Innovations In Clinical Neuroscience

NOV-DEC 2017

A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience

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61 ICNS INNOVATIONS IN CLINICAL NEUROSCIENCE November-December 2017 • Volume 14 • Number 11–12 O R I G I N A L R E S E A R C H range of item content and in-depth coverage of key symptoms domains (e.g., positive, negative, disorganized) relevant to psychotic disorders. In the current study, we took a novel approach to examining the sensitivity of the PANSS to detecting treatment effects. Network analysis was used to examine antipsychotic treatment effects on publicly available archival PANSS data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study 14 in treatment-responsive and treatment- resistant patients with psychotic disorders. Prior CATIE studies demonstrated the efficacy of second-generation antipsychotics for improving symptoms on the PANSS using traditional univariate statistical approaches. A network science approach has several distinct advantages over traditional approaches. First, it allows for the observation of whether treatment-responsive versus treatment- resistant patients differ in terms of how strongly interconnected their networks are at a macroscopic level. Since the macroscopic level characterizes the overall connectedness of the network, the more densely inter-connected networks confer greater overall risk for symptom exacerbation as, in such networks, most of the symptoms fall into a fewer number of clusters and the presence of some symptoms within each cluster increases the risk of occurrence for all other symptoms within that cluster. Alternatively, more inter-connected networks might be adaptive, facilitating rapid treatment response when medications effectively act on some symptoms, thereby improving the entire symptom presentation by spreading to the entire network. Second, network analysis allows for the determination of whether there are a few "clusters" of symptoms (i.e., communities with denser connections inside and fewer connections to the nodes outside the community) that are key players in treatment response, such that the treatment of a few key hub symptoms leads to improvement. Third, network analysis allows for the detection of symptom "centrality," or identification of the symptom that is most core to a patient's pathology (i.e., responsiveness or resistance to antipsychotics). The identification of the key symptom clusters or single central symptom might allow for the application of precision medicine designed to target the core features underlying an individual's illness, rather than a broad approach that targets what is typically effective for a broad diagnostic category. Lastly, calculation of most of the network topological measures is straightforward, which, together with topographic maps (network representations), might enable clinical interpretation and a better understanding of the underlying psychopathology of individuals by clinicians. Given the novelty of the analytic method, we took an exploratory approach to examining the network architecture of treatment- responsive and treatment-resistant patient groups in the CATIE trial. This included examining three aspects of network structure: macroscopic, mesoscopic, and microscopic properties. Macroscopic properties help us to understand the change of collective properties of the network connections as a whole after treatment. More specifically, it is more likely that an increase in density of the network connections after treatment is helpful for the improvement in overall prognosis of patients. Mesoscopic properties provide information about a subset of symptoms in the network (i.e., communities) where the reduction of the number of communities after treatment indicates the less segregated network and more integrated network. The microscopic properties (i.e., degree and closeness centralities) provide insights into the properties of individual symptoms in the network, which could help us identify individual symptoms that receive great impact from treatments (i.e., that experience a change in their centrality values) and could be able to spread the treatment effect via connections with other symptoms to the whole network. The Kolmogorov-Smirnov statistical test was used to examine whether there is a group difference (between treatment- resistant and treatment-responsive) of centrality measures before and after treatment. Identifying central symptoms and examining the change in the centrality patterns of symptoms after treatment could help us better understand the patient's psychopathology representation, which in this case is resistance or responsiveness to the treatment. 15 METHODS Participants. Data were drawn from the baseline and end of Phase I visits of the CATIE study. 14 Details of the CATIE study and primary results have been published previously. 5,21 The purpose of the CATIE study was to conduct a randomized clinical trial comparing the effectiveness of first- and second-generation antipsychotic medications in a large and representative sample of patients with psychotic disorders across a 57-site study. A double-blind design was used for Phase I of CATIE: 1,493 patients were randomized to receive one of five antipsychotics (olanzapine, perphenazine, quetiapine fumarate, risperidone, or ziprasidone hydrochloride) and were evaluated at baseline and again after 18 months or until treatment was discontinued. The sample evaluated for the current study included 1,049 patients who had complete Phase I data for all variables of interest. Of the 1,049 patients, 316 were deemed treatment-resistant and 733 were identified as treatment-responsive based on the efficacy failure outcome criteria of Phase I, which were defined as persisting severe symptoms despite adequate trials of the medications (inadequate therapeutic effect). 21 Study inclusion/exclusion criteria have been published previously. 21 Procedures. The current study was approved by local Institutional Review Boards at each of the 57 sites, and written informed consent was obtained from all participants. Competency to provide consent and decision- making was determined via the MacArthur Competence Assessment Tool for Clinical Research. 22 A full list of measures used in the CATIE study has been published. 21 The primary measure evaluated in the current study was the PANSS, 1 which is a 30-item clinical rating scale that assesses the severity of positive, negative, and general psychiatric symptoms. In this study, the PANSS was administered by experienced, certified clinicians. 29 CATIE PANSS raters were required to undergo a structured certification process that included initial training, initial certification, and then yearly recertification, in order to reduce drift and facilitate continued training. To pass the initial certification, each PANSS rater was required to code a series of recorded PANSS interviews and obtain an at least 0.70 Pearson correlation coefficient (PCC) when compared with the scores of expert raters. Certified raters were then required to maintain ongoing reliability via assessment every four months, during which time all raters were required to code a recorded PANSS interview and achieve a PCC of at least 0.70. 29 Although initial raters did not always assess at all time-points due to staff turnover, all

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