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Record W2122345264 · doi:10.1017/s0022215106002751

Analysis of 2167 head and neck cancer patients' management, treatment compliance and outcomes from a regional cancer centre, Delhi, India

2006· article· en· W2122345264 on OpenAlexaboutno aff
B.K. Mohanti, P L Nachiappan, R. M. Pandey, Ashok Sharma, S. Bahadur, Alok Thakar

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2006
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHead and neck cancerRadiation therapySurgeryChemoradiotherapyCancerPalliative careLarynxStage (stratigraphy)Internal medicineNursing

Abstract

fetched live from OpenAlex

Head and neck cancer care was analysed in 2167 unselected patients for management compliance and outcome. Median age was 55 years, with a male to female ratio of 5.5ratio1. Major sites were oropharynx (32.4 per cent), larynx (19.8 per cent), oral (16.6 per cent) and hypopharynx (12.9 per cent). Stage-wise distribution was I-II=8.9 per cent, III=20.6 per cent and IV=60.3 per cent and unstaged=10.2 per cent. Squamous cell carcinoma was the dominant histology for 90.9 per cent. Clinic-based cancer-directed treatment decisions were made for 1905 patients: curative intent in 53 per cent, palliative in 35 per cent and for the remaining 262 (12 per cent) supportive care. Overall, 1209 (56 per cent) patients complied with the prescribed treatments; 62 per cent, 54 per cent, and 35 per cent of curative, palliative and supportive care intent groups, respectively. Modalities were radiotherapy alone (64.6 per cent), combined surgery with irradiation (17.6 per cent), and chemoradiotherapy (11.2 per cent). Median follow-up periods were 17.5 and three months in curative and palliative groups respectively. Overall, 712 (33 per cent) cases received curative therapy, with three-year disease-specific survival of 49 per cent. Patient compliance was a major obstacle. The comparison of this series with the USA, Canada and Norway showed wide disparities in stage of presentation and survival.

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)0.000
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 score0.009
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.320
Teacher spread0.290 · 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

Citations65
Published2006
Admission routes1
Has abstractyes

Explore more

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