Evidence map›Paper›PMID 31710664›Full record

Observational studyJournal of the National Cancer Institute2020

Factors Associated With Use of High-Cost Agents for the Treatment of Metastatic Non-Small Cell Lung Cancer.

Cathy J Bradley, Megan Eguchi, Marcelo C Perraillon

Open access · bronzeAbstract readObservational Study
In one paragraph

Observational study in Journal of the National Cancer Institute, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
6.0field-weighted citation impact, top 4% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Financial burden of high-cost immunotherapy among cancer survivors in Medicare.Journal of cancer survivorship : research and practice · 2026
    Article
  3. Review
  4. Ecological and individualistic fallacies in health disparities research.Journal of the National Cancer Institute · 2023
    Article
  5. Article
  6. Enhancing Health Equity Through Cancer Health Economics Research.Journal of the National Cancer Institute. Monographs · 2022
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Potential Impact of Cessation Interventions at the Point of Lung Cancer Screening on Lung Cancer and Overall Mortality in the United States.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2020
    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

3 authors at 2 institutions in 1 country.

Cathy J BradleyUniversity of Colorado Cancer Center and the Department of Health, Systems, Management, and Policy, Aurora, CO.
Megan EguchiPopulation Health Shared Resource, University of Colorado Cancer Center, Aurora, CO.
Marcelo C PerraillonDepartment of Health Systems, Management and Policy, University of Colorado, Aurora, CO.
University of Colorado Cancer Center · USUniversity of Colorado Anschutz Medical Campus · US

Funding

University of Colorado Cancer Center Support Grant - Lung Cancer Patient-Derived Xenografts with Autologous Human Immune SystemsP30CA046934 · NCI · UNIVERSITY OF COLORADO DENVER · PI James V Degregori · 1988 to 2026
$117.0M
Addressing Urban Rural Disparities in Cancer: The Case for Registry ExpansionR01CA229551 · NCI · UNIVERSITY OF COLORADO DENVER · PI BRADLEY, CATHY J, PERRAILLON, MARCELO COCA · 2019 to 2022
$1.6M
NCI NIH HHS P30 CA046934NCI NIH HHS R01 CA229551
6 · The paper itself

Abstract

backgroundAntineoplastic agents approved in recent decades are a marked advancement in cancer treatment, but they come at considerable cost. These drugs may widen survival disparities between patients who receive these agents and those who do not. We examine factors associated with the use of high-cost antineoplastic agents for the treatment of metastatic non-small cell lung cancer.

methodsWe conducted a retrospective observational study using 2007-2015 Surveillance, Epidemiology, and End-Results-Medicare data supplemented with the Area Health Resource File. Patients were aged 66 years and older, were enrolled in fee-for-service Medicare Part D, were diagnosed with a first primary diagnosis of metastatic non-small cell lung cancer, and had received an antineoplastic agent. "High-cost agents" were defined as agents costing $5000 or more per month. Independent variables include race/ethnicity, urban or rural residency, census tract poverty, and treatment facility type (eg, National Cancer Institute designation).

resultsPatients who lived in areas of high poverty were 4 percentage points less likely to receive high-cost agents (two-sided P < .001). Patients who were not treated at a National Cancer Institute-designated center were 10 percentage points less likely to receive these agents (two-sided P < .001). A 27 percentage-point increase in the likelihood of receiving a high-cost agent was observed in 2015, as compared to 2007, highlighting the rapid change in practice patterns (two-sided P < .001).

conclusionPotential policy and care delivery solutions involve outreach and support to community physicians who treat patients in remote areas. We estimate that widespread use of these agents conservatively cost approximately $3 billion per year for the treatment of metastatic non-small cell lung cancer alone.

Indexed as

Drug CostsAgedAged, 80 and overAntineoplastic AgentsCarcinoma, Non-Small-Cell LungFemaleHealth Care CostsHumansLung NeoplasmsMaleMedicareNeoplasm MetastasisRetrospective StudiesRisk FactorsSEER ProgramUnited StatesAntineoplastic Agents

Identifiers

PMID31710664
PMCPMC7825480
OpenAlexW2986048075

What OpenQuestion holds

Textmetadata
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.