BACKGROUNDGeneralized pustular psoriasis (GPP) is a rare, life-threatening, inflammatory skin disease characterized by widespread eruption of sterile pustules. Interleukin-36 signaling is involved in the pathogenesis of this disorder. Spesolimab, a humanized anti-interleukin-36 receptor monoclonal antibody, is being studied for the treatment of GPP flares. METHODSIn a phase 2 trial, we randomly assigned patients with a GPP flare in a 2:1 ratio to receive a single 900-mg intravenous dose of spesolimab or placebo. Patients in both groups could receive an open-label dose of spesolimab on day 8, an open-label dose of spesolimab as a rescue medication after day 8, or both and were followed to week 12. The primary end point was a Generalized Pustular Psoriasis Physician Global Assessment (GPPGA) pustulation subscore of 0 (range, 0 [no visible pustules] to 4 [severe pustulation]) at the end of week 1. The key secondary end point was a GP-PGA total score of 0 or 1 (clear or almost clear skin) at the end of week 1; scores range from 0 to 4, with higher scores indicating greater disease severity. RESULTSA total of 53 patients were enrolled: 35 were assigned to receive spesolimab and 18 to receive placebo. At baseline, 46% of the patients in the spesolimab group and 39% of those in the placebo group had a GPPGA pustulation subscore of 3, and 37% and 33%, respectively, had a pustulation subscore of 4. At the end of week 1, a total of 19 of 35 patients (54%) in the spesolimab group had a pustulation subscore of 0, as compared with 1 of 18 patients (6%) in the placebo group (difference, 49 percentage points; 95% confidence interval [CI], 21 to 67; P<0.001). A total of 15 of 35 patients (43%) had a GPPGA total score of 0 or 1, as compared with 2 of 18 patients (11%) in the placebo group (difference, 32 percentage points; 95% CI, 2 to 53; P = 0.02). Drug reactions were reported in 2 patients who received spesolimab, in 1 of them concurrently with a drug-induced hepatic injury. Among patients assigned to the spesolimab group, infections occurred in 6 of 35 (17%) through the first week; among patients who received spesolimab at any time in the trial, infections had occurred in 24 of 51 (47%) at week 12. Antidrug antibodies were detected in 23 of 50 patients (46%) who received at least one dose of spesolimab. CONCLUSIONSIn a phase 2 randomized trial involving patients with GPP, the interleukin-36 receptor inhibitor spesolimab resulted in a higher incidence of lesion clearance at 1 week than placebo but was associated with infections and systemic drug reactions. Longer and larger trials are warranted to determine the effect and risks of spesolimab in patients with pustular psoriasis. (Funded by Boehringer Ingelheim; Effisayil 1 ClinicalTrials.gov number, NCT03782792.

Stratified medicine utilizes individual‐level covariates that are associated with a differential treatment effect, also known as treatment‐covariate interactions. When multiple trials are available, meta‐analysis is used to help detect true treatment‐covariate interactions by combining their data. Meta‐regression of trial‐level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta‐analyses are preferable to examine interactions utilizing individual‐level information. However, one‐stage IPD models are often wrongly specified, such that interactions are based on amalgamating within‐ and across‐trial information. We compare, through simulations and an applied example, fixed‐effect and random‐effects models for a one‐stage IPD meta‐analysis of time‐to‐event data where the goal is to estimate a treatment‐covariate interaction. We show that it is crucial to centre patient‐level covariates by their mean value in each trial, in order to separate out within‐trial and across‐trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta‐analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is −0.011 (95% CI: −0.019 to −0.003; p = 0.004), and thus highly significant, when amalgamating within‐trial and across‐trial information. However, when separating within‐trial from across‐trial information, the interaction is −0.007 (95% CI: −0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta‐analysts should only use within‐trial information to examine individual predictors of treatment effect and that one‐stage IPD models should separate within‐trial from across‐trial information to avoid ecological bias. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

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What is this study about? Spesolimab is a drug developed to treat worsening disease (known as flares) of generalized pustular psoriasis (shortened to GPP). GPP is a rare disease in which pus-filled blisters or pustules suddenly form all over the body. Before a drug can be approved to treat the symptoms of a disease, clinical studies are performed to test how well it works and whether there are any side effects. This summary reports the results from a clinical study called Effisayil™ 1 that was performed to understand if spesolimab is effective at treating people with GPP flares. What were the results? The study showed that a single dose of spesolimab rapidly cleared pustules and skin lesions (areas of skin affected by redness, pustules, and scaling) within 1 week of treatment, and continued to improve skin lesions for up to 12 weeks. Spesolimab also reduced pain and improved the quality of life of participants over time. Some participants experienced side effects, which were mostly mild or moderate. What do the results of the study mean? The results indicate that spesolimab is an effective treatment for GPP flares. Although spesolimab is not yet available for doctors to prescribe as medication to their patients, the results of this study are currently under review by the official body that approves drugs for use in the USA.

This article provides an L 1 analysis of the standard nonparametric kernel-based hazard rate estimator under the random right censorship model. The analysis starts with the asymptotic formula for the integrated mean absolute error (IMAE) and then addresses the issue of bandwidth selection. In particular, we show that as a function of bandwidth, the asymptotic minimum of IMAE occurs at the minimising argument of the dominant term of the IMAE's asymptotic expression. Further, it is noted that finding the minimising argument of the dominant term of the asymptotic IMAE is very close to the similar problem in L 1 density estimation except that, as one would expect, the minimising argument now depends on the functionals of the unknown hazard rate. We then use estimates of these unknown functionals in an algorithm to calculate an adaptive version of the optimal bandwidth. We also show that, asymptotically, both theoretical and adaptive forms of the bandwidths do minimise the L 1 distance between the true hazard rate function and its kernel estimator. We also provide a simulation study to illustrate the methodology and compare L 1 errors of hazard rate estimates which use L 1 and L 2 optimal bandwidths.