Evidence map›Paper›PMID 26583032›Full record

ArticleFrontiers in genetics2015

Classifying aging as a disease in the context of ICD-11.

Alex Zhavoronkov, Bhupinder Bhullar

Abstract read
In one paragraph

Article in Frontiers in genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Targeting Gli1Stem cell reviews and reports · 2026
    Review
  2. Article
  3. Review
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Review
  9. The landscape of aging.Science China. Life sciences · 2022
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Aging, hormones and receptors.Physiological research · 2020
    Review
  16. Article
  17. Review
  18. Article
  19. mTOR and Aging: An Old Fashioned Dress.International journal of molecular sciences · 2019
    Review
  20. Integrating functional ageing into daily clinical practice.Journal of frailty, sarcopenia and falls · 2019
    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

2 authors.

Alex ZhavoronkovThe Biogerontology Research Foundation , Oxford, UK ; Insilico Medicine Inc , Baltimore, MD, USA.
Bhupinder BhullarNovartis Pharma AG, Department of Developmental and Molecular Pathways, Novartis Institute for Biomedical Research , Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging is a complex continuous multifactorial process leading to loss of function and crystalizing into the many age-related diseases. Here, we explore the arguments for classifying aging as a disease in the context of the upcoming World Health Organization's 11th International Statistical Classification of Diseases and Related Health Problems (ICD-11), expected to be finalized in 2018. We hypothesize that classifying aging as a disease with a "non-garbage" set of codes will result in new approaches and business models for addressing aging as a treatable condition, which will lead to both economic and healthcare benefits for all stakeholders. Actionable classification of aging as a disease may lead to more efficient allocation of resources by enabling funding bodies and other stakeholders to use quality-adjusted life years (QALYs) and healthy-years equivalent (HYE) as metrics when evaluating both research and clinical programs. We propose forming a Task Force to interface the WHO in order to develop a multidisciplinary framework for classifying aging as a disease with multiple disease codes facilitating for therapeutic interventions and preventative strategies.

Indexed as

agingbiogerontologydisease classificationICD-10ICD-11QALYtask forceWHO

Identifiers

PMID26583032
PMCPMC4631811

What OpenQuestion 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 OpenQuestion graph.