Open AccessArticle Incidence, Treatment Patterns, and Associated Clinical Conditions of Hyperprolactinemia Identified via Nationwide Claims Data in Korea: A 13-Year Population-Based Study 1 Department of Obstetrics and Gynecology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea 2 Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea 3 Department of Obstetrics and Gynecology, Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea * Author to whom correspondence should be addressed. J. Clin. Med. 2026, 15(12), 4411; https://doi.org/10.3390/jcm15124411 (registering DOI) Submission received: 14 May 2026 / Revised: 2 June 2026 / Accepted: 5 June 2026 / Published: 7 June 2026 Abstract Background: Hyperprolactinemia is a common endocrine disorder with significant reproductive and systemic implications. This study aimed to investigate the nationwide epidemiological trends, longitudinal shifts in pharmacological treatment, and the temporal associations of concurrent conditions and long-term sequelae in Korean women with claims-based hyperprolactinemia. Methods: A nationwide, population-based retrospective cohort study was conducted using data from the Health Insurance Review & Assessment Service (HIRA) of South Korea from 2009 to 2021. Female patients aged 10–59 years with hyperprolactinemia diagnostic claims were evaluated. We analyzed annual prevalence, incidence, diagnostic procedures, and dopamine agonist prescription patterns. Associated clinical conditions were classified into two categories based on the timing of their diagnosis relative to hyperprolactinemia: concurrent or underlying conditions present at baseline, and long-term complications that developed during the follow-up period. Results: A total of 95,616 female patients were identified after applying the selection criteria. The prevalence and incidence of hyperprolactinemia peaked among women in their early thirties, with an absolute peak at age 32. A significant pharmacological paradigm shift was observed: bromocriptine was the predominant therapy during the early study period, but cabergoline prescriptions surpassed bromocriptine in 2017. Regarding clinical work-ups, only 5.3% of the entire cohort underwent a sella magnetic resonance imaging (MRI). Regarding associated clinical conditions, reproductive disorders such as infertility (28.0%) and polycystic ovary syndrome (24.8%) showed high overall prevalence but low incidence of new diagnoses during the follow-up period. Conversely, among the patients affected by bone disorders, more than 60% of the total osteoporosis and osteopenia cases were diagnosed subsequent to the initial hyperprolactinemia diagnosis. Significant post-diagnosis incidence was also observed for metabolic disorders, including dyslipidemia and diabetes mellitus. Conclusions: Hyperprolactinemia in Korean women is highly concentrated in the peak reproductive years. The shift toward cabergoline reflects evolving clinical guidelines and improved drug accessibility. Our findings highlight that while reproductive issues often present concurrently, bone loss and metabolic complications frequently emerge as post-diagnosis sequelae. Therefore, clinical management should extend beyond prolactin normalization to include proactive, multidisciplinary screening for skeletal and metabolic health. Keywords: hyperprolactinemia; prevalence; incidence; cabergoline; bromocriptine 1. Introduction The etiology of hyperprolactinemia is highly diverse, ranging from organic, tumor-related causes to functional and pharmacological factors [ 1, 2, 4, 5]. Prolactin-producing pituitary adenomas (prolactinomas), or mixed co-secreting tumors such as somatotropinomas, represent the primary organic drivers of this condition [ 6, 7]. Conversely, non-tumor-related or functional hyperprolactinemia can arise from secondary factors, including systemic conditions like hypothyroidism [ 8] or chronic kidney disease [ 9], as well as overlapping clinical syndromes such as polycystic ovary syndrome (PCOS) [ 4, 10, 11, 12]. Additionally, it can be drug-induced, stemming from medications that disrupt dopaminergic pathways [ 13]. Furthermore, hyperprolactinemia is clinically intertwined with various systemic conditions through distinct molecular pathways. Patho-physiologically, it impairs reproduction by suppressing hypothalamic kisspeptin-1 and GnRH pulsatility, leading to infertility and anovulatory patterns that frequently overlap with PCOS [ 10, 17, 18, 19, 20]. Chronically elevated prolactin also drives metabolic changes; prolactin receptor activation in