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The transition from phase II to phase III studies

2007· article· en· W4253174027 on OpenAlexaff
Ian F. Tannock, Aliya Gulamhusein, Dominik Berthold

Bibliographic record

VenueJournal of Clinical Oncology · 2007
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsPrincess Margaret Cancer CentreWestern University
Fundersnot available
KeywordsMedicineClinical trialPhase (matter)Phases of clinical researchRegimenRandomized controlled trialInternal medicineOncology

Abstract

fetched live from OpenAlex

6514 Background: Phase II trials are performed to detect potential anti-tumor effects of a new treatment and should be used to decide whether to proceed to a phase 3 trial or not. However, many phase 2 trials never lead to a phase 3 trial despite encouraging results. Here we sought to determine how often (i) positive phase 2 trials have led to phase 3 trials, and (ii) how often phase 2 trials were designed to lead to a phase 3 trial. Methods: We reviewed 200 phase 2 trials, presented at ASCO meetings in 1995–1996, and 2006, selecting randomly 20 abstracts with encouraging results for 5 cancer sites (breast, lung, GI, GU, Gyn) in each time period. For those presented in 1995–1996, we searched systematically for subsequent randomized studies where one treatment arm was similar to that in the phase 2 study. For those presented in 2006, a questionnaire was sent to authors asking whether they recommend evaluating the regimen in a phase 3 trial, whether a phase 3 trial is planned and whether resources (budget, patients, drugs) are available to conduct a phase 3 trial. Results: Ten years after presenting phase 2 trials with positive results, only 13 regimens have been evaluated in a phase 3 trial. Of 100 investigators who presented a phase 2 trial in 2006, 42 returned the questionnaire, 36 confirmed that the results met criteria of efficacy and 25 thought the regimen should be evaluated in a phase 3 trial. Only 10 investigators plan to undertake a phase 3 trial, and 8 stated they had resources to do so. Reasons for not planning a phase 3 study included insufficient efficacy (7), insufficient access to patients (5) or financial support (5), lack of interest from colleagues (6), and lack of support from the company (8). Conclusions: Few (∼13%) phase 2 trials with promising activity are followed by phase 3 trials and this is not increasing with time. Reasons include lack of resources such as money, drugs and patients. Many of these limitations are known when planning the phase 2 study, implying that many phase 2 trials are not planned as precursors of phase 3 trials. Resources spent on such trials would be better applied to practice-changing phase 3 trials. No significant financial relationships to disclose.

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)0.412
metaresearch head score (Gemma)0.369
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.588
Threshold uncertainty score0.725

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4120.369
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.004
Science and technology studies0.0020.003
Scholarly communication0.0120.008
Open science0.0040.005
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0050.003

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 head0.835
GPT teacher head0.752
Teacher spread0.082 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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
Published2007
Admission routes1
Has abstractyes

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