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Record W2046284618 · doi:10.1586/era.09.42

Is neoadjuvant chemotherapy with gemcitabine plus cisplatin beneficial in patients with muscle-invasive bladder cancer?

2009· letter· en· W2046284618 on OpenAlexaff
Faysal A. Yafi, Wassim Kassouf

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2009
Typeletter
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineGemcitabineBladder cancerCisplatinNeoadjuvant therapyCystectomyOncologyChemotherapyVinblastineRegimenInternal medicineUrologyDoxorubicinCancerBreast cancer

Abstract

fetched live from OpenAlex

Evaluation of: Weight CJ, Garcia JA, Hansel DE et al. Lack of pathologic down-staging with neoadjuvant chemotherapy for muscle-invasive urothelial carcinoma of the bladder. Cancer 115, 792-799 (2009). This study by the Glickman Urological Institute fails to show a beneficial role for neoadjuvant chemotherapy in muscle-invasive bladder cancer. The poor outcomes in the study could be attributed to the use of non-methotrexate, vinblastine, doxorubicin and cisplatin regimens and to excessive delays in performing cystectomy. Randomized trials of neoadjuvant chemotherapy have shown improved survival and increased rates of pathologic complete response when using cisplatin-based combination therapies compared with local therapy alone. A regimen consisting of gemcitabine plus cisplatin has shown similar efficacy and less toxicity in the metastatic setting and further research is warranted before its efficacy can be extrapolated to the neoadjuvant setting.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0030.003

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 head0.305
Teacher spread0.288 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2009
Admission routes1
Has abstractyes

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