Evidence map›Paper›PMID 31920351›Full record

ArticleClinicoEconomics and outcomes research : CEOR2019

Healthcare Costs of Potential Glucocorticoid-Associated Adverse Events in Patients with Giant Cell Arteritis.

Jennie H Best, Amanda M Kong, David M Smith, Ibrahim Abbass, Margaret Michalska

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Article in ClinicoEconomics and outcomes research : CEOR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Advances and challenges in management of large vessel vasculitis.Rheumatology and immunology research · 2023
    Article
  5. 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

5 authors.

Jennie H BestGenentech, Inc., South San Francisco, CA, USA.
Amanda M KongIBM Watson Health, Cambridge, MA, USA.ORCID 0000-0002-6210-4185
David M SmithIBM Watson Health, Cambridge, MA, USA.
Ibrahim AbbassGenentech, Inc., South San Francisco, CA, USA.
Margaret MichalskaGenentech, Inc., South San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo quantify the healthcare expenditures associated with potential oral glucocorticoid (OGC)-related adverse events (AEs) in patients with giant cell arteritis (GCA).

methodsPatients with GCA and ≥ 1 OGC prescription fill between 2009 and 2014 were identified from the MarketScan Commercial and Medicare Supplemental claims databases. Patients were stratified into four groups based on cumulative OGC dose (> 0 to ≤ 2607 mg, > 2607 to ≤ 4800 mg, > 4800 to ≤ 7200 mg, and > 7200 mg) during the 1-year follow-up period; incidence of potential AEs and AE-related direct healthcare costs in USD were assessed. Association between the log of cumulative OGC dose and AE-related direct healthcare costs was evaluated, adjusting for baseline characteristics.

resultsOf 1602 patients with GCA included, 69% were women; the mean age was 73 years. The mean cumulative OGC dose was 5806 mg during the 1-year follow-up; most exposure occurred in the first 6 months. The proportion of patients with potential OGC-related AEs was 36.5% overall and increased as cumulative dose increased (30.7%-45.3% across dose groups). Unadjusted mean AE-related costs for patients with an AE was USD $12,818. In the multivariable model including all patients, increasing OGC dose was associated with increasing AE-related healthcare costs (cost ratio, 1.38 [95% CI, 1.16-1.64] per 1-unit increase in log of cumulative OGC dose [

conclusionIn patients with GCA, OGC-related AEs increased with increasing cumulative OGC dose, resulting in increased healthcare costs. These results highlight the need for efficacious therapies that reduce the exposure to and potential risks associated with OGCs.

Indexed as

adverse eventsgiant cell arteritisglucocorticoidhealthcare expenditures

Identifiers

PMID31920351
PMCPMC6934125

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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.