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Record W2252455678 · doi:10.1158/1078-0432.ccr-15-0035

Impact of the 2010 Consensus Recommendations of the Clinical Trial Design Task Force of the NCI Investigational Drug Steering Committee

2015· article· en· W2252455678 on OpenAlexaff
Lesley Seymour, Susan Groshen, Gary L. Rosner, Daniel M. Sullivan, David R. Spriggs, Steven A. Reeves, Amy Gravell, S. Percy Ivy, Mark J. Ratain

Bibliographic record

VenueClinical Cancer Research · 2015
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsKingston Health Sciences Centre
FundersNational Center for Advancing Translational SciencesNational Cancer Institute
KeywordsConcordanceMedicineClinical trialDrug developmentTask forceSteering committeeClinical study designRandomized controlled trialMedical physicsResearch designOncologyInvestigational DrugsDrugInternal medicinePharmacology

Abstract

fetched live from OpenAlex

Oncology phase III trials have a high failure rate, leading to high development costs. The Clinical Trials Design Task Force of the Investigational Drug Steering Committee of the NCI Cancer Therapy and Evaluation Program developed Recommendations regarding the design of phase II trials. We report here on the results of a Concordance Group review charged with documenting whether concordance rates improved after the publication of the Recommendations. One hundred and fifty-five trials were reviewed. Letter of Intents (LOI) from the post-Recommendation period were more likely to be randomized (44% vs. 34%) and biomarker selected (19% vs. 10%). Single-arm studies using time-to-event endpoints (benchmarked against historical data) were similar, as was the type of tumor. There was a significant improvement in the rate of concordance, with 74% of LOIs scored as concordant compared with 58% before the Recommendations (P = 0.042). This included a marked decrease in the use of single-arm designs to evaluate the activity of drug combinations (19% vs. 5%, P = 0.009). There were areas for which clarification was warranted, including the need for protocols to include further development plans, the use of realistic benchmarks, the careful evaluation of historical controls, and the use of a standard treatment option as a control. Ongoing critical evaluation of current trial design methodology and the development of new Guidelines when appropriate will continue to improve drug development ensuring that safe and effective cancer therapeutics are made available to our patients as quickly and efficiently as possible.

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)0.068
metaresearch head score (Gemma)0.521
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0680.521
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
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 head0.943
GPT teacher head0.735
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations2
Published2015
Admission routes1
Has abstractyes

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