Evidence map›Paper›PMID 41326530›Full record

ArticleScientific reports2025

Deriving monetary value of quality-adjusted life years through life extension from the value of a statistical life.

Yusuke Tanizawa, Kazuya Ito, Ryuta Takashima

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yusuke TanizawaDepartment of Industrial and Systems Engineering, Faculty of Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, 278-8510, Japan.
Kazuya ItoDepartment of Industrial and Systems Engineering, Faculty of Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, 278-8510, Japan. kazu-ito@rs.tus.ac.jp.
Ryuta TakashimaDepartment of Industrial and Systems Engineering, Faculty of Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, 278-8510, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To address the recent rise in healthcare expenditure due to an aging population, the rational allocation and efficient use of resources, based on scientific evidence, have become indispensable. This study proposes an alternative framework for estimating quality-adjusted life years (QALY) based on the value of statistical life, which can be used for cost-benefit analysis (CBA) of policy interventions and the efficient allocation of healthcare resources. Specifically, we estimate the monetary value of a QALY based solely on life extension. We assess the accuracy of conventional QALY estimates while proposing a new, more rational, and flexible QALY estimation that combines age and scenario factors. Our numerical analysis suggests that updating QALY by considering regional characteristics such as population, age distribution, and changes in quality of life (QoL) can lead to a more accurate CBA. This metric provides information for decision-making in policy budgeting based on scientific evidence and suggests that this approach may contribute to a more efficient allocation of healthcare resources. Furthermore, increasing the proportion of healthy individuals with a gradual decline in QoL may support efforts to reduce healthcare expenditure.

Indexed as

Life ExpectancyQuality-Adjusted Life YearsValue of LifeAdultAgedCost-Benefit AnalysisFemaleHealth ExpendituresHumansMaleMiddle AgedQuality of LifeCost-benefit analysisHealthcareQuality-adjusted life yearsValue of statistical life

Identifiers

PMID41326530
PMCPMC12770314

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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.