adipose tissue and pancreatic beta-cells worsens insulin resistance and reduces adiponectin, accelerating obesity and metabolic syndrome [ 21, 22, 23, 24]. Moreover, the resulting hypogonadism and estrogen deficiency favor osteoclastogenesis, leading to long-term skeletal risks such as osteopenia and osteoporosis [ 25]. While these pathophysiological mechanisms are well-established, large-scale, population-based epidemiological data on its development and incidence in clinical practice remain limited. Therefore, this study aimed to investigate the epidemiological characteristics, including the nationwide prevalence and incidence, of hyperprolactinemia among Korean women using a comprehensive healthcare claims database. We also sought to evaluate the longitudinal paradigm shifts in pharmacological treatment patterns over a 13-year period and to delineate the temporal associations between hyperprolactinemia and its major associated clinical conditions. 2. Materials and Methods 2.1. Study Design and Data Source This nationwide, population-based retrospective cohort study was conducted using customized research data provided by the Health Insurance Review & Assessment Service (HIRA) of South Korea. The HIRA database contains comprehensive healthcare claims data for the entire South Korean population, including demographic information, diagnostic codes based on the International Classification of Diseases (ICD-10), and detailed records of outpatient visits, inpatient care, procedures, and prescriptions. The data is open for use for research through anonymization and deidentification of the subjects. 2.2. Case Definition and Study Population 2.3. Calculation of Prevalence and Incidence To estimate the annual prevalence of hyperprolactinemia, the total number of patients who met the case definition criteria was divided by the total number of all female population aged 10–59 years for each year. Incidence was defined as the first appearance of diagnostic codes for hyperprolactinemia in health insurance claims, regardless of hospital admissions or outpatient visits. A one-year look-back period method was applied to evaluate the estimated incidence to exclude cases with pre-existing diagnoses, thereby accurately distinguishing newly diagnosed incident cases from prevalent cases [ 29]. Both crude prevalence and incidence rates were expressed as the number of cases per 100,000 persons. Additionally, age-adjusted prevalence rates were calculated utilizing the direct standardization method, using the 2007 study cohort as the standard female population. 2.4. Assessment of Diagnostic and Treatment Patterns Clinical assessment patterns were categorized into two groups: etiological diagnostic evaluations and cardiovascular safety surveillance. Etiological diagnostic evaluations, aimed at identifying underlying structural sellar lesions (such as prolactinoma), were tracked via codes for sella magnetic resonance imaging (MRI) and sella cone view radiography. Of note, sella cone view radiography represents a historical plain-film modality that is not part of modern diagnostic guidelines, but was captured in our dataset to reflect real-world clinical documentation spanning ack to 2009. Cardiovascular safety and complication surveillance—relevant to monitoring potential valvular hear disease from long-term, high-dose cabergoline therapy or secondary cardiovascular risks from prolonged untreated hypogonadism—was assessed using claims codes for electrocardiography (ECG) and echocardiography (transthoracic or transesophageal). Pharmacological treatment patterns were evaluated based on the prescription records of dopamine agonists, specifically bromocriptine and cabergoline. Prescription distributions were analyzed by age group, and longitudinal trends in the annual prescription volume were tracked to assess shifts in clinical practice. 2.5. Definition of Associated Clinical Conditions and Temporal Associations A comprehensive analysis of associated clinical conditions was conducted using ICD-10 codes, classified into four main categories: (1) endocrine and metabolic disorders (diabetes mellitus; E10-E14, thyroid disease; E00-E07, dyslipidemia; E78, obesity; E65-E68, and hypertension; I10-I15), (2) gynecological and reproductive disorders (infertility; N97.0-N97.9, polycystic ovary syndrome; E28.2, (3) bone disorders (osteoporosis; M80-M82, and osteopenia; M85.89), and (4) malignancies (breast cancer; C50, vulvar cancer; C51, vaginal cancer; C52, cervical cancer; C53, endometrial cancer; C54.1, ovarian cancer; C56, and other gynecological cancers; C57). To evaluate the temporal relationship between hyperprolactinemia and these associated conditions, the analysis was distinguished into two metrics: (1) overall prevalence, defined as the proportion of the hyperprolactinemia cohort who had the clinical condition at any point, and (2) post-diagnosis incidence, strictly defined as conditions that were newly diagnosed after the initial diagnosis of hyperprolactinemia. Post-diagnosis incidence was strictly tracked from each patient’s index hyperprolactinemia diagnosis date until 31 December 2021, allowing a longitudinal observation window of up to 13 years. 