Evidence map›Paper›PMID 41723332›Full record

ReviewBiogerontology2026

Gerontology lost in translation from demography to biology of aging and back.

A Golubev

Erratum issuedAbstract readReview
PubMed Publisher
In one paragraph

Review in Biogerontology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Editorial: The Quest for Biomarkers of Biological Age and Longevity Identifies Roles for Small Noncoding RNAs, Including PIWI-Interacting RNAs.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

A GolubevDepartment of Carcinogenesis and Oncogerontology, N.N. Petrov National Medical Research Center of Oncology, 68 Leningradskaya Ul., Pesochny-2, Saint Petersburg, 197758, Russia. lxglbv@rambler.ru.ORCID 0000-0002-2129-6205

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changes in human survival and mortality patterns resulting in life expectancy (LE) increase are profoundly significant for society and critically depend on societal factors but cannot escape frames defined by biology. Demography, a social discipline, uses descriptive terms, such as survival curve rectangularization, mortality compression, lifespan disparity reduction, and mean (modal, median) lifespan increase, to define the beneficial changes thought possible due to deceleration of aging. The reasonability of this objective is questioned in the present article based on the premises that changes in mortality correlate linearly with changes in the pressure of causes of death and exponentially with changes in the ability to resist them. The biological background of these premises is essentially Gompertz-Makeham law (GML) generalization, which accommodates the possibility that the rate of aging and the pressure of causes of death may not be constant during lifespan. This topic is discussed with account for the compensation effect of mortality (CEM): viability correlates positively with the rate of its aging-associated declines. It is concluded that (i) aging deceleration is incompatible with beneficial demographic changes if the GML and CEM are valid; (ii) reducing the pressure of the extrinsic modifiable causes of death in countries featuring the highest LE cannot increase it by more than five years, and (iii) possible increases in LE are negatively correlated with its current levels.

Indexed as

AgingDemographyGeriatricsLife ExpectancyCause of DeathHumansLongevityPopulation DynamicsAgingDemographyForecastingGerontologyGompertz-Makeham LawLife expectancyLifespan distributionModelingSurvival curve

Identifiers

What OpenQuestion holds

Textmetadata
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.