Pharmacological treatment strategies for antipsychotic-induced hyperprolactinemia: a systematic review and network meta-analysis

Antipsychotic-induced prolactin elevation in premenopausal women with schizophrenia: associations with estrogen, disease severity and cognition

PURPOSE

Antipsychotic-induced prolactin elevation may impede protective effects of estrogens in women with schizophrenia-spectrum disorders (SSD). Our study sought to confirm whether the use of prolactin-raising antipsychotics is associated with lower estrogen levels, and to investigate how estrogen and prolactin levels relate to symptom severity and cognition in premenopausal women with SSD.

METHODS

This cross-sectional study included 79 premenopausal women, divided in three groups of women with SSD treated with prolactin-sparing antipsychotics (n = 21) or prolactin-raising antipsychotics (n = 27), and age-matched women without SSD (n = 31). Circulating 17β-estradiol was compared among groups. In patients, we assessed the relationship between prolactin and 17β-estradiol, and the relationships of these hormones to symptom severity and cognition, using correlation analyses and backward regression models.

RESULTS

In women receiving prolactin-raising antipsychotics, 17β-estradiol levels were lower as compared to both other groups (H(2) = 8.34; p = 0.015), and prolactin was inversely correlated with 17β-estradiol (r=-0.42, p = 0.030). In the prolactin-raising group, 17β-estradiol correlated positively with verbal fluency (r = 0.52, p = 0.009), and 17β-estradiol and prolactin together explained 29% of the variation in processing speed (β17β-estradiol = 0.24, βprolactin = -0.45, F(2,25) = 5.98, p = 0.008). In the prolactin-sparing group, 17β-estradiol correlated negatively with depression/anxiety (r = -0.57, p = 0.014), and together with prolactin explained 26% of the variation in total symptoms (β17β-estradiol = -0.41, βprolactin = 0.32, F(2,18) = 4.44, p = 0.027).

CONCLUSIONS

In women with SSD, antipsychotic-induced prolactin elevation was related to lower estrogen levels. Further, estrogens negatively correlated with symptom severity and positively with cognition, whereas prolactin levels correlated negatively with cognition. Our findings stress the clinical importance of maintaining healthy levels of prolactin and estrogens in women with SSD.

Efficacy, acceptability and side-effects of oral versus long-acting- injectables antipsychotics: Systematic review and network meta-analysis

Long-acting injectable antipsychotics (LAIs) are primarily used for relapse prevention, but in some settings and situations, they may also be useful for acute treatment of schizophrenia. We conducted a systematic review and frequentist network meta-analysis of randomized-controlled trials (RCTs), focusing on adult patients in the acute phase of schizophrenia. Interventions were risperidone, paliperidone, aripiprazole, olanzapine, and placebo, administered either orally or as LAI. We synthesized data on overall symptoms, complemented by 17 other efficacy and tolerability outcomes. Confidence in the evidence was assessed with the Confidence-in-Network-Meta-Analysis-framework (CINeMA). We included 115 RCTs with 25,550 participants. All drugs were significantly more efficacious than placebo with the following standardized mean differences and their 95 % confidence intervals: olanzapine LAI -0.66 [-1.00; -0.33], risperidone LAI -0.59[-0.73;-0.46], olanzapine oral -0.55[-0.62;-0.48], aripiprazole LAI -0.54[-0.71; -0.37], risperidone oral -0.48[-0.55;-0.41], paliperidone oral -0.47[-0.58;-0.37], paliperidone LAI -0.45[-0.57;-0.33], aripiprazole oral -0.40[-0.50; -0.31]. There were no significant efficacy differences between LAIs and oral formulations. Sensitivity analyses of the primary outcome overall symptoms largely confirmed these findings. Moreover, some side effects were less frequent under LAIs than under their oral counterparts. Confidence in the evidence was moderate for most comparisons. LAIs are efficacious for acute schizophrenia and may have some benefits compared to oral formulations in terms of side effects. These findings assist clinicians with insights to weigh the risks and benefits between oral and injectable agents when treating patients in the acute phase.

