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Appropriateness of De-Escalation of Medical Therapy in Crohnʼs Disease Patients Who Are in Deep Remission: A RAND Panel Approach

2017· article· en· W2913890298 on OpenAlexaff
Miles Sparrow, Gil Melmed, Shane Devlin, Patricia Kozuch, Laura E. Raffals, Edward V. Loftus, David T. Rubin, Brennan Spiegel, Leonard Baidoo, Brian Bressler, Adam S. Cheifetz, Peter M. Irving, Jennifer Jones, Gilaad G. Kaplan, Fernando Velayos, Corey A. Siegel

Bibliographic record

VenueThe American Journal of Gastroenterology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsDalhousie UniversitySt. Thomas HospitalUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsMedicineCombination therapyDelphi methodDiseaseInternal medicineArtificial intelligence

Abstract

fetched live from OpenAlex

Introduction: Deep remission is a treatment goal for patients with Crohn's disease (CD) and marks a point at which de-escalation of medical therapy may be considered. There are limited data on how best to implement this approach. We aimed to provide guidance for clinicians on the appropriateness of de-escalating immunomodulator (IM) or anti-tumor necrosis factor (TNF) therapy in patients with CD who are in deep remission. Methods: A comprehensive literature review was presented to a panel of 12 international IBD experts. Appropriateness of de-escalation in patients in deep remission for at least 6 months was considered in 240 scenarios in 5 chapters: patients on combination therapy stopping anti-TNF therapy; on combination therapy stopping IM therapy; on combination therapy reducing IM to half the usual dose; stopping anti-TNF monotherapy; and stopping IM monotherapy. Using the RAND/UCLA modified Delphi method, panel members rated appropriateness of de-escalation in each scenario on a 1-9 scale (1-3 inappropriate, 4-6 uncertain, 7-9 appropriate) via a web-based survey, then met to discuss the topic and re-rated the scenarios. Disagreement was assessed using a validated index; scenarios with disagreement were rated as uncertain. Results: De-escalation was rated appropriate in only 32/240 scenarios (13.3%), including 19 scenarios of elderly patients on combination therapy stopping or dose-reducing IM therapy. De-escalation was rated inappropriate in 59/240 scenarios (24.6%), including 22 scenarios of patients on monotherapy and 35 scenarios of patients on combination therapy stopping anti-TNF therapy. More than 60% of scenarios (149/240) were rated uncertain, including 42 scenarios of patients with complicated CD on combination therapy stopping or dose-reducing IM. Disagreement was noted in one scenario: appropriateness of stopping thiopurine monotherapy in young males with uncomplicated CD. Selected examples are shown in Table. 1Table: Table. Appropriateness of de-escalating medical therapy in patients with CD (selected results)Conclusion: In patients with complicated CD, stopping any drug was considered appropriate in only a few scenarios. Stopping anti-TNF or IM in patients with uncomplicated CD on combination therapy was most often considered appropriate in elderly patients. Stopping monotherapy was not considered appropriate in any scenario. However, >60% of scenarios were rated uncertain based on current evidence. Additional data are required to better inform clinicians when and how to de-escalate medical therapy in patients with CD in deep remission.

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)0.211
metaresearch head score (Gemma)0.210
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.973

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2110.210
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0060.003
Science and technology studies0.0030.002
Scholarly communication0.0050.004
Open science0.0030.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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.

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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