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A value framework analysis of the Canadian Cancer Trials Group.

2018· article· en· W2890790704 on OpenAlexaffabout
Joseph C. Del Paggio, Adam Fundytus, Wilma M. Hopman, Joseph L. Pater, Bingshu E. Chen, Michael Brundage, Annette E. Hay, Christopher M. Booth

Bibliographic record

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsQueen's UniversityKingston General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineClinical trialCancerClinical endpointSample size determinationInternal medicineOncologySurrogate endpointStatistical significanceBreast cancerStatistics

Abstract

fetched live from OpenAlex

6614 Background: To identify new therapies that offer substantial benefits to patients, investigators and research funding bodies may wish to consider value framework thresholds in the design of clinical trials. To our knowledge, existing value frameworks have not been applied to the research output of a cooperative cancer trials group. Herein, we apply the European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS) to the published output of the Canadian Cancer Trials Group (CCTG). Methods: Statistical design, study characteristics, and results of all published phase III trials of the CCTG were abstracted. Studies that showed a statistical significance in favor of the experimental therapy were graded using ESMO-MCBS v1.1. To identify the proportion of all trials that were designed to detect a difference which would be considered meaningful, we also applied the ESMO-MCBS to the statistical power calculations. We defined “substantial benefit” as trials that met a grade of A, B, 5, or 4 for the ESMO-MCBS. Results: During 1979-2017, CCTG published 477 trials. 132 trials were phase III and formed the study cohort; 49% of these trials were statistically “positive”. The most common disease sites were breast (18%), hematologic (17%), and lung (15%). Forty-six percent of trials were conducted in the palliative setting. Experimental therapies included cytotoxic (36%), molecular (20%), and hormonal (10%) agents. Median sample size was 490. In 40% of trials the primary endpoint was overall survival; a survival surrogate was used in 33% of trials. Among the 58 “positive” trials for which the ESMO-MCBS could be applied, 28 (48%) met thresholds for substantial benefit. The ESMO-MCBS could be applied to the power calculation for 79 trials; 70% of these trials were designed to detect an effect size that could meet ESMO-MCBS thresholds for substantial benefit. RCT authors were more likely to strongly endorse the experimental therapy among those trials meeting ESMO-MCBS thresholds (74% vs 40%, p = 0.010). Conclusions: The majority of CCTG phase III trials are designed to detect clinically meaningful differences in patient outcome. However, only one quarter of all trials ultimately yield results that meet ESMO-MCBS thresholds for substantial benefit.

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)0.274
metaresearch head score (Gemma)0.596
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score0.896

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2740.596
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.008
Bibliometrics0.0170.025
Science and technology studies0.0020.002
Scholarly communication0.0060.002
Open science0.0040.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.001

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 head0.797
GPT teacher head0.651
Teacher spread0.146 · 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 designQualitative
DomainEvaluation
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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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