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A Nomogram for the Diagnosis of Plaque Psoriasis Using Histopathological Characteristics
1The Department of Dermatology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Background And Objectives:
Diagnostic uncertainty of plaque psoriasis (PP) persists when dermatopathologists encounter clinicopathologically ambiguous cases. We aim to develop a nomogram based on histopathological features to improve the accuracy of the diagnosis of PP.
Method:
A total of 192 samples from 186 patients with PP and 170 samples from 166 control patients were used in the derivation cohort. Their histopathological features were described, and their sensitivity and specificity in diagnosing PP were calculated. Histopathological variables of the study cohort selected by least absolute shrinkage and selection operator regression were compared by multivariate logistic regression analysis. The Akaike information criterion was used to select variables for the nomogram. In total, 170 samples (75 PP and 95 controls) were included in the validation of the diagnostic model. The performance of the nomogram was evaluated regarding its discrimination, calibration, and clinical utility.
Result:
Nine variables were selected for a diagnostic nomogram of PP. The area under the receiver operating characteristic curve of the nomogram was 0.983 [95% confidence interval (CI), 0.971-0.995] in the derivation cohort and 0.971 (95% CI, 0.951-0.992) in the validation cohort, respectively. The calibration plot showed strong agreement between the prediction of the nomogram and the actual diagnosed PP. The decision curve analysis revealed that the nomogram had good clinical utility.
Conclusion:
The sensitivity and specificity of histopathological features were investigated and a well-performing nomogram was developed to aid diagnosing PP. However, broader application awaits further fine tuning of the model.
Insights
A new diagnostic nomogram using histopathological features can improve the accuracy of plaque psoriasis (PP) diagnosis. This tool demonstrated high accuracy in both derivation and validation cohorts, aiding dermatopathologists in challenging cases.
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.
