Early-onset baldness and the risk of aggressive prostate cancer: findings from a case–control study

Factors associated with early-onset androgenetic alopecia: A scoping review

BACKGROUND

Early-onset androgenetic alopecia (AGA) has been associated with various chronic conditions, including metabolic syndrome (MetS). Gaining a deep understanding of early-onset AGA may enable earlier intervention in individuals at high risks. This scoping review aims to explore the risk factors and etiology, associated conditions, and adverse effects on wellbeing in early-onset AGA.

METHODS

Electronic literature searches were conducted in MEDLINE, EMBASE and CENTRIAL. Eligible studies included case-control, cohort, cross-sectional, and meta-analysis studies. Selected studies needed to clearly define early-onset AGA cases or include only cases starting before the age of 40 and compare them with appropriate controls. The exclusion criteria comprised editorials, commentaries, case series, and non-systematic reviews, among others. Data extraction involved collecting study characteristics, methodologies, main outcomes, and findings. Descriptive tables were used to summarize key information and relevant variables when necessary.

RESULTS

Among the 65 eligible articles, 67.69% were case-control studies and 78.46% evaluated only male patients. "Early-onset" was defined as cases developing before the age of 30 years in 43.08% of the studies. The Hamilton-Norwood scale was the most frequently used method for evaluating the severity of alopecia in men (69.23%). Reported risk factors for early-onset AGA included a family history of AGA, cigarette smoking, unhealthy dietary habits, and a high body mass index. Early-onset AGA may also be associated with hormonal profiles, 5α-reductase enzyme activity, androgen receptor genes, and some susceptibility loci. Comorbidities investigated included MetS, cardiovascular disease, insulin resistance, dyslipidemia, and Parkinson's disease. Men with early-onset AGA may have reduced treatment efficacy with drug like rosuvastatin, metformin or lisinopril for dyslipidemia, prediabetes, or hypertension. Additionally, young men with AGA tended to suffer from psychological issues such as anxiety and low self-esteem compared to those without hair loss.

CONCLUSION

Early-onset AGA is a complex condition with various risk factors and etiology, associated comorbidities, and potential implications for treatment response and psychological health.

Male-Pattern Vertex Baldness Trajectories, Chest Hair Patterns, and Odds of Overall and Aggressive Prostate Cancer

BACKGROUND

The link between hormones and hair growth is well established. Inconsistent associations have been found between hair patterns and cancer of the prostate, a hormone-dependent organ. We assessed vertex baldness trajectories, chest hair amount, and their relationships with the odds of developing prostate cancer in a large case-control study in Montreal, Canada.

METHODS

In-person interviews were conducted with 1,931 incident prostate cancer cases and 1,994 population-based age-matched (±5 years) controls. Participants reported their hair patterns using the validated Hamilton-Norwood scale of baldness for 10-year increments starting at age 30, and their current amount of chest hair. Group-based trajectories were used to identify men sharing similar patterns of vertex baldness severity over adulthood. Multivariable logistic regression assessed associations between indicators of baldness (frontal, vertex, age at onset, severity, and trajectories), chest hair, and odds of prostate cancer.

RESULTS

Vertex balding onset at age 30 was associated with increased odds of overall prostate cancer [Odds ratio (OR), 1.30; 95% confidence interval (CI), 1.03-1.64]. Men in the trajectory characterized by early moderate vertex baldness and developing severe baldness had increased odds of overall (OR, 1.42; 95% CI, 1.03-1.96) and especially aggressive prostate cancer (OR, 1.98; 95% CI, 1.21-3.22) compared with men without baldness. Men with little chest hair had higher odds of aggressive tumors than those with a moderate amount/a lot of chest hair.

CONCLUSIONS

Early-onset moderate vertex baldness that progresses and having little chest hair may be useful biomarkers of aggressive prostate cancer.

IMPACT

Integration of early-onset vertex balding patterns into risk prediction models of aggressive prostate cancer should be envisaged.

PCLiON: An Ontology for Data Standardization and Sharing of Prostate Cancer Associated Lifestyles

BACKGROUND

Researches on Lifestyle medicine (LM) have emerged in recent years to garner wide attention. Prostate cancer (PCa) could be prevented and treated by positive lifestyles, but the association between lifestyles and PCa is always personalized.

OBJECTIVES

In order to solve the heterogeneity and diversity of different data types related to PCa, establish a standardized lifestyle ontology, promote the exchange and sharing of disease lifestyle knowledge, and support text mining and knowledge discovery.

METHODS

The overall construction of PCLiON was created in accordance with the principles and methodology of ontology construction. Following the principles of evidence-based medicine, we screened and integrated the lifestyles and their related attributes. Protégé was used to construct and validate the semantic framework. All annotations in PCLiON were based on SNOMED CT, NCI Thesaurus, the Cochrane Library and FooDB, etc. HTML5 and ASP.NET was used to develop the independent Web page platform and corresponding intelligent terminal application. The PCLiON also uploaded to the National Center for Biomedical Ontology BioPortal.

RESULTS

PCLiON integrates 397 lifestyles and lifestyle-related factors associated with PCa, and is the first of its kind for a specific disease. It contains 320 attribute annotations and 11 object attributes. The logical relationship and completeness meet the ontology requirements. Qualitative analysis was carried out for 329 terms in PCLiON, including factors which are protective, risk or associated but functional unclear, etc. PCLiON is publicly available both at http://pcaontology.net/PCaLifeStyleDefault.aspx and https://bioportal.bioontology.org/ontologies/PCALION.

CONCLUSIONS

Through the bilingual online platforms, complex lifestyle research data can be transformed into standardized, reliable and responsive knowledge, which can promote the shared-decision making (SDM) on lifestyle intervention and assist patients in lifestyle self-management toward the goal of PCa targeted prevention.