Time trends of variability in disease activity in systemic lupus erythematosus

Objective Disease activity both between and within patients with SLE is highly variable, yet factors driving this variability remain unclear. This study aimed to identify predictors of variability in SLE disease activity over time.Methods We analysed data from 2930 patients with SLE across 13 countr...

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Main Authors: Tsutomu Takeuchi, Yoshiya Tanaka, Rangi Kandane-Rathnayake, Ning Li, Sang-Cheol Bae, Zhanguo Li, Shereen Oon, Vera Golder, Mandana Nikpour, Masayoshi Harigai, Yi-Hsing Chen, Zhuoli Zhang, Eric Morand, Chak Sing Lau, Worawit Louthrenoo, Sunil Kumar, Michael Lucas Tee, Alberta Hoi, Sandra Navarra, Sean O’Neill, Shue-Fen Luo, Jun Kikuchi, Yanjie Hao, Yasuhiro Katsumata, Aisha Lateef, Laniyati Hamijoyo, Sargunan Sockalingam, Nicola Tugnet, Madelynn Chan, Jiacai Cho, Cherica Tee, Leonid Zamora, Fiona Goldblatt, Kristine Ng, Annie Law, Naoaki Ohkubo, Yeong-Jian Jan Wu, B M D B Basnayake, Jiyoon Choi
Format: Article
Language:English
Published: BMJ Publishing Group 2025-02-01
Series:Lupus Science and Medicine
Online Access:https://lupus.bmj.com/content/12/1/e001335.full
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author Tsutomu Takeuchi
Yoshiya Tanaka
Rangi Kandane-Rathnayake
Ning Li
Sang-Cheol Bae
Zhanguo Li
Shereen Oon
Vera Golder
Mandana Nikpour
Masayoshi Harigai
Yi-Hsing Chen
Zhuoli Zhang
Eric Morand
Chak Sing Lau
Worawit Louthrenoo
Sunil Kumar
Michael Lucas Tee
Alberta Hoi
Sandra Navarra
Sean O’Neill
Shue-Fen Luo
Jun Kikuchi
Yanjie Hao
Yasuhiro Katsumata
Aisha Lateef
Laniyati Hamijoyo
Sargunan Sockalingam
Nicola Tugnet
Madelynn Chan
Jiacai Cho
Cherica Tee
Leonid Zamora
Fiona Goldblatt
Kristine Ng
Annie Law
Naoaki Ohkubo
Yeong-Jian Jan Wu
B M D B Basnayake
Jiyoon Choi
author_facet Tsutomu Takeuchi
Yoshiya Tanaka
Rangi Kandane-Rathnayake
Ning Li
Sang-Cheol Bae
Zhanguo Li
Shereen Oon
Vera Golder
Mandana Nikpour
Masayoshi Harigai
Yi-Hsing Chen
Zhuoli Zhang
Eric Morand
Chak Sing Lau
Worawit Louthrenoo
Sunil Kumar
Michael Lucas Tee
Alberta Hoi
Sandra Navarra
Sean O’Neill
Shue-Fen Luo
Jun Kikuchi
Yanjie Hao
Yasuhiro Katsumata
Aisha Lateef
Laniyati Hamijoyo
Sargunan Sockalingam
Nicola Tugnet
Madelynn Chan
Jiacai Cho
Cherica Tee
Leonid Zamora
Fiona Goldblatt
Kristine Ng
Annie Law
Naoaki Ohkubo
Yeong-Jian Jan Wu
B M D B Basnayake
Jiyoon Choi
author_sort Tsutomu Takeuchi
collection DOAJ
description Objective Disease activity both between and within patients with SLE is highly variable, yet factors driving this variability remain unclear. This study aimed to identify predictors of variability in SLE disease activity over time.Methods We analysed data from 2930 patients with SLE across 13 countries, collected over 38 754 clinic visits between 2013 and 2020. Clinic visit records were converted to panel data with 1-year intervals. The time-adjusted mean disease activity, termed AMS, was calculated. The yearly change in AMS, denoted as ΔAMSt, was regressed onto AMSt−1 and other potential predictors using random-effects models. Some variables were split into a person-mean component to assess between-patient differences and a demeaned component to assess within-patient variability.Results Overall, variability in SLE disease activity exhibited stabilisation over time. A significant inverse relationship emerged between a patient’s disease activity in a given year and variability in disease activity in the subsequent year: a 1-point increase in person-mean disease activity was associated with a 0.27-point decrease (95% CI −0.29 to –0.26, p<0.001) in subsequent variability. Additionally, a 1-point increase in within-patient disease activity variability was associated with a 0.56-point decrease (95% CI −0.57 to –0.55, p<0.001) in the subsequent year. Furthermore, each 1-point increase in the annual average time-adjusted mean Physician Global Assessment was associated with a 0.08-point decrease (90% CI −0.13 to –0.03, p=0.002) in disease activity variability for the following year. Prednisolone dose and the duration of activity in specific organ systems exhibited negative and positive associations, respectively, with disease activity variability in the subsequent year. Patients from less affluent countries displayed greater disease activity variability compared with those from wealthier nations.Conclusion Disease activity tends to be less variable among patients with higher or more variable disease activity in the previous year. Within-patient variability in disease activity has a stronger impact on subsequent fluctuations than differences between individual patients.
