RESUMO
Around a quarter of people who experience a first episode of psychosis (FEP) will develop treatment-resistant schizophrenia (TRS), but there are currently no established clinically useful methods to predict this from baseline. We aimed to explore the predictive potential for clozapine use as a proxy for TRS of routinely collected, objective biomedical predictors at FEP onset, and to externally validate the model in a separate clinical sample of people with FEP. We developed and externally validated a forced-entry logistic regression risk prediction Model fOr cloZApine tReaTment, or MOZART, to predict up to 8-year risk of clozapine use from FEP using routinely recorded information including age, sex, ethnicity, triglycerides, alkaline phosphatase levels, and lymphocyte counts. We also produced a least-absolute shrinkage and selection operator (LASSO) based model, additionally including neutrophil count, smoking status, body mass index, and random glucose levels. The models were developed using data from two UK psychosis early intervention services (EIS) and externally validated in another UK EIS. Model performance was assessed via discrimination and calibration. We developed the models in 785 patients, and validated externally in 1,110 patients. Both models predicted clozapine use well at internal validation (MOZART: C 0.70; 95%CI 0.63,0.76; LASSO: 0.69; 95%CI 0.63,0.77). At external validation, discrimination performance reduced (MOZART: 0.63; 0.58,0.69; LASSO: 0.64; 0.58,0.69) but recovered after re-estimation of the lymphocyte predictor (C: 0.67; 0.62,0.73). Calibration plots showed good agreement between observed and predicted risk in the forced-entry model. We also present a decision-curve analysis and an online data visualisation tool. The use of routinely collected clinical information including blood-based biomarkers taken at FEP onset can help to predict the individual risk of clozapine use, and should be considered equally alongside other potentially useful information such as symptom scores in large-scale efforts to predict psychiatric outcomes.
RESUMO
BACKGROUND: The incidence of head and neck cancer is relatively low in developed countries and highest in South East Asia. Notwithstanding advances in surgery and radiotherapy over the past several decades, the 5-year survival rate for head and neck cancer has stagnated and remains at 50-55%. This is due, in large part, to both regional and distant disease spread, including spinal metastasis. Spinal metastasis from head and neck cancer is rare, has a poor prognosis and can significantly impede end-stage quality of life; normally only palliative care is given.This study aims to conduct a systematic review of the evidence available on management of spinal metastasis from head and neck cancer and to use such evidence to draw up guiding principles in the management of the distant spread. METHODS: Systematic review of the electronic literature was conducted regarding the management of spinal metastasis of head and neck malignancies. RESULTS: Due to the exceptional rarity of head and neck cancers metastasizing to the spine, there is a paucity of good randomized controlled trials into the management of spinal metastasis. This review produced only 12 case studies/reports and 2 small retrospective cohort studies that lacked appropriate controls. CONCLUSION: Management should aim to improve end-stage quality of life and maintain neurological function. This review has found that radiotherapy +/- medical adjuvant is considered the principle treatment of spinal metastasis of head and neck cancers.There is an absence of a definitive treatment protocol for head and neck cancer spinal metastasis. Our failure to find and cite high-quality scientific evidence only serves to stress the need for good quality research in this area.