Clin Psychopharmacol Neurosci.  2023 Nov;21(4):769-777. 10.9758/cpn.23.1057.

Prolactin Level Changes according to Atypical Antipsychotics Use: A Study Based on Clinical Data Warehouse

Affiliations
  • 1Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Korea
  • 2Department of Psychiatry, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Suwon, Korea

Abstract


Objective
Antipsychotic drugs are known as the major cause of non-neoplastic hyperprolactinemia. This study aimed to investigate the levels of serum prolactin depending on the use of antipsychotic drugs in patients through the Clinical Data Warehouse (CDW).
Methods
We conducted a cohort search in the CDW application and got 260 patients’ medical records diagnosed with schizophrenia, schizotypal and delusional disorders, manic episodes, and bipolar affective disorders who were taking one of risperidone, blonanserin, amisulpride, and olanzapine. After that, we reviewed the medical data and used the ANCOVA analysis and the post hoc test to compare serum prolactin levels among four antipsychotic drug groups.
Results
Among the 117 subjects included in the analysis, the mean serum prolactin level was 64.6 ± 54.6 ng/ml. Serum prolactin levels were significantly higher in subjects taking risperidone or amisulpride compared to blonanserin and olanzapine. The female subjects who took blonanserin, olanzapine, and risperidone had significantly higher prolactin levels, but there was no difference in serum prolactin levels between sex in the subjects who took amisulpride.
Conclusion
This study suggests the need for regular monitoring of serum prolactin levels in patients who are taking antipsychotics, especially in female patients. And we showed that there is a possibility to conduct more effective and simpler big data research using the CDW. Further studies on the subjects with controlled confounding variables and larger sample groups are needed.

Keyword

Antipsychotic agents; Prolactin; Hyperprolactinemia; Affective disorder, psychotic; Big data
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