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spelling doaj-art-70f24325ee9d4445bd2a09e9d7902cf92025-08-20T02:41:17ZengBMJ Publishing GroupLupus Science and Medicine2053-87902025-02-0112110.1136/lupus-2024-001335Time trends of variability in disease activity in systemic lupus erythematosusTsutomu Takeuchi0Yoshiya Tanaka1Rangi Kandane-Rathnayake2Ning Li3Sang-Cheol Bae4Zhanguo Li5Shereen Oon6Vera Golder7Mandana Nikpour8Masayoshi Harigai9Yi-Hsing Chen10Zhuoli Zhang11Eric Morand12Chak Sing Lau13Worawit Louthrenoo14Sunil Kumar15Michael Lucas Tee16Alberta Hoi17Sandra Navarra18Sean O’Neill19Shue-Fen Luo20Jun Kikuchi21Yanjie Hao22Yasuhiro Katsumata23Aisha Lateef24Laniyati Hamijoyo25Sargunan Sockalingam26Nicola Tugnet27Madelynn Chan28Jiacai Cho29Cherica Tee30Leonid Zamora31Fiona Goldblatt32Kristine Ng33Annie Law34Naoaki Ohkubo35Yeong-Jian Jan Wu36B M D B Basnayake37Jiyoon Choi387 Saitama Medical University, Saitama, JapanThe First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan1 Monash University, Melbourne, Victoria, Australia1 Monash University, Melbourne, Victoria, Australia19 Hanyang University Hospital for Rheumatic Diseases, Seongdong-gu, Korea (the Republic of)14 People’s Hospital, Peking University Health Science Center, Beijing, China11 The University of Melbourne at St Vincent’s Hospital, Fitzroy, Victoria, Australia1 Monash University, Melbourne, Victoria, Australia8 The University of Sydney, Sydney, New South Wales, Australia17 Tokyo Women`s Medical University, Shinjuku, Japan26 Taichung Veterans General Hospital, Taichung, Taiwan12 Peking University First Hospital, Beijing, China1 Monash University, Melbourne, Victoria, Australia9 University of Hong Kong Faculty of Medicine, Hong Kong4 Chiang Mai University, Chiang Mai, Thailand29 Middlemore Hospital, Auckland, New Zealand30 University of the Philippines, Manila, Philippines1 Monash University, Melbourne, Victoria, Australia15 Rheumatology, University of Santo Tomas, Manila, Philippines8 The University of Sydney, Sydney, New South Wales, Australia3 Chang Gung Memorial Hospital, Tao-Yuan, Taiwan21 Keio University, Minato, Japan11 The University of Melbourne at St Vincent’s Hospital, Fitzroy, Victoria, Australia17 Tokyo Women`s Medical University, Shinjuku, Japan7 Woodlands Health, Singapore10 University of Padjadjaran Faculty of Medicine, Bandung, Indonesia5 University of Malaya, Kuala Lumpur, Malaysia24 Auckland District Health Board, Auckland, New Zealand13 Tan Tock Seng Hospital, Singapore6 National University Hospital, Singapore30 University of the Philippines, Manila, Philippines16 University of Santo Tomas, Manila, Philippines18 Flinders Medical Centre, Bedford Park, South Australia, Australia23 North Shore Hospital, Health New Zealand Waitemata, Auckland, New Zealand28 Singapore General Hospital, Singapore25 University of Occupational and Environmental Health Japan, Kitakyushu, Japan3 Chang Gung Memorial Hospital, Tao-Yuan, Taiwan27 Teaching Hospital Kandy, Kandy, Sri Lanka31 Bristol Myers Squibb, New Brunswick, New Jersey, USAObjective Disease activity both between and within patients with SLE is highly variable, yet factors driving this variability remain unclear. This study aimed to identify predictors of variability in SLE disease activity over time.Methods We analysed data from 2930 