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Record W2141933631 · doi:10.1158/1078-0432.ccr-08-1622

Successes and Challenges in Translational Research: The Development of Targeted Therapy for Gastrointestinal Stromal Tumours

2009· article· en· W2141933631 on OpenAlexaff
Daniel J. Renouf, Lora A. Wilson, Charles D. Blanke

Bibliographic record

VenueClinical Cancer Research · 2009
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsGiSTImatinibImatinib mesylateMedicineTyrosine-kinase inhibitorTargeted therapyGastrointestinal tractStromal cellClinical trialOncologyMesenchymal stem cellTyrosine kinaseStomachStromal tumorInternal medicineCancer researchPathologyCancerReceptor

Abstract

fetched live from OpenAlex

Gastrointestinal stromal tumors (GISTs) are mesenchymal neoplasms that most commonly affect the stomach or small intestine, but that can occur anywhere within the gastrointestinal tract. The annual incidence of GISTs is estimated to be 10 to 20 cases per million. Traditionally, the only effective treatment was surgical resection, and recurrences were common even with complete removal of tumor. Systemic therapy with standard cytotoxic chemotherapeutic agents was completely ineffective. A series of exciting laboratory developments led to the discovery that the small molecule tyrosine kinase inhibitor STI571 (imatinib mesylate) has significant clinical activity in GISTs, representing one of the first therapeutic uses of a targeted agent directed against a solid tumor. In this article we will describe the key steps that led to the initial clinical trials of imatinib in GISTs, and we will also discuss the process of incorporating this novel therapy into mainstream oncologic practice.

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)0.105
metaresearch head score (Gemma)0.052
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.557

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1050.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0020.013
Scholarly communication0.0110.017
Open science0.0030.006
Research integrity0.0080.014
Insufficient payload (model declined to judge)0.0050.002

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 head0.588
GPT teacher head0.561
Teacher spread0.026 · 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
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

Citations6
Published2009
Admission routes1
Has abstractyes

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