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Record W4416799561 · doi:10.1136/bmjopen-2025-111418

Comparison of intention-to-treat and per-protocol results in non-inferiority trials: a methodological review protocol

2025· review· en· W4416799561 on OpenAlexaff
Sameer Parpia, Sandra Ofori, Tyler McKechnie, Borong Wang, Gordon Guyatt

Bibliographic record

VenueBMJ Open · 2025
Typereview
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsProtocol (science)Research ethicsHealth services researchSystematic reviewMEDLINERegister (sociolinguistics)Research design

Abstract

fetched live from OpenAlex

INTRODUCTION: Non-inferiority (NI) trial designs, which assess whether an experimental intervention is no worse than the standard of care, have become increasingly prevalent in recent years. Current thinking suggests that the intention-to-treat (ITT) analysis is considered anti-conservative in the presence of protocol violations when compared with the per-protocol (PP) analysis. METHODS AND ANALYSIS: We aim to conduct a methodological review of NI trials to compare the results from ITT and PP analysis in NI trials. A comprehensive electronic search strategy will be used to identify studies indexed in MEDLINE, Embase and Cochrane Central Register of Controlled Trials databases. We will include 390 NI trials published prior to 31 December 2024. The primary outcomes are the treatment effect estimates from ITT and PP analyses. Secondary outcomes are the CI widths and the bounds of the CIs from the ITT and PP analyses. Analysis will calculate the relative difference in the point estimates, CI widths and CI bounds between the two approaches. Linear models will be used to investigate the relationship between the outcomes and the proportion of patients excluded from the PP analysis. ETHICS AND DISSEMINATION: This is a methodological review that has been registered on the International Prospective Register for Systematic Reviews (PROSPERO, CRD420251125360). Research ethics is not required as the project is a methodological review of previously published trials. Study findings will be shared via peer-reviewed publications and presentations at academic conferences.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearch
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.128
metaresearch head score (Gemma)0.765
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1280.765
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0200.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0010.001
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 head0.957
GPT teacher head0.814
Teacher spread0.143 · 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

Labeled directly by 2 models reading the full record.

Study designSystematic review
DomainMethods
GenreProtocol

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

Citations1
Published2025
Admission routes1
Has abstractyes

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