Treatment of hyperprolactinemia in women: A Position Statement from the Brazilian Federation of Gynecology and Obstetrics Associations (Febrasgo) and the Brazilian Society of Endocrinology and Metabolism (SBEM)

Dopamine agonists are the first line of treatment for patients with symptomatic hyperprolactinemia due to prolactinomas and in those with idiopathic hyperprolactinemia. Treatment with these agents is effective in 80%-90% of the cases. Infertility treatment of patients with hyperprolactinemia is also carried out with dopamine agonists, aiming for the normalization of prolactin levels. The risk of symptomatic growth of prolactinomas during pregnancy is dependent on the tumor's size, duration of previous treatments, and prolactin levels. Notably, the corresponding risk is relatively low in cases of microprolactinomas (<5%). Remission of hyperprolactinemia occurs in about 30% of the patients after drug treatment and may also occur after pregnancy and menopause. The use of some drugs, such as antidepressants and antipsychotics, is a frequent cause of hyperprolactinemia, and managing this occurrence involves unique considerations. This position statement by the Brazilian Federation of Gynecology and Obstetrics Associations (Febrasgo) and Brazilian Society of Endocrinology and Metabolism (SBEM) addresses the recommendations for measurement of serum prolactin levels and the investigations of symptomatic and asymptomatic hyperprolactinemia and drug-induced hyperprolactinemia in women.

Treatment of antipsychotic-induced hyperprolactinemia: an umbrella review of systematic reviews and meta-analyses

Background

Hyperprolactinemia is a common antipsychotic-induced adverse event in psychiatric patients, and the quality of clinical studies investigating the best treatments has varied. Thus, to better summarize the clinical evidence, we performed an umbrella review of overlapping systematic reviews and meta-analyses for the treatment of antipsychotic-induced hyperprolactinemia.

Methods

The PubMed, Cochrane Library, PsycINFO, Scopus and EMBASE were searched, and reviews and meta-analyses meeting our inclusion criteria were selected. Relevant data were extracted, and an umbrella review was conducted of all included meta-analyses. The quality of included meta-analyses was assessed by using PRISMA scores and AMSTAR 2 quality evaluation. Finally, the clinical evidence for appropriate treatments was summarized and discussed.

Results

Five meta-analyses published between 2013 and 2020 met the requirements for inclusion in this umbrella review. The PRISMA scores of the included meta-analyses ranged from 19.5-26. AMSTAR 2 quality evaluation showed that 2 of the 5 included meta-analyses were of low quality and 3 were of very low quality. The included meta-analyses provide clinical evidence that adding aripiprazole or a dopamine agonist can effectively and safely improve antipsychotic-induced hyperprolactinemia. Two meta-analyses also showed that adjunctive metformin can reduce serum prolactin level, but more clinical trials are needed to confirm this finding.

Conclusion

Adjunctive dopamine agonists have been proven to be effective and safe for the treatment of antipsychotic-induced hyperprolactinemia. Among the researched treatments, adding aripiprazole may be the most appropriate.

Evidence-Based Recommendations for the Pharmacological Treatment of Women with Schizophrenia Spectrum Disorders

PURPOSE OF REVIEW

Despite clear evidence that sex differences largely impact the efficacy and tolerability of antipsychotic medication, current treatment guidelines for schizophrenia spectrum disorders (SSD) do not differentiate between men and women. This review summarizes the available evidence on strategies that may improve pharmacotherapy for women and provides evidence-based recommendations to optimize treatment for women with schizophrenia.

RECENT FINDINGS

We systematically searched PubMed and Embase for peer-reviewed studies on three topics: (1) sex differences in dose-adjusted antipsychotic serum concentrations, (2) hormonal augmentation therapy with estrogen and estrogen-like compounds to improve symptom severity, and (3) strategies to reduce antipsychotic-induced hyperprolactinemia. Based on three database studies and one RCT, we found higher dose-adjusted concentrations in women compared to men for most antipsychotics. For quetiapine, higher concentrations were specifically found in older women. Based on two recent meta-analyses, both estrogen and raloxifene improved overall symptomatology. Most consistent findings were found for raloxifene augmentation in postmenopausal women. No studies evaluated the effects of estrogenic contraceptives on symptoms. Based on two meta-analyses and one RCT, adjunctive aripiprazole was the best-studied and safest strategy for lowering antipsychotic-induced hyperprolactinemia. Evidence-based recommendations for female-specific pharmacotherapy for SSD consist of (1) female-specific dosing for antipsychotics (guided by therapeutic drug monitoring), (2) hormonal replacement with raloxifene in postmenopausal women, and (3) aripiprazole addition as best evidenced option in case of antipsychotic-induced hyperprolactinemia. Combining these strategies could reduce side effects and improve outcome of women with SSD, which should be confirmed in future longitudinal RCTs.

