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Record W3195314083 · doi:10.21203/rs.3.rs-806031/v1

Adjudicating mild cognitive impairment due to Alzheimer’s disease as a novel endpoint event in the TOMMORROW prevention clinical trial

2021· preprint· en· W3195314083 on OpenAlexaff
Lon S. Schneider, David A. Bennett, Martin R. Farlow, Elaine R. Peskind, Murray A. Raskind, Mary Sano, Yaakov Stern, Stephen Haneline, Kathleen A. Welsh‐Bohmer, Janet O’Neil, Ryan Walter, Sylvia Maresca, Meredith Culp, Robert Alexander, Ann M. Saunders, Daniel K. Burns, Carl Chiang

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsColumbia College
Fundersnot available
KeywordsCognitive impairmentDiseaseCognitionMedicineEvent (particle physics)Alzheimer's diseaseClinical trialPsychologyPhysical medicine and rehabilitationInternal medicinePsychiatryPhysics

Abstract

fetched live from OpenAlex

Abstract Background The onset of mild cognitive impairment (MCI) is an essential outcome in Alzheimer’s disease (AD) prevention trials and a compelling milestone for clinically meaningful change. Determining MCI, however, may be variable and subject to disagreement. Adjudication procedures may improve the reliability of these determinations. We report the performance of an adjudication committee for an AD prevention trial. Methods The TOMMORROW prevention trial selected cognitively normal participants at increased genetic risk for AD and randomized them to low-dose pioglitazone or placebo treatment. When adjudication criteria were triggered, a participant’s clinical information was randomly assigned to a three-member panel of a six-member independent adjudication committee. Determination of whether or not a participant reached MCI or AD proceeded through up to three review stages – independent review, collaborative review, and full committee review – requiring a unanimous decision and ratification by the chair. Results Of 3494 participants randomized, the committee adjudicated on 648 cases from 386 participants, resulting in 96 primary endpoint events. Most participants had cases that were adjudicated once (n = 235, 60.9%); the rest had cases that were adjudicated multiple times. Cases were evenly distributed among the eight possible three-member panels. Most adjudicated cases (485/648, 74.8%) were decided within the independent review (stage 1); 14.0% required broader collaborative review (stage 2), and 11.1% needed full committee discussion (stage 3). The primary endpoint event decision rate was 39/485 (8.0%) for stage 1, 29/91 (31.9%) for stage 2, and 28/72 (38.9%) for stage 3. Agreement between the primary event outcomes supported by investigators’ clinical diagnoses and the decisions of the adjudication committee increased from 50% to approximately 93% (after around 100 cases) before settling at 80–90% for the remainder of the study. Conclusions The adjudication process was designed to provide independent, consistent determinations of the trial endpoints. These outcomes demonstrated the extent of uncertainty among trial investigators and agreement between adjudicators when the transition to MCI due to AD was prospectively assessed. These methods may inform clinical endpoint determination in future AD secondary prevention studies. Reliable, accurate assessment of clinical events is critical for prevention trials and may mean the difference between success and failure. Trial registration: NCT01931566

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)0.170
metaresearch head score (Gemma)0.167
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.170
Threshold uncertainty score0.900

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1700.167
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.224
GPT teacher head0.536
Teacher spread0.312 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations1
Published2021
Admission routes1
Has abstractyes

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