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Record W4283367578 · doi:10.1200/go.22.00034

Defining Essential Childhood Cancer Medicines to Inform Prioritization and Access: Results From an International, Cross-Sectional Survey

2022· article· en· W4283367578 on OpenAlex
Avram Denburg, Adam Fundytus, Muhammad Saghir Khan, Scott C. Howard, Federico Antillón‐Klussmann, Manju Sengar, Dorothy Lombe, Wilma M. Hopman, Matthew Jalink, Bishal Gyawali, Dario Trapani, Felipe Roitberg, Elisabeth G.E. de Vries, Lorenzo Moja, André Ilbawi, Richard Sullivan, Christopher M. Booth

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

VenueJCO Global Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsQueen's UniversityPublic Health OntarioUniversity of Toronto
FundersDaiichi Sankyo EuropeMedical Research CouncilEuropean Society for Medical OncologyRegeneron PharmaceuticalsWorld Health OrganizationGenentechAstraZenecaServierG1 TherapeuticsPfizerAmgen
KeywordsEssential medicinesMedicineContext (archaeology)Family medicineDeveloping countryAccess to medicinesCancerEnvironmental healthInternal medicineNursingPublic healthEconomic growthGeography

Abstract

fetched live from OpenAlex

PURPOSE: Access to essential cancer medicines is a major determinant of childhood cancer outcomes globally. The degree to which pediatric oncologists deem medicines listed on WHO's Model List of Essential Medicines for Children (EMLc) essential is unknown, as is the extent to which such medicines are accessible on the front lines of clinical care. METHODS: An electronic survey developed was distributed through the International Society of Pediatric Oncology mailing list to members from 87 countries. Respondents were asked to select 10 cancer medicines that would provide the greatest benefit to patients in their context; subsequent questions explored medicine availability and cost. Descriptive and bivariate statistics compared access to medicines between low- and lower-middle-income countries (LMICs), upper-middle-income countries (UMICs), and high-income countries (HICs). RESULTS: Among 159 respondents from 44 countries, 43 (27%) were from LMICs, 79 (50%) from UMICs, and 37 (23%) from HICs. The top five medicines were methotrexate (75%), vincristine (74%), doxorubicin (74%), cyclophosphamide (69%), and cytarabine (65%). Of the priority medicines identified, 87% (27 of 31) are represented on the 2021 EMLc and 77% (24 of 31) were common to the lists generated by LMIC, UMIC, and HIC respondents. The proportion of respondents indicating universal availability for each of the top medicines ranged from 9% to 46% for LMIC, 25% to 89% for UMIC, and 67% to 100% for HIC. Risk of catastrophic expenditure was more common in LMIC (8%-20%), compared with UMIC (0%-28%) and HIC (0%). CONCLUSION: Most medicines that oncologists deem essential for childhood cancer treatment are currently included on the EMLc. Barriers remain in access to these medicines, characterized by gaps in availability and risks of catastrophic expenditure for families that are most pronounced in low-income settings but evident across all income contexts.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.209
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.079
GPT teacher head0.501
Teacher spread0.422 · 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