RESUMEN
BACKGROUND: Although clozapine is the most effective drug for treatment-resistant schizophrenia, its use remains restricted in clinical practice in India. The delay in initiating treatment with clozapine and its impact on disease outcome needs evaluation. AIM: To identify the implications of delaying clozapine initiation in clinical outcomes among people with treatment-resistant schizophrenia. METHODS: Subjects with treatment-resistant schizophrenia, stabilised on clozapine monotherapy, were recruited from the outpatient clinic of a general hospital psychiatry unit offering tertiary care services in Thrissur district, Kerala, India. A retrospective cohort design was employed, and information on duration of illness, total duration of treatment and duration of treatment with clozapine was collected. Present symptom status was measured using the Positive and Negative Syndrome Scale. Factors associated with higher symptom scores were analysed using an independent sample t test, Spearman correlation and multiple linear regression. RESULTS: Forty subjects stabilised on long-term clozapine therapy formed the study sample. The mean dose of clozapine used in the study population was 200 mg. The mean duration of antipsychotic treatment before starting clozapine was 89.3 months (7.4 years). The duration of treatment before starting clozapine was found to have a significant positive association with the total Positive and Negative Syndrome Scale score (correlation coefficient 0.40; p=0.01) and negative symptom score (correlation coefficient 0.33; p=0.04). The multiple regression analysis adjusting for covariates showed that the duration of treatment before starting clozapine was an independent factor associated with a higher negative symptom score in the Positive and Negative Syndrome Scale (slope ß=0.05; p=0.02; R2=0.27). CONCLUSION: Poor treatment outcomes in treatment-resistant schizophrenia could be secondary to a delay in initiating clozapine therapy.
RESUMEN
Negative control exposure analysis is a very effective tool in evaluating the effect of unmeasured confounding in observational epidemiological studies. Several biases, including recall bias, time-varying confounding factors, measurement bias and so on, can affect the credibility of negative control exposure analysis for causal interpretations. The article focuses on the implications of differential measurement error across exposed group and negative controls to causal interpretations on negative control exposure analysis.