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Record W4294761314 · doi:10.9778/cmajo.20220077

Cost-effectiveness of remdesivir plus usual care versus usual care alone for hospitalized patients with COVID-19: an economic evaluation as part of the Canadian Treatments for COVID-19 (CATCO) randomized clinical trial

2022· article· en· W4294761314 on OpenAlexafffundvenueabout
Vincent Lau, Robert Fowler, Ruxandra Pinto, Alain Tremblay, Sergio Borgia, François Martin Carrier, Matthew P. Cheng, John Conly, Cecilia T. Costiniuk, Peter Daley, Erick Duan, Madéleine Durand, Patrícia S. Fontela, George Farjou, Mike Fralick, Anna Geagea, Jennifer Grant, Yoav Keynan, Kosar Khwaja, Nelson Lee, Todd C. Lee, Rachel Lim, Conar O’Neil, Jesse Papenburg, Makeda Semret, Michael Silverman, Wendy Sligl, Ranjani Somayaji, Darrell H. S. Tan, Jennifer Tsang, Jason Weatherald, Cédric P. Yansouni, Ryan Zarychanski, Srinivas Murthy

Bibliographic record

VenueCMAJ Open · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsAlberta Health Services
FundersNorthern Alberta Clinical Trials and Research CentreVancouver Coastal Health Research InstituteCanadian Institutes of Health ResearchSunnybrook Research Institute
KeywordsMedicineConfidence intervalRandomized controlled trialCoronavirus disease 2019 (COVID-19)RandomizationClinical trialEmergency medicineHealth careInternal medicineDisease

Abstract

fetched live from OpenAlex

<h3>Background:</h3> The role of remdesivir in the treatment of hospitalized patients with COVID-19 remains ill-defined. We conducted a cost-effectiveness analysis alongside the Canadian Treatments for COVID-19 (CATCO) open-label, randomized clinical trial evaluating remdesivir. <h3>Methods:</h3> Patients with COVID-19 in Canadian hospitals from Aug. 14, 2020, to Apr. 1, 2021, were randomly assigned to receive remdesivir plus usual care versus usual care alone. Taking a public health care payer’s perspective, we collected in-hospital outcomes and health care resource utilization alongside estimated unit costs in 2020 Canadian dollars over a time horizon from randomization to hospital discharge or death. Data from 1281 adults admitted to 52 hospitals in 6 Canadian provinces were analyzed. <h3>Results:</h3> The total mean cost per patient was $37 918 (standard deviation [SD] $42 413; 95% confidence interval [CI] $34 617 to $41 220) for patients randomly assigned to the remdesivir group and $38 026 (SD $46 021; 95% CI $34 480 to $41 573) for patients receiving usual care (incremental cost −$108 [95% CI −$4953 to $4737], <i>p</i> &gt; 0.9). The difference in proportions of in-hospital deaths between remdesivir and usual care groups was −3.9% (18.7% v. 22.6%, 95% CI −8.3% to 1.0%, <i>p</i> = 0.09). The difference in proportions of incident invasive mechanical ventilation events between groups was −7.0% (8.0% v. 15.0%, 95% CI −10.6% to −3.4%, <i>p</i> = 0.006), whereas the difference in proportions of total mechanical ventilation events between groups was −5.7% (16.4% v. 22.1%, 95% CI −10.0% to −1.4%, <i>p</i> = 0.01). Remdesivir was the dominant intervention (but only marginally less costly, with mildly lower mortality) with an incalculable incremental cost effectiveness ratio; we report results of incremental costs and incremental effects separately. For willingness-to-pay thresholds of $0, $20 000, $50 000 and $100 000 per death averted, a strategy using remdesivir was cost-effective in 60%, 67%, 74% and 79% of simulations, respectively. The remdesivir costs were the fifth highest cost driver, offset by shorter lengths of stay and less mechanical ventilation. <h3>Interpretation:</h3> From a health care payer perspective, treating patients hospitalized with COVID-19 with remdesivir and usual care appears to be preferrable to treating with usual care alone, albeit with marginal incremental cost and small clinical effects. The added cost of remdesivir was offset by shorter lengths of stay in the intensive care unit and less need for ventilation. <h3>Study registration:</h3> ClinicalTrials. gov, no. NCT04330690

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)0.009
metaresearch head score (Gemma)0.121
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.121
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.239
GPT teacher head0.540
Teacher spread0.301 · 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 designRandomized trial
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

Citations10
Published2022
Admission routes4
Has abstractyes

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