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Introduction <p>Switching biologics within or across classes can improve outcomes for patients with psoriasis who failed to meet their treatment goals on their original therapy. The objective of this study was to identify real-world baseline features which are associated with switching psoriasis therapies following sustained use of a biologic therapy.</p> Methods <p>The study was a retrospective analysis of the prospective, multicenter, non-interventional PPD™ CorEvitas™ Psoriasis Registry cohort. Patient sociodemographics, comorbidities, treatment history, disease activity, and patient-reported outcome measures were assessed at baseline visits, along with changes in disease activity and treatment at follow-up visits. Patients were classified at each follow-up visit as either switchers from one biologic therapy to another or non-switchers. Three analytic strategies—logistic regression, random forest, and decision trees—were used to identify features associated with switching.</p> Results <p>Patients contributed 14,729 follow-up visits, of which 995 episodes (6.8%) reflected a switch in biologic therapy. In logistic regression models, statistically significant associations with switching were seen for features including body surface area (BSA) involvement at baseline, change in BSA involvement from baseline to follow-up, and addition of at least one non-biologic systemic medication to treatment between baseline and follow-up. In random forest estimations, these three variables along with patient-reported fatigue and quality of life were determined to be most important. Finally, in the decision tree analysis, four subgroups of patients with moderate/severe BSA involvement at baseline in combination with other specific variables were identified as having a &gt; 50% likelihood of switching.</p> Conclusion <p>Identification and recognition of these features and combinations thereof can facilitate shared decision-making between clinicians and patients to improve both outcomes of and patient satisfaction with biologic therapy.</p>

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Features Associated with Therapy Switch Among PPD CorEvitas Psoriasis Registry Patients

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月19日

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  • Andrea M. Austin,
  • Scott C. Henderson,
  • Natasha C. Trujillo,
  • Robert Low,
  • Melissa Eliot,
  • Sandra I. Main,
  • Heather J. Litman,
  • Omeed Nabavian

摘要

Introduction

Switching biologics within or across classes can improve outcomes for patients with psoriasis who failed to meet their treatment goals on their original therapy. The objective of this study was to identify real-world baseline features which are associated with switching psoriasis therapies following sustained use of a biologic therapy.

Methods

The study was a retrospective analysis of the prospective, multicenter, non-interventional PPD™ CorEvitas™ Psoriasis Registry cohort. Patient sociodemographics, comorbidities, treatment history, disease activity, and patient-reported outcome measures were assessed at baseline visits, along with changes in disease activity and treatment at follow-up visits. Patients were classified at each follow-up visit as either switchers from one biologic therapy to another or non-switchers. Three analytic strategies—logistic regression, random forest, and decision trees—were used to identify features associated with switching.

Results

Patients contributed 14,729 follow-up visits, of which 995 episodes (6.8%) reflected a switch in biologic therapy. In logistic regression models, statistically significant associations with switching were seen for features including body surface area (BSA) involvement at baseline, change in BSA involvement from baseline to follow-up, and addition of at least one non-biologic systemic medication to treatment between baseline and follow-up. In random forest estimations, these three variables along with patient-reported fatigue and quality of life were determined to be most important. Finally, in the decision tree analysis, four subgroups of patients with moderate/severe BSA involvement at baseline in combination with other specific variables were identified as having a > 50% likelihood of switching.

Conclusion

Identification and recognition of these features and combinations thereof can facilitate shared decision-making between clinicians and patients to improve both outcomes of and patient satisfaction with biologic therapy.