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- Ge, R, et al.
(författare)
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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
- 2023
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Ingår i: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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| 3. |
- Sommer, IE, et al.
(författare)
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The clinical course of schizophrenia in women and men-a nation-wide cohort study
- 2020
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Ingår i: NPJ schizophrenia. - : Springer Science and Business Media LLC. - 2334-265X. ; 6:1, s. 12-
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Tidskriftsartikel (refereegranskat)abstract
- Gender differences in schizophrenia have been reported in different aspect of the course of disease and may urge special clinical interventions for female patients. Current literature provides insufficient information to design guidelines for treating women with schizophrenia. We aim to quantify the clinical course of schizophrenia in men and women on premorbid hospitalizations and prescription drugs, age at diagnosis, pharmacological treatment, comorbidity, number of re-hospitalizations, and mortality. Our nationwide cohort study included all patients admitted for the first time to hospital during 2000–2014 for schizophrenia or schizo-affective disorder in Finland. Gender differences were compared with logistic regression, by calculating incidence rates, and mortality was assessed with Cox proportional hazard model. We included 7142 women and 9006 men with schizophrenia/schizo-affective disorder and found that both women (71%) and men (70%) had often been hospitalized for another psychiatric disorder in the 5 years before diagnosis. In women, the last psychiatric hospitalization before schizophrenia/schizo-affective diagnosis was often for mood disorders (62%, OR 2.56, 95% CI 2.28–2.87). Men were diagnosed earlier (mean 34.4 [SD12.6] vs. 38.2 [SD 13.8]) with peak incidence around 22, while incidence in women declining only slowly between age 18 and 65. During ten years follow-up, 69.5% of both genders needed at least one re-hospitalization, with slightly more hospitalizations in women. Women were less often prescribed clozapine or long-acting antipsychotics. Mortality was lower in women (HR = 0.54, 95% CI 0.50–0.60), with fewer suicide and cardiovascular deaths, but more cancer deaths. These results suggest a diagnostic delay for women, which might be shortened by screening women aged 20–65 participating in affective disorder programs. As number of hospitalizations is not lower for women, clinicians should take care not to undertreat women with schizophrenia.
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