2.6. Statistical Analyses All descriptive statistics were reported as numbers and percentages. Categorical variables were expressed as frequencies and proportions. A 95% binomial confidence interval (CI) was initially considered for estimating the prevalence and incidence. However, owing to the exceptionally large population size of this cohort, the standard errors were negligibly small, resulting in values that were virtually identical to the point estimates for all prevalence and incidence rates. Therefore, we decided not to indicate the 95% CIs for the prevalence and incidence values throughout the text. All statistical analyses were performed using SAS software, version 9.2 (SAS Institute, Cary, NC, USA). 2.7. Statement of Ethics Access to the dataset was strictly restricted to researchers authorized by HIRA. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (IRB) of the Catholic University of Korea (PC22ZISI0086, 6 May 2022). The requirement for informed consent was waived because all data were fully anonymized and de-identified by HIRA prior to the analysis. 3. Results 3.1. Study Population Selection From the initial screening, 115,906 female patients with a diagnostic claim for hyperprolactinemia (ICD-10: E221) were identified. After applying the exclusion criteria—removing 19,010 patients during the 2007–2008 look-back period, 85 patients with Parkinson’s disease, and 1195 patients aged 9 years or younger and 60 years or older—a final cohort of 95,616 patients aged 10 to 59 years was established for longitudinal analysis. 3.2. Prevalence of Hyperprolactinemia The total number of treated patients continuously increased from 10,895 in 2007 to a peak of 14,848 in 2020, but showed a slight decreasing trend to 12,672 in 2021 ( Figure 1). Table 1 shows the crude prevalence rate by age group from 2007 to 2021. The overall crude prevalence rate increased steadily from 60 per 100,000 persons in 2007 to 86 per 100,000 persons in 2020, and was recorded at 75 per 100,000 persons in 2021. The age-adjusted prevalence rate exhibited a similar pattern, starting at 60 per 100,000 persons in 2007, rising to 88 per 100,000 persons in 2020, and dropping to 75 per 100,000 persons in 2021. Age-specific analysis revealed that the prevalence rate increased gradually through the teens and early twenties, and showed a sharp upward curve starting in the late twenties (25–29 years) ( Figure 2a). Specifically, the number of patients surged from 4223 at age 25 to 6242 at age 29, and the highest concentration of patients was observed in the subsequent early thirties (30–34 years) age group. The absolute peak in prevalence was recorded among women age 32 years, reaching a total of 7405 patients ( Figure 2b). Following this peak, a steady and distinct declining trend was observed as age increased, dropping to 5154 patients at age 40, 2802 at age 50, and eventually falling to 507 patients at age 59. 3.3. Incidence of Hyperprolactinemia Analysis of the incidence data over the 13-year period from 2009 to 2021 identified a total of 95,616 newly diagnosed cases of hyperprolactinemia. The annual number of incident cases initially showed a decreasing trend from 6724 cases in 2009 to 5692 cases in 2013. However, the incidence gradually rebounded and steadily climbed thereafter, reaching a peak of 9914 newly diagnosed cases in 2020, followed by 8137 incident cases in 2021 ( Figure 3). Age-specific incidence analysis corroborated the prevalence patterns, demonstrating that the onset of the disease was highly concentrated among women of childbearing age. The 30–34 age group accounted for the largest proportion of all incident cases with 21,220 newly diagnosed patients (22.2%), followed by the 25–29 age group (16,743 cases, 17.5%) and the 35–39 age group (16,385 cases, 17.1%) ( Figure 4). 