ArticleLung cancer management2020
Computed tomography texture analysis of response to second-line nivolumab in metastatic non-small cell lung cancer.
Article in Lung cancer management, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- Pretreatment CT Texture Analysis for Predicting Survival Outcomes in Advanced Nonsmall Cell Lung Cancer Patients Receiving Immunotherapy: A Systematic Review and Meta-Analysis.Thoracic cancer · 2025Pooled it
- Current status and quality of radiomic studies for predicting immunotherapy response and outcome in patients with non-small cell lung cancer: a systematic review and meta-analysis.European journal of nuclear medicine and molecular imaging · 2021Pooled it
- Radiomics-based explainable artificial intelligence to predict treatment response following lung stereotactic body radiation therapy.The British journal of radiology · 2025Article
- Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours.Nature reviews. Cancer · 2024Review
- A whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still lacking?NPJ precision oncology · 2024Review
- Development and validation of an MRI-Based nomogram to predict the effectiveness of immunotherapy for brain metastasis in patients with non-small cell lung cancer.Frontiers in immunology · 2024Article
- Application of radiomics in diagnosis and treatment of lung cancer.Frontiers in pharmacology · 2023Review
- The Role of Radiomics in the Era of Immune Checkpoint Inhibitors: A New Protagonist in the Jungle of Response Criteria.Journal of clinical medicine · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesAssess computed tomography texture analysis of patients likely to benefit from nivolumab. MATERIALS &
methodsTexture analysis was used to quantify heterogeneity within the largest tumor before immunotherapy. Histogram analysis was classified as hyperdense (positive skewness) or hypodense (negative skewness) and subclassified on median standard deviation value or entropy measurement.
results47 patients were included. At a median follow-up of 18 months, statistical significant differences in progression-free survival were observed when stratified by positive skewness with low entropy, hazard ratio: 0.43 (0.19-0.95); p = 0.036, and positive skewness with low standard deviation, hazard ratio: 0.42 (0.18-0.96); p = 0.04.
conclusionPatients who derive a clinical benefit to Nivolumab show a computed tomography texture of a hyperdense yet homogenous tumor.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.