Evidence map›Paper›PMID 40248725›Full record

ArticleTranslational lung cancer research2025

Nomogram based on computed tomography radiomics features and clinicopathological factors to predict the prognosis of patients with non-small cell lung cancer receiving immune checkpoint inhibitor rechallenge.

Junfeng Zhao, Ying Li, Ruyue Li, Xiujing Yao, Xue Dong, Lin Su, Yintao Li

Abstract read
In one paragraph

Article in Translational lung cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
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4 · The record

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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

7 authors.

Junfeng Zhao *Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.ORCID https://orcid.org/0009-0000-1935-9214
Ying Li *Department of Respiratory Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.ORCID https://orcid.org/0009-0006-8813-133X
Ruyue LiDepartment of Respiratory Oncology, Shandong Cancer Hospital and Institute, Affiliated Hospital of Weifang Medical University, School of Clinical Medicine, Weifang Medical University, Weifang, China.
Xiujing YaoDepartment of Respiratory Oncology, Shandong Cancer Hospital and Institute, Affiliated Hospital of Weifang Medical University, School of Clinical Medicine, Weifang Medical University, Weifang, China.
Xue DongDepartment of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Lin SuDepartment of Respiratory Medicine, Jinan Fourth People's Hospital, Jinan, China.
Yintao LiDepartment of Respiratory Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.ORCID https://orcid.org/0000-0003-4665-8900

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Whether patients with advanced non-small cell lung cancer (NSCLC) who experience progressive disease (PD) after the initial immunotherapy treatment benefit from subsequent immunotherapy remains unclear. In this study, we aimed to identify predictive factors and develop a nomogram to predict successful immunotherapy rechallenge for such patients with NSCLC to guide clinical treatment and improve prognosis. Methods: Between January 2019 and December 2022, 352 patients with advanced NSCLC who received immunotherapy rechallenge after experiencing PD were divided into the training (n=246) and validation (n=106) cohorts. Clinicopathological factors and radiomics features were included in the univariate and multivariate analyses, with significant predictive factors being used to develop the nomogram. Results: Univariate and multivariate analyses showed that time from the initial immunotherapy to PD occurrence (duration), clinical N stage, liver metastasis, treatment after PD following the first immunotherapy (post-PD treatment), and radiomics features were independent predictive factors for progression-free survival (PFS). In addition, age, duration, clinical N stage, post-PD treatment, and radiomics were independent predictive factors for overall survival (OS). Accordingly, these predictive factors were used to develop a nomogram. The area under the curves (AUCs) of the nomogram for predicting 6-, 12-, and 18-month PFS and 12-, 18-, and 24-month OS were 0.731, 0.809, 0.878, 0.742, 0.782, and 0.868, respectively, in the training cohorts, whereas the corresponding values in the validation cohort were 0.672, 0.774, 0.826, 0.833, 0.705, and 0.762. This indicated good discrimination. Conclusions: We developed and validated a predictive nomogram based on clinicopathological factors and radiomics features for the prognosis of patients with advanced NSCLC who received immunotherapy rechallenge following PD after the first immunotherapy. The nomogram showed strong predictive utility and can be a suitable tool for such patients with advanced NSCLC.

Indexed as

Antiangiogenic therapyimmune checkpoint inhibitor (ICI)immunotherapynomogramnon-small cell lung cancer (NSCLC)

Identifiers

PMID40248725
PMCPMC12000940

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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.