Evidence map›Paper›PMID 42201623›Full record

ArticleRheumatology and therapy2026

Clinical and Economic Burden Among People with Knee Osteoarthritis and Obesity in the United States: A Retrospective Analysis.

David Schapiro, Magaly Perez-Nieves, Sylvia Gonsahn-Bollie, Kendra Terrell, Ahong Huang, Wenyang Mao, Alexandra Meeks, Pedram Azimzadeh, Julia Fraseur

Abstract read
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Article in Rheumatology and therapy, 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. 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

9 authors.

David SchapiroEli Lilly and Company, Indianapolis, IN, USA. schapiro_david@lilly.com.ORCID http://orcid.org/0000-0002-3083-3615
Magaly Perez-NievesEli Lilly and Company, Indianapolis, IN, USA.
Sylvia Gonsahn-BollieEli Lilly and Company, Indianapolis, IN, USA.
Kendra TerrellEli Lilly and Company, Indianapolis, IN, USA.
Ahong HuangTigermed-BDM, Somerset, NJ, USA.
Wenyang MaoTigermed-BDM, Somerset, NJ, USA.
Alexandra MeeksEli Lilly and Company, Indianapolis, IN, USA.
Pedram AzimzadehEli Lilly and Company, Indianapolis, IN, USA.
Julia FraseurEli Lilly and Company, Indianapolis, IN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionObesity and knee osteoarthritis (KOA) are prevalent conditions that significantly impact public health and healthcare costs. We aimed to quantify the economic burden and explore the relationship between obesity and KOA pain.

methodsThis study used Optum's de-identified Market Clarity Data from October 1, 2015, to March 31, 2024. Adults (≥ 45 years) with moderate-to-severe osteoarthritis (MTS-OA) knee pain (index date: first-observed claim with a KOA diagnosis between October 1, 2016, and March 31, 2023), with continuous enrollment in commercial, Medicare, or Medicaid healthcare plans for 1 year before and after post index, were included. The presence of KOA pain was identified using a previously validated algorithm. Adjusted annualized all-cause and KOA-related healthcare resource utilization and costs were assessed in the first year after index date, stratified by body mass index (BMI) categories: normal (≥ 18.5 to < 25 kg/m

resultsThe prevalence of obesity-related complications was high, particularly among those with a BMI ≥ 35 kg/m

conclusionsIn people with MTS-OA knee pain, this descriptive analysis revealed higher observed average overall and disease-specific healthcare expenditure in Class 2 and 3 obesity than in other BMI categories.

Indexed as

ComorbiditiesHealth economicsKnee osteoarthritisModerate-to-severe osteoarthritisObesity

Identifiers

PMID42201623
PMCPMC13407822

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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.