PeakPASI as a marker of maximum psoriasis severity: a single‐center, cross‐sectional retrospective and questionnaire‐based study

BACKGROUND: The Psoriasis Area and Severity Index (PASI) is the standard measure for psoriasis severity but reflects only a single time point and may underestimate long-term disease burden. To assess whether the highest-ever recorded PASI (PeakPASI) can serve as a marker of historical disease severity and correlate with treatment burden and comorbidities. PATIENTS AND METHODS: A cross-sectional analysis of 308 psoriasis patients from a German university hospital was conducted. Data on PASI, PeakPASI, therapies, and comorbidities were obtained from self-report and medical records. Group comparisons used non-parametric tests; Poisson regression assessed PeakPASI as a predictor of systemic therapy use and comorbidity burden. RESULTS: Median PeakPASI (11.4 [IQR 5.9-17.0]) exceeded current PASI (2.0 [IQR 1.0-5.1]). PeakPASI ≥ 10 was associated with more systemic therapies (p < 0.001), phototherapy (p < 0.001), smoking (p = 0.021), and diabetes (p = 0.020). PeakPASI correlated with number of systemic (ρ = 0.296), topical therapies (ρ = 0.367), and hospital visits (ρ = 0.186). It significantly predicted systemic therapy use (β = 0.355, p < 0.001), but not comorbidity burden. CONCLUSIONS: PeakPASI may complement current measures by reflecting historical severity and informing treatment. While not a cumulative burden marker, it may prevent underestimation of long-term disease impact. Prospective validation is warranted.

Authors

Institutions

Publication Details

Journal
JDDG Journal der Deutschen Dermatologischen Gesellschaft
Published
2026-05-31
DOI
https://doi.org/10.1111/ddg.70201
Primary Topic
Psoriasis: Treatment and Pathogenesis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PeakPASI as a marker of maximum psoriasis severity: a single‐center, cross‐sectional retrospective and questionnaire‐based study

Stefanie Ziehfreund, Hanna Wecker, Enya Müller, Simran Wilkhoo et al.
JDDG Journal der Deutschen Dermatologischen Gesellschaft
Psoriasis: Treatment and Pathogenesis
article

PeakPASI as a marker of maximum psoriasis severity: a single‐center, cross‐sectional retrospective and questionnaire‐based study

Stefanie Ziehfreund, Hanna Wecker, Enya Müller, Simran Wilkhoo, Stefanie Eyerich, Tilo Biedermann, Alexander Zink
article en

Abstract

BACKGROUND: The Psoriasis Area and Severity Index (PASI) is the standard measure for psoriasis severity but reflects only a single time point and may underestimate long-term disease burden. To assess whether the highest-ever recorded PASI (PeakPASI) can serve as a marker of historical disease severity and correlate with treatment burden and comorbidities. PATIENTS AND METHODS: A cross-sectional analysis of 308 psoriasis patients from a German university hospital was conducted. Data on PASI, PeakPASI, therapies, and comorbidities were obtained from self-report and medical records. Group comparisons used non-parametric tests; Poisson regression assessed PeakPASI as a predictor of systemic therapy use and comorbidity burden. RESULTS: Median PeakPASI (11.4 [IQR 5.9-17.0]) exceeded current PASI (2.0 [IQR 1.0-5.1]). PeakPASI ≥ 10 was associated with more systemic therapies (p < 0.001), phototherapy (p < 0.001), smoking (p = 0.021), and diabetes (p = 0.020). PeakPASI correlated with number of systemic (ρ = 0.296), topical therapies (ρ = 0.367), and hospital visits (ρ = 0.186). It significantly predicted systemic therapy use (β = 0.355, p < 0.001), but not comorbidity burden. CONCLUSIONS: PeakPASI may complement current measures by reflecting historical severity and informing treatment. While not a cumulative burden marker, it may prevent underestimation of long-term disease impact. Prospective validation is warranted.

JDDG Journal der Deutschen Dermatologischen Gesellschaft
Helmholtz Zentrum München (DE), Technical University of Munich (DE)
Good health and well-being
Openalex Percentile: Top 8%
Psoriasis: Treatment and Pathogenesis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.