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Record W1973332555 · doi:10.1159/000227248

Mitomycin in Anal Canal Carcinoma

2009· article· en· W1973332555 on OpenAlexaff
Bernard Cummings, Thomas J. Keane, Brian O’Sullivan, C. Shun Wong, Charles Catton

Bibliographic record

VenueOncology · 2009
Typearticle
Languageen
FieldMedicine
TopicColorectal and Anal Carcinomas
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineMitomycin CAnal canalRadiation therapyAnal cancerSurgeryEpidermoid carcinomaToxicityCarcinomaAnal CarcinomaCancerOncologyFluorouracilChemotherapyInternal medicineRectum

Abstract

fetched live from OpenAlex

One hundred and ten patients with primary epidermoid cancers of the anal canal were treated in a series of prospectively designed, nonrandomized protocols of split-course radiation therapy with concurrent administration of 5-fluorouracil (5-FU) with or without mitomycin. The addition of mitomycin was associated with improved primary tumor control rates (87 vs. 58% at 4 years, p = 0.005) and improved 4-year actuarial cause-specific survival (80 vs. 64%, p = 0.02). Hematologic toxicity was the most frequent acute side effect of mitomycin use. No long-term toxicity was attributed to mitomycin only. Mitomycin appeared to benefit patients principally through improved control of cancer in the irradiated volume; there was no evidence of reduced risk of extrapelvic metastases. Several investigators have reported high rates of control of epidermoid anal cancers with preservation of anorectal function following concurrent treatment with mitomycin, 5-FU, and radiation. Mitomycin's role in anal cancer is being evaluated in a randomized clinical trial by the Radiation Therapy Oncology Group. The mechanisms of any interactions between mitomycin and radiation or other cytotoxic drugs in clinical practice remain to be determined.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.017
GPT teacher head0.311
Teacher spread0.294 · 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 designNon-randomized trial
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

Citations33
Published2009
Admission routes1
Has abstractyes

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