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1.
J Clin Oncol ; 42(13): 1509-1519, 2024 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-38335465

RESUMO

PURPOSE: To compare the cumulative incidence of mental disorders among adolescents and young adults (AYAs) diagnosed with cancer with the general population and their unaffected siblings. METHODS: A retrospective, population-based, matched cohort design was used to investigate the impact of cancer diagnosis on mental disorders among individuals age 15-39 diagnosed between 1989 and 2019. Two cancer-free cohorts were identified: matched population-based and sibling cohorts. Outcomes included incidence of mood and anxiety disorders, substance use disorders, suicide outcomes, psychotic disorders, and any of the preceding four categories within 5 years of cancer diagnosis. Competing risk regression was used to estimate adjusted subhazard ratios (aSHR) and 95% CIs. RESULTS: Among 3,818 AYAs with cancer matched to the population-based cancer-free cohort, individuals with cancer were more likely to be diagnosed with incident mental disorders than those without cancer; the risk was highest immediately after a cancer diagnosis and decreased over time with aSHR [95% CI] for mood and anxiety disorders at 0-6 months (11.27 [95% CI, 6.69 to 18.97]), 6-12 months (2.35 [95% CI, 1.54 to 3.58]), and 12-24 months (2.06 [95% CI, 1.55 to 2.75]); for substance use disorders at 0-6 months (2.73 [95% CI, 1.90 to 3.92]); for psychotic disorders at 0-6 months (4.69 [95% CI, 2.07 to 10.65]); and for any mental disorder at 0-6 months (4.46 [95% CI, 3.41 to 5.85]), 6-12 months (1.56 [95% CI, 1.14 to 2.14]), and 12-24 months (1.7 [95% CI, 1.36 to 2.13]) postcancer diagnosis. In sibling comparison, cancer diagnosis was associated with a higher incidence of mood and anxiety and any mental disorder during first 6 months of cancer diagnosis. CONCLUSION: AYAs with cancer experience a greater incidence of mental disorders after cancer diagnosis relative to population-based and sibling cohorts without cancer, primarily within first 2 years, underscoring the need to address mental health concerns during this period.


Assuntos
Transtornos Mentais , Neoplasias , Irmãos , Humanos , Neoplasias/psicologia , Neoplasias/epidemiologia , Adolescente , Masculino , Feminino , Adulto Jovem , Irmãos/psicologia , Adulto , Transtornos Mentais/epidemiologia , Estudos Retrospectivos , Canadá/epidemiologia , Incidência , Estudos de Coortes
2.
Neuroimage ; 258: 119364, 2022 09.
Artigo em Inglês | MEDLINE | ID: mdl-35690257

RESUMO

Even when subjects are at rest, it is thought that brain activity is organized into distinct brain states during which reproducible patterns are observable. Yet, it is unclear how to define or distinguish different brain states. A potential source of brain state variation is arousal, which may play a role in modulating functional interactions between brain regions. Here, we use simultaneous resting state functional magnetic resonance imaging (fMRI) and pupillometry to study the impact of arousal levels indexed by pupil area on the integration of large-scale brain networks. We employ a novel sparse dictionary learning-based method to identify hub regions participating in between-network integration stratified by arousal, by measuring k-hubness, the number (k) of functionally overlapping networks in each brain region. We show evidence of a brain-wide decrease in between-network integration and inter-subject variability at low relative to high arousal, with differences emerging across regions of the frontoparietal, default mode, motor, limbic, and cerebellum networks. State-dependent changes in k-hubness relate to the actual patterns of network integration within these hubs, suggesting a brain state transition from high to low arousal characterized by global synchronization and reduced network overlaps. We demonstrate that arousal is not limited to specific brain areas known to be directly associated with arousal regulation, but instead has a brain-wide impact that involves high-level between-network communications. Lastly, we show a systematic change in pairwise fMRI signal correlation structures in the arousal state-stratified data, and demonstrate that the choice of global signal regression could result in different conclusions in conventional graph theoretical analysis and in the analysis of k-hubness when studying arousal modulations. Together, our results suggest the presence of global and local effects of pupil-linked arousal modulations on resting state brain functional connectivity.


Assuntos
Encéfalo , Imageamento por Ressonância Magnética , Nível de Alerta/fisiologia , Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Mapeamento Encefálico/métodos , Humanos , Imageamento por Ressonância Magnética/métodos , Rede Nervosa/diagnóstico por imagem , Rede Nervosa/fisiologia , Pupila/fisiologia
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