Cargando…
The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study
BACKGROUND: Relapse is a great barrier to improving the effectiveness of methadone maintenance treatment (MMT). Participants with different treatment durations could vary in their compliance with MMT, which may lead to different levels of relapse risk. This study aims to identify the risk factors fo...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886899/ https://www.ncbi.nlm.nih.gov/pubmed/36733286 http://dx.doi.org/10.3389/fpubh.2022.1032217 |
_version_ | 1784880220700934144 |
---|---|
author | Tang, Xijia Fan, Chaonan Wang, Chijie Wang, Wenjuan Chen, Zouxiang Xu, Chaofan Ling, Li |
author_facet | Tang, Xijia Fan, Chaonan Wang, Chijie Wang, Wenjuan Chen, Zouxiang Xu, Chaofan Ling, Li |
author_sort | Tang, Xijia |
collection | PubMed |
description | BACKGROUND: Relapse is a great barrier to improving the effectiveness of methadone maintenance treatment (MMT). Participants with different treatment durations could vary in their compliance with MMT, which may lead to different levels of relapse risk. This study aims to identify the risk factors for relapse and assess the relapse risk of MMT participants of different treatment durations. METHOD: This retrospective study used data collected from seven MMT clinics in Guangdong Province, China, from January 2010 to April 2017. Newly enrolled participants who received 6 (n = 903) and 12 (n = 710) months of consecutive treatment with complete data were included. We selected significant risk factors for relapse through the group lasso regression and then incorporated them into Bayesian networks to reveal relationships between factors and predict the relapse risk. RESULTS: The results showed that participants who received 6-month treatment had a lower relapse rate (32.0%) than those of 12-month treatment (39.0%, P < 0.05). Factors including personal living status and daily methadone dose were only influential to those who received the 6-month treatment. However, age, age at the initial drug use, HIV infection status, sexual behaviors, and continuous treatment days were common factors of both durations. The highest relapse risk for those after the 6-month treatment was inferred as 66.7% while that of the 12-month treatment was 83.3%. Farmers and those who have high accessibility to MMT services may require additional attention. CONCLUSION: It is necessary to implement targeted interventions and education based on the treatment durations of participants to decrease the relapse rate. Meanwhile, those about HIV/sexually transmitted infection prevention and anti-narcotics should be held in the whole process. |
format | Online Article Text |
id | pubmed-9886899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98868992023-02-01 The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study Tang, Xijia Fan, Chaonan Wang, Chijie Wang, Wenjuan Chen, Zouxiang Xu, Chaofan Ling, Li Front Public Health Public Health BACKGROUND: Relapse is a great barrier to improving the effectiveness of methadone maintenance treatment (MMT). Participants with different treatment durations could vary in their compliance with MMT, which may lead to different levels of relapse risk. This study aims to identify the risk factors for relapse and assess the relapse risk of MMT participants of different treatment durations. METHOD: This retrospective study used data collected from seven MMT clinics in Guangdong Province, China, from January 2010 to April 2017. Newly enrolled participants who received 6 (n = 903) and 12 (n = 710) months of consecutive treatment with complete data were included. We selected significant risk factors for relapse through the group lasso regression and then incorporated them into Bayesian networks to reveal relationships between factors and predict the relapse risk. RESULTS: The results showed that participants who received 6-month treatment had a lower relapse rate (32.0%) than those of 12-month treatment (39.0%, P < 0.05). Factors including personal living status and daily methadone dose were only influential to those who received the 6-month treatment. However, age, age at the initial drug use, HIV infection status, sexual behaviors, and continuous treatment days were common factors of both durations. The highest relapse risk for those after the 6-month treatment was inferred as 66.7% while that of the 12-month treatment was 83.3%. Farmers and those who have high accessibility to MMT services may require additional attention. CONCLUSION: It is necessary to implement targeted interventions and education based on the treatment durations of participants to decrease the relapse rate. Meanwhile, those about HIV/sexually transmitted infection prevention and anti-narcotics should be held in the whole process. Frontiers Media S.A. 2023-01-17 /pmc/articles/PMC9886899/ /pubmed/36733286 http://dx.doi.org/10.3389/fpubh.2022.1032217 Text en Copyright © 2023 Tang, Fan, Wang, Wang, Chen, Xu and Ling. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Tang, Xijia Fan, Chaonan Wang, Chijie Wang, Wenjuan Chen, Zouxiang Xu, Chaofan Ling, Li The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study |
title | The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study |
title_full | The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study |
title_fullStr | The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study |
title_full_unstemmed | The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study |
title_short | The risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: A group-LASSO based Bayesian network study |
title_sort | risk assessment of relapse among newly enrolled participants in methadone maintenance treatment: a group-lasso based bayesian network study |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886899/ https://www.ncbi.nlm.nih.gov/pubmed/36733286 http://dx.doi.org/10.3389/fpubh.2022.1032217 |
work_keys_str_mv | AT tangxijia theriskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT fanchaonan theriskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT wangchijie theriskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT wangwenjuan theriskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT chenzouxiang theriskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT xuchaofan theriskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT lingli theriskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT tangxijia riskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT fanchaonan riskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT wangchijie riskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT wangwenjuan riskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT chenzouxiang riskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT xuchaofan riskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy AT lingli riskassessmentofrelapseamongnewlyenrolledparticipantsinmethadonemaintenancetreatmentagrouplassobasedbayesiannetworkstudy |