Independent Factors Associated with Short-Term Treatment Response in Schizophrenia: A Nomogram-Based Predictive Model

Area of Science:

• Psychiatry
• Clinical Medicine
• Medical Informatics

Background:

• Schizophrenia treatment response varies significantly among individuals.
• Identifying predictive factors for short-term treatment outcomes is crucial for personalized medicine.

Purpose of the Study:

• To identify independent factors influencing short-term treatment responses in schizophrenia.
• To develop and validate a nomogram prediction model for treatment outcomes.

Main Methods:

• Analysis of clinical data from 446 schizophrenia patients.
• Logistic regression and LASSO for factor identification.
• Nomogram construction and validation using ROC curves and calibration plots.

Main Results:

• Gender, age, smoking, LDL, homocysteine, and folic acid were identified as key predictors.
• The nomogram model demonstrated good predictive performance with an AUC of 0.814 (training) and 0.7863 (validation).
• The model showed clinical utility and good calibration.

Conclusions:

• These factors independently influence psychiatric symptom improvement in schizophrenia.
• The developed nomogram is a practical tool for predicting treatment response.
• The model supports clinical decision-making for schizophrenia management.