Ketamine-Assisted Psychotherapy Provides Lasting and Effective Results in the Treatment of Depression, Anxiety, and Post-Traumatic Stress Disorder at 3 and 6 Months: Findings from a Large Retrospective Effectiveness Study.

Importance: Ketamine-assisted psychotherapy (KAP) is an emerging treatment option to alleviate treatment-resistant affective disorders, but its long-term effectiveness remains unclear.

Objective: To examine the treatment effects of KAP on anxiety, depression, and post-traumatic stress disorder (PTSD) at 1, 3, and 6 months post-treatment.

Design Setting And Participants: This retrospective effectiveness study included self-reported outcomes from adults with a history of major depressive disorder, generalized anxiety disorder (GAD), or PTSD who had not responded to prior treatment interventions and received KAP administered across 11 Field Trip Health clinics in North America between March 13, 2020, and June 16, 2022.

Multi-scale entropy assessment of magnetoencephalography signals in schizophrenia.

Schizophrenia is a severe disruption in cognition and emotion, affecting fundamental human functions. In this study, we applied Multi-Scale Entropy analysis to resting-state Magnetoencephalography data from 54 schizophrenia patients and 98 healthy controls. This method quantifies the temporal complexity of the signal across different time scales using the concept of sample entropy.

Validating a model for predicting breast cancer and nonbreast cancer death in women aged 55 years and older.

Background: To support mammography screening decision making, we developed a competing-risk model to estimate 5-year breast cancer risk and 10-year nonbreast cancer death for women aged 55 years and older using Nurses' Health Study data and examined model performance in the Black Women's Health Study (BWHS). Here, we examine model performance in predicting 10-year outcomes in the BWHS, Women's Health Initiative-Extension Study (WHI-ES), and Multiethnic Cohort (MEC) and compare model performance to existing breast cancer prediction models.

Methods: We used competing-risk regression and Royston and Altman methods for validating survival models to calculate our model's calibration and discrimination (C index) in BWHS (n = 17 380), WHI-ES (n = 106 894), and MEC (n = 49 668).

Predicting All-Cause Mortality in Women With and Without Breast Cancer Using the Schonberg Index: A Women's Health Initiative Study.

Background: When treating older women with breast cancer, life expectancy is an important consideration. ASCO recommends calculating 10-year mortality probabilities to inform treatment decisions. One useful tool is the Schonberg index, which predicts risk-based all-cause 10-year mortality.