Risk factors of hyperprolactinemia induced by risperidone and olanzapine and their correlations with plasma glucose and lipids

Challenges and opportunities in the diagnosis and treatment of early-onset psychosis: a case series from the youth affective disorders clinic in Stockholm, Sweden

Early-onset psychosis is linked to adverse long-term outcomes, recurrent disease course, and prolonged periods of untreated illness; thus highlighting the urgency of improving early identification and intervention. This paper discusses three cases where initial emphasis on psychosocial treatments led to diagnostic and therapeutic delays: (1) a 15-year-old misdiagnosed with emotionally unstable personality disorder and autism, who improved on bipolar medication and antipsychotics; (2) another 15-year-old misdiagnosed with autism, who stabilized on lithium and antipsychotics, subsequently allowing for gender dysphoria evaluation; (3) a 9-year-old autistic boy incorrectly treated for ADHD, who recovered with appropriate antipsychotic treatment. These cases illuminate the vital importance of adhering to a diagnostic hierarchy, prioritizing diagnostic utility, and conducting longitudinal evaluations to facilitate early targeted treatment of psychotic symptoms in early-onset psychosis. Adherence to such strategies can minimize delays in managing early-onset psychosis and improve long-term prognoses.

Safety, tolerability, and pharmacokinetics of JX11502MA in Chinese healthy subjects: a first-in-human, randomized, double-blind, placebo-controlled study following single-dose administration

BACKGROUND

JX11502MA is a potent partial agonist of dopamine D2 and D3 receptors, with a preferential binding profile for D3 receptors in vitro, potentially for treating schizophrenia.

METHODS

A first-in-human, randomized, double-blind, placebo-controlled, single ascending dose clinical trial was designed. The subjects were randomly assigned to receive JX11502MA and placebo capsules with seven ascending dose groups: 0.25 mg, 0.5 mg, 1 mg, 2 mg, 3 mg, 6 mg, and 8 mg. The PK profiles of JX11502MA and its metabolites were evaluated, along with a safety and tolerability assessment.

RESULTS

Considering the safety of participants, the dose escalation was halted at 3 mg. Following single-dose administration, JX11502MA exhibited rapid absorption with a median Tmax ranging from 1 to 1.75 h. The terminal half-life of JX11502MA ranged from 73.62 to 276.85 h. The most common treatment-emergent adverse events (TEAEs) for subjects receiving JX11502MA were somnolence (56.3%), dizziness (18.8%), nausea (21.9%), vomiting (18.8%), and hiccups (18.8%).

CONCLUSIONS

JX11502MA was generally well tolerated at a single dose of 0.25 to 3 mg. The PK profiles and safety characteristics in this study indicated that JX11502MA has the potential to be a favorable treatment option for patients with schizophrenia.

TRIAL REGISTRATION

https://clinicaltrials.gov (identifier: NCT05233657).

Association of Serum Prolactin With Type 2 Diabetes Mellitus: A Comparative Cross-Sectional Study From South India

BACKGROUND

 The association of serum prolactin (PRL) with diabetes is still uncertain, with a paucity of data in the south Indian population. This study aims to compare the serum PRL levels between type 2 diabetes mellitus (T2DM) patients and normoglycaemic volunteers and correlate the serum PRL level with fasting plasma glucose (FPG), postprandial plasma glucose (PPG), glycated haemoglobin (HbA1c) levels, and the lipid profile in the study population.

METHODS

 This was a comparative cross-sectional study among 112 T2DM participants and 112 healthy volunteers in a tertiary care centre in India. All participants were tested for FPG, PPG, HbA1c, fasting serum lipid profile, and serum PRL, which were compared between T2DM patients and healthy volunteers.

RESULTS

 The serum PRL in T2DM patients was significantly lower compared to healthy volunteers (8.67 ± 4.37 vs. 13.76 ± 6.55 ng/ml, P < 0.001). FPG, PPG, and HbA1c correlated inversely with serum PRL in our study population. On multivariable logistic regression adjusted for age and sex, a higher serum PRL level within the physiological range was protective for T2DM (adjusted odds ratio: 0.83, 95% CI: 0.77-0.90, P < 0.001). Serum PRL levels were inversely correlated with serum total cholesterol, low-density lipoprotein cholesterol, and triglycerides, but not with high-density lipoprotein cholesterol.

