ArticlemedRxiv : the preprint server for health sciences2022
Health impacts of COVID-19 disruptions to primary cervical screening by time since last screen: A model-based analysis for current and future disruptions.
Article in medRxiv : the preprint server for health sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed, 0 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
- Updated by
Authors and funding
13 authors at 6 institutions in 6 countries.
Funding
Abstract
Background: 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. Methods: 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 HPV-based screening. Results: 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 under-screened women whose last cytology screen was 5 years prior to the disruption period compared with guidelines-compliant women (i.e., last screen three 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. Conclusions: 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 under-screened women, underpinning the importance of reaching such women as a critical area of focus, regardless of temporary disruptions. Funding: This study was supported by funding from the National Cancer Institute (U01CA199334). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Cancer Institute. Megan A Smith receives salary support from the National Health and Medical Research Council, Australia (APP1159491) and Cancer Institute NSW (ECF181561). Matejka Rebolj is funded by Cancer Research UK (reference: C8162/A27047). James O'Mahony is funded by Ireland's Health Research Board (EIA2017054). Karen Canfell receives salary support from the National Health and Medical Research Council, Australia (APP1194679). Emily A. Burger receives salary support from the Norwegian Cancer Society.
Identifiers
What OpenQuestion holds
Registered trials
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.