Evidence map›Paper›PMID 34241630›Full record

ArticleJAMA network open2021

Trends in Patient Volume by Hospital Type and the Association of These Trends With Time to Cancer Treatment Initiation.

Zachary A K Frosch, Nicholas Illenberger, Nandita Mitra, Daniel J Boffa, Matthew A Facktor, Heidi Nelson, Bryan E Palis, Justin E Bekelman, Lawrence N Shulman, Samuel U Takvorian

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.8field-weighted citation impact, top 12% 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

19 citing papers in PubMed, 31 citations in OpenAlex.

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  10. "Cancer's a demon": a qualitative study of fear and multilevel factors contributing to cancer treatment delays.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Article
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  12. Organization of Cancer Specialists in US Physician Practices and Health Systems.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 1 country.

Zachary A K FroschDivision of Hematology & Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Nicholas IllenbergerDepartment of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Nandita MitraPenn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia.
Daniel J BoffaSection of Thoracic Surgery, Department of Surgery, Yale School of Medicine, New Haven, Connecticut.
Matthew A FacktorDepartment of Thoracic Surgery, Geisinger Heart Institute, Danville, Pennsylvania.
Heidi NelsonCancer Programs, American College of Surgeons, Chicago, Illinois.
Bryan E PalisCancer Programs, American College of Surgeons, Chicago, Illinois.
Justin E BekelmanPenn Center for Cancer Care Innovation, Abramson Cancer Center, University of Pennsylvania, Philadelphia.
Lawrence N ShulmanDivision of Hematology & Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Samuel U TakvorianDivision of Hematology & Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
University of Pennsylvania · USAbramson Cancer CenterAmerican College of Surgeons · USGeisinger Neuroscience Institute · USYale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
CANCER RESEARCH TRAINING PROGRAMT32CA009615 · NCI · UNIVERSITY OF PENNSYLVANIA · PI Gregory L Beatty, MICHAEL D HOGARTY · 1988 to 2026
$10.4M
NCATS NIH HHS UL1 TR001863NCI NIH HHS T32 CA009615
6 · The paper itself

Abstract

Importance: Increasing demand for cancer care may be outpacing the capacity of hospitals to provide timely treatment, particularly at referral centers such as National Cancer Institute (NCI)-designated and academic centers. Whether the rate of patient volume growth has strained hospital capacity to provide timely treatment is unknown. Objective: To evaluate trends in patient volume by hospital type and the association between a hospital's annual patient volume growth and time to treatment initiation (TTI) for patients with cancer. Design, Setting, and Participants: This retrospective, hospital-level, cross-sectional study used longitudinal data from the National Cancer Database from January 1, 2007, to December 31, 2016. Adult patients older than 40 years who had received a diagnosis of 1 of the 10 most common incident cancers and initiated their treatment at a Commission on Cancer-accredited hospital were included. Data were analyzed between December 19, 2019, and March 27, 2020. Exposures: The mean annual rate of patient volume growth at a hospital. Main Outcomes and Measures: The main outcome was TTI, defined as the number of days between diagnosis and the first cancer treatment. The association between a hospital's mean annual rate of patient volume growth and TTI was assessed using a linear mixed-effects model containing a patient volume × time interaction. The mean annual change in TTI over the study period by hospital type was estimated by including a hospital type × time interaction term. Results: The study sample included 4 218 577 patients (mean [SD] age, 65.0 [11.4] years; 56.6% women) treated at 1351 hospitals. From 2007 to 2016, patient volume increased 40% at NCI centers, 25% at academic centers, and 8% at community hospitals. In 2007, the mean TTI was longer at NCI and academic centers than at community hospitals (NCI: 50 days [95% CI, 48-52 days]; academic: 43 days [95% CI, 42-44 days]; community: 37 days [95% CI, 36-37 days]); however, the mean annual increase in TTI was greater at community hospitals (0.56 days; 95% CI, 0.49-0.62 days) than at NCI centers (-0.73 days; 95% CI, -0.95 to -0.51 days) and academic centers (0.14 days; 95% CI, 0.03-0.26 days). An annual volume growth rate of 100 patients, a level observed at less than 1% of hospitals, was associated with a mean increase in TTI of 0.24 days (95% CI, 0.18-0.29 days). Conclusions and Relevance: In this cross-sectional study, from 2007 to 2016, across the studied cancer types, patients increasingly initiated their cancer treatment at NCI and academic centers. Although increases in patient volume at these centers outpaced that at community hospitals, faster growth was not associated with clinically meaningful treatment delays.

Indexed as

AgedCross-Sectional StudiesFemaleHospitalsHumansMaleMiddle AgedNational Cancer Institute (U.S.)NeoplasmsPatient Acceptance of Health CareRetrospective StudiesTime-to-TreatmentUnited States

Identifiers

PMID34241630
PMCPMC8271360
OpenAlexW3178276814

What OpenQuestion holds

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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.