ArticleEuropean journal of nuclear medicine and molecular imaging2017
Correlation of pretreatment
Article in European journal of nuclear medicine and molecular imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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
21 citing papers in PubMed, 35 citations in OpenAlex.
- Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [Japanese journal of radiology · 2025Article
- Prognostic impact of the combination of HIF‑1α and GLUT1 in patients with oesophageal squamous cell carcinoma.Oncology letters · 2023Article
- The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [Molecular imaging and biology · 2023Article
- Radiomics in Hypopharyngeal Cancer Management: A State-of-the-Art Review.Biomedicines · 2023Review
- Comprehensive prognostic modeling of locoregional recurrence after radiotherapy for patients with locoregionally advanced hypopharyngeal squamous cell carcinoma.Frontiers in oncology · 2023Article
- Computed tomography-based radiomics signature as a pretreatment predictor of progression-free survival in locally advanced hypopharyngeal carcinoma with a different response to induction chemotherapy.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.Diagnostics (Basel, Switzerland) · 2022Review
- Improved risk stratification by PET-based intratumor heterogeneity in children with high-risk neuroblastoma.Frontiers in oncology · 2022Article
- A Systematic Review of PET Textural Analysis and Radiomics in Cancer.Diagnostics (Basel, Switzerland) · 2021Review
- Interpretation and visualization techniques for deep learning models in medical imaging.Physics in medicine and biology · 2021Review
- Identification of Stage IIIC/IV EGFR-Mutated Non-Small Cell Lung Cancer Populations Sensitive to Targeted Therapy Based on a PET/CT Radiomics Risk Model.Frontiers in oncology · 2021Article
- Texture indices of 4'-[methyl-European journal of hybrid imaging · 2020Article
- Prognostic value of the radiomics-based model in progression-free survival of hypopharyngeal cancer treated with chemoradiation.European radiology · 2020Article
- Histometabolic Tumor Imaging of Hypoxia in Oral Cancer: Clinicopathological Correlation for Prediction of an Aggressive Phenotype.Frontiers in oncology · 2020Article
- Radiomics Analysis of PET and CT Components of PET/CT Imaging Integrated with Clinical Parameters: Application to Prognosis for Nasopharyngeal Carcinoma.Molecular imaging and biology · 2019Article
- Prognostic value of pre-treatment CT texture analysis in combination with change in size of the primary tumor in response to induction chemotherapy for HPV-positive oropharyngeal squamous cell carcinoma.Quantitative imaging in medicine and surgery · 2019Article
- Volumetric and texture analysis of pretherapeuticEndocrine · 2019Article
- The prognostic value of hypoxia-inducible factor-1α in advanced cancer survivors: a meta-analysis with trial sequential analysis.Therapeutic advances in medical oncology · 2019Article
- Radiomics in Oncological PET/CT: Clinical Applications.Nuclear medicine and molecular imaging · 2018Review
- Associations of Tumor PD-1 Ligands, Immunohistochemical Studies, and Textural Features inScientific reports · 2018Article
Corrections and comments
- Commented on by
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study investigated the correlation of the matrix heterogeneity of tumors on
methodsWe retrospectively reviewed the records of 57 patients with stage III-IV oropharyngeal or hypopharyngeal cancer who had completed definitive therapy. Four groups of the textural features as well as 31 indices were studied in addition to maximum standard uptake value, metastatic tumor volume, and total lesion glycolysis. Immunohistochemical data from pretreatment biopsy specimens (Glut1, CAIX, VEGF, HIF-1α, EGFR, Ki-67, Bcl-2, CLAUDIN-4, YAP-1, c-Met, and p16) were analyzed. The relationships between the indices and genomic expression were studied, and the robustness of various textural features relative to cause-specific survival and primary relapse-free survival was analyzed.
resultsThe overexpression of VEGF was positively associated with the increased values of the matrix heterogeneity obtained using gray-level nonuniformity for zone (GLNUz) and run-length nonuniformity (RLNU). Advanced T stage (p = 0.01, hazard ratio [HR] = 3.38), a VEGF immunoreactive score of >2 (p = 0.03, HR = 2.79), and a higher GLNUz value (p = 0.04, HR = 2.51) were prognostic factors for low cause-specific survival, whereas advanced T stage, a HIF-1α staining percentage of ≥80%, and a higher GLNUz value were prognostic factors for low primary-relapse free survival.
conclusionsThe overexpression of VEGF was associated with the increased matrix index of GLNUz and RLNU. For patients with pharyngeal cancer requiring radiotherapy, the treatment outcome can be stratified according to the textural features, T stage, and biomarkers.
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.