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2,756
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Dataset results
2,756 results for “Head and neck”
MAGE-A10ᶜ⁷⁹⁶T for Urothelial Cancer, Melanoma or Head and Neck Cancers
ClinicalTrials.gov study NCT02989064. IPD Sharing: Not stated. Countries: 3. Publications: 1.
The Influence of Head and Neck Position on the Oropharyngeal Leak Pressure Using Air-Q SP Airway
ClinicalTrials.gov study NCT02402387. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Paclitaxel, Cisplatin, and Filgrastim Combined With Radiation Therapy in Treating Patients With Locally Recurrent Head and Neck Cancer
ClinicalTrials.gov study NCT00005087. IPD Sharing: Not stated. Countries: 2. Publications: 2.
Surgical Resection and Intraoperative Cesium-131 Brachytherapy for Head and Neck Cancer
ClinicalTrials.gov study NCT02467738. IPD Sharing: Not stated. Countries: 1. Publications: 1.
An Optimization in the Postoperative Treatment in Head and Neck--surgical Patients.
ClinicalTrials.gov study NCT04021186. IPD Sharing: NO. Countries: 1. Publications: 1.
SCT200 in Combination With SCT-I10A/Paclitaxel/Docetaxel in Recurrent/Metastatic Head and Neck Squamous Cell Carcinoma
ClinicalTrials.gov study NCT05552807. IPD Sharing: NO. Countries: 1. Publications: 1.
Combination Chemotherapy Plus Radiation Therapy in Treating Patients With Advanced Head and Neck Cancer
ClinicalTrials.gov study NCT00003888. IPD Sharing: Not stated. Countries: 15. Publications: 2.
Mucosal Melanoma of Head and Neck in Intensity-modulated Radiotherapy Era
ClinicalTrials.gov study NCT03138642. IPD Sharing: NO. Countries: 1. Publications: 24.
Impact of Fixed Dentures in Head and Neck Cancer (IMFDHAC)
ClinicalTrials.gov study NCT03753932. IPD Sharing: NO. Countries: 1. Publications: 30.
Surgery and Radiation Therapy Compared With Chemotherapy and Radiation Therapy in Treating Patients With Stage III or Stage IV Head and Neck Cancer That Can Be Removed During Surgery
ClinicalTrials.gov study NCT00003576. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Resistance Exercise Training for the Shoulder and Neck Following Surgery for Head and Neck Cancer
ClinicalTrials.gov study NCT00248235. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Exploratory Study of Early Biomarkers Allowing Dynamic Assessment of Response to Treatment in Cancers of the Head and Neck
ClinicalTrials.gov study NCT05644457. IPD Sharing: NO. Countries: 1. Publications: 11.
Comparison of Craniocervical Flexion and Scapular Stabilization Exercises in Forward Head Posture and Neck Pain
ClinicalTrials.gov study NCT04557904. IPD Sharing: NO. Countries: 1. Publications: 16.
Leg Function and ADL After ALT Reconstruction for Head and Neck Cancer
ClinicalTrials.gov study NCT02332161. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Temperature Response to a Head-Neck Cooling System
ClinicalTrials.gov study NCT00025987. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Mapping the EORTC QLQ-C30 and QLQ-H&N35 to the EQ-5D for head and neck cancer: can disease-specific utilities be obtained?
