Impact of repeatedly screening negative on cervical cancer risk

Triennial screening that includes HPV testing becomes inefficient after a single and more so after multiple negative screens. These data support the use of longer screening intervals, especially following negative screen(s).

Authors

Institutions

Publication Details

Journal
JNCI Journal of the National Cancer Institute
Published
2025-10-29
DOI
https://doi.org/10.1093/jnci/djaf317
Primary Topic
Cervical Cancer and HPV Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of repeatedly screening negative on cervical cancer risk

Thomas Lorey, Brian Befano, Li C. Cheung, Nancy Poitras et al.
JNCI Journal of the National Cancer Institute
Cervical Cancer and HPV Research
article

Impact of repeatedly screening negative on cervical cancer risk

Thomas Lorey, Brian Befano, Li C. Cheung, Nancy Poitras, Nicolas Wentzensen, Marianne Hyer, Philip E. Castle
article en

Abstract

Triennial screening that includes HPV testing becomes inefficient after a single and more so after multiple negative screens. These data support the use of longer screening intervals, especially following negative screen(s).

JNCI Journal of the National Cancer InstituteVol. 118(2)
Kaiser Permanente (US), University of Washington (US), Information Management Services (US), Colorado Permanente Medical Group (US), National Cancer Institute (MY), National Cancer Institute (US), Division of Cancer Epidemiology and Genetics
Openalex Percentile: Top 57%
Cervical Cancer and HPV Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.