Evidence map›Paper›PMID 36222673›Full record

ArticleeLife2022

A model-based analysis of the health impacts of COVID-19 disruptions to primary cervical screening by time since last screen for current and future disruptions.

Emily A Burger, Inge M C M de Kok, James F O'Mahony, Matejka Rebolj, Erik E L Jansen, Daniel D de Bondt, James Killen, Sharon J Hanley, Alejandra Castanon, Mary Caroline Regan and 3 more

Open access · goldAbstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 36% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Impacts of a Public Health Emergency on Cancer Testing Rates, Follow-up, and Cancer Diagnosis: An Evaluation of the COVID-19 Pandemic.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 8 countries.

Emily A BurgerCenter for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, United States.ORCID 0000-0002-6657-5849
Inge M C M de Kok *Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.
James F O'Mahony *Centre for Health Policy & Management, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Matejka ReboljFaculty of Life Sciences & Medicine, School of Cancer & Pharmaceutical Sciences, King's College London, London, United Kingdom.ORCID 0000-0001-9597-645X
Erik E L JansenDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.ORCID 0000-0003-0436-6918
Daniel D de BondtDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.
James KillenCancer Research Division, Cancer Council NSW, Sydney, Australia.
Sharon J HanleyHokkaido University Center for Environmental and Health Sciences, Sapporo, Japan.ORCID 0000-0002-7554-004X
Alejandra CastanonFaculty of Life Sciences & Medicine, School of Cancer & Pharmaceutical Sciences, King's College London, London, United Kingdom.
Mary Caroline ReganCenter for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, United States.
Jane J KimCenter for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, United States.
Karen CanfellDaffodil Centre, University of Sydney, a joint venture with Cancer Council NSW, Sydney, Australia.
Megan A SmithDaffodil Centre, University of Sydney, a joint venture with Cancer Council NSW, Sydney, Australia.ORCID 0000-0002-0401-2653
Cancer Council NSW · AUErasmus MC · NLKing's College London · GBHokkaido University · JPTrinity College Dublin · IEUniversity of Oslo · NO

Funding

Comparative Modeling to Inform Cervical Cancer Control Policies: USPSTF SupplementU01CA253912 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI BARNABAS, RUANNE VANESSA, CANFELL, KAREN · 2020 to 2024
$7.9M
Comparative Modeling to Inform Cervical Cancer Control PoliciesU01CA199334 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI BARNABAS, RUANNE VANESSA, CANFELL, KAREN · 2015 to 2019
$6.4M
Cancer Research UK 27047Cancer Research UK C8162/A27047NCI NIH HHS U01 CA199334NCI NIH HHS U01 CA253912
6 · The paper itself

Abstract

We evaluated how temporary disruptions to primary cervical cancer (CC) screening services may differentially impact women due to heterogeneity in their screening history and test modality. We used three CC models to project the short- and long-term health impacts assuming an underlying primary screening frequency (i.e., 1, 3, 5, or 10 yearly) under three alternative COVID-19-related screening disruption scenarios (i.e., 1-, 2-, or 5-year delay) versus no delay in the context of both cytology-based and human papillomavirus (HPV)-based screening. Models projected a relative increase in symptomatically detected cancer cases during a 1-year delay period that was 38% higher (Policy1-Cervix), 80% higher (Harvard), and 170% higher (MISCAN-Cervix) for underscreened women whose last cytology screen was 5 years prior to the disruption period compared with guidelines-compliant women (i.e., last screen 3 years prior to disruption). Over a woman's lifetime, temporary COVID-19-related delays had less impact on lifetime risk of developing CC than screening frequency and test modality; however, CC risks increased disproportionately the longer time had elapsed since a woman's last screen at the time of the disruption. Excess risks for a given delay period were generally lower for HPV-based screeners than for cytology-based screeners. Our independent models predicted that the main drivers of CC risk were screening frequency and screening modality, and the overall impact of disruptions from the pandemic on CC outcomes may be small. However, screening disruptions disproportionately affect underscreened women, underpinning the importance of reaching such women as a critical area of focus, regardless of temporary disruptions.

Indexed as

COVID-19Papillomavirus InfectionsUterine Cervical NeoplasmsCervix UteriEarly Detection of CancerFemaleHumanscervical cancercomputational biologyCOVID-19nonesimulation modelingsystems biology

Identifiers

PMID36222673
PMCPMC9555861
OpenAlexW4304190139

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.