A Nomogram for the Diagnosis of Plaque Psoriasis Using Histopathological Characteristics

Area of Science:

• Dermatopathology
• Medical Diagnostics
• Biostatistics

Background:

• Clinicopathologically ambiguous cases of plaque psoriasis (PP) present diagnostic challenges for dermatopathologists.
• Existing diagnostic methods may lack sufficient accuracy in differentiating PP from other conditions.

Purpose of the Study:

• To develop a predictive nomogram utilizing histopathological features to enhance the diagnostic accuracy of plaque psoriasis.
• To provide a quantitative tool for dermatopathologists to aid in the diagnosis of PP.

Main Methods:

• A derivation cohort of 192 PP samples and 170 control samples were analyzed for histopathological features.
• Least absolute shrinkage and selection operator regression and multivariate logistic regression were employed to select key variables.
• A validation cohort of 170 samples was used to assess the nomogram's discrimination, calibration, and clinical utility.

Main Results:

• Nine histopathological variables were identified and incorporated into the diagnostic nomogram for PP.
• The nomogram achieved high diagnostic accuracy, with an area under the receiver operating characteristic curve of 0.983 in the derivation cohort and 0.971 in the validation cohort.
• Strong agreement was observed between the nomogram's predictions and actual diagnoses, indicating good calibration and clinical utility.

Conclusions:

• A robust diagnostic nomogram based on histopathological features has been developed to assist in diagnosing plaque psoriasis.
• The nomogram demonstrates significant potential for improving diagnostic accuracy in challenging cases.
• Further refinement of the model is recommended for broader clinical application.