Schizophrenia in Women: Clinical Considerations

Men and women, for biologic and sociocultural reasons, differ in the nature of their risks for schizophrenia and also in their care needs. Women with schizophrenia have several reproduction-associated risks and care needs that require special clinical consideration. They also have several specific risks related to antipsychotics and gender-associated needs not necessarily related to biology. These require clinicians' diagnostic acumen, treatment skills, cultural sensitivity, and advocacy know-how. Although this does not pertain to everyone, awareness on the part of clinicians is essential. This article addresses the current evidence for difference.

Therapeutic outcomes wide association scan of different antipsychotics in patients with schizophrenia: Randomized clinical trials and multi-ancestry validation

AIM

This study identified discrepant therapeutic outcomes of antipsychotics.

METHODS

A total of 5191 patients with schizophrenia were enrolled, 3030 as discovery cohort, 1395 as validation cohort, and 766 as multi-ancestry validation cohort. Therapeutic Outcomes Wide Association Scan was conducted. Types of antipsychotics (one antipsychotic vs other antipsychotics) were dependent variables, therapeutic outcomes including efficacy and safety were independent variables.

RESULTS

In discovery cohort, olanzapine related to higher risk of weight gain (AIWG, OR: 2.21-2.86), liver dysfunction (OR: 1.75-2.33), sedation (OR: 1.76-2.86), increased lipid level (OR: 2.04-2.12), and lower risk of extrapyramidal syndrome (EPS, OR: 0.14-0.46); risperidone related to higher risk of hyperprolactinemia (OR: 12.45-20.53); quetiapine related to higher risk of sedation (OR = 1.73), palpitation (OR = 2.87), increased lipid level (OR = 1.69), lower risk of hyperprolactinemia (OR: 0.09-0.11), and EPS (OR: 0.15-0.44); aripiprazole related to lower risk of hyperprolactinemia (OR: 0.09-0.14), AIWG (OR = 0.44), sedation (OR: 0.33-0.47), and QTc prolongation (β = -2.17); ziprasidone related to higher risk of increased QT interval (β range: 3.11-3.22), nausea (OR: 3.22-3.91), lower risk of AIWG (OR: 0.27-0.46), liver dysfunction (OR: 0.41-0.38), and increased lipid level (OR: 0.41-0.55); haloperidol related to higher risk of EPS (OR: 2.64-6.29), hyperprolactinemia (OR: 5.45-9.44), and increased salivation (OR: 3.50-3.68). Perphenazine related to higher risk of EPS (OR: 1.89-2.54). Higher risk of liver dysfunction in olanzapine and lower risk of hyperprolactinemia in aripiprazole were confirmed in validation cohort, and higher risk of AIWG in olanzapine and hyperprolactinemia in risperidone were confirmed in multi-ancestry validation cohort.

CONCLUSION

Future precision medicine should focus on personalized side-effects.

Relapse in patients with schizophrenia and amisulpride-induced hyperprolactinemia or olanzapine-induced metabolic disturbance after switching to other antipsychotics

Hyperprolactinemia and metabolic disturbance are common side effects of antipsychotics that cause intolerance. Despite its potential influence on relapse, there are no established guidelines for antipsychotic switching. This naturalistic study explored the association between antipsychotic switching, baseline clinical status, metabolic changes, and relapse in patients with schizophrenia. In total, 177 patients with amisulpride-induced hyperprolactinemia and 274 with olanzapine-induced metabolic disturbance were enrolled. Relapse was determined by assessing changes in Positive and Negative Syndrome Scale (PANSS) total scores from baseline to 6 months (increased over 20% or 10% reaching 70). Metabolic indices were measured at baseline and 3 months. Patients with baseline PANSS >60 were more likely to relapse. Further, patients switching to aripiprazole had a higher risk of relapse regardless of their original medication. Participants who originally used amisulpride had reduced prolactin levels following medication change, while switching to olanzapine caused increased weight and blood glucose levels. In patients originally using olanzapine, only switching to aripiprazole reduced insulin resistance. Adverse effects on weight and lipid metabolism were observed in patients who switched to risperidone, while amisulpride improved lipid profiles. Changing schizophrenia treatment requires careful consideration of multiple variables, particularly the choice of substituted drug and the patient's baseline symptoms.

