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Assessment of Food and Drug Administration– and European Medicines Agency–Approved Systemic Oncology Therapies and Clinically Meaningful Improvements in Quality of Life

2021· review· en· W3129179838 on OpenAlexafffund
Vanessa Sarah Arciero, Seanthel Delos Santos, Liza Koshy, Amanda Putri Rahmadian, Ronak Saluja, Louis Everest, Ambica Parmar, Kelvin Chan

Bibliographic record

VenueJAMA Network Open · 2021
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsCanadian Centre for Applied Research in Cancer ControlPublic Health OntarioUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Cancer Society Research InstituteCanadian Centre for Applied Research in Cancer Control
KeywordsMedicineQuality of life (healthcare)Food and drug administrationClinical trialInternal medicineOff-label useOncologyIntensive care medicinePharmacology

Abstract

fetched live from OpenAlex

Importance: For patients with cancer treated with palliative intent, quality of life (QOL) is a critical aspect of treatment decision-making, alongside survival. However, regulatory approval can be based solely on survival measures or antitumor activities, without QOL evidence. Objective: To investigate whether recently approved oncology therapies demonstrate clinically meaningful improvements in QOL. Evidence Review: This systematic review study identified oncology drug indications approved by the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) from January 2006 to December 2017 and supporting clinical trials (QOL publications identified to October 2019). Indications were evaluated for the presence of published QOL evidence; QOL benefits according to the American Society of Clinical Oncology Value Framework version 2.0 (ASCO-VF) and European Society of Medical Oncology Magnitude of Clinical Benefit Scale version 1.1 (ESMO-MCBS) QOL bonus criteria; and clinically meaningful improvements in QOL beyond minimal clinically important differences. Hematology trials were not evaluated by ESMO-MCBS. Associations between QOL evidence and approval year were examined using logistic regression models. Findings: In total, 214 FDA-approved (77 [36%] hematological) and 170 EMA-approved (52 [31%] hematological) indications were included. QOL evidence was published for 40% and 58% of FDA- and EMA-approved indications, respectively. QOL bonus criterion for ASCO-VF and ESMO-MCBS was met in 13% and 17% of FDA-approved and 21% and 24% of EMA-approved indications, respectively. Clinically meaningful improvements in QOL beyond minimal clinically important differences were noted in 6% and 11% of FDA- and EMA-approved indications, respectively. Availability of published QOL evidence at the time of approval increased over time for EMA (odds ratio [OR], 1.13; P = .03), however not for FDA (OR, 1.10; P = .12). Over time, no increase in awarded QOL bonuses or clinically meaningful improvements in QOL were found. Conclusions and Relevance: The findings of this systematic review suggest that approved systemic oncology therapies often do not have published evidence to suggest QOL improvement, despite its recognized importance. Of indications with evidence of statistical improvement, few have demonstrated clinically meaningful improvements.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.068
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0070.008
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.122
GPT teacher head0.391
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations46
Published2021
Admission routes2
Has abstractyes

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