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Record W2793895834 · doi:10.1093/ecco-jcc/jjx180.102

DOP065 Long-term cost-effectiveness of tight control for Crohn’s disease with adalimumab-based treatment: economic evaluation beyond 48 weeks of CALM trial

2018· article· en· W2793895834 on OpenAlexaff
Remo Panaccione, Peter Bossuyt, Filip Baert, Tomáš Vaňásek, Ahmet Danalıoğlu, Gottfried Novacek, Alessandro Armuzzi, Walter Reinisch, Scott J. Johnson, Marric Buessing, Ezequiel Neimark, J Petersson, Anne Robinson, Roopal Thakkar, W J Lee, Martha Skup, Geert D’Haens

Bibliographic record

VenueJournal of Crohn s and Colitis · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineAdalimumabFaecal calprotectinQuality of life (healthcare)Crohn's diseaseInternal medicineIndirect costsPediatricsPhysical therapyDiseaseInflammatory bowel diseaseCalprotectin

Abstract

fetched live from OpenAlex

Tight control (TC) for Crohn’s disease (CD), using biomarkers (faecal calprotectin and C-reactive protein) to direct adalimumab (ADA) treatment, was associated with improved outcomes and considered cost-effective compared with clinical management (CM) in a 48-week (week) multicentre, randomised controlled trial (CALM).1,2 In this analysis, long-term cost-effectiveness (CE) was assessed beyond 48 week. The CE of TC vs. CM was assessed in a UK setting. An ordered probit regression estimated CDAI-based health state (remission: CDAI <150, moderate: CDAI ≥150 to <300, severe: CDAI ≥300 to <450, very severe: CDAI ≥450) transition matrices for TC and CM patients; the matrices predicted patient health states weekly over 5 years. A probit predicted likelihood of hospitalisation as a function of health state and randomisation to TC or CM. Observed ADA 40 mg injections were summed over 48 week, average injections over week 23 to 48 were assumed to continue from week 49 to 260. ADA costs were based on ex-factory prices. Health states were associated with health utility and costs from prior UK analyses.3,4 Remission rate, CD-related hospitalisations, ADA injections, other direct medical costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) were calculated at 2 and 5 years. Work Productivity and Activity Impairment was converted into productivity measures using UK average weekly earnings, and probabilistic sensitivity analyses (PSA) were conducted. Over 2 years, TC was associated with a higher remission rate (65.3% vs. 50.7%), fewer CD-related hospitalisations (0.275 vs. 0.720/person year) and more ADA injections (mean 61.34 vs. 46.17) than CM. Total medical costs over 2 years were £25808 and £24939 for TC and CM; TC had 0.09 higher QALYs (95% confidence interval [CI]: 0.16 to 0.03) and £868 higher total medical costs (95% CI: £4551 to −£34094). The ICER was £10102 per QALY (95% CI: £119525 to −£405732). PSA simulations indicated 67.1% of the time an ICER was below a cost-per-QALY threshold of £30000. TC became dominant (i.e., ICER<0) when including the costs associated with work productivity gained (−£9328 in TC and −£6206 in CM). The results for 5-year timeframe were similar, with an ICER of £9030 in base case and a negative ICER when including work productivity costs. Cost-effectiveness of TC improved over time when extrapolating outcomes from the CALM trial. Incorporating costs related to work productivity further strengthened the economic value of TC. 1. Colombel, et al. Lancet, 2017. 2. Panaccione, et al. OP017 UEGW 2017. 3. Buxton, et al. Value Health, 2007;10:214–20. 4. Bassi, et al. Gut, 2004;53:1471-–8.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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