Evidence map›Paper›PMID 36307575›Full record

ArticleAdvances in therapy2023

Projecting the Epidemiological and Economic Impact of Chronic Kidney Disease Using Patient-Level Microsimulation Modelling: Rationale and Methods of Inside CKD.

Navdeep Tangri, Steven Chadban, Claudia Cabrera, Lise Retat, Juan José García Sánchez

Open access · hybridAbstract read
In one paragraph

Article in Advances in therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 4% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Review
  6. Article
  7. Article
  8. "Kidney international reports · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

5 authors at 4 institutions in 5 countries.

Navdeep TangriUniversity of Manitoba, Winnipeg, MB, R3T 2N2, Canada.
Steven ChadbanRoyal Prince Alfred Hospital, Camperdown, NSW, 2050, Australia.
Claudia CabreraReal World Science and Analytics, BioPharmaceuticals Medical, AstraZeneca, 431 83, Gothenburg, Sweden.
Lise RetatHealthLumen Limited, London, EC3N 2PJ, UK.
Juan José García SánchezGlobal Market Access and Pricing, BioPharmaceuticals, AstraZeneca, Academy House, 136 Hills Road, Cambridge, CB2 8PA, UK. juanjose.garciasanchez@astrazeneca.com.ORCID http://orcid.org/0000-0001-6546-7769
AstraZeneca (Sweden) · SEAstraZeneca (United Kingdom) · GBRoyal Prince Alfred Hospital · AUUniversity of Manitoba · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionChronic kidney disease (CKD) is a serious condition associated with significant morbidity and healthcare costs. Despite this, early-stage CKD is often undiagnosed, and globally there is substantial variation in the effectiveness of screening and subsequent management. Microsimulations can estimate future epidemiological costs, providing useful insights for clinicians, policymakers and researchers. Inside CKD is a programme designed to analyse the projected prevalence and burden of CKD for countries across the world, and to simulate hypothetical intervention strategies that can then be assessed for potential impact on health and economic outcomes at a national and a global level.

methodsInside CKD uses a population-based approach that creates virtual individuals for a given country, with this simulated population progressing through a microsimulation in 1-year increments. A series of data inputs derived from national statistics and key literature defined the likelihood of a change in health state for each individual. Input modules allow for the input of nationally specific demographic and CKD status (including prevalence, diagnosis rates, disease stage and likelihood of renal replacement therapy), disease progression, critical comorbidities, and mortality. Health economics are reflected in cost data and a flexible intervention module allows for the testing of hypothetical policies-such as screening strategies-that may alter disease progression and outcomes.

resultsUsing input data from the UK as a case study and a 6-year simulation period, Inside CKD estimated a prevalence of 9.2 million individuals (both diagnosed and estimated undiagnosed) with CKD by 2027 and a 5.0% increase in costs for diagnosed CKD and renal replacement therapy. External validation and sensitivity analyses confirmed the observed trends, substantiating the robustness of the microsimulation.

conclusionsUsing a microsimulation approach, Inside CKD extends the reach of current CKD policy analyses by factoring in multiple inputs that reflect national healthcare systems and enable analysis of the effect of multiple hypothetical screening scenarios on disease progression and costs.

Indexed as

Renal Insufficiency, ChronicComorbidityDelivery of Health CareDisease ProgressionHealth Care CostsHumansBurden of diseaseChronic kidney diseaseDialysisMethodologyMicrosimulationModelPolicyPrevalence

Identifiers

PMID36307575
PMCPMC9616410
OpenAlexW4307730286

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.