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Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden

BACKGROUND: For patients with schizophrenia, relapse is a recurring feature of disease progression, often resulting in substantial negative impacts for the individual. Although a patient’s relapse history (specifically the number of prior relapses) has been identified as a strong risk factor for fut...

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Autores principales: Jørgensen, Kristian Tore, Bøg, Martin, Kabra, Madhu, Simonsen, Jacob, Adair, Michael, Jönsson, Linus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8690369/
https://www.ncbi.nlm.nih.gov/pubmed/34933680
http://dx.doi.org/10.1186/s12888-021-03634-z
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author Jørgensen, Kristian Tore
Bøg, Martin
Kabra, Madhu
Simonsen, Jacob
Adair, Michael
Jönsson, Linus
author_facet Jørgensen, Kristian Tore
Bøg, Martin
Kabra, Madhu
Simonsen, Jacob
Adair, Michael
Jönsson, Linus
author_sort Jørgensen, Kristian Tore
collection PubMed
description BACKGROUND: For patients with schizophrenia, relapse is a recurring feature of disease progression, often resulting in substantial negative impacts for the individual. Although a patient’s relapse history (specifically the number of prior relapses) has been identified as a strong risk factor for future relapse, this relationship has not yet been meticulously quantified. The objective of this study was to use real-world data from Sweden to quantify the relationship of time to relapse in schizophrenia with a patient’s history of prior relapses. METHODS: Data from the Swedish National Patient Register and Swedish Prescribed Drug Register were used to study relapse in patients with schizophrenia with a first diagnosis recorded from 2006–2015, using proxy definitions of relapse. The primary proxy defined relapse as a psychiatric hospitalisation of ≥7 days’ duration. Hazard ratios (HRs) were calculated for risk of each subsequent relapse, and Aalen-Johansen estimators were used to estimate time to next relapse. RESULTS: 2,994 patients were included, and 5,820 relapse episodes were identified using the primary proxy. As the number of previous relapses increased, there was a general trend of decreasing estimated time between relapses. Within 1.52 years of follow-up, 50% of patients with no history of relapse were estimated to have suffered their first relapse episode. 50% of patients with one prior relapse were estimated to have a second relapse within 1.23 years (HR: 1.84 [1.71–1.99]) and time to next relapse further decreased to 0.89 years (HR: 2.77 [2.53–3.03]) and 0.22 years (HR: 18.65 [15.42–22.56]) for 50% of patients with two or ten prior relapses, respectively. Supplementary analyses using different inclusion/exclusion criteria for the study population and redefined proxies of relapse reflected the pattern observed with the primary analyses of a higher number of prior relapses linked with increased risk of/reduced estimated time to the next relapse. CONCLUSIONS: The results suggested a trend of accelerating disease progression in schizophrenia, each relapse episode predisposing an individual to the next within a shorter time period. These results emphasise the importance of providing early, effective, and tolerable treatments that better meet a patient’s individual needs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-021-03634-z.
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spelling pubmed-86903692021-12-21 Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden Jørgensen, Kristian Tore Bøg, Martin Kabra, Madhu Simonsen, Jacob Adair, Michael Jönsson, Linus BMC Psychiatry Research BACKGROUND: For patients with schizophrenia, relapse is a recurring feature of disease progression, often resulting in substantial negative impacts for the individual. Although a patient’s relapse history (specifically the number of prior relapses) has been identified as a strong risk factor for future relapse, this relationship has not yet been meticulously quantified. The objective of this study was to use real-world data from Sweden to quantify the relationship of time to relapse in schizophrenia with a patient’s history of prior relapses. METHODS: Data from the Swedish National Patient Register and Swedish Prescribed Drug Register were used to study relapse in patients with schizophrenia with a first diagnosis recorded from 2006–2015, using proxy definitions of relapse. The primary proxy defined relapse as a psychiatric hospitalisation of ≥7 days’ duration. Hazard ratios (HRs) were calculated for risk of each subsequent relapse, and Aalen-Johansen estimators were used to estimate time to next relapse. RESULTS: 2,994 patients were included, and 5,820 relapse episodes were identified using the primary proxy. As the number of previous relapses increased, there was a general trend of decreasing estimated time between relapses. Within 1.52 years of follow-up, 50% of patients with no history of relapse were estimated to have suffered their first relapse episode. 50% of patients with one prior relapse were estimated to have a second relapse within 1.23 years (HR: 1.84 [1.71–1.99]) and time to next relapse further decreased to 0.89 years (HR: 2.77 [2.53–3.03]) and 0.22 years (HR: 18.65 [15.42–22.56]) for 50% of patients with two or ten prior relapses, respectively. Supplementary analyses using different inclusion/exclusion criteria for the study population and redefined proxies of relapse reflected the pattern observed with the primary analyses of a higher number of prior relapses linked with increased risk of/reduced estimated time to the next relapse. CONCLUSIONS: The results suggested a trend of accelerating disease progression in schizophrenia, each relapse episode predisposing an individual to the next within a shorter time period. These results emphasise the importance of providing early, effective, and tolerable treatments that better meet a patient’s individual needs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-021-03634-z. BioMed Central 2021-12-21 /pmc/articles/PMC8690369/ /pubmed/34933680 http://dx.doi.org/10.1186/s12888-021-03634-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jørgensen, Kristian Tore
Bøg, Martin
Kabra, Madhu
Simonsen, Jacob
Adair, Michael
Jönsson, Linus
Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden
title Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden
title_full Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden
title_fullStr Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden
title_full_unstemmed Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden
title_short Predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in Sweden
title_sort predicting time to relapse in patients with schizophrenia according to patients’ relapse history: a historical cohort study using real-world data in sweden
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8690369/
https://www.ncbi.nlm.nih.gov/pubmed/34933680
http://dx.doi.org/10.1186/s12888-021-03634-z
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