Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Polyvictimization and Psychiatric Sequelae Associated with Female Genital Mutilation/Cutting (FGM/C)

Female Genital mutilation/cutting (FGM/C) is associated with enduring psychiatric complications. In this study, we investigate the rates of co-morbid abuses and polyvictimization experienced by survivors of FGM/C. This is a sub-analysis of a cohort study examining the patient population at the EMPOWER Center for Survivors of Sex Trafficking and Sexual Violence in New York City. A retrospective chart-review of electronic medical records was conducted for all consenting adult patients who had FGM/C and had an intake visit between January 16, 2014 and March 6, 2020. Of the 80 participants, ages ranged from 20 to 62 years with a mean of 37.4 (SD?=?9.1) years. In addition to FGM/C, participants were victims of physical abuse (43; 53.8%), emotional abuse (35; 43.8%), sexual abuse (35; 43.8%), forced marriage (20; 25%), child marriage (13; 16.3%), and sex trafficking (1; 1.4%). There was a high degree of polyvictimization, with 41 (51.2%) experiencing 3 or more of the aforementioned abuses. Having FGM/C on or after age 13 or having a higher total abuse score was also found to be strong predictors of depression and PTSD. The high rates of polyvictimization among survivors of FGM/C are associated with development of depression and PTSD. Despite co-morbid abuses, patients still attribute substantial psychiatric symptoms to their FGM/C. Health care providers should understand the high risk of polyvictimization when caring for this patient population.