patients with SLE across 13 countries, collected over 38 754 clinic visits between 2013 and 2020. Clinic visit records were converted to panel data with 1-year intervals. The time-adjusted mean disease activity, termed AMS, was calculated. The yearly change in AMS, denoted as ΔAMSt, was regressed onto AMSt−1 and other potential predictors using random-effects models. Some variables were split into a person-mean component to assess between-patient differences and a demeaned component to assess within-patient variability.Results Overall, variability in SLE disease activity exhibited stabilisation over time. A significant inverse relationship emerged between a patient’s disease activity in a given year and variability in disease activity in the subsequent year: a 1-point increase in person-mean disease activity was associated with a 0.27-point decrease (95% CI −0.29 to –0.26, p<0.001) in subsequent variability. Additionally, a 1-point increase in within-patient disease activity variability was associated with a 0.56-point decrease (95% CI −0.57 to –0.55, p<0.001) in the subsequent year. Furthermore, each 1-point increase in the annual average time-adjusted mean Physician Global Assessment was associated with a 0.08-point decrease (90% CI −0.13 to –0.03, p=0.002) in disease activity variability for the following year. Prednisolone dose and the duration of activity in specific organ systems exhibited negative and positive associations, respectively, with disease activity variability in the subsequent year. Patients from less affluent countries displayed greater disease activity variability compared with those from wealthier nations.Conclusion Disease activity tends to be less variable among patients with higher or more variable disease activity in the previous year. Within-patient variability in disease activity has a stronger impact on subsequent fluctuations than differences between individual patients.https://lupus.bmj.com/content/12/1/e001335.full
spellingShingle Tsutomu Takeuchi
Yoshiya Tanaka
Rangi Kandane-Rathnayake
Ning Li
Sang-Cheol Bae
Zhanguo Li
Shereen Oon
Vera Golder
Mandana Nikpour
Masayoshi Harigai
Yi-Hsing Chen
Zhuoli Zhang
Eric Morand
Chak Sing Lau
Worawit Louthrenoo
Sunil Kumar
Michael Lucas Tee
Alberta Hoi
Sandra Navarra
Sean O’Neill
Shue-Fen Luo
Jun Kikuchi
Yanjie Hao
Yasuhiro Katsumata
Aisha Lateef
Laniyati Hamijoyo
Sargunan Sockalingam
Nicola Tugnet
Madelynn Chan
Jiacai Cho
Cherica Tee
Leonid Zamora
Fiona Goldblatt
Kristine Ng
Annie Law
Naoaki Ohkubo
Yeong-Jian Jan Wu
B M D B Basnayake
Jiyoon Choi
Time trends of variability in disease activity in systemic lupus erythematosus
Lupus Science and Medicine
title Time trends of variability in disease activity in systemic lupus erythematosus
title_full Time trends of variability in disease activity in systemic lupus erythematosus
title_fullStr Time trends of variability in disease activity in systemic lupus erythematosus
title_full_unstemmed Time trends of variability in disease activity in systemic lupus erythematosus
title_short Time trends of variability in disease activity in systemic lupus erythematosus
title_sort time trends of variability in disease activity in systemic lupus erythematosus
url https://lupus.bmj.com/content/12/1/e001335.full
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