ArticleCancer immunology, immunotherapy : CII2025
Multicenter evaluation of predictive clinical and imaging factors for pathological response in non-small cell lung cancer patients treated with neoadjuvant chemotherapy and immune checkpoint inhibitors.
Article in Cancer immunology, immunotherapy : CII, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- A narrative review of pathologic response in non-small cell lung cancer: challenges, implications, and future directions.Translational lung cancer research · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aimed to identify clinical factors and develop a predictive model for pathological complete response (pCR) and major pathological response (MPR) in non-small cell lung cancer (NSCLC) patients receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors (ICIs).
methodsCases meeting inclusion criteria were divided into high- and low-risk groups according to 75 clinical indicators based on tenfold LASSO selection. Logistic regression was employed to analyze both pCR and MPR. The accuracy of the nomograms was assessed using the time-dependent area under the curve (AUC).
resultsA total of 297 patients from four multiple centers were included in the study, with 212 assigned to the training set and 85 to the testing set. The AUC was determined for the prediction of pCR (training: 0.97; testing: 0.88) and MPR (training: 0.98; testing: 0.81). Significant associations were observed between the preoperative tumor maximum diameter, preoperative tumor maximum standardized uptake value (SUV
conclusionsThe combined application of clinical indicators including non-invasive tumor imaging and hematology can help clinicians to obtain a higher ability to predict NSCLC patient's pathological remission, and the effect is better than that of clinical factors alone. These findings could help guide personalized treatment strategies in this patient population.
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Registered trials
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 Socratic graph.