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Record W2998937382 · doi:10.1093/ecco-jcc/jjz203.933

P805 Patients with Crohn’s disease treated with ustekinumab vs. vedolizumab in real-world settings

2020· article· en· W2998937382 on OpenAlexaff
Michael Chiorean, Jiaojiao Jiang, Ninfa Candela, G Chen, Hela Romdhani, Dominick Latrémouille-Viau, Sherry Shi, Rebecca Bungay, Tianxiang Fan

Bibliographic record

VenueJournal of Crohn s and Colitis · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsVedolizumabMedicineUstekinumabDiscontinuationRetrospective cohort studyCrohn's diseaseInternal medicineHealth careDiseasePediatricsInfliximab

Abstract

fetched live from OpenAlex

Abstract Background Ustekinumab (UST) and vedolizumab (VDZ) are approved biologic therapies for moderate to severe Crohn’s disease (CD). Comparative data on real-world patient characteristics and healthcare costs for these drugs are scarce. Methods We examined healthcare costs associated with UST (healthcare common procedure coding system [HCPCS]: J3357, J3358, C9261, C9487, Q9989) and VDZ (HCPCS: C9026, J3380) in a retrospective cohort study of Truven commercial claims data (2009–2018) for adults with CD (international classification of diseases-9/10 codes: 555/K50). Eligible patients (18–89 years old) initiated UST or VDZ (index drug) on/after Sept 26, 2016, had CD as the latest relevant autoimmune disease on or before index drug initiation (index) date, ≥6 months of data available both before and after the index date, completed induction, and initiated maintenance therapy. Entropy balancing was used to address confounding factors (baseline characteristics). Primary outcome was healthcare costs assessed from a US payer perspective from index date to treatment discontinuation or end of follow-up (time on treatment). Cost were reported in 2018 US$ per patient per month and compared between treatment groups overall, and for biologic-naïve and -experienced (≥1 pre-index biologic therapy for CD) subgroups, using mean cost differences (MCD) obtained from weighted two-part models. Results The 599 (117 biologic-naive) UST- and 589 (172 biologic-naive) VDZ-treated patients who met eligibility criteria were similar in sex (54% and 57% female), mean age (41 ± 14 and 44 ± 14 years), time since diagnosis (42 ± 33 and 46 ± 35 months) and Charlson comorbidity index (0.4 ± 1.0 and 0.6 ± 1.1). Disease location, follow-up duration, and prior therapies and surgeries were also comparable. Characteristics were similar in biologic-naïve and -experienced patients. Mean weighted time on treatment was 11.4 and 12.1 months in UST- and VDZ-treated patients. Mean weighted total healthcare costs per patient per month was higher with UST vs. VDZ (MCD=$5051) driven by total index drug costs (MCD=$4946; Table). Cost differences were consistent in biologic-naïve and -experienced patients (total cost MCD=$4466 and $4836, both p < 0.01). Conclusion Characteristics of UST- and VDZ-treated patients in real-world settings were comparable. In this population of patients receiving maintenance treatment for CD, index drug costs make UST treatment substantially more costly than VDZ. Further comparison of healthcare outcomes in patients treated with UST vs. VDZ is warranted.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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

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