[Expert Consensus on Precision Management of Pulmonary Nodules (2026 Version)].

Authors

Juan Zhou, Yudong Zhang, Qinghua Zhou, Chang Chen, Chunxia Su, Editorial Committee of Consensus on Precision Management of Pulmonary Nodules (2026 Version)

Published in

Zhongguo fei ai za zhi = Chinese journal of lung cancer. Volume 29. Issue 5. Pages 315-331. May 20, 2026.

Abstract

With the wide application of low-dose spiral computed tomography and the advancement of imaging technology, the detection rate of pulmonary nodules has significantly increased. However, the traditional "one-size-fits-all" management strategy has been unable to meet the needs of precise diagnosis and treatment. This expert consensus was initiated by Professor Chunxia SU's team and Professor Chang CHEN's team from Shanghai Pulmonary Hospital and jointly formulated by experts from multiple disciplines including oncology, respiratory medicine, thoracic surgery, interventional medicine, radiology, and pathology. The aim is to provide scientific and practical decision-making references for clinical controversies that are less addressed or have differences in existing guidelines. The consensus uses the GRADE method for evidence assessment and forms 18 recommendations through two rounds of Delphi questionnaire surveys, focusing on differentiated screening for special populations, artificial intelligence assisted diagnosis, robot-assisted puncture, application of molecular markers, active monitoring of low-risk nodules, timing of invasive intervention, termination conditions of follow-up, management strategies for multiple nodules, and selection of individualized lymph node dissection range and surgical methods for early-stage lung cancer. This consensus would provides supplementary guidance for the entire process of precise management of pulmonary nodules from screening to treatment, with expectation of improving the long-term survival rate of lung cancer patients while minimizing unnecessary medical interventions and enhancing the quality of life of patients.
.

PMID:
42452861
Bibliographic data and abstract were imported from PubMed on 15 Jul 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.