3.4. Diagnostic and Cardiovascular Safety Surveillance Patterns During the study period, for etiological diagnostic evaluations, a total of 5076 patients (5.3%) underwent sella MRI, while sella cone view radiography was performed in 1468 patients (1.5%). For cardiovascular safety and complication surveillance, claims for ECG were documented in 34,589 patients (36.2%), and echocardiography was performed in 505 patients (0.5%) among the total cohort. 3.5. Pharmacological Treatment Patterns Among the 95,616 cases of hyperprolactinemia, pharmacological treatment with dopamine agonists was initiated in a substantial proportion of patients (44.5%, n = 42,503). Bromocriptine was the most frequently prescribed medication, administered in 25.75% of the patients ( n = 24,622), while cabergoline was prescribed to 18.7% ( n = 17,881). The age-specific prescription distribution revealed that both medications were most frequently prescribed to patients in their early thirties (30–34 years), which coincides with the peak prevalence age group. Specifically, within this age group, bromocriptine and cabergoline were prescribed in 6550 and 4562 cases, respectively, marking the highest prescription rate across all age brackets. A longitudinal analysis of annual prescription volumes showed a gradual change in the choice of dopamine agonists ( Figure 5). In the early observation period, bromocriptine was predominantly prescribed, with the annual prescription volume increasing to 10,812 cases in 2014. However, cabergoline prescriptions began to increase steadily after its initial recording in 2011 (136 cases), reaching 5524 cases in 2015. A crossover in prescription frequency occurred between 2016 and 2017; by 2017, cabergoline (10,619 cases) surpassed bromocriptine (8217 cases). This trend continued until the end of the study period in 2021, at which point cabergoline was prescribed in 12,218 cases compared to 3745 cases for bromocriptine. 3.6. Associated Clinical Conditions and Temporal Associations A comprehensive analysis of associated clinical conditions was conducted, differentiating between the overall prevalence of associated diseases and their new incidence occurring subsequent to the diagnosis of hyperprolactinemia (Supplemental Table S1). Endocrine and Metabolic Disorders: Dyslipidemia was the most prevalent associated condition overall, affecting 55.8% ( n = 53,337) of the cohort, with 24.8% ( n = 23,758) of these cases developing after the initial diagnosis of hyperprolactinemia. Thyroid disease was also highly prevalent, observed in 48.4% ( n = 46,315) of patients, with a post-diagnosis incidence of 19.9% ( n = 19,005). Furthermore, diabetes mellitus (DM) and hypertension demonstrated a prevalence of 23.7% ( n = 22,656) and 15.4% ( n = 14,759), respectively, and a post-diagnosis incidence of 12.7% ( n = 12,107) and 7.5% ( n = 7147), respectively. Gynecological and Reproductive Disorders: Infertility exhibited a high overall prevalence of 28.0% ( n = 26,738), but a relatively low incidence of 6.3% ( n = 6062) developing after the diagnosis of hyperprolactinemia. Similarly, polycystic ovarian syndrome (PCOS) had a notable prevalence of 24.8% ( n = 23,740), accompanied by a post-diagnosis incidence rate of 6.7% ( n = 6422). Bone Disorders: Osteoporosis and osteopenia were identified in 13.1% ( n = 12,490) and 3.3% ( n = 3318) of the patients, respectively. The rates of incidence developing after the hyperprolactinemia diagnosis were 8.2% ( n = 7799) for osteoporosis and 2.0% ( n = 1892) for osteopenia. Malignancy: Ovarian (1.4%, n = 1364) and breast (1.2%, n = 1132) cancers were the most common malignancies. A substantial majority of breast cancer (0.9%, n = 876) developed after the diagnosis of hyperprolactinemia. 4. Discussion This nationwide, population-based retrospective cohort study provides a comprehensive overview of the epidemiological characteristics, longitudinal shifts in pharmacological treatments, and the temporal dynamics of clinical conditions associated with hyperprolactinemia in Korean women. By utilizing an extensive 13-year dataset, the study captures real-world clinical trajectories and highlights critical shifts in disease management. A pivotal finding of this study is the distinct paradigm shift in the pharmacological management of hyperprolactinemia. Our longitudinal analysis demonstrates a definitive crossover between 2016 and 2017, where cabergoline prescription volumes surpassed those of bromocriptine. By 2021, cabergoline had firmly established itself as the dominant primary therapy. This transition is intrinsically linked to the historical changes in drug accessibility in South Korea. Prior to 