Guven Gunver Mehmet, Senocak Mustafa, Ilhan Reyhan, Aktas Hazal, Kilic Sevgi, Oksuz Ozden, Taha Esmeray Muhammed, Lacin Hamide, Kemal Arikan Mehmet
Department of Biostatistics, Istanbul University School of Medicine, Istanbul, Turkey.
Department of Biostatistics, Istanbul University Cerrahpasa School of Medicine, Istanbul, Turkey.
Psychiatry Clin Psychopharmacol. 2021 Sep 1;31(3):292-302. doi: 10.5152/pcp.2021.21386. eCollection 2021 Sep.
The Hamilton Depression Rating Scale (HDRS-17) and the Hamilton Anxiety Rating Scale (HARS-14) have been acknowledged as gold standards in evaluating the severity of depression and anxiety. The specificity and sensitivity of these scales in predicting somatic complaints of depression and anxiety are issues in both clinical and research areas. The present study proposes a new model to enhance the sensitivity and specificity of HDRS-17 and HARS-14 for predicting symptoms of insomnia, inappetence, and loss of libido in psychiatric patients.
This study included 1507 patients diagnosed withbipolar disorder, depression, panic disorder, obsessive-compulsive disorder, and generalized anxiety disorder. The HDRS-17 and the HARS-14 were utilized as predictive scales for the prediction of patients' sleep, appetite, and libido. The sensitivity and specificity were computed using the receiver operating characteristic (ROC). Logistic regression was performed to enhance the predictive values. The predictive value of the logistic regression model was not satisfactory, and a conversion table was therefore designed for each symptom-diagnosis subgroup. The new joint ROC model was then used to recalculate the sensitivity and specificity of the 2 scales for each symptom-diagnosis subgroup. The outcome is a prediction table, presented for use by clinicians.
It was observed that the new statistical model, the joint ROC, increased the sensitivity and specificity of the HDRS-17 and the HARS-14.
: Based on the results of the evaluations with the HDRS and the HARS, the joint ROC method was developed to better predict the presence of symptoms.
汉密尔顿抑郁量表（HDRS - 17）和汉密尔顿焦虑量表（HARS - 14）已被公认为评估抑郁和焦虑严重程度的金标准。这些量表在预测抑郁和焦虑的躯体症状方面的特异性和敏感性是临床和研究领域都存在的问题。本研究提出一种新模型，以提高HDRS - 17和HARS - 14预测精神病患者失眠、食欲不振和性欲减退症状的敏感性和特异性。
本研究纳入了1507例被诊断为双相情感障碍、抑郁症、惊恐障碍、强迫症和广泛性焦虑症的患者。使用HDRS - 17和HARS - 14作为预测量表来预测患者的睡眠、食欲和性欲。使用受试者工作特征曲线（ROC）计算敏感性和特异性。进行逻辑回归以提高预测值。逻辑回归模型的预测值并不理想，因此为每个症状 - 诊断亚组设计了一个转换表。然后使用新的联合ROC模型重新计算每个症状 - 诊断亚组中这两个量表的敏感性和特异性。结果是一个供临床医生使用的预测表。
观察到新的统计模型，即联合ROC，提高了HDRS - 17和HARS - 14的敏感性和特异性。
基于使用HDRS和HARS进行评估的结果，开发了联合ROC方法以更好地预测症状的存在。
