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Record W4321612529 · doi:10.1001/jamaoncol.2022.7770

Exposure to US Cancer Drugs With Lack of Confirmed Benefit After US Food and Drug Administration Accelerated Approval

2023· article· en· W4321612529 on OpenAlexfundno aff
Ravi B. Parikh, Rebecca A. Hubbard, Erkuan Wang, Trevor J. Royce, Aaron B. Cohen, Amy S. Clark, Ronac Mamtani

Bibliographic record

VenueJAMA Oncology · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
FundersNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of HealthAstellas PharmaSeagenFlatiron HealthEmerson CollectiveNational Palliative Care Research CenterEisaiNational Comprehensive Cancer NetworkF. Hoffmann-La RocheUniversity of PennsylvaniaMyriad GeneticsProstate Cancer FoundationAstraZenecaEli Lilly and CompanyBristol-Myers SquibbCancer Care OntarioPfizerAmgenConquer Cancer Foundation
KeywordsMedicineFood and drug administrationCancer drugsDrug approvalDrugDrug administrationAdministration (probate law)CancerPharmacologyIntensive care medicineOncologyFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

This cross-sectional study evaluates patient exposure to oncology drugs withdrawn from the US Food and Drug Administration (FDA) Accelerated Approval program.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.284
GPT teacher head0.438
Teacher spread0.154 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations25
Published2023
Admission routes1
Has abstractyes

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