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Bevacizumab for Metastatic Colorectal Cancer: A Global Cost-Effectiveness Analysis

2017· article· en· W2621574813 on OpenAlexaffabout
Daniel A. Goldstein, Qiushi Chen, Turgay Ayer, Kelvin Chan, Kiran Virik, Ariel Hammerman, Baruch Brenner, Christopher R. Flowers, Peter S Hall

Bibliographic record

VenueThe Oncologist · 2017
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsCanadian Centre for Applied Research in Cancer ControlHealth Sciences CentreSunnybrook Health Science Centre
FundersEuropean Society for Medical OncologyClalit Health ServicesBurroughs Wellcome Fund
KeywordsMedicineBevacizumabColorectal cancerIncremental cost-effectiveness ratioQuality-adjusted life yearCost effectivenessCost-effectiveness analysisWillingness to payCost–benefit analysisAdverse effectOncologyDemographyInternal medicineChemotherapyCancer

Abstract

fetched live from OpenAlex

BACKGROUND: In the U.S., the addition of bevacizumab to first-line chemotherapy in metastatic colorectal cancer (mCRC) has been demonstrated to provide 0.10 quality-adjusted life years (QALYs) at an incremental cost-effectiveness ratio (ICER) of $571,000/QALY. Due to variability in pricing, value for money may be different in other countries. Our objective was to establish the cost-effectiveness of bevacizumab in mCRC in the U.S., U.K., Canada, Australia, and Israel. METHODS: We performed the analysis using a previously established Markov model for mCRC. Input data for efficacy, adverse events, and quality of life were considered to be generalizable and therefore identical for all countries. We used country-specific prices for medications, administration, and other health service costs. All costs were converted from local currency to U.S. dollars at the exchange rates in March 2016. We conducted one-way and probabilistic sensitivity analyses (PSA) to assess the model robustness across parameter uncertainties. RESULTS: Base case results demonstrated that the highest ICER was in the U.S. ($571,000/QALY) and the lowest was in Australia ($277,000/QALY). In Canada, the U.K., and Israel, ICERs ranged between $351,000 and $358,000 per QALY. PSA demonstrated 0% likelihood of bevacizumab being cost-effective in any country at a willingness to pay threshold of $150,000 per QALY. CONCLUSION: The addition of bevacizumab to first-line chemotherapy for mCRC consistently fails to be cost-effective in all five countries. There are large differences in cost-effectiveness between countries. This study provides a framework for analyzing the value of a cancer drug from the perspectives of multiple international payers. IMPLICATIONS FOR PRACTICE: The cost-effectiveness of bevacizumab varies significantly between multiple countries. By conventional thresholds, bevacizumab is not cost-effective in metastatic colon cancer in the U.S., the U.K., Australia, Canada, and Israel.

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)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.090
GPT teacher head0.441
Teacher spread0.352 · 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 designSimulation or modeling
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

Citations35
Published2017
Admission routes2
Has abstractyes

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