2015, cabergoline was not commercially distributed by local pharmaceutical companies and was only available through the Korea Orphan & Essential Drug Center, which severely limited its clinical use. The formal inclusion of cabergoline in the national health insurance coverage in January 2015 marked a pivotal turning point in its clinical adoption, significantly enhancing its accessibility. This policy change enabled clinicians to fully leverage cabergoline’s superior efficacy in normalizing serum prolactin levels, alongside its highly favorable tolerability profile and convenient weekly dosing schedule [ 7, 15]. A key finding reflecting real-world clinical practice in Korea is that only 5.3% of the entire cohort underwent a sella MRI. In highly controlled clinical guidelines, neuroimaging is strongly recommended to differentiate organic prolactinomas from non-tumor etiologies [ 7]. However, our findings reflect a distinct real-world pattern where a vast majority of claims-defined cases are managed in primary or secondary care settings as functional, transient, or drug-induced conditions, without escalating to high-cost diagnostic imaging. This structural heterogeneity is a primary characteristic of population-level claims data, and the pattern aligns with large-scale European epidemiological registries, such as the PROLEARS study in Scotland [ 35], which demonstrated that a substantial portion of hyperprolactinemia cases in the general population are transient or drug-induced rather than verified organic adenomas. The stratification of associated clinical conditions into overall prevalence and post-diagnosis incidence yields profound clinical insights. Gynecological and reproductive conditions, notably infertility and PCOS, exhibited high overall prevalence but a markedly low subsequent incidence. The general prevalence of infertility in the South Korean female population is estimated to be approximately 13.5% [ 36], which aligns with the global estimate of 1 in 6 individuals (approximately 15%) reported by the World Health Organization (WHO) [ 37]. Similarly, recent nationwide studies report the age-adjusted prevalence of PCOS among Korean women to be approximately 4.3% [ 38], which is lower than the global estimate of 10–13% [ 39]. Our hyperprolactinemia cohort demonstrated exceptionally high overall prevalence for these conditions (28.0% for infertility and 24.8% for PCOS). This pronounced discrepancy from the general population, coupled with their notably low post-diagnosis incidence, strongly suggests that hyperprolactinemia and these reproductive disorders are frequently evaluated and diagnosed concurrently during the initial work-up for menstrual irregularities or infertility. Rather than hyperprolactinemia acting solely as a downstream cause, these conditions share complex, overlapping endocrine pathways that prompt simultaneous identification [ 10, 18, 40]. This finding is further supported by Luque-Ramirez et al. [ 41], who highlighted that mild hyperprolactinemia is a common feature in women with PCOS. In contrast, among patients who developed bone disorders, the vast majority of cases occurred subsequent to the hyperprolactinemia diagnosis. Specifically, 62.4% of all osteoporosis cases ( n = 7799 out of 12,490) and 60.3% of all osteopenia cases ( n = 1892 out of 3138) were newly documented after the index hyperprolactinemia claim. Patho-physiologically, hyperprolactinemia inhibits hypothalamic GnRH secretion, leading to a state of secondary hypogonadism and chronic estrogen deficiency [ 1, 42]. This hormonal imbalance disrupts the bone remodeling equilibrium, favoring bone resorption over formation and ultimately resulting in bone mineral density loss [ 25]. Our findings support the necessity of early and regular bone mineral density (BMD) monitoring, a clinical imperative also emphasized by Naliato et al., who demonstrated that significant bone density deficits can persist in women with prolactinoma even after the initiation of dopamine agonist therapy [ 43]. Furthermore, Bussade et al. [ 44] reported that a substantial reduction in BMD occurs even in premenopausal women with prolactinoma, highlighting that the hypogonadal environment associated with elevated prolactin poses a severe skeletal risk regardless of the patient’s age or menopausal status. Consequently, our data reinforce the importance of bone health management as a standard component of long-term care for all women with hyperprolactinemia. Substantial proportions of diabetes mellitus (53.44%) and hypertension (48.42%) cases