CONCLUSIONS

A high serum PRL within the physiological range was inversely associated with the prevalence of T2DM in the south Indian population. Serum PRL also correlated inversely with glycaemic and blood lipid parameters. Larger longitudinal studies are required to further validate the association of serum PRL with various components of metabolic syndrome in the south Indian population.

Integrating machine learning with electronic health record data to facilitate detection of prolactin level and pharmacovigilance signals in olanzapine-treated patients

BACKGROUND AND AIM

Available evidence suggests elevated serum prolactin (PRL) levels in olanzapine (OLZ)-treated patients with schizophrenia. However, machine learning (ML)-based comprehensive evaluations of the influence of pathophysiological and pharmacological factors on PRL levels in OLZ-treated patients are rare. We aimed to forecast the PRL level in OLZ-treated patients and mine pharmacovigilance information on PRL-related adverse events by integrating ML and electronic health record (EHR) data.

METHODS

Data were extracted from an EHR system to construct an ML dataset in 672×384 matrix format after preprocessing, which was subsequently randomly divided into a derivation cohort for model development and a validation cohort for model validation (8:2). The eXtreme gradient boosting (XGBoost) algorithm was used to build the ML models, the importance of the features and predictive behaviors of which were illustrated by SHapley Additive exPlanations (SHAP)-based analyses. The sequential forward feature selection approach was used to generate the optimal feature subset. The co-administered drugs that might have influenced PRL levels during OLZ treatment as identified by SHAP analyses were then compared with evidence from disproportionality analyses by using OpenVigil FDA.

RESULTS

The 15 features that made the greatest contributions, as ranked by the mean (|SHAP value|), were identified as the optimal feature subset. The features were gender_male, co-administration of risperidone, age, co-administration of aripiprazole, concentration of aripiprazole, concentration of OLZ, progesterone, co-administration of sulpiride, creatine kinase, serum sodium, serum phosphorus, testosterone, platelet distribution width, α-L-fucosidase, and lipoprotein (a). The XGBoost model after feature selection delivered good performance on the validation cohort with a mean absolute error of 0.046, mean squared error of 0.0036, root-mean-squared error of 0.060, and mean relative error of 11%. Risperidone and aripiprazole exhibited the strongest associations with hyperprolactinemia and decreased blood PRL according to the disproportionality analyses, and both were identified as co-administered drugs that influenced PRL levels during OLZ treatment by SHAP analyses.

CONCLUSIONS

Multiple pathophysiological and pharmacological confounders influence PRL levels associated with effective treatment and PRL-related side-effects in OLZ-treated patients. Our study highlights the feasibility of integration of ML and EHR data to facilitate the detection of PRL levels and pharmacovigilance signals in OLZ-treated patients.

Safety and related factors of treatment with long-term atypical antipsychotic in Chinese patients with schizophrenia: observational study

Background

Atypical antipsychotics as first-line drugs have been used in patients with schizophrenia in China and abroad. However, its safety still needs to be evaluated in a large population, especially in Chinese patients.

Objective

The main objective of this study is to evaluate the safety and related factors of long-term atypical antipsychotic use in patients with schizophrenia in China. The secondary objective includes the long-term efficacy of atypical antipsychotics in these patients, as well as pharmacoeconomic evaluation, population pharmacokinetic studies and pharmacogenomics studies.

Methods

This study has an observational design. The atypical antipsychotics include quetiapine, olanzapine, risperidone, aripiprazole, ziprasidone, paliperidone, amisulpride, perospirone and clozapine. Visits occur at 0, 4, 8, 13, 26, 52, 78, 104, 130 and 156 weeks. The efficacy evaluations include symptoms, social function, recurrence rate and hospitalisation. The safety measures include physical examination, vital signs, abdominal circumference, laboratory tests (such as blood cell analysis, blood biochemical tests and serum prolactin/thyroxine levels), 12-lead ECG, extrapyramidal syndrome assessment, sexual function evaluation, medication and other adverse events. The secondary measures include the Positive and Negative Syndrome Scale, Clinical Global Impression-Severity of Illness Scale, Calgary Depression Scale for Schizophrenia, Personal and Social Performance Scale, relapse rate, drug consolidation, medical-related expenses, income, drug plasma concentration and genetic information.

Results

This is a large sample, non-interventional and long-term prospective clinical study designed to truly reflect the specific details of clinical practice, fully respect patients' needs, and understand patients' treatment intentions and actual treatment details.

Conclusions

This research method details the aims, methods, study design, strengths and limitations of the study.