Evidence map›Paper›PMID 41796339›Full record

ArticlePopulation health metrics2026

Reframing disease burden: validation of DALY-per-case as a per-diagnosis severity metric.

Omar Freihat

Abstract readValidation Study
In one paragraph

Article in Population health metrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

1 author.

Omar FreihatDepartment of environmental and public health, college of health science, Abu Dhabi University, Abu Dhabi, 59911, UAE. Freihat.omar@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation-weighted metrics (incidence, mortality, disability-adjusted life years (DALYs), mortality to incidence ratio (MIR) can obscure per-case severity for less prevalent but high-impact conditions. This paper introduces DALY per case, total DALYs divided by incident cases, as a standardized estimate of healthy life-years lost per new diagnosis, integrating years of life lost (YLL) and years lived with disability (YLD). Validated using cancers and applied across diverse diseases, the metric enables prevalence-independent severity comparisons.

methodsUsing GBD 2021, we computed DALY per case across diseases (all ages, both sexes), validated on 34 cancers, and tested generalizability in five non-cancer conditions (type 2-diabetes, tuberculosis, HIV/AIDS, ischemic heart disease, Alzheimer's). We compared rankings with incidence, mortality, and total DALYs. A 2-Dimensional framework plotted total DALYs (population burden) vs. DALY-per-case (individual severity) with median-based quadrant thresholds. Uncertainty intervals (UIs) were propagated per GBD conventions; stability was assessed via relative UI width, band-crossing, and sensitivity analyses. Construct/convergent validity used correlations with 5-year survival Surveillance, Epidemiology, and End Results Program (SEER) and MIR; full and reduced regressions tested independence.

resultsHigh-severity cancers included malignant bone tumours (27.6 DALYs/case), neuroblastoma (26.3), and brain/CNS (24.9), contrasting with population-dominant burdens such as lung (46.5 million DALYs; 20.4/case) and colorectal (24.4 million; 11.1/case). Relative uncertainty spanned 27% (breast) to 96% (Hodgkin lymphoma); rankings were largely preserved despite wide UIs in select sites. DALY-per-case correlated inversely with 5-year survival (r=-0.72, p < 0.001) and positively with MIR (r = 0.75, p < 0.001). In regression, MIR showed the strongest effect (β = 0.52, p = 0.06); survival lost significance when MIR was included, indicating shared but non-redundant variance.

conclusionsDALY-per-case provides a disease-agnostic toolkit, including a 2Dimensional burden-severity framework and validation against existing indicators, to quantify per-diagnosis severity and inform policy across communicable and non-communicable diseases.

Indexed as

Cost of IllnessDisability-Adjusted Life YearsQuality-Adjusted Life YearsAdultAgedFemaleHumansIncidenceMaleMiddle AgedNeoplasmsSeverity of Illness IndexBurden decompositionComparative epidemiologyDisability-adjusted life yearsGlobal health metricsMortality-to-incidence ratioPer-incident burdenSeverity stratification

Identifiers

PMID41796339
PMCPMC13081330

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LicenceCC BY-NC-ND
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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.