Prolactin levels and breast cancer risk by tumor expression of prolactin-related markers

Antipsychotic Use and Risk of Breast Cancer in Women With Severe Mental Illness: Replication of a Nationwide Nested Case-Control Database Study

BACKGROUND AND HYPOTHESIS

Breast cancer is more prevalent in women with severe mental illness than in the general population, and use of prolactin-increasing antipsychotics may be a contributing factor.

STUDY DESIGN

A nested case-control study was conducted using the Swedish nationwide registers (inpatient/outpatient care, sickness absence, disability pension, prescribed drugs, cancers). All women aged 18-85 years with schizophrenia/schizoaffective/other nonaffective psychotic disorder/bipolar disorder and breast cancer (cases) were matched for age, primary psychiatric diagnosis, and disease duration with five women without cancer (controls). The association between cumulative exposure to prolactin-increasing/prolactin-sparing antipsychotics and breast cancer was analyzed using conditional logistic regression, adjusted for comorbidities and co-medications.

STUDY RESULTS

Among 132 061 women, 1642 (1.24%) developed breast cancer between 2010 and 2021, at a mean age of 63.3 ± 11.8 years. Compared with 8173 matched controls, the odds of breast cancer increased in women with prior exposure to prolactin-increasing antipsychotics for 1-4 years (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI] = 1.03-1.41), and for ≥ 5 years (aOR = 1.47, 95%CI = 1.26-1.71). There were no increased or decreased odds of breast cancer with exposure to prolactin-sparing antipsychotics of either 1-4 years (aOR = 1.17, 95%CI = 0.98-1.40) or ≥5 years (aOR = 0.99, 95%CI = 0.78-1.26). The results were consistent across all sensitivity analyses (ie, according to different age groups, cancer types, and primary psychiatric diagnosis).

CONCLUSIONS

Although causality remains uncertain, exposure to prolactin-elevating antipsychotics for ≥ 1 year was associated with increased odds of breast cancer in women with severe mental illness. When prescribing antipsychotics, a shared decision-making process should consider individual risk factors for breast cancer.

A contemporary review of breast cancer risk factors and the role of artificial intelligence

Background

Breast cancer continues to be a significant global health issue, necessitating advancements in prevention and early detection strategies. This review aims to assess and synthesize research conducted from 2020 to the present, focusing on breast cancer risk factors, including genetic, lifestyle, and environmental aspects, as well as the innovative role of artificial intelligence (AI) in prediction and diagnostics.

Methods

A comprehensive literature search, covering studies from 2020 to the present, was conducted to evaluate the diversity of breast cancer risk factors and the latest advances in Artificial Intelligence (AI) in this field. The review prioritized high-quality peer-reviewed research articles and meta-analyses.

Results

Our analysis reveals a complex interplay of genetic, lifestyle, and environmental risk factors for breast cancer, with significant variability across different populations. Furthermore, AI has emerged as a promising tool in enhancing the accuracy of breast cancer risk prediction and the personalization of prevention strategies.

Conclusion

The review highlights the necessity for personalized breast cancer prevention and detection approaches that account for individual risk factor profiles. It underscores the potential of AI to revolutionize these strategies, offering clear recommendations for future research directions and clinical practice improvements.

Effects of Prolactin on Brain Neurons under Hypoxia

The levels and potential role of prolactin (PRL) in the brain under conditions of acute systemic hypoxia were examined, focusing on the accumulation of PRL in cerebrospinal fluid (CSF) and its effects on neuronal activity and injury. The amount of PRL in the brain was investigated using brain tissues from forensic autopsy cases. We counted the number of neurites that formed in human primary neurons (HNs) after the addition of PRL. Furthermore, HNs supplemented with PRL or triiodothyronine (T3) were exposed to hypoxic conditions, and the dead cells were counted. The results showed correlations between brain PRL and CSF PRL levels. Additionally, PRL accumulation in the brain was observed in cases of asphyxia. In vitro experimental findings indicated increased neurite formation in the HNs treated with PRL. Moreover, both PRL and T3 demonstrated neuroprotective effects against hypoxia-induced neuronal cell death, with PRL showing stronger neuroprotective potential than T3. These results suggest that PRL accumulates in the brain during hypoxia, potentially influences neuronal activity, and exhibits neuroprotective properties against hypoxia-induced neuronal injury.