Professor ABHISHEK ABHISHEK ABHISHEK.ABHISHEK@NOTTINGHAM.AC.UK
CLINICAL PROFESSOR
Professor ABHISHEK ABHISHEK ABHISHEK.ABHISHEK@NOTTINGHAM.AC.UK
CLINICAL PROFESSOR
Dr MATTHEW GRAINGE MATTHEW.GRAINGE@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Dr TIM CARD tim.card@nottingham.ac.uk
CLINICAL ASSOCIATE PROFESSOR
Professor HYWEL WILLIAMS HYWEL.WILLIAMS@NOTTINGHAM.AC.UK
PROFESSOR OF DERMATO-EPIDEMIOLOGY
Professor MAARTEN TAAL M.TAAL@NOTTINGHAM.AC.UK
PROFESSOR OF MEDICINE
Professor GURUPRASAD AITHAL Guru.Aithal@nottingham.ac.uk
PROFESSOR OF HEPATOLOGY
Professor CHRIS FOX Christopher.Fox@nottingham.ac.uk
CLINICAL PROFESSOR IN HAEMATOLOGY
Christian D Mallen
Matthew D Stevenson
Dr GEORGINA NAKAFERO Georgina.Nakafero@nottingham.ac.uk
SENIOR RESEARCH FELLOW
Richard Riley
Background Sulfasalazine-induced cytopenia, nephrotoxicity and hepatotoxicity is uncommon during long-term treatment. Some guidelines recommend 3 monthly monitoring blood tests indefinitely during long-term treatment while others recommend stopping monitoring after 1 year. To rationalise monitoring, we developed and validated a prognostic model for clinically significant blood, liver or kidney toxicity during established sulfasalazine treatment. Design Retrospective cohort study. Setting UK primary care. Data from Clinical Practice Research Datalink Gold and Aurum formed independent development and validation cohorts. Participants Age ≥18 years, new diagnosis of an inflammatory condition and sulfasalazine prescription. Study period 1 January 2007 to 31 December 2019. Outcome Sulfasalazine discontinuation with abnormal monitoring blood-test result. Analysis Patients were followed up from 6 months after first primary care prescription to the earliest of outcome, drug discontinuation, death, 5 years or 31 December 2019. Penalised Cox regression was performed to develop the risk equation. Multiple imputation handled missing predictor data. Model performance was assessed in terms of calibration and discrimination. Results 8936 participants were included in the development cohort (473 events, 23 299 person-years) and 5203 participants were included in the validation cohort (280 events, 12 867 person-years). Nine candidate predictors were included. The optimism adjusted R2D and Royston D statistic in the development data were 0.13 and 0.79, respectively. The calibration slope (95% CI) and Royston D statistic (95% CI) in validation cohort was 1.19 (0.96 to 1.43) and 0.87 (0.67 to 1.07), respectively. Conclusion This prognostic model for sulfasalazine toxicity uses readily available data and should be used to risk-stratify blood-test monitoring during established sulfasalazine treatment.
Abhishek, A., Grainge, M., Card, T., Williams, H. C., Taal, M. W., Aithal, G. P., Fox, C. P., Mallen, C. D., Stevenson, M. D., Nakafero, G., & Riley, R. (2024). Risk-stratified monitoring for sulfasalazine toxicity: prognostic model development and validation. RMD Open, 10(1), Article e003980. https://doi.org/10.1136/rmdopen-2023-003980
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 30, 2024 |
Online Publication Date | Mar 7, 2024 |
Publication Date | 2024-01 |
Deposit Date | Feb 16, 2024 |
Publicly Available Date | Feb 16, 2024 |
Journal | RMD Open |
Electronic ISSN | 2056-5933 |
Publisher | BMJ Publishing Group |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Issue | 1 |
Article Number | e003980 |
DOI | https://doi.org/10.1136/rmdopen-2023-003980 |
Keywords | Immunology; Immunology and Allergy; Rheumatology |
Public URL | https://nottingham-repository.worktribe.com/output/31450846 |
Publisher URL | https://rmdopen.bmj.com/content/10/1/e003980 |
Risk-stratified monitoring for sulfasalazine toxicity
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Risk-stratified monitoring for sulfasalazine toxicity: prognostic model development and validation
(2023)
Preprint / Working Paper
Richter's transformation: Transforming the clinical landscape
(2023)
Journal Article
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