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Record W2008980700 · doi:10.1259/bjr/57750595

Local tumour control in women with carcinoma of the cervix treated with the addition of nitroimidazole agents to radiotherapy: a meta-analysis

2005· review· en· W2008980700 on OpenAlexaff
Ian S. Dayes, S Abuzallouf

Bibliographic record

VenueBritish Journal of Radiology · 2005
Typereview
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsJuravinski Cancer CentreMcMaster University
Fundersnot available
KeywordsMedicineMeta-analysisOdds ratioConfidence intervalRandomized controlled trialOncologyInternal medicineRadiation therapySubgroup analysisCarcinomaCervixCancerSurgery

Abstract

fetched live from OpenAlex

The purpose of this paper was to estimate the effect of nitroimidazoles on the local control and overall survival of women receiving radiotherapy for carcinoma of the cervix. Sources searched included Medline, Cancerlit and national cancer organizations. Proceedings of meetings were hand-searched. Trial selection and quality score were performed in duplicate. Data extraction was performed by a single author. Five trials involving 849 patients were included. Median follow-up was typically 4 years or greater. The odds ratio (OR) for local recurrence did not demonstrate a significant effect (OR: 1.14; 95% confidence interval (CI): 0.78-1.66). The difference in mortality was also non-significant (OR: 1.26; 95% CI: 0.95-1.66). A significant increase in neuropathy was found (OR: 3.21; 95% CI: 1.36-7.55). Subgroup analysis did not reveal any sources of heterogeneity between trials. Despite five published randomized trials, evidence supporting the use of nitroimidazoles in the treatment of cervical cancer is lacking. Meta-analysis revealed no significant effect on local tumour control with a weak, non-significant trend suggesting a decrease in overall survival. There is, however, a significant increase in the rate of neurotoxicity with the use of these compounds. This overview can not support the use of these agents.

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)0.001
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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.690
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.301
Teacher spread0.262 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations11
Published2005
Admission routes1
Has abstractyes

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