Evidence map›Paper›PMID 35005670›Full record

ArticleThe Lancet regional health. Western Pacific2022

Unequal impact of the COVID-19 pandemic on paediatric cancer care: a population-based cohort study in China.

Hong Xiao, Fang Liu, Yao He, Xiaochen Dai, Zhenhui Liu, Weiyan Jian, Joseph M Unger

Open access · goldAbstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 17% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

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  6. Influence of the COVID-19 pandemic on the incidence and mortality of primary spinal tumors in the United States: A SEER analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025
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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 at 5 institutions in 2 countries.

Hong XiaoPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
Fang LiuChinese Center for Disease Control and Prevention, Beijing, China.
Yao HeDepartment of Global Health, University of Washington, Seattle, WA.
Xiaochen DaiInstitute for Health Metrics and Evaluation, Seattle, WA.
Zhenhui LiuAffiliated Hospital of Jining Medical University, Shandong, China.
Weiyan JianSchool of Public Health, Peking University, Beijing, China.
Joseph M UngerPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
Fred Hutch Cancer Center · USUniversity of Washington · USAffiliated Hospital of Jining Medical University · CNChinese Center For Disease Control and Prevention · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has had widespread adverse collateral effects on health care delivery for non-COVID-19 disease conditions. Paediatric oncology care is reliant on prompt testing and diagnosis and on timely and coordinated multimodal treatment, all of which have been impacted by the pandemic. This study aimed to quantify the initial and enduring effects of the COVID-19 pandemic on the utilization of paediatric cancer care and to examine whether the pandemic differentially impacted specific demographic groups.

methodWe performed an interrupted time series analysis using negative binomial regression to estimate the change in the monthly admissions for paediatric cancer patients (Age 0-17) associated with the COVID-19 pandemic and subsequent lockdown policies. We obtained data from deidentified individual electronic medical records of paediatric cancer inpatients admitted between January 1, 2015 and May 31, 2021 to a tertiary hospital that provides general and specialized healthcare services to an estimated population of 8.4 million in Jining China. Relative risk (RR) estimates representing monthly admissions compared with expected admissions had the pandemic not occurred were derived. The number of inpatient admissions lost due to the pandemic were estimated.

findingsThe overall denominator for the paediatric population was 1 858 209 individuals in January 2015, which increased to 2 043 803 by May 2021. In total, there were 4 901 admissions for paediatric cancer during the study period, including 1 479 (30%) since February 2020 when the lockdown was implemented. A 33% reduction (95% CI: -43% to -22%) in admissions was observed in February 2020, with the largest relative reduction (-48%, 95% CI: -64% to -24%) among first-time admissions and admissions for patients from rural districts (-46%, 95% CI: -55% to -36%). Admissions quickly rebounded in March 2020 when many government-imposed mobility restrictions were lifted, and continued to resume gradually over time since April 2020, leading to a full recovery as of November 2020. However, the recovery for first-time admissions, and among female patients, younger patients (<5 years) and patients from rural districts was slower over time and incomplete (first-time admissions and rural patients) as of January 2021.

interpretationThe COVID-19 pandemic has had substantial impact on the timely utilization of paediatric oncology services in China, particularly in the early stage of the first wave. Importantly, some population groups were disproportionately affected and the recovery of admissions among those subgroups has been slow and incomplete, warranting targeted approaches to address potentially exacerbated gender and socio-economic inequalities in access to healthcare resources.

Identifiers

PMID35005670
PMCPMC8718443
OpenAlexW4206213687

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.