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Record W2007010482 · doi:10.1159/000330206

Outcomes of Patients with Metastatic Melanoma Treated with Molecularly Targeted Agents in Phase I Clinical Trials

2011· article· en· W2007010482 on OpenAlexaff
M. Blanco Codesido, André T. Brunetto, Sophia Frentzas, Dionysis Papadatos-Pastos, Joanna Vitfell Pedersen, Leonardo Trani, M. Puglisi, L. Rhoda Molife, Udai Banerji

Bibliographic record

VenueOncology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsInstitute of Cancer Research
Fundersnot available
KeywordsMedicineDacarbazineInternal medicineClinical trialChemotherapyTemozolomidePhases of clinical researchOncologyMelanomaCytokineGastroenterologySurgeryCancer research

Abstract

fetched live from OpenAlex

INTRODUCTION: First-line treatment options utilizing chemotherapy and cytokine-based treatments for patients with metastatic melanoma (MM) are unsatisfactory. We analyzed the clinical outcomes of patients with MM treated in phase I trials of novel agents. We hypothesized that patients included in phase I clinical trials did not have worse outcomes than with the chemotherapy and cytokine-based first-line treatment. METHODS: Data of patients with MM treated at The Drug Development Unit between 2004 and 2010 were collected. The response rate (RR) and time to progression (TTP) for first-line therapy were compared to those of phase I trial therapy. Patients acted as their own controls for statistical analyses. RESULTS: Sixty-five patients were treated in 31 phase I trials. First-line treatment included dacarbazine or temozolomide in 58 (89%) cases and interferon-α in 5 patients (8%) and cisplatin-based treatment in 2 patients (3%). There was no significant difference in either the RR (11 vs. 14%, p = 0.87) or TTP (90 vs. 53 days, p = 0.15) in patients treated with first-line treatment versus phase I treatment, respectively. CONCLUSION: Phase I clinical trials of molecularly targeted agents show clinical activity that is not dissimilar to that of treatment with existing chemotherapy and cytokine-based treatment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.119
GPT teacher head0.392
Teacher spread0.273 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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