Literature DB >> 31765712

The cost-effectiveness of human papillomavirus self-collection among cervical cancer screening non-attenders in El Salvador.

Nicole G Campos1, Karla Alfaro2, Mauricio Maza2, Stephen Sy3, Mario Melendez2, Rachel Masch2, Montserrat Soler4, Gabriel Conzuelo-Rodriguez5, Julia C Gage6, Todd A Alonzo7, Philip E Castle8, Juan C Felix9, Miriam Cremer10, Jane J Kim3.   

Abstract

Cervical cancer screening with human papillomavirus (HPV) DNA testing has been incorporated into El Salvador's national guidelines. The feasibility of home-based HPV self-collection among women who do not attend screening at the clinic (i.e., non-attenders) has been demonstrated, but cost-effectiveness has not been evaluated. Using cost and compliance data from El Salvador, we informed a mathematical microsimulation model of HPV infection and cervical carcinogenesis to conduct a cost-effectiveness analysis from the societal perspective. We estimated the reduction in cervical cancer risk, lifetime cost per woman (2017 US$), life expectancy, and incremental cost-effectiveness ratio (ICER, 2017 US$ per year of life saved [YLS]) of a program with home-based self-collection of HPV (facilitated by health promoters) for the 18% of women reluctant to screen at the clinic. The model was calibrated to epidemiologic data from El Salvador. We evaluated health and economic outcomes of the self-collection intervention for women aged 30 to 59 years, alone and in concert with clinic-based HPV provider-collection. Home-based self-collection of HPV was projected to reduce population cervical cancer risk by 14% and cost $1210 per YLS compared to no screening. An integrated program reaching 99% coverage with both provider- and home-based self-collection of HPV reduced cancer risk by 74% (compared to no screening), and cost $1210 per YLS compared to provider-collection alone. Self-collection facilitated by health promoters is a cost-effective strategy for increasing screening uptake in El Salvador.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cancer screening; Cost-effectiveness analysis; Decision analysis; El Salvador; HPV DNA tests; HPV self-collection; Human papillomavirus (HPV); Mathematical model; Uterine cervical neoplasms

Year:  2019        PMID: 31765712     DOI: 10.1016/j.ypmed.2019.105931

Source DB:  PubMed          Journal:  Prev Med        ISSN: 0091-7435            Impact factor:   4.018


  1 in total

1.  Optimization of Cervical Cancer Screening: A Stacking-Integrated Machine Learning Algorithm Based on Demographic, Behavioral, and Clinical Factors.

Authors:  Lin Sun; Lingping Yang; Xiyao Liu; Lan Tang; Qi Zeng; Yuwen Gao; Qian Chen; Zhaohai Liu; Bin Peng
Journal:  Front Oncol       Date:  2022-02-15       Impact factor: 6.244

  1 in total

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