Pharmacological Strategies for Bipolar Disorders in Acute Phases and Chronic Management with a Special Focus on Lithium, Valproic Acid, and Atypical Antipsychotics

Bipolar disorders (BDs) are a heterogeneous group of severe affective disorders generally described by the alternation of (hypo)manic, depressive, and mixed phases, with euthymic intervals of variable duration. BDs are burdened with high psychiatric and physical comorbidity, increased suicide risk and reduced life expectancy. In addition, BDs can progress into complicated forms (e.g., mixed states, rapid/irregular cycling), which are more difficult to treat and often require personalized pharmacological combinations. Mood stabilizers, particularly Lithium and Valproic acid (VPA), still represent the cornerstones of both acute and chronic pharmacotherapies of BDs. Lithium is the gold standard in BD-I and BDII with typical features, while VPA seems more effective for atypical forms (e.g., mixed-prevalence and rapid-cycling). However, despite appropriate mood stabilization, many patients show residual symptoms, and more than a half recur within 1-2 years, highlighting the need of additional strategies. Among these, the association of atypical antipsychotics (AAPs) with mood stabilizers is recurrent in the treatment of acute phases, but it is also being growingly explored in the maintenance pharmacotherapy. These combinations are clinically more aggressive and often needed in the acute phases, whereas simplifying pharmacotherapies to mood stabilizers only is preferable in the long-term, whenever possible. When mood stabilizers are not enough for maintenance treatment, Quetiapine and, less consistently, Aripiprazole have been proposed as the most advisable adjunctive strategies, for their safety and tolerability profiles. However, in view of the increased risk of serious adverse effects, a careful patient-centered balance between costs and benefits is mandatory.

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.

Factors influencing prolactin levels in chronic long-term hospitalized schizophrenic patients with co-morbid type 2 diabetes mellitus

BACKGROUND

For long-term hospitalized patients suffering from schizophrenia, metabolic disease and hyperprolactinemia (HPRL) are common comorbidities. This article is aimed at analyzing the factors influencing comorbid type 2 diabetes mellitus (T2DM) on prolactin (PRL) levels in long-term hospitalized patients suffering from schizophrenia.

METHODS

This study included 378 long-term hospitalized patients with schizophrenia. Common metabolic markers and PRL levels of included samples were collected, and the severity of psychopathology was assessed using the Positive and Negative Symptoms Scale (PANSS). Based on the patients with or without T2DM, the samples were divided into two groups. The differences in clinical parameters between the two groups were compared, and the effects of the parameters on the PRL levels were analyzed.

RESULTS

Compared with non-DM patients, the patients in the DM subgroup had lower PRL levels (P < 0.0001) and rather severe psychiatric symptoms (P = 0.016). Female, treated by risperidone, and high levels of triglyceride (TG) were faced with risk for HPRL (B = 26.31, t = 5.39, P < 0.0001; B = 19.52, t = 4.00, P < 0.0001; B = 2.71, t = 2.31, P = 0.022, respectively). Meanwhile, co-morbid DM and aripiprazole treatment were protective factors (B = 15.47, t = 3.05, P = 0.002; B = -23.77, t = -2.47, P = 0.014; respectively). Ultimately, in the DM subgroup, the dose of metformin was found to be a protective factor for HPRL (B = -0.01, t = -1.46, P = 0.047), while female and aripiprazole were risk factors (B = 16.06, t = 3.26, P = 0.001; B = 20.13, t = 2.57, P = 0.011; respectively).

CONCLUSION

Aripiprazole is a protective factor for HPRL in long-term hospitalized patients, whereas the female is a risk factor. Metformin is beneficial in reducing PRL levels in patients with co-morbid DM. More aggressive and effective interventions are required for preventing adverse drug reactions in women and patients with co-DM.