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Record W1990116660 · doi:10.2310/7070.2003.37133

Evaluation of Chest Radiography versus Chest Computed Tomography in Screening for Pulmonary Malignancy in Advanced Head and Neck Cancer

2003· article· en· W1990116660 on OpenAlexvenueno aff
Giles Warner, Graham J. Cox

Bibliographic record

VenueThe Journal of Otolaryngology · 2003
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiologyChest radiographMalignancyRadiographyLung cancerPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the role of chest radiography versus chest computed tomography (CT) in screening for pulmonary malignancy in advanced head and neck squamous cell carcinoma (HNSCC). DESIGN: Retrospective review of imaging. SETTING: Head and neck cancer unit. METHOD: Over a period of 1 year, 26 patients with advanced HNSCC (T3/T4) were screened for pulmonary malignancy with both chest radiography and chest CT prior to definitive therapy. OUTCOME MEASURES: Radiologic evidence of malignancy. RESULTS: Twenty patients had a normal chest radiograph and a normal CT scan. Four patients had a normal chest radiograph but an abnormal CT scan. Three of these patients had a pulmonary malignancy and one had a suspicious lesion that resolved following surgery to the index tumour. Two patients had both an abnormal chest radiograph and CT scan. One of these had a pulmonary malignancy and one had a CT-guided biopsy of the chest lesion 4 weeks postoperatively, which was normal. Chest CT scanning therefore identified three chest malignancies that would have been missed by chest radiography alone. CONCLUSIONS: Chest CT is an effective tool in screening for malignant pulmonary disease in patients with advanced head and neck cancer and should be used instead of chest radiography to avoid false-negative results.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.344
Teacher spread0.287 · 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 teacher head, 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

Citations41
Published2003
Admission routes1
Has abstractyes

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