Abstract
IntroductionTreatment response at an early stage of schizophrenia is of considerable value with regard to future management of the disorder; however, there are currently no biomarkers that can inform physicians about the likelihood of response.ObjectsWe aim to develop and validate regional brain activity derived from functional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia.MethodsAmplitude of low‐frequency fluctuation (ALFF) was measured at the start of the first/single episode resulting in hospitalization. Inpatients were included in a principal dataset (n = 79) and a replication dataset (n = 44). Two groups of healthy controls (n = 87; n = 106) were also recruited for each dataset. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFFratio, was evaluated based on diagnostic tests and clinical correlates.ResultsIn the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non‐responders. ALFFratio of responders before treatment was significantly higher than that of non‐responders (p < 0.001). The area under the receiver operating characteristic curve was 0.746 for baseline ALFFratio to distinguish responders from non‐responders, and the sensitivity, specificity, and accuracy were 72.7%, 68.6%, and 70.9%, respectively. Similar results were found in the independent replication dataset.ConclusionsBaseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. This study shows that psycho‐neuroimaging holds promise for influencing the clinical treatment and management of schizophrenia.
Highlights
Treatment response at an early stage of schizophrenia is of considera‐ ble value with regard to future management of the disorder; there are cur‐ rently no biomarkers that can inform physicians about the likelihood of response
A subset of participants included in this study have been previously reported; 28 of the 79 patients in the principle data‐ set (Cui et al, 2016; Cui, Liu et al, 2017) and 23 of the 44 patients in the replication dataset (Cui et al, 2018). These articles deal with neural substrates of auditory verbal hallucinations and disease defi‐ nition using functional connectivity, whereas in this manuscript we report on the predictive capacity of brain activity after early treat‐ ment for schizophrenia
In the Receiver oper‐ ating characteristic (ROC) analysis, similar results were observed for calculating the sensitiv‐ ity (82.1%), specificity (62.5%), and accuracy (75.0%) for predic‐ tion, as well as area under ROC curve (0.735 [p = 0.010; 95% CI: 0.570, 0.901]), the correlation did not remain significant between ALFFratio and change in PANSS (r = 0.153, p = 0.320), HAMA (r = −0.019, p = 0.928), or the natural log transformed ill‐ ness duration (r = 0.108, p = 0.483)
Summary
Treatment response at an early stage of schizophrenia is of considera‐ ble value with regard to future management of the disorder; there are cur‐ rently no biomarkers that can inform physicians about the likelihood of response. Objects: We aim to develop and validate regional brain activity derived from func‐ tional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFFratio, was evaluated based on diagnostic tests and clinical correlates. Results: In the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non‐responders. Conclusions: Baseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. Quantifying the relationship between brain changes and different treatment re‐ sponses, and understanding whether these changes can be used as predictive biomarkers for treatment response could help to address this challenge. Functional brain imaging‐based prognostic markers require further investigation before being used clinically for individ‐ ualized psychosis treatment decisions (Keefe & Kahn, 2017)
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