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Record W4397042280 · doi:10.1681/asn.20233411s1974b

Modeling Based on NefIgArd Two-Year eGFR Total Slope Predicts Long-Term Clinical Benefit of Nefecon in a Real-World IgA Nephropathy (IgAN) Population

2023· article· en· W4397042280 on OpenAlexaff
Jonathan Barratt, Andrew Stone, Heather N. Reich, Richard Lafayette

Bibliographic record

VenueJournal of the American Society of Nephrology · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsNephropathyMedicineTerm (time)PopulationRenal functionInternal medicineEndocrinologyEnvironmental healthDiabetes mellitus

Abstract

fetched live from OpenAlex

Background: Nefecon, a targeted-release budesonide formulation, is approved for the treatment of patients (pts) with immunoglobulin A nephropathy (IgAN). Data from the full Phase 3 NefIgArd trial showed that 9 months of Nefecon 16 mg/d preserved estimated glomerular filtration rate (eGFR) and reduced urine protein-creatinine ratio (UPCR) vs placebo. These effects were maintained during the 15-month off-drug follow-up period, indicating that Nefecon is disease-modifying. We conducted a modeling analysis to predict the potential long-term benefit of Nefecon on clinical outcome (i.e., a composite endpoint of end stage renal disease, eGFR <15 mL/min/1.73m2, or sustained doubling of serum creatinine) in a real-world IgAN population. Methods: In the final analysis of the NefIgArd trial, there was a treatment benefit in 2-year eGFR total slope of 2.78 mL/min/1.73m2 per year (95% confidence interval [CI] 1.39-4.17) with Nefecon vs placebo (linear spline mixed-effect model). This difference was applied to a published linear regression between treatment effects for the change in 2-year eGFR total slope and the log hazard ratio (HR) of clinical outcome, based on a meta-analysis involving >60K CKD pts (Inker et al. JASN 2019;30:1735-45). Median time to clinical outcome for a reference group receiving supportive standard of care (SoC) only was estimated by modeling long-term registry data from pts at Leicester General Hospital (LGH), UK, matching NefIgArd-recruited pts to individual LGH pt records based on their baseline UPCR and eGFR. Time to clinical outcome for SoC pts was estimated using a Weibull model. Results: 352/364 NefIgArd pts were matched with 886 unique records from 192 LGH pts, which contained 287 clinical outcome event-times from 68 LGH pts. The NefIgArd 2-year eGFR total slope translated to a log HR for clinical outcome of 0.38 (95% CI 0.21-0.63), a 62% risk reduction vs placebo. Median time to clinical outcome was estimated at 9.6 years in SoC pts and 22.4 years in Nefecon-treated pts (median delay 12.8 [95% CI 4.8-27.9] years). 52% of SoC pts were predicted to have a clinical outcome within 10 years vs 24% of Nefecon-treated pts. Conclusions: Modeling analyses indicate that the clinical benefit seen with Nefecon predicts a substantial delay in progression to kidney failure. Funding: Commercial Support - Calliditas Therapeutics

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)0.020
metaresearch head score (Gemma)0.018
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 score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.012
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.033
GPT teacher head0.339
Teacher spread0.306 · 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
Published2023
Admission routes1
Has abstractyes

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