Evidence map›Paper›PMID 26181909›Full record

ArticleJAMA oncology2015

Trends in Advance Care Planning in Patients With Cancer: Results From a National Longitudinal Survey.

Amol K Narang, Alexi A Wright, Lauren H Nicholas

Abstract readComment
In one paragraph

Article in JAMA oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
12.6field-weighted citation impact, top 1% 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

51 citing papers in PubMed, 1 synthesis or guideline pooled it, 123 citations in OpenAlex.

  1. Pooled it
  2. The Impact of Machine Learning Mortality Risk Prediction on Clinician Prognostic Accuracy and Decision Support: A Randomized Vignette Study.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
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  16. When does early palliative care influence aggressive care at the end of life?Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Amol K NarangDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland.
Alexi A WrightDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts3Harvard Medical School, Boston, Massachusetts.
Lauren H NicholasDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland5Department of Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland.
Harvard University · USJohns Hopkins Medicine · USJohns Hopkins University · US

Funding

Chemotherapy Near Death: Modifiable Factors and Outcomes in Ovarian CancerK07CA166210 · NCI · DANA-FARBER CANCER INST · PI WRIGHT, ALEXI A · 2013 to 2017
$886k
Geographic Variation in the Health and Economic Determinants and Outcomes of ElecK01AG041763 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NICHOLAS, LAUREN HERSCH · 2012 to 2016
$622k
NCI NIH HHS K07 CA166210NCI NIH HHS K07CA166210NIA NIH HHS K01 AG041763NIA NIH HHS K01AG041763
6 · The paper itself

Abstract

importanceAdvance care planning (ACP) may prevent end-of-life (EOL) care that is nonbeneficial and discordant with patient wishes. Despite long-standing recognition of the merits of ACP in oncology, it is unclear whether participation in ACP by patients with cancer has increased over time.

objectivesTo characterize trends in durable power of attorney (DPOA) assignment, living will creation, and participation in discussions of EOL care preferences and to explore associations between ACP subtypes and EOL treatment intensity as reflected in EOL care decisions and terminal hospitalizations. DESIGN, SETTING, AND

participantsWe analyzed prospectively collected survey data from 1985 next-of-kin surrogates of Health and Retirement Study (HRS) participants with cancer who died between 2000 and 2012, including data from in-depth "exit" interviews conducted with the surrogates after the participant's death. The HRS is a nationally representative, biennial, longitudinal panel study of US residents older than 50 years. Trends in ACP subtypes were tested, and multivariable logistic regression models examined for associations between ACP subtypes and measures of treatment intensity. MAIN OUTCOMES AND MEASURES: Trends in the surrogate-reported frequency of DPOA assignment, living will creation, and participation in discussions of EOL care preferences; associations between ACP subtypes and both surrogate-reported EOL care decisions and terminal hospitalizations.

resultsFrom 2000 to 2012, there was an increase in DPOA assignment (52% to 74%, P = .03), without significant change in use of living wills (49% to 40%, P = .63) or EOL discussions (68% to 60%, P = .62). Surrogate reports that patients received "all care possible" at EOL increased during the period (7% to 58%, P = .004), and rates of terminal hospitalizations were unchanged (29% to 27%, P = .70). Limiting or withholding treatment was associated with living wills (adjusted odds ratio [AOR], 2.51; 95% CI, 1.53-4.11; P < .001) and EOL discussions (AOR, 1.93; 95% CI, 1.53-3.14; P = .002) but not with DPOA assignment. CONCLUSIONS AND RELEVANCE: Use of DPOA increased significantly between 2000 and 2012 but was not associated with EOL care decisions. Importantly, there was no growth in key ACP domains such as discussions of care preferences. Efforts that bolster communication of EOL care preferences and also incorporate surrogate decision makers are critically needed to ensure receipt of goal-concordant care.

Indexed as

Health Maintenance OrganizationsFemaleHealth ResourcesHumansMaleNeoplasmsTerminal Care

Identifiers

PMID26181909
PMCPMC4537325
OpenAlexW2148213673

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.