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An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts

BACKGROUND: Evidence-based smoking cessation guidelines recommend nicotine replacement therapy (NRT), bupropion SR and varenicline as first-line therapy in combination with behavioural interventions. However, there are limited data to guide clinicians in recommending one form over another, using com...

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Detalles Bibliográficos
Autores principales: Bader, P, McDonald, P, Selby, P
Formato: Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2614465/
https://www.ncbi.nlm.nih.gov/pubmed/18845621
http://dx.doi.org/10.1136/tc.2008.025635
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author Bader, P
McDonald, P
Selby, P
author_facet Bader, P
McDonald, P
Selby, P
author_sort Bader, P
collection PubMed
description BACKGROUND: Evidence-based smoking cessation guidelines recommend nicotine replacement therapy (NRT), bupropion SR and varenicline as first-line therapy in combination with behavioural interventions. However, there are limited data to guide clinicians in recommending one form over another, using combinations, or matching individual smokers to particular forms. OBJECTIVE: To develop decision rules for clinicians to guide differential prescribing practices and tailoring of pharmacotherapy for smoking cessation. METHODS: A Delphi approach was used to build consensus among a panel of 37 international experts from various health disciplines. Through an iterative process, panellists responded to three rounds of questionnaires. Participants identified and ranked “best practices” used by them to tailor pharmacotherapy to aid smoking cessation. An independent panel of 10 experts provided cross-validation of findings. RESULTS: There was a 100% response rate to all three rounds. A high level of consensus was achieved in determining the most important priorities: (1) factors to consider in prescribing pharmacotherapy: evidence, patient preference, patient experience; (2) combinations based on: failed attempt with monotherapy, patients with breakthrough cravings, level of tobacco dependence; (3) specific combinations, main categories: (a) two or more forms of NRT, (b) bupropion + form of NRT; (4) specific combinations, subcategories: (1a) patch + gum, (1b) patch + inhaler, (1c) patch + lozenge; (2a) bupropion + patch, (2b) bupropion + gum; (5) impact of comorbidities on selection of pharmacotherapy: contraindications, specific pharmacotherapy useful for certain comorbidities, dual purpose medications; (6) frequency of monitoring determined by patient needs and type of pharmacotherapy. CONCLUSION: An algorithm and guide were developed to assist clinicians in prescribing pharmacotherapy for smoking cessation. There appears to be good justification for “off-label” use such as higher doses of NRT or combination therapy in certain circumstances. This practical tool reflects best evidence to date of experts in tobacco cessation.
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spelling pubmed-26144652009-02-01 An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts Bader, P McDonald, P Selby, P Tob Control Research Papers BACKGROUND: Evidence-based smoking cessation guidelines recommend nicotine replacement therapy (NRT), bupropion SR and varenicline as first-line therapy in combination with behavioural interventions. However, there are limited data to guide clinicians in recommending one form over another, using combinations, or matching individual smokers to particular forms. OBJECTIVE: To develop decision rules for clinicians to guide differential prescribing practices and tailoring of pharmacotherapy for smoking cessation. METHODS: A Delphi approach was used to build consensus among a panel of 37 international experts from various health disciplines. Through an iterative process, panellists responded to three rounds of questionnaires. Participants identified and ranked “best practices” used by them to tailor pharmacotherapy to aid smoking cessation. An independent panel of 10 experts provided cross-validation of findings. RESULTS: There was a 100% response rate to all three rounds. A high level of consensus was achieved in determining the most important priorities: (1) factors to consider in prescribing pharmacotherapy: evidence, patient preference, patient experience; (2) combinations based on: failed attempt with monotherapy, patients with breakthrough cravings, level of tobacco dependence; (3) specific combinations, main categories: (a) two or more forms of NRT, (b) bupropion + form of NRT; (4) specific combinations, subcategories: (1a) patch + gum, (1b) patch + inhaler, (1c) patch + lozenge; (2a) bupropion + patch, (2b) bupropion + gum; (5) impact of comorbidities on selection of pharmacotherapy: contraindications, specific pharmacotherapy useful for certain comorbidities, dual purpose medications; (6) frequency of monitoring determined by patient needs and type of pharmacotherapy. CONCLUSION: An algorithm and guide were developed to assist clinicians in prescribing pharmacotherapy for smoking cessation. There appears to be good justification for “off-label” use such as higher doses of NRT or combination therapy in certain circumstances. This practical tool reflects best evidence to date of experts in tobacco cessation. BMJ Publishing Group 2009-02 2008-10-13 /pmc/articles/PMC2614465/ /pubmed/18845621 http://dx.doi.org/10.1136/tc.2008.025635 Text en © Bader et al 2009 http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Papers
Bader, P
McDonald, P
Selby, P
An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts
title An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts
title_full An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts
title_fullStr An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts
title_full_unstemmed An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts
title_short An algorithm for tailoring pharmacotherapy for smoking cessation: results from a Delphi panel of international experts
title_sort algorithm for tailoring pharmacotherapy for smoking cessation: results from a delphi panel of international experts
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2614465/
https://www.ncbi.nlm.nih.gov/pubmed/18845621
http://dx.doi.org/10.1136/tc.2008.025635
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