Evidence map›Paper›PMID 37515440›Full record

ArticleJournal of the American Geriatrics Society2023

Aggressive end-of-life care across gradients of cognitive impairment in nursing home patients with metastatic cancer.

Siran M Koroukian, Sara L Douglas, Long Vu, Hannah L Fein, Richa Gairola, David F Warner, Nicholas K Schiltz, Jennifer Cullen, Cynthia Owusu, Martha Sajatovic and 1 more

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Siran M KoroukianDepartment of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.ORCID 0000-0002-8106-9581
Sara L DouglasCase Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.ORCID 0000-0002-9444-4387
Long VuDepartment of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
Hannah L FeinDepartment of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
Richa GairolaDepartment of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, USA.
David F WarnerDepartment of Sociology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Nicholas K SchiltzFrances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio, USA.ORCID 0000-0003-0122-6477
Jennifer CullenDepartment of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
Cynthia OwusuCase Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.
Martha SajatovicDepartment of Neurology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
Johnie RoseDepartment of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA.

Funding

TUMOR METABOLISM PROGRAMP30CA043703 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI Amar Desai · 1987 to 2026
$142.3M
NCI NIH HHS P30 CA043703
6 · The paper itself

Abstract

backgroundStudies examining end-of-life (EOL) care in older cancer patients are scarce, and prior studies have not accounted for gradients of cognitive impairment (COG-I). We examine EOL care patterns across COG-I gradients, hypothesizing that greater COG-I severity is associated with lower odds of receiving aggressive EOL care.

methodsUsing data from the linked Surveillance Epidemiology and End Results (SEER) -Medicare -Minimum Data Set (MDS) 3.0, we identified patients with nursing facility stays (NFS) and who died with metastatic cancer from 2013 to 2017. Markers of aggressive EOL care were: cancer-directed treatment, intensive care unit admission, >1 emergency department visit, or >1 hospitalization in the last 30 days of life, hospice enrollment in the last 3 days of life, and in-hospital death. In addition to descriptive analysis, we conducted multivariable logistic regression analysis to evaluate the independent association between COG-I severity and receipt of aggressive EOL care.

resultsOf the 40,833 patients in our study population, 49.2% were cognitively intact; 24.4% had mild COG-I; 19.7% had moderate COG-I; and 6.7% had severe COG-I. The percent of patients who received aggressive EOL care was 62.6% and 74.2% among those who were cognitively intact and those with severe COG-I, respectively. Compared with cognitively intact patients, those with severe COG-I had 86% higher odds of receiving any type of aggressive EOL care (adjusted odds ratio (aOR): 1.86 (95% confidence interval: 1.70-2.04)), which were primarily associated with higher odds of in-hospital death. The odds of in-hospital death associated with severe COG-I were higher among those with short- than with long-term stays (aOR:2.58 (2.35-2.84) and aOR:1.40 (1.17-1.67), respectively).

conclusionsContrary to our hypothesis, aggressive EOL care in older metastatic cancer patients with NFS was highest among those suffering severe COG-I. These findings can inform the development of interventions to help reduce aggressive EOL care in this patient population.

Indexed as

Cognitive DysfunctionHospice CareNeoplasmsTerminal CareAgedHospital MortalityHumansMedicareNursing HomesRetrospective StudiesUnited Statesaggressive end-of-life caremetastatic cancernursing home status

Identifiers

PMID37515440
PMCPMC10907987

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.