, Zheng Rongshou, et al. Changing cancer survival in China during 2003-15: a pooled analysis of 17 population-based cancer registries[J]. Lancet Glob Health, 2018, 6(5): e555.
8
Oudkerk Matthijs, Liu ShiYuan, Heuvelmans Marjolein A, et al. Lung cancer LDCT screening and mortality reduction evidence, pitfalls and future perspectives[J]. Nat Rev Clin Oncol, 2021, 18(3): 135-151.
9
Sullivan Donald R, Golden Sara E, Ganzini Linda, et al. 'I still don’t know diddly’:a longitudinal qualitative study of patients’ knowledge and distress while undergoing evaluation of incidental pulmonary nodules[J]. NPJ Prim Care Respir Med, 2015, 25: 15028.
10
刘 丹,黄 燕,周清华,等. 肺结节/肺癌患者全程管理模式的设计与应用[J]. 中国肺癌杂志2020, 23(5): 299-305.
11
Ye Xin, Fan Weijun, Wang Hui, et al. Expert consensus workshop report: Guidelines for thermal ablation of primary and metastatic lung tumors (2018 edition)[J]. J Cancer Res Ther, 2018, 14(4): 730-744.
12
Zhao Ze-Rui, Situ Dong-Rong, Lau Rainbow WH, et al. Comparison of segmentectomy and lobectomy in stage IA adenocarcinomas[J]. J Thorac Oncol, 2017, 12(5): 890-896.
13
Hong Qun-Ying, Wu Guo-Ming, Qian Gui-Sheng, et al. Prevention and management of lung cancer in China[J]. Cancer, 2015, 121(Suppl 17): 3080-3088.
14
Shi Ju-Fang, Wang Le, Wu Ning, et al. Clinical characteristics and medical service utilization of lung cancer in China, 2005-2014: Overall design and results from a multicenter retrospective epidemiologic survey[J]. Lung Cancer, 2019, 128: 91-100.
15
Leung Clarus, Shaipanich Tawimas. Current practice in the management of pulmonary nodules detected on computed tomography chest scans[J]. Can Respir J, 2019, 2019: 9719067.
16
Stokes Sean M, Massarweh Nader N, Stringham John R, et al. Clinical-pathologic correlation and guideline concordance in resectable non-small cell lung cancer[J]. Ann Thorac Surg, 2019, 108(3): 837-844.
17
Kerpel-Fronius Anna, Tammemägi Martin, Cavic Milena, et al. Screening for lung cancer in individuals who never smoked: an international association for the study of lung cancer early detection and screening committee report[J]. J Thorac Oncol, 2022, 17(1): 56-66.
18
Network, N.C.C., NCCN clinical practice guidelines in oncology (NCCN Guidelines) lung cancer screening version 1.2021. 2021.
19
US Preventive Services Task Force, Krist Alex H, Davidson Karina W,et al. Screening for lung cancer: US preventive services task force recommendation statement[J]. Jama, 2021, 325(10): 962-969.
20
Bai Chunxue, Choi Chang-Min, Chu Chung Ming, et al. Evaluation of pulmonary nodules: clinical practice consensus guidelines for asia[J]. Chest, 2016, 150(4): 877-893.
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