Effect of Costimulatory Blockade With Abatacept After Ustekinumab Withdrawal in Patients With Moderate to Severe Plaque Psoriasis: The PAUSE Randomized Clinical Trial.

IMPORTANCE: Psoriasis relapse may involve compensatory T-cell activation pathways in the presence of CD28-CD80/CD86 blockade with abatacept. OBJECTIVE: To determine whether costimulatory signaling blockade with abatacept prevents psoriasis relapse after ustekinumab withdrawal. DESIGN, SETTING, AND PARTICIPANTS: Psoriasis Treatment with Abatacept and Ustekinumab: a Study of Efficacy (PAUSE), a parallel-design, double-blind, placebo-controlled randomized clinical trial, was conducted at 10 sites in the US and Canada. Participant enrollment opened on March 19, 2014, and concluded on April 11, 2016. Participants were adults with moderate to severe plaque psoriasis and received ustekinumab in a lead-in phase. Those who responded to ustekinumab at week 12 were randomized 1:1 to either the continued with ustekinumab group (ustekinumab group) or the switched to abatacept group (abatacept group). Treatment was discontinued at week 39, and participants were followed up for psoriasis relapse until week 88. Statistical analyses were performed in the intention-to-treat (ITT) and safety samples from May 3, 2018, to July 6, 2021. INTERVENTIONS: Participants received subcutaneous ustekinumab at weeks 0 and 4 (45 mg per dose for those ≤100 kg; 90 mg per dose for those >100 kg). Participants randomized to the abatacept group at week 12 received subcutaneous abatacept, 125 mg weekly, from weeks 12 to 39 and ustekinumab placebo at weeks 16 and 28. Participants randomized to the ustekinumab group received ustekinumab at weeks 16 and 28 and abatacept placebo weekly from weeks 12 to 39. MAIN OUTCOMES AND MEASURES: The primary end point was the proportion of participants with psoriasis relapse (loss of ≥50% of the initial Psoriasis Area and Severity Index improvement) between weeks 12 and 88. Secondary end points included time to psoriasis relapse, proportion of participants with psoriasis relapse between weeks 12 and 40, and adverse events. The psoriasis transcriptome and serum cytokines were evaluated. RESULTS: A total of 108 participants (mean [SD] age, 46.1 [12.1] years; 73 [67.6%] men) were treated with open-label ustekinumab; 91 were randomized to blinded treatment. Similar proportions of participants in the abatacept group and the ustekinumab group relapsed between weeks 12 and 88 (41 of 45 [91.1%] vs 40 of 46 [87.0%]; P = .41). Median time to relapse from the last dose of ustekinumab was similar between groups as well: 36 weeks (95% CI, 36-48 weeks) in the abatacept group vs 32 weeks (95% CI, 28-40 weeks) in the ustekinumab group. Similar numbers and rates of adverse events occurred. Abatacept did not maintain suppression of the pathogenic IL-23-mediated psoriasis molecular signature in lesions after ustekinumab withdrawal, and serum IL-19 levels increased. CONCLUSIONS AND RELEVANCE: This parallel-design, double-blind randomized clinical trial found that abatacept did not prevent psoriasis relapse that occurred after ustekinumab withdrawal because it did not completely block the pathogenic psoriasis molecular pathways that led to relapse. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01999868.

Pesticides on household surfaces may influence dietary intake of children.

The physical and chemical environment influences children's exposures to pesticides in and around the home. Children's activities, which increase their potential for exposure especially during eating, have been captured in the Children's Dietary Intake Model (CDIM). In addition to the chemical exposure associated with the food itself, this model incorporates excess dietary exposures due to handling of food during consumption. To stochastically evaluate CDIM, distributions of measured, and in some cases estimated, model factors were determined from measurements of permethrin, chlorpyrifos, and diazinon derived from assembled databases and laboratory experiments. Using the distributions of these factors, Monte Carlo simulations were performed to obtain distributions of total dietary intake of pesticides. To target the sources of pesticide contamination that were influencing total dietary intake, each factor was evaluated. We found pesticide surface concentration to be highly influential. By excluding surface concentration, we were also able to determine the influence of the other factors based on the F-statistic. Transfer efficiencies, followed by pesticide residue in consumed foods and amount of food consumed, were the next most influential factors within the model. With these distributions for model inputs, CDIM has the potential to more accurately predict total dietary intake of a contaminant by a child.