were also newly diagnosed subsequent to the onset of hyperprolactinemia. Considering the potential impact of prolactin-induced insulin resistance or prolonged hormonal imbalance on metabolic syndrome [ 45, 46], prophylactic monitoring of metabolic parameters should be incorporated into the routine management of these patients. This study has several limitations inherent to the use of administrative claims data. First, exact clinical parameters, including serum prolactin concentration levels, specific pituitary tumor dimensions (microadenoma vs. macroadenoma), and body mass index (BMI), were inaccessible. Consequently, a definitive biochemical or radiological differentiation between pure organic prolactinomas, drug-induced hyperprolactinemia, and rare overlapping conditions like growth hormone-secreting somatotropinomas could not be executed. While patients with Parkinson’s disease were excluded to filter out high-dose dopamine agonist users, the clinical heterogeneity within the broad E221 claim code remains an inherent constraint in etiological subgrouping. Furthermore, actual patient adherence to the prescribed dopamine agonists cannot be definitively confirmed through prescription claims alone. Additionally, while our study captured the 2017 nationwide shift from bromocriptine to cabergoline, individual dose titrations and drug-switching patterns were not analyzed. These population-level trends reflect overall healthcare utilization rather than personalized therapeutic scaling or patient compliance. Second, as the HIRA database consists of administrative claims data primarily designed for billing and reimbursement, it lacks the level of detail found in specialized clinical research databases. Since diagnoses are defined based on ICD-10 codes, discrepancies may exist between billed claims and actual clinical diagnoses, potentially introducing misclassification bias. Furthermore, the true burden of the disease may be underestimated, as patients with mild symptoms or those who did not seek medical care are not captured in the database. Third, it is possible that our operational definition, which relied solely on diagnostic codes without requiring a minimum number of medical visits (e.g., at least one hospitalization or two outpatient visits) or the presence of pharmacological treatment, may have led to an overestimation of the patient count. However, we deliberately avoided visit-based restrictions to prevent selection bias, which can occur by excluding subjects at the temporal boundaries of the cohort window. Moreover, since pharmacological therapy is not clinically mandatory for all hyperprolactinemia cases depending on the patient’s condition, its presence was not required for inclusion in the study cohort. Despite these limitations, the strength of our study lies in its massive, nationwide cohort and the precise temporal delineation of associated clinical conditions. The findings clearly illustrate a modernized landscape of hyperprolactinemia treatment and strongly demonstrates the need for a multidisciplinary clinical approach. Recognizing the high post-diagnosis rate of bone and metabolic disorders will enable clinicians to optimize preventative care, thereby improving the long-term quality of life for women diagnosed with hyperprolactinemia. 5. Conclusions This 13-year nationwide study reveals that hyperprolactinemia in Korean women peaks during the early thirties, significantly impacting reproductive health. We identified a major pharmacological shift from bromocriptine to cabergoline, primarily driven by the 2015 expansion of national health insurance coverage. Crucially while PCOS and infertility typically diagnosed concurrently with hyperprolactinemia, bone loss and metabolic complications frequently emerge as long-term sequelae. Therefore, clinical management must extend beyond prolactin normalization to include proactive, multidisciplinary screening for skeletal and metabolic health to improve long-term quality of life. Supplementary Materials The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/jcm15124411/s1: Table S1: Prevalence and post-diagnosis incidence of comorbidities in women with hyperprolactinemia. Author Contributions Conceptualization, J.N. and S.K.; methodology, K.-H.C., S.K. and J.N.; software, K.-H.C. and S.K.; validation, K.-H.C., S.K. and J.N.; formal analysis, K.-H.C., H.Y. and J.N.; investigation, H.K., Y.J. and C.K.; resources, K.-H.C.; data curation, K.-H.C. and J.N.; writing—original draft preparation, H.Y. and H.K.; writing—review and editing, H.Y., Y.J., C.K., K.