Individualized prediction of three- and six-year outcomes of psychosis in a longitudinal multicenter study: a machine learning approach.

Schizophrenia and related disorders have heterogeneous outcomes. Individualized prediction of long-term outcomes may be helpful in improving treatment decisions. Utilizing extensive baseline data of 523 patients with a psychotic disorder and variable illness duration, we predicted symptomatic and global outcomes at 3-year and 6-year follow-ups. We classified outcomes as (1) symptomatic: in remission or not in remission, and (2) global outcome, using the Global Assessment of Functioning (GAF) scale, divided into good (GAF ≥ 65) and poor (GAF < 65). Aiming for a robust and interpretable prediction model, we employed a linear support vector machine and recursive feature elimination within a nested cross-validation design to obtain a lean set of predictors. Generalization to out-of-study samples was estimated using leave-one-site-out cross-validation. Prediction accuracies were above chance and ranged from 62.2% to 64.7% (symptomatic outcome), and 63.5-67.6% (global outcome). Leave-one-site-out cross-validation demonstrated the robustness of our models, with a minor drop in predictive accuracies of 2.3% on average. Important predictors included GAF scores, psychotic symptoms, quality of life, antipsychotics use, psychosocial needs, and depressive symptoms. These robust, albeit modestly accurate, long-term prognostic predictions based on lean predictor sets indicate the potential of machine learning models complementing clinical judgment and decision-making. Future model development may benefit from studies scoping patient's and clinicians' needs in prognostication.

The bumpy road to achieve reliability of clinical profile characteristics in psychosis and related disorders.

OBJECTIVES: Profile characteristics are factors that are relevant for diagnosis, prognosis or treatment. The present study aims to develop a set of clinically relevant profile characteristics. Moreover, our goal is to determine the inter-rater reliability (IRR) of the selected profile characteristics. METHODS: Potential profile characteristics were determined by literature review. Assessment of IRR was done by comparing scores on profile characteristics determined by two researchers. We conducted three subsequent studies: (1) assessment of pre-training IRR, (2) IRR following implementation of an instruction manual, (3) IRR after optimizing scoring methods. IRR was measured with the Intraclass Correlation Coefficient (ICC). RESULTS: IRR scores of profile characteristic Illegal activities were high across the three studies (ICC ≥ 0.75). Following training procedures in study 2 and 3, reliability estimates remained low to moderate (ICC < 0.75) for the profile characteristics Support of relatives, Aggression recent and lifetime, substance use and insight recent. IRR scores of the other eight profile characteristics varied from low, moderate to high across studies. CONCLUSION: IRR scores of profile characteristics were highly variable, and mostly inadequate in all three studies. Consequently, further research should focus on specification of severity scores of profile characteristics, optimizing scoring methods and re-evaluation of IRR.

Association between cognitive phenotype in unaffected siblings and prospective 3- and 6-year clinical outcome in their proband affected by psychosis.

BACKGROUND: Cognitive alterations are a central and heterogeneous trait in psychotic disorders, driven by environmental, familial and illness-related factors. In this study, we aimed to prospectively investigate the impact of high familial risk for cognitive alterations, unconfounded by illness-related factors, on symptomatic outcomes in patients. METHODS: In total, 629 probands with non-affective psychosis and their sibling not affected by psychosis were assessed at baseline, 3- and 6-year follow-up. Familial cognitive risk was modeled by three cognitive subtypes ('normal', 'mixed' and 'impaired') in the unaffected siblings. Generalized linear mixed models assessed multi-cross-sectional associations between the sibling cognitive subtype and repeated measures of proband symptoms across all assessments. Between-group differences over time were assessed by adding an interaction effect of time and sibling cognitive subtype. RESULTS: Probands affected by psychosis with a sibling of the impaired cognitive subtype were less likely to be in symptomatic remission and showed more disorganization across all time points. When assessing differences over time, probands of siblings with the impaired cognitive subtype showed less remission and less improvement of disorganization after 3 and 6 years relative to the other subtypes. They also showed less reduction of positive, negative and excitement symptoms at 6-year follow-up compared to probands with a sibling of the normal cognitive subtype. CONCLUSIONS: Cross-sibling pathways from higher levels of familial cognitive vulnerability to worse long-term outcomes may be informative in identifying cognition-related environmental and genetic risks that impact psychotic illness heterogeneity over time.

Biofabrication of multi-material anatomically shaped tissue constructs.

Additive manufacturing in the field of regenerative medicine aims to fabricate organized tissue-equivalents. However, the control over shape and composition of biofabricated constructs is still a challenge and needs to be improved. The current research aims to improve shape, by converging a number of biocompatible, quality construction materials into a single three-dimensional fiber deposition process. To demonstrate this, several models of complex anatomically shaped constructs were fabricated by combined deposition of poly(vinyl alcohol), poly(ε-caprolactone), gelatin methacrylamide/gellan gum and alginate hydrogel. Sacrificial components were co-deposited as temporary support for overhang geometries and were removed after fabrication by immersion in aqueous solutions. Embedding of chondrocytes in the gelatin methacrylamide/gellan component demonstrated that the fabrication and the sacrificing procedure did not affect cell viability. Further, it was shown that anatomically shaped constructs can be successfully fabricated, yielding advanced porous thermoplastic polymer scaffolds, layered porous hydrogel constructs, as well as reinforced cell-laden hydrogel structures. In conclusion, anatomically shaped tissue constructs of clinically relevant sizes can be generated when employing multiple building and sacrificial materials in a single biofabrication session. The current techniques offer improved control over both internal and external construct architecture underscoring its potential to generate customized implants for human tissue regeneration.