Trial reportScientific reports2018
A response prediction model for taxane, cisplatin, and 5-fluorouracil chemotherapy in hypopharyngeal carcinoma.
Trial report in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 18 citations in OpenAlex.
- Identification and validation of disulfidptosis-related gene signature revealed DKK1 as a therapeutic target in head and neck squamous cell carcinoma.Scientific reports · 2026Article
- Artificial Intelligence in the Diagnosis, Treatment, and Prognosis of Hypopharyngeal Carcinoma: A Scoping Review.Clinical medicine & research · 2025Article
- Missense variants ofMolecular genetics and metabolism reports · 2024Article
- Neoadjuvant therapy with chemotherapy and immune checkpoint inhibitor for laryngeal function preservation in locally advanced hypopharyngeal cancer.Frontiers in immunology · 2024Article
- Taxanes in the Treatment of Head and Neck Squamous Cell Carcinoma.Biomedicines · 2023Review
- Suppression of TLR signaling by IRAK-1 and -4 dual inhibitor decreases TPF-resistance-induced pro-oncogenic effects in HNSCC.3 Biotech · 2023Article
- Exploration of a predictive model based on genes associated with fatty acid metabolism and clinical treatment for head and neck squamous cell carcinoma.Journal of clinical laboratory analysis · 2022Article
- Identification of tumor antigens and immune subtypes in head and neck squamous cell carcinoma for mRNA vaccine development.Frontiers in cell and developmental biology · 2022Article
- Predictive Biomarkers for Response and Toxicity of Induction Chemotherapy in Head and Neck Cancers.Frontiers in oncology · 2022Review
- An ion-channel-gene-based prediction model for head and neck squamous cell carcinoma: Prognostic assessment and treatment guidance.Frontiers in immunology · 2022Article
- SNRPB is a mediator for cellular response to cisplatin in non-small-cell lung cancer.Medical oncology (Northwood, London, England) · 2021Article
- Prognostic Value of Eight-Gene Signature in Head and Neck Squamous Carcinoma.Frontiers in oncology · 2021Article
- Pan-Cancer Transcriptional Models Predicting Chemosensitivity in Human Tumors.Cancer informatics · 2021Article
- Genome-wide analysis of therapeutic response uncovers molecular pathways governing tamoxifen resistance in ER+ breast cancer.EBioMedicine · 2020Article
- Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery.Clinical and experimental otorhinolaryngology · 2020Review
- pathCHEMO, a generalizable computational framework uncovers molecular pathways of chemoresistance in lung adenocarcinoma.Communications biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 8 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. The five-year survival rate of HNSCC has not improved even with major technological advancements in surgery and chemotherapy. Currently, docetaxel, cisplatin, and 5-fluoruracil (TPF) treatment has been the most popular chemotherapy method for HNSCC; but only a small percentage of HNSCC patients exhibit a good response to TPF treatment. Unfortunately, at present, no reasonably effective prediction model exists to assist clinicians with patient treatment. For this reason, patients have no other alternative but to risk neoadjuvant chemotherapy in order to determine their response to TPF. In this study, we analyzed the gene expression profile in TPF-sensitive and non-sensitive patient samples. We identified a gene expression signature between these two groups. We further chose 10 genes and trained a support vector machine (SVM) model. This model has 88.3% sensitivity and 88.9% specificity to predict the response to TPF treatment in our patients. In addition, four more TPF responsive and four more TPF non-sensitive patient samples were used for further validation. This SVM model has been proven to achieve approximately 75.0% sensitivity and 100% specificity to predict TPF response in new patients. This suggests that our 10-genes SVM prediction model has the potential to assist clinicians to personalize treatment for HNSCC patients.
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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 OpenQuestion graph.