Development and validation of a prognostic model for predicting the risk of allopurinol-induced severe cutaneous adverse reactions: a retrospective new-user cohort study using linked primary care, hospitalisation, and mortality data.
Edoardo Cipolletta, Georgina Nakafero, Davide Rozza, Satveer K Mahil, Catherine H Smith, Richard D Riley, Abhishek Abhishek
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引用次数: 0
Abstract
Background: Allopurinol, the most prescribed urate-lowering drug, is a known cause of severe cutaneous adverse reactions. We aimed to develop and validate a model to assess the risk of allopurinol-induced severe cutaneous adverse reactions in adults newly prescribed allopurinol.
Methods: In this retrospective new-user cohort study, we developed and validated a prognostic model using primary care, hospitalisation, and mortality data extracted from the UK Clinical Practice Research Datalink (CPRD) primary care database, for the period Jan 1, 2001, to March 29, 2021. Data from CPRD Aurum was used for model development and data from and CPRD GOLD was used for model validation. Adults (aged ≥18 years) residing in England who were newly prescribed allopurinol were followed up for 100 days to assess whether a severe cutaneous adverse reaction was recorded in hospitalisation or mortality records. Risk predictors included in the model were age, sex, ethnicity, chronic kidney disease stage, initial allopurinol dose, ischaemic heart disease, and heart failure. The primary outcome was to predict the 100-day risk of allopurinol-induced severe cutaneous adverse reactions in people newly prescribed allopurinol. We developed the model using multivariable Cox regression and pseudo-values, followed by penalisation and external validation. We assessed calibration, discrimination, and clinical utility in the risk range of 0·0001 to 0·003. People with lived experience of allopurinol use or gout were not involved in developing this research question, but will be involved in the dissemination of results.
Findings: 225 761 patients newly prescribed allopurinol were registered in the CPRD Aurum database (development cohort) and 173 812 were included in the study. 44 630 (25·7%) of 173 812 patients were female, 129 182 (74·3%) were male, 154 323 (88·8%) were White, and the mean age was 63·9 years (SD 15·0). Of the patients newly prescribed allopurinol with data in the CPRD GOLD database (validation cohort), 55 395 patients were screened and 41 610 were included in the study. 10 829 (26·0%) of 41 610 patients were female, 30 781 (74·0%) were male, 37 242 (89·5%) were White and the mean age was 64·4 years (SD 14·9). 63 (0·04%) severe cutaneous adverse events occurred in 173 812 patients in the development cohort and 16 (0·04%) occurred in 41 610 patients in the validation cohort. Age (adjusted hazard ratio 1·03 [95% CI 1·01-1·06]), chronic kidney disease stages 3, 4, and 5 (2·24 [1·20-4·17] for stage 3; 6·65 [2·90-15·23] for stage 4; 18·85 [6·32-56·19] for stage 5), initial allopurinol dose of 300 mg or higher (5·99 [3·56-0·08]), South Asian ethnicity (5·35 [2·37-12·07]), and other Asian ethnicity (5·63 [1·34-23·61]) were associated with the 100-day risk of allopurinol-induced severe cutaneous adverse reactions. In the development dataset, after optimism-adjustment, the model's explained variation (Royston and Sauerbrei's R2D) was 0·50 and Harrell's C was 0·82. In the validation dataset, the calibration slope was 0·93 (95% CI 0·18-1·68), the R2D was 0·44 (95% CI 0·20-0·62), and Harrell's C was 0·79 (95% CI 0·71-0·88). The model had clinical utility across the prespecified risk range.
Interpretation: We developed and validated a prognostic model for the 100-day risk of an allopurinol-induced severe cutaneous adverse reaction with good predictive performance and clinical utility. This model could be used to inform the choice of urate-lowering drugs.
期刊介绍:
The Lancet Rheumatology, an independent journal, is dedicated to publishing content relevant to rheumatology specialists worldwide. It focuses on studies that advance clinical practice, challenge existing norms, and advocate for changes in health policy. The journal covers clinical research, particularly clinical trials, expert reviews, and thought-provoking commentary on the diagnosis, classification, management, and prevention of rheumatic diseases, including arthritis, musculoskeletal disorders, connective tissue diseases, and immune system disorders. Additionally, it publishes high-quality translational studies supported by robust clinical data, prioritizing those that identify potential new therapeutic targets, advance precision medicine efforts, or directly contribute to future clinical trials.
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