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Record W4366455290 · doi:10.1016/j.eclinm.2023.101966

Evidence of clinical benefit of WHO essential anticancer medicines for children, 2011–2021

2023· article· en· W4366455290 on OpenAlexaff
Lin Bai, Yuqi Zhan, Yue Zhou, Yichen Zhang, Luwen Shi, Sumit Gupta, Avram Denburg, Xiaodong Guan

Bibliographic record

VenueEClinicalMedicine · 2023
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersLondon School of Economics and Political ScienceHarvard Medical School
KeywordsMedicineEvidence-based medicineFamily medicineMEDLINEAlternative medicinePathology

Abstract

fetched live from OpenAlex

Background: Access to essential cancer medicines is a key determinant of childhood cancer survival. WHO published the Model List of Essential Medicine for Children (EMLc) and updated it every two years since 2007 to promote better access to medicines for children. This study aimed to assess whether the inclusion of essential anticancer medicines for respective indications for children was based on evidence of significant clinical benefit between 2011 and 2021. Methods: We identified all anticancer medicine indications added to the WHO EMLc Section 8 since 2011 and extracted evidence of benefit documented in the corresponding technical reports. Evidence in children was defined as evidence that included participants under 12, and graded into five levels, according to the Oxford Centre for Evidence-Based Medicine Levels of Evidence. We analyzed whether each anticancer medicine indication was listed with documented OS benefit or improvements in surrogate measures based on the highest level of documented evidence in children. Findings: A total of 115 anticancer medicine indications were added to the EMLc from 2011 to 2021, of which 101 (87.8%) had some clinical evidence in children and 4 (3.5%) were added without any clinical evidence. Among the 101 medicine indications, none were added with level-1 evidence in children, and 43 (42.6%), 11 (10.9%), 41 (40.6%), and 6 (5.9%) were listed with level-2, level-3, level-4, and level-5 evidence in children, respectively. Only eight (7.9%) medicine indications were reported to have OS benefit, another 12 (11.9%) were reported to have improvements on surrogate measures, and 81 (80.2%) were listed in the EMLc without documented improvements in either OS or surrogate measures. Interpretation: Most anticancer medicine indications of the WHO EMLc were added based on limited evidence of statistically significant clinical benefit in children. Our results suggest that WHO should refine requirements for clinical benefit criteria and permissible forms, quality, and reporting of evidence of essential anticancer medicines for children, specify whether anticancer medicine indications have required evidence of clinical benefit in children, and provide further details in its technical reports that summarise the available evidence. Funding: Not applicable.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.251
GPT teacher head0.548
Teacher spread0.297 · 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.

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

Citations7
Published2023
Admission routes1
Has abstractyes

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