Evidence map›Paper›PMID 39830771›Full record

ArticleTranslational lung cancer research2024

Radiomicsmetabolic signature profiles for advanced non-small cell lung cancer with chemoimmunotherapy by reflecting biological function and survival.

Yuxin Jiang, Tao Liu, Ke Xu, Wanjun Lu, Qinpei Cheng, Jingyuan Xie, Mo Chen, Xiangyu Bian, Tangfeng Lv, Jiang Wu and 2 more

Abstract read
In one paragraph

Article in Translational lung cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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. Review
  2. Review
  3. Journal of translational medicine · 2026
    Article
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

12 authors.

Yuxin Jiang *School of Medicine, Southeast University, Nanjing, China.
Tao Liu *Department of Nuclear Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Ke XuDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Wanjun LuDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Qinpei ChengDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Jingyuan XieDepartment of Respiratory and Critical Care Medicine, the First People's Hospital of Changzhou, the Third Affiliated Hospital of Soochow University, Soochow, China.
Mo ChenDepartment of Respiratory and Critical Care Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Xiangyu BianDepartment of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, China.
Tangfeng LvSchool of Medicine, Southeast University, Nanjing, China.
Jiang WuDepartment of Nuclear Medicine, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Yong SongSchool of Medicine, Southeast University, Nanjing, China.
Ping ZhanSchool of Medicine, Southeast University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Resistance to chemoimmunotherapy in patients with advanced non-small cell lung cancer (NSCLC) necessitates effective prognostic biomarkers. Although Methods: We retrospectively recruited unresectable advanced NSCLC patients receiving immunotherapy in Jinling Hospital from 2018 to 2023 as the training cohort. The Cancer Imaging Archive (TCIA) cohort with early-stage NSCLC patients undergoing surgical resection was used for validation and the assessment of the biological function and tumor microenvironment (TME). PET/CT-based parameters were extracted, including radiomics score (Rad-score), bone marrow to liver ratio (BLR), tMTV, and total lesion glycolysis (TLG). The end-point events included overall survival (OS) and progression-free survival (PFS). Step-wise multivariate Cox regression and the least absolute shrinkage and selection operator (LASSO) were used to identify candidate variables and establish models. Results: A total of 220 patients were identified for analysis, including 139 with unresectable advanced NSCLC receiving immunotherapy and 81 from TCIA. The Radiomicsmetabolicos model for OS encompassing Rad-score >0.705 [hazard ratio (HR) =2.455; 95% confidence interval (CI): 1.324-4.550], squamous cell subtype (HR =1.641; 95% CI: 0.900-2.992), liver metastases (HR =3.496; 95% CI: 1.435-8.517), BLR >0.94 (HR =1.885; 95% CI: 1.013-3.507), and tMTV >105 mL (HR =2.162; 95% CI: 1.134-4.119) exhibited reliable prognostic capacity with a notable 3-year area under the curve (AUC) of 0.837. Patients with Rad-score ≤0.705 demonstrated upregulation of immune-related pathways and favorable survival. Additionally, distant metastases metabolic tumor volume (MTV) and TLG, as well as intrathoracic lymph nodes MTV were associated with survival independently. For patients with similar tMTV (≤105 mL), the number of FDG-avid lesions was an independent protective factor for more-than-1-year OS, which indicated that patients with smaller lesions seemed to have better long-term prognoses than those with larger lesions, even of fewer in number. Conclusions: Our findings proved that PET/CT could reveal survival and tumor heterogeneity in advanced NSCLC patients undergoing chemoimmunotherapy, which might guide the selection of immune-monotherapy for low-risk patients and facilitate the advancement of precision treatment.

Indexed as

Fluorodeoxyglucose positron emission tomography (FDG PET)immunotherapynon-small cell lung cancer (NSCLC)radiomicstumor microenvironment (TME)

Identifiers

PMID39830771
PMCPMC11736617

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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.