Evidence map›Paper›PMID 37902756›Full record

ArticleJAMA network open2023

Alterations in Cancer Treatment During the First Year of the COVID-19 Pandemic in the US.

Lauren M Janczewski, Joseph Cotler, Ryan P Merkow, Bryan Palis, Heidi Nelson, Timothy Mullett, Daniel J Boffa

Abstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Impact of the COVID-19 Pandemic on Inpatient Cancer Treatment and Outcomes in the United States.Mayo Clinic proceedings. Innovations, quality & outcomes · 2026
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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

7 authors.

Lauren M JanczewskiDepartment of Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Joseph CotlerAmerican College of Surgeons Cancer Programs, Chicago, Illinois.
Ryan P MerkowDepartment of Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Bryan PalisAmerican College of Surgeons Cancer Programs, Chicago, Illinois.
Heidi NelsonAmerican College of Surgeons Cancer Programs, Chicago, Illinois.
Timothy MullettDepartment of Surgery, University of Kentucky College of Medicine, Lexington.
Daniel J BoffaSection of Thoracic Surgery, Department of Surgery, Yale School of Medicine, New Haven, Connecticut.

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
COllaborative Northwestern Surgical Oncology Research Training (CONSORT)T32CA247801 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ACKERMANN, RONALD T., KHAN, SEEMA AHSAN · 2020 to 2024
$1.3M
NCATS NIH HHS UL1 TR001863NCI NIH HHS T32 CA247801
6 · The paper itself

Abstract

Importance: The COVID-19 pandemic created challenges to the evaluation and treatment of cancer, and abrupt resource diversion toward patients with COVID-19 put cancer treatment on hold for many patients. Previous reports have shown substantial declines in cancer screening and diagnoses in 2020; however, the extent to which the delivery of cancer care was altered remains unclear. Objective: To assess alterations in cancer treatment in the US during the first year of the COVID-19 pandemic. Design, Setting, and Participants: This retrospective cohort study used data from the National Cancer Database (NCDB) on patients older than 18 years with newly diagnosed cancer from January 1, 2018, to December 31, 2020. Main Outcomes and Measures: The main outcomes were accessibility (time to treatment, travel distance, and multi-institutional care), availability (proportional changes in cancer treatment between years), and utilization (reductions by treatment modality, hospital type) of cancer treatment in 2020 compared with 2018 to 2019. Autoregressive models forecasted expected findings for 2020 based on observations from prior years. Results: Of 1 229 654 patients identified in the NCDB in 2020, 1 074 225 were treated for cancer, representing a 16.8% reduction from what was expected. Patients were predominately female (53.8%), with a median age of 66 years (IQR, 57-74 years), similar to demographics in 2018 and 2019. Median time between diagnosis and treatment was 26 days (IQR, 0-36 days) in 2020, and median travel distance for care was 11.1 miles (IQR, 5.0-25.3 miles), similar to 2018 and 2019. In 2020, fewer patients traveled longer distances (20.2% reduction of patients traveling >35 miles). The proportions of patients treated with chemotherapy (32.0%), radiation (29.5%), and surgery (57.1%) were similar to those in 2018 and 2019. Overall, 146 805 fewer patients than expected underwent surgery, 80 480 fewer received radiation, and 68 014 fewer received chemotherapy. Academic hospitals experienced the greatest reduction in cancer surgery and treatment, with a decrease of approximately 484 patients (-19.0%) per hospital compared with 99 patients (-12.6%) at community hospitals and 110 patients (-12.8%) at integrated networks. Conclusions and Relevance: This study found that among patients diagnosed with cancer in 2020, access and availability of treatment remained intact; however, reductions in treated patients varied across treatment modalities and were greater at academic hospitals than at community hospitals and integrated networks compared with expected values. These results suggest the resilience of cancer service lines and frame the economic losses from reductions in cancer treatment during the pandemic.

Indexed as

COVID-19NeoplasmsAgedDatabases, FactualFemaleHospitals, CommunityHumansMaleMiddle AgedPandemicsRetrospective Studies

Identifiers

PMID37902756
PMCPMC10616721

What OpenQuestion holds

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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.