Evidence map›Paper›PMID 42008267›Full record

ArticleJAMA network open2026

Financial Hardship, End-of-Life Health Care Use, and Costs in Patients With Cancer.

Veena Shankaran, Li Li, Sara Khor, Kaiyue Yu, C Natasha Kwendakwema, Catherine Fedorenko, Karma Kreizenbeck, Hiba M Khan, Shannon Kestner, Winona Wright and 1 more

Abstract read
In one paragraph

Article in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Veena ShankaranHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Li LiHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Sara KhorThe Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, University of Washington, Seattle.
Kaiyue YuDepartment of Public Health Sciences, College of Medicine, Pennsylvania State University, Hershey.
C Natasha KwendakwemaHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Catherine FedorenkoHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Karma KreizenbeckHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Hiba M KhanHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Shannon KestnerHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Winona WrightHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.
Scott RamseyHutchinson Institute for Cancer Outcomes Research, Fred Hutch Cancer Center, Seattle, Washington.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Patients with cancer are at higher risk of adverse financial events (AFEs) compared with individuals without cancer. However, little is known about how personal finances affect cancer care, particularly at the end of life (EOL). Objective: To investigate the association between AFEs and health care use and costs at EOL among patients with cancer. Design, Setting, and Participants: In this cohort study, Western Washington Surveillance, Epidemiology, and End Results cancer registry cases were linked to claims from commercial payers and Medicare and to credit records from TransUnion. Patients with American Joint Committee on Cancer stage I to IV solid tumors who died between January 1, 2013, and December 31, 2019, were identified. Data analysis was performed from January 2023 and June 2025. Main Outcomes and Measures: Emergency department (ED) and inpatient visits in the last 3 months of life, place of death, and mean adjusted health care costs per patient were compared between patients with vs without new AFEs in the 2 years preceding EOL (charge-offs, third-party collections, tax liens, delinquent mortgage payments, foreclosures, or repossessions). A multivariate logistic regression analysis evaluated the association between AFEs and the outcomes of ED or inpatient visits and inpatient death. Health care costs in the last 3 and 6 months of life were analyzed using 2-part models to account for zero costs and right-skewed positive expenditures; adjusted average treatment effects were estimated. Results: A total of 10 826 patients (median [IQR] age, 75 [69-83] years; 5877 [54%] male; 932 [8.6%] with AFEs) were included. Patients with AFEs were more likely to have multiple ED or inpatient visits (odds ratio [OR], 1.41; 95% CI, 1.22-1.62; P < .001) and die in a hospital (OR, 1.50; 95% CI, 1.30-1.75; P < .001). Mean (SD) adjusted total health care costs were higher in patients with AFEs than those without in the last 3 months ($35 115 [$1415] vs $31 031 [$389]) and 6 months ($57 401 [$2181] vs $51 602 [$581]) of life, yielding a mean adjusted incremental costs in the AFE group of $4084 (95% CI, $1287-$7087; P = .006) and $5799 (95% CI, $1235-$9996; P = .01), respectively. Conclusions and Relevance: In this cohort study, AFEs were associated with greater ED and inpatient use, higher risk of inpatient death, and higher care costs at EOL. These findings point to the need for future studies investigating whether interventions that mitigate financial hardship could improve the EOL experience and decrease health care costs for patients with cancer.

Indexed as

Financial StressHealth Care CostsHealth ExpendituresNeoplasmsPatient Acceptance of Health CareTerminal CareAgedAged, 80 and overCohort StudiesEmergency Room VisitsEmergency Service, HospitalFemaleHumansMaleMiddle AgedSEER Program

Identifiers

PMID42008267
PMCPMC13096980

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LicenceCC BY
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Registered trials

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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.