Evidence map›Paper›PMID 37204513›Full record

ArticleJournal of cancer research and clinical oncology2023

Radiomics nomogram for the prediction of Ki-67 index in advanced non-small cell lung cancer based on dual-phase enhanced computed tomography.

Haitao Sun, Peng Zhou, Guoyue Chen, Zhengjun Dai, Peiji Song, Jian Yao

Abstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Haitao SunMedical Imaging Center, Central Hospital Affiliated to Shandong First Medical University, 105 Jiefang Road, Lixia District, Jinan, 250013, Shandong, China.
Peng ZhouMedical Imaging Center, Central Hospital Affiliated to Shandong First Medical University, 105 Jiefang Road, Lixia District, Jinan, 250013, Shandong, China.
Guoyue ChenMedical Imaging Center, Central Hospital Affiliated to Shandong First Medical University, 105 Jiefang Road, Lixia District, Jinan, 250013, Shandong, China.
Zhengjun DaiScientific Research Department of Huiying Medical Technology Co., Ltd, 66 Xixiaokou Road, Haidian District, Beijing, 100192, China.
Peiji SongMedical Imaging Center, Central Hospital Affiliated to Shandong First Medical University, 105 Jiefang Road, Lixia District, Jinan, 250013, Shandong, China.
Jian YaoMedical Imaging Center, Central Hospital Affiliated to Shandong First Medical University, 105 Jiefang Road, Lixia District, Jinan, 250013, Shandong, China. radiologistyj@163.com.ORCID http://orcid.org/0009-0000-4682-4433

Funding

National Funds for Guiding Local Scientific and Technological Development YDZX2021012
6 · The paper itself

Abstract

purposeTo develop a radiomics nomogram based on dual-phase enhanced computed tomography (CT) for predicting the Ki-67 index status in patients with advanced non-small cell lung cancer (NSCLC).

methods137 patients with NSCLC who had undergone dual-phase enhanced CT scans and Ki-67 examination within 2 weeks were retrospectively enrolled between January 2020 and December 2022. Clinical and laboratory data were collected, and the patients were categorized based on low or high expression of Ki-67 index, with a cut-off value of 40%. The cohort was randomly divided into a training group (n = 95) and a testing group (n = 42) at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was employed to select the most valuable radiomics features from the dual-phase enhanced CT images. Subsequently, a nomogram that incorporated the radiomics score and clinical factors associated with Ki-67 index status was established through univariate and multivariate logistic regression analyses. The predictive performance of the nomogram was evaluated using the area under the curve (AUC).

resultsThe AUC values of the radiomics features of artery phase and vein phase CT in the testing group were 0.748 and 0.758, respectively. The AUC of the dual-phase enhanced CT was 0.785, and the AUC of the developed nomogram was 0.859, which was higher than those of the radiomics (AUC, 0.785) and clinical models (AUC, 0.736).

conclusionsThe radiomics nomogram based on dual-phase enhanced CT images provides a promising method for predicting the Ki-67 index status in patients with advanced NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsHumansKi-67 AntigenNomogramsRetrospective StudiesTomography, X-Ray ComputedKi-67 AntigenComputed tomographyKi-67NomogramNon-small cell lung cancerRadiomics

Identifiers

PMID37204513
PMCPMC11798201

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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.