Evidence map›Paper›PMID 39825570›Full record

ArticleCPT: pharmacometrics & systems pharmacology2025

Modeling of Disease Progression of Type 2 Diabetes Using Real-World Data: Quantifying Competing Risks of Morbidity and Mortality.

Hanna Kunina, Stefan Franzén, Maria C Kjellsson

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Hanna KuninaDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.ORCID 0009-0000-0512-545X
Stefan FranzénSchool of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.ORCID 0000-0002-9640-0927
Maria C KjellssonDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.ORCID 0000-0003-3531-9452

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes (T2D) is a progressive metabolic disorder that could be an underlying cause of long-term complications that increase mortality. The assessment of the probability of such events could be essential for mortality risk management. This work aimed to establish a framework for risk predictions of macrovascular complications (MVC) and diabetic kidney disease (DKD) in patients with T2D, using real-world data from the Swedish National Diabetes Registry (NDR), in the presence of mortality as a competing risk. The study consisted of 41,517 patients with T2D registered in NDR between 2005 and 2013. At inclusion, patients were newly diagnosed (T2D < 1 year) and had no prior evidence of DKD or MVC. Using three-quarters of the data, a five-state multistate model was established to describe competing events of MVC, DKD, a combination thereof, and the terminal state, death. Two hypotheses were investigated: (1) the risk of MVC and DKD are mutually independent, and (2) mortality is independent of morbidities. At the end of the study, the majority of individuals remained in uncomplicated T2D; however, the probability of transition to complications and death increased over time. The mortality hazard depended on the presence of morbidities and was quantified as a life expectancy decreased by 5.0, 9.7, and 12.2 years for MVC, DKD, and the combined morbidity, respectively, compared to uncomplicated T2D. An established framework with a five-state model incorporating competing events was shown to be a useful tool for comorbidities risk assessment in newly diagnosed patients with T2D.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesAgedDisease ProgressionFemaleHumansMaleMiddle AgedMorbidityRegistriesRisk AssessmentRisk FactorsSwedencompeting risksmulti‐state modelNONMEMregistry datatype 2 diabetes

Identifiers

PMID39825570
PMCPMC11919267

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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 OpenQuestion graph.