Evidence map›Paper›PMID 41540661›Full record

ArticleTherapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy2026

Predicting the Future Burden of Renal Replacement Therapy in Türkiye Using National Registry Data and Comparative Modeling Approaches.

Arzu Akgül, Neriman Sıla Koç, Berrak Itır Aylı

Abstract readComparative Study
In one paragraph

Article in Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy, 2026. 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.

Arzu AkgülDepartment of Internal Medicine, Division of Nephrology, Ankara Etlik City Hospital, Ankara, Türkiye.ORCID https://orcid.org/0009-0007-8119-3893
Neriman Sıla KoçDepartment of Internal Medicine, Division of Nephrology, Ankara Etlik City Hospital, Ankara, Türkiye.ORCID https://orcid.org/0000-0002-4654-9002
Berrak Itır AylıUniversity of Westminster, London, UK.ORCID https://orcid.org/0000-0002-0834-900X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is steadily increasing. Türkiye has experienced a similar rise in both the incidence and prevalence of renal replacement therapy over the past decades; however, national-level projections of future renal replacement therapy demand are lacking.

aimsThis study aimed to forecast the future burden of renal replacement therapy in Türkiye by modeling historical incidence and prevalence trends using national registry data and demographic projections.

methodsNational renal replacement therapy registry data from 2012 to 2024 were analyzed together with demographic projections from the Turkish Statistical Institute extending to 2035. Four models were constructed separately for incidence and prevalence. Model performance was compared using the coefficient of determination, root mean square error, and Akaike information criterion. Leave-one-out cross-validation was used to assess model robustness. The modeling was further validated on data from Japan and the United Kingdom.

resultsAll models indicated a consistent upward trend in renal replacement therapy incidence in Türkiye over the next decade. By 2035, the prevalence of renal replacement therapy in Türkiye is projected to reach approximately 1150-1250 per million population. The models demonstrated strong goodness of fit, and cross-validation supported good internal consistency, although the machine-learning model showed some overfitting for prevalence.

conclusionThe national demand for renal replacement therapy in Türkiye is projected to continue increasing through 2035. Incorporating predictive modeling into national registry surveillance can help guide proactive capacity planning and fair resource distribution for dialysis and transplantation services. At the same time, public health strategies aimed at preventing and slowing the progression of chronic kidney disease remain essential to mitigate the growing burden of end-stage renal disease.

Indexed as

Renal Insufficiency, ChronicRenal Replacement TherapyFemaleForecastingHumansIncidenceJapanModels, StatisticalPrevalenceRegistriesTurkeydialysisdisease predictionend stage renal diseasemodelingregistryrenal replacement therapy

Identifiers

PMID41540661
PMCPMC12957726

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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 OpenQuestion graph.