Abstract
Background/Objectives: Polycystic Ovary Syndrome (PCOS) is a multifactorial endocrine disorder with significant clinical and reproductive implications. Identifying dose-response relationships between clinical, physical, and reproductive factors and PCOS can enhance diagnostic accuracy and inform treatment strategies. This study utilized a data-driven approach to analyze the associations between key factors, including age, weight, menstrual cycle length, Anti-Mullerian Hormone (AMH) levels, and follicle count, with PCOS prevalence. Methods: A retrospective analysis was conducted on a dataset of 539 participants to determine the optimal ranges of these factors associated with an increased likelihood of PCOS diagnosis. Statistical analyses were conducted using Python, including correlation matrix, univariate and multivariate logistic regression, and dose-response evaluations. Results: Our findings demonstrated that the risk of PCOS increases positively in women under 32 years of age. AMH levels above 4.18 ng/mL were strongly associated with PCOS, suggesting that higher AMH levels may reflect excessive follicular activity rather than enhanced ovarian function. Weight was positively correlated with PCOS, emphasizing the role of metabolic disturbances in its pathophysiology. Additionally, menstrual cycle length exhibited a non-linear association with PCOS, with both shortened and prolonged cycles being indicative of hormonal dysregulation. A higher follicle count was consistently linked to PCOS, reinforcing its diagnostic significance. Conclusions: This study provides evidence of non-linear dose-response relationships between PCOS and clinical, physical, and reproductive factors. The proposed optimal ranges may serve as valuable reference points for clinicians, aiding in early diagnosis and personalized management strategies for women with PCOS.