Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy

Summary Background Patients with psoriasis are often concerned about the risk of serious infection associated with systemic psoriasis treatments. Objectives To develop and externally validate a prediction model for serious infection in patients with psoriasis within 1 year of starting systemic therapies. Methods The risk prediction model was developed using the British Association of Dermatologists Biologic Interventions Register (BADBIR), and the German Psoriasis Registry PsoBest was used as the validation dataset. Model discrimination and calibration were assessed internally and externally using the C‐statistic, the calibration slope and the calibration in the large. Results Overall 175 (1·7%) out of 10 033 participants from BADBIR and 41 (1·7%) out of 2423 participants from PsoBest developed a serious infection within 1 year of therapy initiation. Selected predictors in a multiple logistic regression model included nine baseline covariates, and starting infliximab was the strongest predictor. Evaluation of model performance showed a bootstrap optimism‐corrected C‐statistic of 0·64 [95% confidence interval (CI) 0·60–0·69], calibration in the large of 0·02 (95% CI −0·14 to 0·17) and a calibration slope of 0·88 (95% CI 0·70–1·07), while external validation performance was poor, with C‐statistic 0·52 (95% CI 0·42–0·62), calibration in the large 0·06 (95% CI −0·25 to 0·37) and calibration slope 0·36 (95% CI −0·24 to 0·97). Conclusions We present the first results of the development of a multivariable prediction model. This model may help patients and dermatologists in the U.K. and the Republic of Ireland to identify modifiable risk factors and inform therapy choice in a shared decision‐making process.
What's already known about this topic? Patients and their clinicians are often concerned about the risk of serious infection associated with biological therapies for the treatment of psoriasis.However, there are no current tools available to estimate an individual's risk of serious infection when starting a systemic therapy. What does this study add? This study found that the serious infection risk prediction model had good calibration and moderate discriminationThe model included chronic obstructive pulmonary disease, alcohol intake, number of comorbidities and employment status, in addition to age, sex, Psoriasis Area and Severity Index, choice of starting therapy and body mass index.These are the first results of the multivariable prediction model, which may help patients and dermatologists in the U.K. and the Republic of Ireland to identify modifiable risk factors and inform therapy choice in a shared decision‐making process. https://www.bjdonline.com/article/Development-and-validation-of-a-multivariable-risk-prediction-model-for-serious-infection-in-patients-with-psoriasis-receiving-systemic-therapy/ https://doi.org/10.1111/bjd.17664 available online