Developing prediction models for symptom severity around the time of discharge from a tertiary-care program for treatment-resistant psychosis

Antipsychotics are the only therapeutic class indicated in the symptomatic management of psychotic disorders. However, individuals diagnosed with schizophrenia or schizoaffective disorder may not always benefit from these first-line agents. This refractoriness to conventional treatment can be difficult to address in most clinical settings. Therefore, a referral to a tertiary-care program that is better able to deliver specialized care in excess of the needs of most individuals may be necessary. The average outcome following a period of treatment at these programs tends to be one of improvement. Nonetheless, accurate prognostication of individual-level responses may be useful in identifying those who are unlikely to improve despite receiving specialized care. Thus, the main objective of this study was to predict symptom severity around the time of discharge from the Refractory Psychosis Program in British Columbia, Canada using only clinicodemographic information and prescription drug data available at the time of admission. To this end, a different boosted beta regression model was trained to predict the total score on each of the five factors of the Positive and Negative Syndrome Scale (PANSS) using a data set composed of 320 hospital admissions. Internal validation of these prediction models was then accomplished by nested cross-validation. Insofar as it is possible to make comparisons of model performance across different outcomes, the correlation between predictions and observations tended to be higher for the negative and disorganized factors than the positive, excited, and depressed factors on internal validation. Past scores had the greatest effect on the prediction of future scores across all 5 factors. The results of this study serve as a proof of concept for the prediction of symptom severity using this specific approach

SMAD4 Loss in Colorectal Cancer Patients Correlates with Recurrence, Loss of Immune Infiltrate, and Chemoresistance

SMAD4 has shown promise in identifying patients with colorectal cancer at high risk of recurrence or death. A discovery cohort and independent validation cohort were classified by SMAD4 status. SMAD4 status and immune infiltrate measurements were tested for association with recurrence-free survival (RFS). Patient-derived xenografts from SMAD4-deficient and SMAD4-retained tumors were used to examine chemoresistance. The discovery cohort consisted of 364 patients with stage I-IV colorectal cancer. Median age at diagnosis was 53 years. The cohort consisted of 61% left-sided tumors and 62% stage II/III patients. Median follow-up was 5.4 years (interquartile range, 2.3-8.2). SMAD4 loss, noted in 13% of tumors, was associated with higher tumor and nodal stage, adjuvant therapy use, fewer tumor-infiltrating lymphocytes (TIL), and lower peritumoral lymphocyte aggregate (PLA) scores (all < 0.04). SMAD4 loss was associated with worse RFS ( = 0.02). When stratified by SMAD4 and immune infiltrate status, patients with SMAD4 loss and low TIL or PLA had worse RFS ( = 0.002 and = 0.006, respectively). Among patients receiving 5-fluorouracil (5-FU)-based systemic chemotherapy, those with SMAD4 loss had a median RFS of 3.8 years compared with 13 years for patients with SMAD4 retained. In xenografted mice, the SMAD4-lost tumors displayed resistance to 5-FU. An independent cohort replicated our findings, in particular, the association of SMAD4 loss with decreased immune infiltrate, as well as worse disease-specific survival. Our data show SMAD4 loss correlates with worse clinical outcome, resistance to chemotherapy, and decreased immune infiltrate, supporting its use as a prognostic marker in patients with colorectal cancer