Evidence map›Paper›PMID 38020124›Full record

ArticleFrontiers in medicine2023

Candidate composite biomarker to inform drug treatments for diabetic kidney disease.

Roger D Jones, Seyum Abebe, Veronica Distefano, Gert Mayer, Irene Poli, Claudio Silvestri, Debora Slanzi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Information Transmission in G Protein-Coupled Receptors.International journal of molecular sciences · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 3 countries.

Roger D JonesEuropean Centre for Living Technology, Ca' Foscari University of Venice, Venice, Italy.
Seyum AbebeEuropean Centre for Living Technology, Ca' Foscari University of Venice, Venice, Italy.
Veronica DistefanoEuropean Centre for Living Technology, Ca' Foscari University of Venice, Venice, Italy.
Gert MayerInternal Medicine IV, Medical University Innsbruck, Innsbruck, Austria.
Irene PoliEuropean Centre for Living Technology, Ca' Foscari University of Venice, Venice, Italy.
Claudio SilvestriEuropean Centre for Living Technology, Ca' Foscari University of Venice, Venice, Italy.
Debora SlanziEuropean Centre for Living Technology, Ca' Foscari University of Venice, Venice, Italy.
Ca' Foscari University of Venice · ITEuropean Centre for Living Technology · ITInnsbruck Medical University · ATUniversity of Salento · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Current guidelines recommend renin angiotensin system inhibitors (RASi) as key components of treatment of diabetic kidney disease (DKD). Additional options include sodium-glucose cotransporter-2 inhibitors (SGLT2i), glucagon-like peptide 1 receptor agonists (GLP1a), and mineralocorticoid receptor antagonists (MCRa). The identification of the optimum drug combination for an individual is difficult because of the inter-, and longitudinal intra-individual heterogeneity of response to therapy. Results: Using data from a large observational study (PROVALID), we identified a set of parameters that can be combined into a meaningful composite biomarker that appears to be able to identify which of the various treatment options is clinically beneficial for an individual. It uses machine-earning techniques to estimate under what conditions a treatment of RASi plus an additional treatment is different from the treatment with RASi alone. The measure of difference is the annual percent change (ΔeGFR) in the estimated glomerular filtration rate (ΔeGFR). The 1eGFR is estimated for both the RASi-alone treatment and the add-on treatment. Discussion: Higher estimated increase of eGFR for add-on patients compared with RASi-alone patients indicates that prognosis may be improved with the add-on treatment. The personalized biomarker value thus identifies which patients may benefit from the additional treatment.

Indexed as

biomarkersclinical datadiabetic kidney diseaseMCRaprecision medicineRASiSGLT2i

Identifiers

PMID38020124
PMCPMC10646536
OpenAlexW4388126282

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.