Evidence map›Paper›PMID 42095257›Full record

ArticleACR open rheumatology2026

Lupus, a Leading Cause of Years of Potential Life Lost in Young Women: Implications for Public Health Priorities and Research Funding.

Eric Y Yen, Elizabeth J Park, Ram Raj Singh

Abstract read
In one paragraph

Article in ACR open rheumatology, 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

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. 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

3 authors.

Eric Y YenDepartment of Medicine, University of California at Los Angeles (UCLA).
Elizabeth J ParkDepartment of Medicine, University of California at Los Angeles (UCLA).
Ram Raj SinghDepartment of Medicine, University of California at Los Angeles (UCLA).ORCID https://orcid.org/0000-0002-6831-4538

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePremature mortality burden is an important component of disease burden and can help guide health care and research priorities. However, relying solely on mortality rates may underestimate lupus mortality burden because a substantial proportion of deaths occur at younger ages. Years of potential life lost (YPLL) captures premature mortality by applying a predefined age threshold. We estimated the YPLL from lupus in US women relative to leading causes of death and other autoimmune diseases.

methodsUsing the US population-based national Multiple Cause-of-Death database, we obtained death counts for 28 diseases, including lupus, the Centers for Disease Control and Prevention's 15 leading causes of death, and 12 additional autoimmune diseases. We calculated YPLL before age 75 years by summing 75 minus age at death for deaths occurring before age 75. Official cause-of-death rankings were obtained from the Web-based Injury Statistics Query and Reporting System (WISQARS). Sensitivity analyses were repeated in female decedents during 2018 to 2024.

resultsFrom 2000 to 2015, 304.2 thousand years were lost to lupus in US women aged 15 to 44 years. Lupus-associated YPLL ranked 14th in women aged 15 to 44 years and 9th in women aged 15 to 24, exceeding diabetes mellitus, HIV disease, septicemia, chronic lower respiratory disease, anemias, nephritis, and cerebrovascular disease. Among autoimmune diseases, lupus YPLL ranked first in women aged 15 to 24 years and second in women aged 15 to 44 years.

conclusionLupus is a major contributor to premature mortality in young women. Quantifying premature mortality burden through YPLL provides a complementary public health perspective and may inform prioritization of research and public health initiatives.

Identifiers

PMID42095257
PMCPMC13150475

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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.