Evidence map›Paper›PMID 37627933›Full record

ReviewDiagnostics (Basel, Switzerland)2023

Managing Persistent Subsolid Nodules in Lung Cancer: Education, Decision Making, and Impact of Interval Growth Patterns.

Yung-Chi Liu, Chia-Hao Liang, Yun-Ju Wu, Chi-Shen Chen, En-Kuei Tang, Fu-Zong Wu

Open access · goldAbstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 2 countries.

Yung-Chi LiuDepartment of Radiology, Xiamen Chang Gung Hospital, Xiamen 361028, China.
Chia-Hao LiangDepartment of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei 112304, Taiwan.
Yun-Ju WuDepartment of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung 81362, Taiwan.
Chi-Shen ChenPhysical Examination Center, Kaohsiung Veterans General Hospital, Kaohsiung 81362, Taiwan.
En-Kuei TangDepartment of Surgery, Kaohsiung Veterans General Hospital, Kaohsiung 813414, Taiwan.ORCID 0000-0001-8721-8173
Fu-Zong WuDepartment of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung 81362, Taiwan.ORCID 0000-0003-2556-6118
Kaohsiung Veterans General Hospital · TWNational Kaohsiung Normal University · TWNational Sun Yat-sen University · TWNational Yang Ming Chiao Tung University · TWXiamen Chang Gung Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the popularization of lung cancer screening, many persistent subsolid nodules (SSNs) have been identified clinically, especially in Asian non-smokers. However, many studies have found that SSNs exhibit heterogeneous growth trends during long-term follow ups. This article adopted a narrative approach to extensively review the available literature on the topic to explore the definitions, rationale, and clinical application of different interval growths of subsolid pulmonary nodule management and follow-up strategies. The development of SSN growth thresholds with different growth patterns could support clinical decision making with follow-up guidelines to reduce over- and delayed diagnoses. In conclusion, using different SSN growth thresholds could optimize the follow-up management and clinical decision making of SSNs in lung cancer screening programs. This could further reduce the lung cancer mortality rate and potential harm from overdiagnosis and over management.

Indexed as

interval growthlung canceroverdiagnosissubsolid nodules

Identifiers

PMID37627933
PMCPMC10453827
OpenAlexW4385795932

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.