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Record W2755064755 · doi:10.1001/jamaneurol.2017.2107

Survival End Points for Huntington Disease Trials Prior to a Motor Diagnosis

2017· article· en· W2755064755 on OpenAlexaffabout
Jeffrey D. Long, James A. Mills, Blair R. Leavitt, Alexandra Dürr, Raymund A.C. Roos, Julie C. Stout, Ralf Reilmann, G. Bernhard Landwehrmeyer, Sarah Gregory, Rachael I. Scahill, Douglas R. Langbehn, Sarah J. Tabrizi

Bibliographic record

VenueJAMA Neurology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of British Columbia
FundersMedical Research CouncilAllerganAOP OrphanAmarin CorporationWellcome TrustPfizerCure Huntington's Disease InitiativeIpsenH. Lundbeck A/SAlnylam PharmaceuticalsBundesministerium für Bildung und ForschungTeva Pharmaceutical IndustriesEuropean Huntington's Disease NetworkCHDI FoundationEuropean CommissionSanofiDeutsche ForschungsgemeinschaftGlaxoSmithKline
KeywordsCohortMedicineCohort studyClinical trialInternal medicine

Abstract

fetched live from OpenAlex

Importance: Predictive genetic testing in Huntington disease (HD) enables therapeutic trials in HTT gene expansion mutation carriers prior to a motor diagnosis. Progression-free survival (PFS) is the composite of a motor diagnosis or a progression event, whichever comes first. Objective: To determine if PFS provides feasible sample sizes for trials with mutation carriers who have not yet received a motor diagnosis. Design, Setting, and Participants: This study uses data from the 2-phase, longitudinal cohort studies called Track and from a longitudinal cohort study called the Cooperative Huntington Observational Research Trial (COHORT). Track had 167 prediagnosis mutation carriers and 156 noncarriers, whereas COHORT had 366 prediagnosis mutation carriers and noncarriers. Track studies were conducted at 4 sites in 4 countries (Canada, France, England, and the Netherlands) from which data were collected from January 17, 2008, through November 17, 2014. The COHORT was conducted at 38 sites in 3 countries (Australia, Canada, and the United States) from which data were collected from February 14, 2006, through December 31, 2009. Results from the Track data were externally validated with data from the COHORT. The required sample size was estimated for a 2-arm prediagnosis clinical trial. Data analysis took place from May 1, 2016, to June 10, 2017. Main Outcomes and Measures: The primary end point is PFS. Huntington disease progression events are defined for the Unified Huntington's Disease Rating Scale total motor score, total functional capacity, symbol digit modalities test, and Stroop word test. Results: Of Track's 167 prediagnosis mutation carriers, 93 (55.6%) were women, and the mean (SD) age was 40.06 (8.92) years; of the 156 noncarriers, 87 (55.7%) were women, and the mean (SD) age was 45.58 (10.30) years. Of the 366 COHORT participants, 229 (62.5%) were women and the mean (SD) age was 42.21 (12.48) years. The PFS curves of the Track mutation carriers showed good external validity with the COHORT mutation carriers after adjusting for initial progression. For required sample size, PFS with a motor diagnosis or total motor score progression required about 4 times fewer participants than a motor diagnosis alone. Including additional cognitive progression events further reduced the number. For example, a 3-year trial with 10% attrition and a treatment effect of 50% requires a total of 661 with motor diagnosis as the survival end point but only 177 with a total motor score PFS. Conclusions and Relevance: Reasonably sized prediagnosis Huntington disease trials can be planned with PFS, and there is evidence of generalizability of this approach.

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)0.067
metaresearch head score (Gemma)0.089
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.089
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.092
GPT teacher head0.352
Teacher spread0.260 · 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 designTheoretical or conceptual
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

Citations11
Published2017
Admission routes2
Has abstractyes

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