{Reference Type}: Journal Article
{Title}: Negative symptoms in treatment-resistant schizophrenia and its relationship with functioning.
{Author}: Lui SSY;Lam EHY;Wang LL;Leung PBM;Cheung ESL;Wong CHY;Zhan N;Wong RWK;Siu BWM;Tang DYY;Liu ACY;Chan RCK;
{Journal}: Schizophr Res
{Volume}: 270
{Issue}: 0
{Year}: 2024 Aug 11
{Factor}: 4.662
{DOI}: 10.1016/j.schres.2024.07.008
{Abstract}: <B>BACKGROUND: </B>Recent operational criteria for treatment-resistant schizophrenia (TRS) recognized positive and negative symptoms. TRS patients may have heterogeneity in negative symptoms, but empirical data were lacking. We aimed to characterize TRS patients based on negative symptoms using cluster analysis, and to examine between-cluster differences in social functioning.<BR><B>METHODS: </B>We administered the Clinical Assessment Interview of Negative symptoms (CAINS), Brief Negative Symptom Scale (BNSS), the Positive and Negative Syndrome Scale (PANSS) and the Social and Occupational Functional Assessment (SOFAS to 126 TRS outpatients. All patients also completed the Temporal Experience of Pleasure Scale (TEPS), the Emotion Expressivity Scale (EES), and the Social Functional Scale (SFS). A two-stage hierarchical cluster analysis was performed with the CAINS, TEPS and EES as clustering variables. We validated the clusters using ANOVAs to compare group differences in the BNSS, PANSS, SOFAS and SFS.<BR><B>RESULTS: </B>Clustering indices supported a 3-cluster solution. Clusters 1 (n = 46) and 3 (n = 16) exhibited higher CAINS scores than Cluster 2 (n = 64), and were negative-symptom TRS subtypes. Cluster 1 reported lower TEPS than Cluster 3; but Cluster 3 reported lower EES than Cluster 1. Upon validation, Clusters 1 and 3 exhibited higher BNSS scores than Cluster 2, but only Cluster 1 exhibited lower SOFAS and higher PANSS general symptoms than Cluster 2. Both Clusters 1 and 3 had higher self-report functioning than Cluster 2.<BR><B>CONCLUSIONS: </B>We provided evidence for heterogeneity of negative symptoms in TRS. Negative symptoms can characterize TRS patients and predict functional outcome.