Evidence map›Paper›PMID 38676975›Full record

ArticleJournal of geriatric oncology2024

Predictors of high-intensity care at the end of life among older adults with solid tumors: A population-based study.

Courtney E Baird, Elizabeth Wulff-Burchfield, Pamela C Egan, Lee A Hugar, Ami Vyas, Nikolaos A Trikalinos, Michael A Liu, Emmanuelle Bélanger, Adam J Olszewski, Leonidas E Bantis and 1 more

Open access · greenAbstract read
In one paragraph

Article in Journal of geriatric oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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

11 authors at 6 institutions in 1 country.

Courtney E BairdCenter for Gerontology and Healthcare Research, Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, RI, USA. Electronic address: courtney_baird@brown.edu.
Elizabeth Wulff-BurchfieldMedical Oncology Division and Palliative Medicine Division, Department of Internal Medicine, University of Kansas School of Medicine, University of Kansas Cancer Center, The University of Kansas Health System, Kansas City, KS, USA.
Pamela C EganDepartment of Medicine, The Warren Alpert Medical School of Brown University, Providence, RI, USA.
Lee A HugarDepartment of Genitourinary Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA.
Ami VyasUniversity of Rhode Island, College of Pharmacy, Department of Pharmacy Practice, Kingston, RI, USA.
Nikolaos A TrikalinosDivision of Oncology, Department of Medicine, Washington University Medical School Campus, St. Louis, MO, USA; Siteman Cancer Center, St. Louis, MO, USA.
Michael A LiuColumbia University Medical Center, Herbert Irving Comprehensive Cancer Center, New York, NY, USA.
Emmanuelle BélangerCenter for Gerontology and Healthcare Research, Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, RI, USA.
Adam J OlszewskiDepartment of Medicine, The Warren Alpert Medical School of Brown University, Providence, RI, USA.
Leonidas E BantisDepartment of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
Orestis A PanagiotouCenter for Gerontology and Healthcare Research, Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, RI, USA.
Brown University · USHerbert Irving Comprehensive Cancer CenterMoffitt Cancer Center · USRhode Island College · USThe University of Kansas Cancer Center · USUniversity of Kansas Medical Center · US

Funding

RADx-UP: Improving the Response of Local Urban and Rural Communities to Disparities in Covid-19 TestingUL1TR002366 · NCATS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Mario Castro, JAMES STEVEN LEEDER · 2017 to 2026
$44.3M
Molecular Oncology Training ProgramT32CA203703 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Katherine D Crew, DAWN HERSHMAN · 2016 to 2026
$4.1M
NCATS NIH HHS UL1 TR002366NCI NIH HHS HHSN261201800009CNCI NIH HHS HHSN261201800009INCI NIH HHS HHSN261201800015CNCI NIH HHS HHSN261201800015INCI NIH HHS HHSN261201800032CNCI NIH HHS HHSN261201800032INCI NIH HHS T32 CA203703
6 · The paper itself

Abstract

introductionHigh-intensity end-of-life (EoL) care can be burdensome for patients, caregivers, and health systems and does not confer any meaningful clinical benefit. Yet, there are significant knowledge gaps regarding the predictors of high-intensity EoL care. In this study, we identify risk factors associated with high-intensity EoL care among older adults with the four most common malignancies, including breast, prostate, lung, and colorectal cancer. MATERIALS AND

methodsUsing SEER-Medicare data, we conducted a retrospective analysis of Medicare beneficiaries aged 65 and older who died of breast, prostate, lung, or colorectal cancer between 2011 and 2015. We used multivariable logistic regression to identify clinical, demographic, socioeconomic, and geographic predictors of high-intensity EoL care, which we defined as death in an acute care hospital, receipt of any oral or parenteral chemotherapy within 14 days of death, one or more admissions to the intensive care unit within 30 days of death, two or more emergency department visits within 30 days of death, or two or more inpatient admissions within 30 days of death.

resultsAmong 59,355 decedents, factors associated with increased likelihood of receiving high-intensity EoL care were increased comorbidity burden (odds ratio [OR]:1.29; 95% confidence interval [CI]:1.28-1.30), female sex (OR:1.05; 95% CI:1.01-1.09), Black race (OR:1.14; 95% CI:1.07-1.23), Other race/ethnicity (OR:1.20; 95% CI:1.10-1.30), stage III disease (OR:1.11; 95% CI:1.05-1.18), living in a county with >1,000,000 people (OR:1.23; 95% CI:1.16-1.31), living in a census tract with 10%-<20% poverty (OR:1.09; 95% CI:1.03-1.16) or 20%-100% poverty (OR:1.12; 95% CI:1.04-1.19), and having state-subsidized Medicare premiums (OR:1.18; 95% CI:1.12-1.24). The risk of high-intensity EoL care was lower among patients who were older (OR:0.98; 95% CI:0.98-0.99), lived in the Midwest (OR:0.69; 95% CI:0.65-0.75), South (OR:0.70; 95% CI:0.65-0.74), or West (OR:0.81; 95% CI:0.77-0.86), lived in mostly rural areas (OR:0.92; 95% CI:0.86-1.00), and had poor performance status (OR:0.26; 95% CI:0.25-0.28). Results were largely consistent across cancer types. DISCUSSION: The risk factors identified in our study can inform the development of new interventions for patients with cancer who are likely to receive high-intensity EoL care. Health systems should consider incorporating these risk factors into decision-support tools to assist clinicians in identifying which patients should be referred to hospice and palliative care.

Indexed as

MedicareNeoplasmsSEER ProgramTerminal CareAgedAged, 80 and overBreast NeoplasmsColorectal NeoplasmsFemaleHospitalizationHumansLogistic ModelsLung NeoplasmsMaleProstatic NeoplasmsRetrospective StudiesBreast cancerGastrointestinal cancerGeriatric oncologyLung cancerPalliative careProstate cancer

Identifiers

PMID38676975
PMCPMC11162260
OpenAlexW4395684191

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.