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Record W2130172613 · doi:10.1002/hed.21941

Detection of circulating tumor cells in advanced head and neck cancer using the cellsearch system

2011· article· en· W2130172613 on OpenAlexaff
Anthony C. Nichols, Lori E. Lowes, Christopher C. T. Szeto, John Basmaji, Sandeep Dhaliwal, Corina Chapeskie, Biljana Todorović, Nancy Read, Varugar Venkatesan, Alex Hammond, David A. Palma, Eric Winquist, Scott Ernst, Kevin Fung, Jason Franklin, John Yoo, James Koropatnick, Joe S. Mymryk, John W. Barrett, Alison L. Allan

Bibliographic record

VenueHead & Neck · 2011
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsCirculating tumor cellMedicineInternal medicineOncologyStage (stratigraphy)Head and neck cancerCancerHead and neck squamous-cell carcinomaHead and neckAdjuvantSurgeryBiologyMetastasis

Abstract

fetched live from OpenAlex

BACKGROUND: Early detection of circulating tumor cells (CTCs) offers the possibility of improved outcome for patients with head and neck squamous cell cancer (HNSCC). METHODS: Patients with advanced-stage HNSCC (stage III/IV) were tested for CTCs using the CellSearch system (a registered trade name), which has been approved by the U.S. Food and Drug Administration (FDA) for monitoring CTCs in other cancers. RESULTS: CTCs were detected in 6 of 15 patients with advanced-stage HNSCC (range, 1-2 cells/7.5 mL of blood). CTCs were significantly associated with patients with lung nodules >1 cm (p = .04). There was also a suggestion of improved survival in the CTC-negative versus the CTC-positive patients (p = .11). CONCLUSIONS: CTCs can be successfully isolated in patients with advanced-stage HNSCC using the CellSearch system. CTC detection may be important for prognosis, evaluating treatment outcome, and for determining efficacy of adjuvant treatments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.064
GPT teacher head0.321
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations115
Published2011
Admission routes1
Has abstractyes

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