Evidence map›Paper›PMID 37990211›Full record

ArticleBMC pulmonary medicine2023

Factors associated with overdiagnosis of benign pulmonary nodules as malignancy: a retrospective cohort study.

Xirui Duan, Zhiqiang Ouyang, Shasha Bao, Lu Yang, Ailin Deng, Guangrong Zheng, Yu Zhu, Guochen Li, Jixiang Chu, Chengde Liao

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC pulmonary medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Xirui Duan *Department of Radiology, Yan'an Hospital of Kunming City (Yan'an Hospital Affiliated to Kunming Medical University; Yunnan Cardiovascular Hospital), Kunming, China.
Zhiqiang Ouyang *Department of Radiology, Yan'an Hospital of Kunming City (Yan'an Hospital Affiliated to Kunming Medical University; Yunnan Cardiovascular Hospital), Kunming, China.
Shasha BaoDepartment of Radiology, Yan'an Hospital of Kunming City (Yan'an Hospital Affiliated to Kunming Medical University; Yunnan Cardiovascular Hospital), Kunming, China.
Lu YangDepartment of Radiology, Yunnan Cancer Hospital/Center, Third Affiliated Hospital of Kunming Medical University, Kunming, China.
Ailin DengDepartment of Radiology, Yunnan Cancer Hospital/Center, Third Affiliated Hospital of Kunming Medical University, Kunming, China.
Guangrong ZhengDepartment of Radiology, Yan'an Hospital of Kunming City (Yan'an Hospital Affiliated to Kunming Medical University; Yunnan Cardiovascular Hospital), Kunming, China.
Yu ZhuDepartment of Radiology, Yunnan Cancer Hospital/Center, Third Affiliated Hospital of Kunming Medical University, Kunming, China.
Guochen LiDepartment of Radiology, Yan'an Hospital of Kunming City (Yan'an Hospital Affiliated to Kunming Medical University; Yunnan Cardiovascular Hospital), Kunming, China.
Jixiang ChuDepartment of Radiology, Yunnan Cancer Hospital/Center, Third Affiliated Hospital of Kunming Medical University, Kunming, China.
Chengde LiaoDepartment of Radiology, Yan'an Hospital of Kunming City (Yan'an Hospital Affiliated to Kunming Medical University; Yunnan Cardiovascular Hospital), Kunming, China. 846681160@qq.com.
Kunming Medical University · CNFuwai Yunnan Cardiovascular Hospital · CNYan'an Hospital Affiliated To Kunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo establish a preoperative model for the differential diagnosis of benign and malignant pulmonary nodules (PNs), and to evaluate the related factors of overdiagnosis of benign PNs at the time of imaging assessments. MATERIALS AND

methodsIn this retrospective study, 357 patients (median age, 52 years; interquartile range, 46-59 years) with 407 PNs were included, who underwent surgical histopathologic evaluation between January 2020 and December 2020. Patients were divided into a training set (n = 285) and a validation set (n = 122) to develop a preoperative model to identify benign PNs. CT scan features were reviewed by two chest radiologists, and imaging findings were categorized. The overdiagnosis rate of benign PNs was calculated, and bivariate and multivariable logistic regression analyses were used to evaluate factors associated with benign PNs that were over-diagnosed as malignant PNs.

resultsThe preoperative model identified features such as the absence of part-solid and non-solid nodules, absence of spiculation, absence of vascular convergence, larger lesion size, and CYFRA21-1 positivity as features for identifying benign PNs on imaging, with a high area under the receiver operating characteristic curve of 0.88 in the validation set. The overdiagnosis rate of benign PNs was found to be 50%. Independent risk factors for overdiagnosis included diagnosis as non-solid nodules, pleural retraction, vascular convergence, and larger lesion size at imaging.

conclusionWe developed a preoperative model for identifying benign and malignant PNs and evaluating factors that led to the overdiagnosis of benign PNs. This preoperative model and result may help clinicians and imaging physicians reduce unnecessary surgery.

Indexed as

Lung NeoplasmsMultiple Pulmonary NodulesAntigens, NeoplasmHumansKeratin-19Middle AgedOverdiagnosisRetrospective Studiesantigen CYFRA21.1Antigens, NeoplasmKeratin-19Benign pulmonary nodulesImaging featuresMalignant pulmonary nodulesOverdiagnosisPreoperative model

Identifiers

PMID37990211
PMCPMC10664309
OpenAlexW4388866018

What OpenQuestion holds

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LicenceCC BY
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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.