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Colorectal Neoplasia Surveillance in Patients with Inflammatory Bowel Disease and Primary Sclerosing Cholangitis: An Economic Evaluation

2013· article· en· W2977681181 on OpenAlexaff
María E. Negrón, Gilaad G. Kaplan, Herman W. Barkema, Bertus Eksteen, Fiona Clement, Braden Manns, Stephanie Coward, Remo Panaccione, Subrata Ghosh, Steven J. Heitman

Bibliographic record

VenueThe American Journal of Gastroenterology · 2013
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineColonoscopyInflammatory bowel diseasePrimary sclerosing cholangitisDysplasiaColorectal cancerInternal medicineCohortDiseaseQuality-adjusted life yearCost effectivenessCancerGastroenterology

Abstract

fetched live from OpenAlex

Purpose: Annual colonoscopy for detection of colorectal neoplasia is recommended among patients with inflammatory bowel disease (IBD) and primary sclerosing cholangitis (PSC). However, it is not known whether annual surveillance is cost-effective. Our aim was to determine whether annual colonoscopy among patients with IBD-PSC is cost-effective compared to less frequent intervals from a publicly funded health care system perspective. Methods: A Markov model was constructed to simulate a 35-year-old male cohort with IBD-PSC, followed for 11-years after coexistence of both diseases. A cost-utility analysis was performed comparing the following strategies: no surveillance, annual colonoscopy, biennial colonoscopy, and colonoscopy performed every 5 years. Cancers were modeled to arise through both a dysplasia-carcinoma sequence and through a more rapid pathway without any prior identifiable dysplastic lesion. Outcome measures included: costs, number of cases of dysplasia found, number of cancers found and missed, deaths, quality-adjusted life-years (QALYs) gained, and incremental cost-utility ratios. A willingness to pay threshold of $50,000 per QALY was assumed. Sensitivity analyses were performed to assess the extent to which uncertain parameters affected the model results. Results: In the base-case analysis, no surveillance was the least expensive and least effective strategy. For every 1,000 IBD-PSC patients, biennial colonoscopy reduced the number of cancers and cancer-related deaths by 51% and 73%, respectively, at a cost per QALY of CAN $42,000 compared to no surveillance. Surveillance every 5 years was less costly, but also less effective than biennial surveillance and had a higher incremental cost-utility ratio than biennial surveillance. Annual surveillance was more effective than biennial surveillance, but at an incremental cost of CAN $147,000 per QALY gained. Annual surveillance became the preferred strategy when the annual incidence of neoplasia was increased to 2.8%. Conclusion: Biennial surveillance is the most cost-effective strategy for colorectal neoplasia surveillance among IBD-PSC patients over an 11-year time horizon. However, with biennial surveillance, we would expect to miss an additional 20 cancers and would anticipate 1 additional cancer-related death that could be prevented with annual surveillance at an additional average cost of $4,400 per patient.

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)0.009
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.213
Teacher spread0.208 · 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 designSimulation or modeling
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
Published2013
Admission routes1
Has abstractyes

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