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Record W3101633024 · doi:10.2215/cjn.10140620

Effects of Canagliflozin in Patients with Baseline eGFR <30 ml/min per 1.73 m2

2020· article· en· W3101633024 on OpenAlexaff
George L. Bakris, Megumi Oshima, Kenneth W. Mahaffey, Rajiv Agarwal, Christopher P. Cannon, George Capuano, David M. Charytan, Dick de Zeeuw, Robert Edwards, Tom Greene, Hiddo J.L. Heerspink, Adeera Levin, Bruce Neal, Richard Oh, Carol A. Pollock, Norman Rosenthal, David C. Wheeler, Hong Zhang, Bernard Zinman, Meg Jardine, Vlado Perkovic

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai HospitalUniversity of British Columbia
FundersJanssen PharmaceuticalsJanssen Research and DevelopmentUniversity of ChicagoRelypsaBristol-Myers SquibbAkebia TherapeuticsMitsubishi Tanabe Pharma CorporationNovo NordiskEisaiUniversity of Chicago MedicinePfizerInnovent BiologicsAstraZenecaAmarin CorporationRegeneron PharmaceuticalsIronwood Pharmaceuticals, IncorporatedAlnylam PharmaceuticalsDaiichi Sankyo EuropeGilead SciencesKowa CompanySanofiGlaxoSmithKlineAmgenCelgeneEli Lilly and Company
KeywordsCanagliflozinMedicineRenal functionHazard ratioInternal medicineConfidence intervalPopulationEmpagliflozinUrologyDiabetes mellitusCreatininePlaceboAlbuminuriaType 2 diabetesGastroenterologyEndocrinology

Abstract

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Background and objectives The Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial demonstrated that the sodium glucose cotransporter 2 (SGLT2) inhibitor canagliflozin reduced the risk of kidney failure and cardiovascular events in participants with type 2 diabetes mellitus and CKD. Little is known about the use of SGLT2 inhibitors in patients with eGFR <30 ml/min per 1.73 m 2 . The participants in the CREDENCE study had type 2 diabetes mellitus, a urinary albumin-creatinine ratio >300–5000 mg/g, and an eGFR of 30 to <90 ml/min per 1.73 m 2 at screening. This post hoc analysis evaluated participants with eGFR <30 ml/min per 1.73 m 2 at randomization. Design, setting, participants, & measurements Effects of eGFR slope through week 130 were analyzed using a piecewise, linear, mixed-effects model. Efficacy was analyzed in the intention-to-treat population, on the basis of Cox proportional hazard models, and safety was analyzed in the on-treatment population. At randomization (an average of 29 days after screening), 174 of 4401 (4%) participants had an eGFR <30 ml/min per 1.73 m 2 (mean [SD] eGFR, 26 [3] ml/min per 1.73 m 2 ). Results From weeks 3 to 130, there was a 66% difference in the mean rate of eGFR decline with canagliflozin versus placebo (mean slopes, −1.30 versus −3.83 ml/min per 1.73 m 2 per year; difference, −2.54 ml/min per 1.73 m 2 per year; 95% confidence interval [CI], 0.90 to 4.17). Effects of canagliflozin on kidney, cardiovascular, and mortality outcomes were consistent for those with eGFR <30 and ≥30 ml/min per 1.73 m 2 (all P interaction >0.20). The estimate for kidney failure in participants with eGFR <30 ml/min per 1.73 m 2 (hazard ratio, 0.67; 95% CI, 0.35 to 1.27) was similar to those with eGFR ≥30 ml/min per 1.73 m 2 (hazard ratio, 0.70; 95% CI, 0.54 to 0.91; P interaction=0.80). There was no imbalance in the rate of kidney-related adverse events or AKI associated with canagliflozin between participants with eGFR <30 and ≥30 ml/min per 1.73 m 2 (all P interaction >0.12). Conclusions This post hoc analysis suggests canagliflozin slowed progression of kidney disease, without increasing AKI, even in participants with eGFR <30 ml/min per 1.73 m 2 .

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.289
Teacher spread0.274 · 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 designObservational
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".

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Citations136
Published2020
Admission routes1
Has abstractyes

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