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Record W2156778867 · doi:10.1093/jnci/djs141

Assumptions of Expected Benefits in Randomized Phase III Trials Evaluating Systemic Treatments for Cancer

2012· review· en· W2156778867 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2012
Typereview
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsMcMaster UniversityPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineConfidence intervalRandomized controlled trialInternal medicineClinical endpointCancerClinical trialSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: In designing phase III randomized clinical trials (RCTs), the expected magnitude of the benefit of the experimental therapy (δ) determines the number of patients required and the number of person-years of follow-up. We conducted a systematic review to evaluate how reliably δ approximates the observed benefit (B) in RCTs that evaluated cancer treatment. METHODS: RCTs evaluating systemic therapy in adult cancer patients published in 10 journals from January 1, 2005, through December 31, 2009, were identified. Data were extracted from each publication independently by two investigators. The related-samples Sign test was used to determine whether the median difference between δ and B was statistically significant in different study subsets and was two-sided. RESULTS: A total of 253 RCTs met the eligibility criteria and were included in the analysis. Regardless of whether benefit was defined as proportional change (median difference between δ and B = -13.0%, 95% confidence interval [CI] = -21.0% to -8.0%), absolute change (median difference between δ and B = -8.0%, 95% CI = -9.9% to -5.1%), or median increase in a time-to-event endpoint (median difference between δ and B = -1.4 months, 95% CI = -2.1 to -0.8 months), δ was consistently and statistically significantly larger than B (P < .001, for each, respectively). This relationship between δ and B was independent of year of publication, industry funding, management by cooperative trial groups, type of control arm, type of experimental arm, disease site, adjuvant treatment, or treatment for advanced disease, and likely contributed to the high proportion of negative RCTs (158 [62.5%] of 253 studies). CONCLUSIONS: Investigators consistently make overly optimistic assumptions regarding treatment benefits when designing RCTs. Attempts to reduce the number of negative RCTs should focus on more realistic estimations of δ. Increased use of interim analyses, certain adaptive trial designs, and better biological characterization of patients are potential ways of mitigating this problem.

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.

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)0.033
metaresearch head score (Gemma)0.213
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.213
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.922
GPT teacher head0.726
Teacher spread0.196 · 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