Earlier Onset Increases Risk of Treatment-Resistant Schizophrenia

Younger age at the time of first antipsychotic and more inpatient days in the 3 months before and after the first antipsychotic are among several predictors of treatment-resistant schizophrenia, suggest findings from a new study published in PLOS One.

“Younger age at onset is the most consistent risk factor identified to date for treatment-resistant schizophrenia, and this study provides further evidence in support of this,” wrote corresponding author Giouliana Kadra-Scalzo, PhD, of the King’s College London Institute of Psychiatry, Psychology, and Neuroscience, and coauthors.

The study included clinical record data for 1515 patients with a schizophrenia spectrum disorder, 17% of whom developed treatment-resistant schizophrenia.

In addition to younger age at first antipsychotic and more inpatient days in the 3 months before and after the first antipsychotic, predictors of treatment-resistant schizophrenia included more community face-to-face clinical contact in the 3 months before the first antipsychotic and having minor cognitive problems requiring no action — as opposed to having no problems or severe problems.

The study also found the hazard of developing treatment-resistant schizophrenia was constant over a period of 10 years, suggesting the probability of developing treatment resistance does not stabilize over the treatment course.

The Cox Least Absolute Shrinkage and Selection Operator survival model produced an internally validated Harrel’s C index of 0.60, researchers reported.

“In conclusion, routinely collected information, readily available at the start of treatment, gives some indication of treatment-resistant schizophrenia but is unlikely to be adequate alone. Future studies that develop clinical risk prediction tools can combine these predictors with other identified predictors, which will increase the likelihood of success,” researchers wrote. “In addition, further work investigating the biological underpinnings would be extremely useful.”

Reference:
Kadra-Scalzo G, Fonseca de Freitas D, Agbedjro D, et al. A predictor model of treatment resistance in schizophrenia using data from electronic health records. PLoS One. Published online September 19, 2022. doi:10.1371/journal.pone.0274864