Evidence mapPaperPMID 31050099Full record

ArticleDiabetes, obesity & metabolism2019

Identification of subgroups of patients with type 2 diabetes with differences in renal function preservation, comparing patients receiving sodium-glucose co-transporter-2 inhibitors with those receiving dipeptidyl peptidase-4 inhibitors, using a supervised machine-learning algorithm (PROFILE study): A retrospective analysis of a Japanese commercial medical database.

Fang L Zhou, Hirotaka Watada, Yuki Tajima, Mathilde Berthelot, Dian Kang, Cyril Esnault, Yujin Shuto, Hiroshi Maegawa, Daisuke Koya

Open access · hybridAbstract readComparative Study
In one paragraph

Article in Diabetes, obesity & metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

10 citing papers in PubMed, 23 citations in OpenAlex.

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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

9 authors at 6 institutions in 3 countries.

Fang L ZhouReal World Evidence Generation, Sanofi, Bridgewater, New Jersey.ORCID 0000-0003-1353-6376
Hirotaka WatadaDepartment of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan.ORCID 0000-0001-5961-1816
Yuki TajimaMedical Affairs, Sanofi K.K., Tokyo, Japan.ORCID 0000-0003-3405-6136
Mathilde BerthelotData Science Consulting, Quinten, Paris, France.
Dian KangData Science Consulting, Quinten, Paris, France.
Cyril EsnaultData Science Consulting, Quinten, Paris, France.
Yujin ShutoMedical Affairs, Sanofi K.K., Tokyo, Japan.
Hiroshi MaegawaDepartment of Medicine, Shiga University of Medical Science, Otsu, Japan.
Daisuke KoyaDepartment of Diabetology and Endocrinology, Kanazawa Medical University, Uchinada, Japan.
DATA4 (France) · FRSanofi (Japan) · JPJuntendo University · JPKanazawa Medical University · JPSanofi (United States) · USShiga University of Medical Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo investigate the effects of sodium-glucose co-transporter-2 (SGLT2) inhibitors vs. dipeptidyl peptidase-4 (DPP-4) inhibitors on renal function preservation (RFP) using real-world data of patients with type 2 diabetes in Japan, and to identify which subgroups of patients obtained greater RFP benefits with SGLT2 inhibitors vs. DPP-4 inhibitors.

methodsWe retrospectively analysed claims data recorded in the Medical Data Vision database in Japan of patients with type 2 diabetes (aged ≥18 years) prescribed any SGLT2 inhibitor or any DPP-4 inhibitor between May 2014 and September 2016 (identification period), in whom estimated glomerular filtration rate (eGFR) was measured at least twice (baseline, up to 6 months before the index date; follow-up, 9 to 15 months after the index date) with continuous treatment until the follow-up eGFR. The endpoint was the percentage of patients with RFP, defined as no change or an increase in eGFR from baseline to follow-up. A proprietary supervised learning algorithm (Q-Finder; Quinten, Paris, France) was used to identify the profiles of patients with an additional RFP benefit of SGLT2 inhibitors vs. DPP-4 inhibitors.

resultsData were available for 990 patients prescribed SGLT2 inhibitors and 4257 prescribed DPP-4 inhibitors. The proportion of patients with RFP was significantly greater in the SGLT2 inhibitor group (odds ratio 1.27; P = 0.01). The Q-Finder algorithm identified four clinically relevant subgroups showing superior RFP with SGLT2 inhibitors (P < 0.1): no hyperlipidaemia and eGFR ≥79 mL/min/1.73 m

conclusionSGLT2 inhibitors were associated with more favourable RFP vs. DPP-4 inhibitors in patients with certain profiles in real-world settings in Japan.

Indexed as

AdultAlgorithmsDatabases, FactualDiabetes Mellitus, Type 2Dipeptidyl-Peptidase IV InhibitorsFemaleGlomerular Filtration RateHumansHypoglycemic AgentsJapanKidneyMaleMiddle AgedRetrospective StudiesSodium-Glucose Transporter 2 InhibitorsSupervised Machine LearningDipeptidyl-Peptidase IV InhibitorsHypoglycemic AgentsSodium-Glucose Transporter 2 InhibitorsDPP-4 inhibitormachine-learning algorithmreal-world clinical practicerenal functionSGLT2 inhibitortype 2 diabetes

Identifiers

PMID31050099
PMCPMC6771907
OpenAlexW2948458961

What Socratic holds

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Registered trials

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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.