MétaCan
Menu
← Back to cohort

S0819 Evaluating Cost Per Remission and Cost of Serious Adverse Events in Advanced Therapies for Ulcerative Colitis

2020· article· en· W3094396954 on OpenAlexaff
Vipul Jairath, Russell D. Cohen, Edward V. Loftus, Ninfa Candela, Karen Lasch, Bob G. Schultz

Bibliographic record

VenueThe American Journal of Gastroenterology · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineVedolizumabAdalimumabUlcerative colitisInfliximabNumber needed to treatAdverse effectTofacitinibNumber needed to harmPopulationInternal medicineGolimumabRegimenSurgeryConfidence intervalRelative riskRheumatoid arthritisTumor necrosis factor alphaDisease

Abstract

fetched live from OpenAlex

INTRODUCTION: Patients with ulcerative colitis (UC) incur >3-fold higher direct costs of care compared to the general patient population, largely due to use of biologic therapy.1 Direct2 and indirect3 comparisons of advanced therapies (AT) for UC have demonstrated differences in effectiveness and safety. We compared cost per remission for UC at 52 weeks, considering probability of clinical remission, as well as costs of serious adverse events (SAE) and serious infections (SI) for different ATs for UC. METHODS: Comparators were vedolizumab IV (VDZ), infliximab 5 and 10 mg/kg (IFX-5 and IFX-10), adalimumab 40 mg (ADA), tofacitinib 5 and 10 mg (TOF-5 and TOF-10), ustekinumab 90 mg (UST), and golimumab 100 mg (GOL). Numbers needed to treat and to harm (NNT/NNH), derived from network meta-analysis (NMA) of pivotal trials,3 were clinical inputs. Wholesale acquisition costs, derived from REDBOOK,4 were used to calculate costs of induction and maintenance regimens for labeled dosing. Infusion-related costs were included for IV AT. NNT for induction and maintenance was combined with regimen costs to calculate cost per clinical remission, as defined in the pivotal trials. Patients who were nonresponders to induction treatment did not incur maintenance costs. NNH for SAE and SI was used to incorporate costs attributed to treating AE, with VDZ used as reference because its SAE rate was lowest in the NMA.2 AE costs were derived from the Healthcare Cost and Utilization Project and weighted from AE rates comprising SAE and SI. RESULTS: Costs per remission after 52 weeks of treatment were lowest for TOF-10 ($187K) and TOF-5 ($228K), and highest for UST ($730K) (Figure 1). Mean SAE and SI costs per 100 patients in comparison to VDZ as the reference ($ = 0) were lowest for UST ($6K), and highest for TOF-5 ($118K) (Figure 2). CONCLUSION: Using data from pivotal trials and REDBOOK to estimate costs of treatment, accounting for probability of clinical remission and costs of SAE/SI, we found that TOF-5, TOF-10, IFX-5, and VDZ are less than half the cost of GOL, ADA, and UST. When considering AE-related costs, TOF-5 and GOL cost an additional ∼$100K per 100 patients treated compared to VDZ.Figure 1.: Cost per Remitter at 52 Weeks. Q8W, every 8 weeks; SC, subcutaneous.Figure 2.: Average AE Cost per 100 Patients (serious AEs). Dollar amounts represent the total combined costs of both serious AEs and serious infections. Bars to the left of the dark line represent costs that are less than those of the reference treatment, vedolizumab, and that partially offset the costs that are greater than those of the reference treatment (to the right of the line). AE, adverse event; Q8W, every 8 weeks; SC, subcutaneous.

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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.006
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.168
GPT teacher head0.419
Teacher spread0.251 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueThe American Journal of Gastroenterology→Same topicHealth Systems, Economic Evaluations, Quality of Life→French-language works237,207→