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Record W4307340693 · doi:10.1002/alz.12811

Cost‐effectiveness models for Alzheimer's disease and related dementias: IPECAD modeling workshop cross‐comparison challenge

2022· article· en· W4307340693 on OpenAlexaff
Ron Handels, Colin Green, Anders Gustavsson, William L. Herring, Bengt Winblad, Anders Wimo, Anders Sköldunger, Andreas Karlsson, Robert M. Anderson, Mark Belger, Chiara C. Brück, Robert Espinosa, Jakub Hlávka, Eric Jutkowitz, Pei‐Jung Lin, Mauricio Lopez Mendez, Javier Mar, Peter Shewmaker, Eldon Spackman, Ali Tafazzoli, Bryan Tysinger, Linus Jönsson

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Calgary
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekUniversiteit MaastrichtUniversity of ExeterKarolinska InstitutetLondon School of Economics and Political ScienceTufts Medical CenterUniversity of Southern CaliforniaNational Institute on AgingEli Lilly and Company
KeywordsDementiaContext (archaeology)ConcordanceCredibilityDiseaseMedicinePsychological interventionPsychologyCognitionGerontologyPsychiatryInternal medicinePolitical scienceGeography

Abstract

fetched live from OpenAlex

INTRODUCTION: The credibility of model-based economic evaluations of Alzheimer's disease (AD) interventions is central to appropriate decision-making in a policy context. We report on the International PharmacoEconomic Collaboration on Alzheimer's Disease (IPECAD) Modeling Workshop Challenge. METHODS: Two common benchmark scenarios, for the hypothetical treatment of AD mild cognitive impairment (MCI) and mild dementia, were developed jointly by 29 participants. Model outcomes were summarized, and cross-comparisons were discussed during a structured workshop. RESULTS: A broad concordance was established among participants. Mean 10-year restricted survival and time in MCI in the control group ranged across 10 MCI models from 6.7 to 9.5 years and 3.4 to 5.6 years, respectively; and across 4 mild dementia models from 5.4 to 7.9 years (survival) and 1.5 to 4.2 years (mild dementia). DISCUSSION: The model comparison increased our understanding of methods, data used, and disease progression. We established a collaboration framework to assess cost-effectiveness outcomes, an important step toward transparent and credible AD models.

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)0.302
metaresearch head score (Gemma)0.338
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.302
Threshold uncertainty score0.861

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3020.338
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0050.007
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0060.000

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 head0.448
GPT teacher head0.448
Teacher spread0.000 · 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 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

Citations19
Published2022
Admission routes1
Has abstractyes

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