Evidence map›Paper›PMID 39103468›Full record

ArticleScientific reports2024

Nomogram model for the diagnosis of solitary nodular pulmonary mucinous adenocarcinoma.

Feiyang Zhong, Lijun Wu, Zhenxing Liu, Wenping Li, Shaohong Zhao

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2024. 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Feiyang Zhong *Department of Radiology, The First Medical Center of the Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
Lijun Wu *Department of Radiology, The First Medical Center of the Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
Zhenxing LiuDepartment of Neurology, Yiling Hospital of Yichang City, Yichang, Hubei, China.
Wenping LiDepartment of Radiology, The Sixth Medical Center of the Chinese PLA General Hospital, Beijing, China.
Shaohong ZhaoDepartment of Radiology, The First Medical Center of the Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China. zhaoshaohong@aliyun.com.

Funding

Special project of health development and scientific research in capital 2022-2-5023
6 · The paper itself

Abstract

The objective of this study was to develop a nomogram model based on the natural progression of tumor and other radiological features to discriminate between solitary nodular pulmonary mucinous adenocarcinoma and non-mucinous adenocarcinomas. A retrospective analysis was conducted on 15,655 cases of lung adenocarcinoma diagnosed at our institution between January 2010 and June 2023. Primary nodular invasive mucinous adenocarcinomas and non-mucinous adenocarcinomas with at least two preoperative CT scans were included. These patients were randomly assigned to training and validation sets. Univariate and multivariate analyses were employed to compare tumor growth rates and clinical radiological characteristics between the two groups in the training set. A nomogram model was constructed based on the results of multivariate analysis. The diagnostic value of the model was evaluated in both the training and validation sets using calibration curves and receiver operating characteristic curves (ROC). The study included 174 patients, with 58 cases of mucinous adenocarcinoma and 116 cases of non-mucinous adenocarcinoma. The nomogram model incorporated the maximum tumor diameter, the consolidation/tumor ratio (CTR), and the specific growth rate (SGR) to generate individual scores for each patient, which were then accumulated to obtain a total score indicative of the likelihood of developing mucinous or non-mucinous adenocarcinoma. The model demonstrated excellent discriminative ability with an area under the receiver operating characteristic curve of 0.784 for the training set and 0.833 for the testing set. The nomogram model developed in this study, integrating SGR with other radiological and clinical parameters, provides a valuable and accurate tool for differentiating between solitary nodular pulmonary mucinous adenocarcinoma and non-mucinous adenocarcinomas. This prognostic model offers a robust and objective basis for personalized management of patients with pulmonary adenocarcinomas.

Indexed as

Adenocarcinoma, MucinousLung NeoplasmsNomogramsAdenocarcinoma of LungAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveSolitary Pulmonary NoduleTomography, X-Ray ComputedLung cancerPulmonary mucinous adenocarcinomaSpecific growth rateVolume doubling time

Identifiers

PMID39103468
PMCPMC11300590

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