<p class="Default"><b>Introduction</b></p> <p class="Default">Innovations in head and neck cancer (HNC) treatment are often subject to economic evaluation prior to their reimbursement and subsequent access for patients. Mapping functions facilitate economic evaluation of new treatments when the required utility data is absent, but quality of life data is available. The objective of this study is to develop a mapping function translating the EORTC QLQ-C30 to EQ-5D-derived utilities for HNC through regression modeling, and to explore the added value of disease-specific EORTC QLQ-H&N35 scales to the model.</p> <p class="Default"> </p> <p class="Default"><b>Methods</b></p> <p class="Default">Data was obtained on patients with primary HNC treated with curative intent derived from two hospitals. Model development was conducted in two phases: 1. Predictor selection based on theory- and data-driven methods, resulting in three sets of potential predictors from the quality of life questionnaires; 2. Selection of the best out of four methods: ordinary-least squares, mixed-effects linear, Cox and beta regression, using the first set of predictors from EORTC QLQ-C30 scales with most correspondence to EQ-5D dimensions. Using a stepwise approach, we assessed added values of predictors in the other two sets. Model fit was assessed using Akaike and Bayesian Information Criterion (AIC and BIC) and model performance was evaluated by MAE, RMSE and limits of agreement (LOA).</p> <p class="Default"> </p> <p class="Default"><b>Results </b></p> <p class="Default">The beta regression model showed best model fit, with global health status, physical-, role- and emotional functioning and pain scales as predictors. Adding HNC-specific scales did not improve the model. Model performance was reasonable; R<sup>2</sup>=0.39, MAE=0.0949, RMSE=0.1209, 95% LOA of -0.243 to 0.231 (bias -0.01), with an error correlation of 0.32. The estimated shrinkage factor was 0.90.</p> <p class="Default"> </p> <p class="Default"><b>Conclusions</b></p> <p>Selected scales from the EORTC QLQ-C30 can be used to estimate utilities for HNC using beta regression. Including EORTC QLQ-H&N35 scales does not improve the mapping function. The mapping model may serve as a tool to enable cost-effectiveness analyses of innovative HNC treatments, for example for reimbursement issues. Further research should assess the robustness and generalizability of the function by validating the model in an external cohort of HNC patients.</p>
Machine Learning-assisted immunophenotyping of peripheral blood identifies innate immune cells as best predictor of response to induction chemo-immunotherapy in head and neck squamous cell carcinoma – knowledge obtained from the CheckRad-CD8 trial
<p>Raw cell counts from peripheral blood immune phenotyping across individual patients.</p>
Genomic and single-cell characterization of patient-derived tumor organoid models of head and neck squamous cell carcinoma
Open the record for dataset details and reuse information.
Data from: Analysis of head and neck carcinoma progression reveals novel and relevant stage-specific changes associated with immortalisation and malignancy
Head and neck squamous cell carcinoma (HNSCC) is a widely prevalent cancer globally with high mortality and morbidity. We report here changes in the genomic landscape in the development of these tumours from potentially premalignant lesions (PPOLS) to malignancy and lymph node metastases. Frequent likely pathological mutations are restricted to a relatively small set of genes including TP53, CDKN2A, FBXW7, FAT1, NOTCH1 and KMT2D; these arise early in tumour progression and are present in PPOLs with NOTCH1 mutations restricted to cell lines from lesions that subsequently progressed to HNSCC. The most frequent genetic changes are of consistent somatic copy number alterations (SCNA). The earliest SCNAs involved deletions of CSMD1 (8p23.2), FHIT (3p14.2) and CDKN2A (9p21.3) together with gains of chromosome 20. CSMD1 deletions or promoter hypermethylation were present in all of the immortal PPOLs and occurred at high frequency in the immortal HNSCC cell lines (promoter hypermethylation ~63%, hemizygous deletions ~75%, homozygous deletions ~18%). Forced expression of CSMD1 in the HNSCC cell line H103 showed significant suppression of proliferation (p=0.0053) and invasion in vitro (p=5.98X10-5) supporting a role for CSMD1 inactivation in early head and neck carcinogenesis. In addition, knockdown of CSMD1 in the CSMD1-expressing BICR16 cell line showed significant stimulation of invasion in vitro (p=1.82 x 10-5) but not cell proliferation (p=0.239). HNSCC with and without nodal metastases showed some clear differences including high copy number gains of CCND1, hsa-miR-548k and TP63 in the metastases group. GISTIC peak SCNA regions showed significant enrichment (adj P<0.01) of genes in multiple KEGG cancer pathways at all stages with disruption of an increasing number of these involved in the progression to lymph node metastases. Sixty-seven genes from regions with statistically significant differences in SCNA/LOH frequency between immortal PPOL and HNSCC cell lines showed correlation with expression including 5 known cancer drivers.
Compendium of primary head and neck cancer gene expression datasets with accompanying clinical data
<p>We assembled a compendium of 30 primary HNC gene expression datasets with accompanying clinical data, representing the largest such resource for HNC. This resource was specifically built to identify genes associated with two outcome variables: patient survival and lymph node metastasis (LNM) status. Meta-analyses were applied to uniformly preprocessed gene expression data, as in our PRECOG resource (Gentles et al, Nat Med, 2016). Briefly, datasets were quality controlled, normalized, log transformed, and standardized to calculate gene expression profiles. Clinical data were manually curated and included survival and LNM status as well as variables relevant to HNC prognosis, such as tumor grade, tumor subanatomic location, and HPV status. The resulting 30 cleaned studies included 2,134 HNC tumors. 1,666 patients (across 17 cohorts) had survival outcome data and 1,490 patients (21 cohorts) had LNM status. Fully processed datasets are provided here as a resource to enable efficient meta-analyses of gene expression data in head and neck cancer.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.