-H.C. and J.N.; visualization, K.-H.C.; supervision, S.K. and J.N.; project administration, J.N.; funding acquisition, none. All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (IRB) of the Catholic University of Korea (PC22ZISI0086, 6 May 2022). Informed Consent Statement Patient consent was waived because all data were fully anonymized and de-identified by HIRA prior to the analysis. Data Availability Statement The raw data supporting the conclusions of this article will be made available by the authors on request. Conflicts of Interest The authors declare no conflicts of interest. References Mancini, T.; Casanueva, F.F.; Giustina, A. Hyperprolactinemia and prolactinomas. Endocrinol. Metab. Clin. N. Am. 2008, 37, 67–99. [] [ CrossRef] [ PubMed] Chahal, J.; Schlechte, J. Hyperprolactinemia. Pituitary 2008, 11, 141–146. [] [ CrossRef] [ PubMed] Halbreich, U.; Kinon, B.J.; Gilmore, J.A.; Kahn, L.S. Elevated prolactin levels in patients with schizophrenia: Mechanisms and related adverse effects. Psychoneuroendocrinology 2003, 28, 53–67. [] [ CrossRef] Capozzi, A.; Scambia, G.; Pontecorvi, A.; Lello, S. Hyperprolactinemia: Pathophysiology and therapeutic approach. Gynecol. Endocrinol. 2015, 31, 506–510. 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( b) Peak age of prevalence. Figure 3. Annual incidence case (orange) and incidence rate (blue) of hyperprolactinemia, 2009–2021. Figure 3. Annual incidence case (orange) and incidence rate (blue) of hyperprolactinemia, 2009–2021. Figure 4. ( a) Annual incidence rate for hyperprolactinemia by age group, 2009–2021. ( b) Cumulative incidence rate for hyperprolactinemia by age group, 2009–2021. Figure 4. ( a) Annual incidence rate for hyperprolactinemia by age group, 2009–2021. ( b) Cumulative incidence rate for hyperprolactinemia by age group, 2009–2021. Figure 5. Annual trends in the prescription of dopamine agonists (bromocriptine vs. cabergoline), 2009–2021. Figure 5. Annual trends in the prescription of dopamine agonists (bromocriptine vs. cabergoline), 2009–2021. Table 1. The crude prevalence rate, 2007–2021. Table 1. The crude prevalence rate, 2007–2021. 10~14 Years 15~19 Years 20~24 Years 25~29 Years 30~34 Years 35~39 Years 40~44 Years 45~49 Years 50~54 Years 55~59 Years Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population Case (Per 100,000) Population 2007 21 1 1,653,961 216 14 1,539,263 802 49 1,634,016 2065 105 1,957,996 2877 142 2,030,319 2023 90 2,253,058 1315 65 2,029,760 1020 48 2,134,888 446 27 1,640,953 110 9 1,209,075 2008 16 1 1,631,851 218 14 1,579,662 684 44 1,548,865 1995 101 1,973,735 2514 128 1,958,242 1984 88 2,246,169 1353 65 2,068,594 1110 51 2,156,501 445 26 1,738,721 128 10 1,250,799 2009 28 2 1,600,103 171 11 1,614,483 555 37 1,505,980 1645 85 1,938,744 2303 121 1,905,463 1934 87 2,220,229 1298 61 2,129,227 994 46 2,146,753 538 29 1,854,222 135 10 1,299,880 2010 13 1 1,567,231 199 12 1,648,470 538 36 1,489,000 1431 77 1,847,775 2149 113 1,908,572 1764 81 2,171,434 1297 60 2,165,754 994 47 2,115,794 573 29 1,958,329 179 13 1,398,967 2011 19 1 1,524,601 211 13 1,662,199 561 37 1,499,241 1340 77 1,746,765 2165 112 1,936,026 1691 81 2,096,955 1333 60 2,213,982 930 45 2,060,008 542 26 2,055,638 174 11 1,527,939 2012 17 1 1,452,667 236 14 1,649,308 707 46 1,538,723 1245 76 1,642,257 2107 107 1,962,313 1658 82 2,027,689 1320 59 2,248,909 1005 50 2,026,583 596 28 2,128,758 189 12 1,631,898 2013 26 2 1,375,262 261 16 1,627,421 709 45 1,578,376 1242 80 1,558,881 2081 105 1,978,039 1627 83 1,955,181 1385 62 2,240,479 1021 49 2,063,381 587 27 2,148,726 213 12 1,728,364 2014 34 3 1,307,481 284 18 1,596,576 815 51 1,613,095 1297 85 1,517,074 2102 108 1,943,364 1668 88 1,902,830 1414 64 2,213,903 997 47 2,122,496 594 28 2,137,493 249 14 1,842,154 2015 18 1 1,226,236 326 21 1,564,661 915 56 1,647,071 1459 97 1,499,816 2323 125 1,853,636 1976 104 1,906,997 1513 70 2,165,573 1170 54 2,158,416 600 28 2,106,345 264 14 1,945,185 2016 35 3 1,153,484 407 27 1,522,737 1,112 67 1,660,504 1680 111 1,508,716 2498 142 1,753,196 2248 116 1,935,025 1666 80 2,091,518 1394 63 2,206,120 656 32 2,050,850 290 14 2,041,486 2017 28 2 1,130,276 478 33 1,451,429 1,324 80 1,647,663 1864 120 1,546,920 2557 155 1,648,854 2502 128 1,961,526 1871 93 2,022,653 1616 72 2,241,024 736 36 2,017,624 331 16 2,114,005 2018 34 3 1,127,731 504 37 1,374,316 1,529 94 1,625,826 2193 138 1,585,850 2529 162 1,565,828 2651 134 1,977,219 1873 96 1,950,445 1700 76 2,232,481 866 42 2,054,134 338 16 2,134,289 2019 37 3 1,117,638 488 37 1,306,357 1,512 95 1,594,617 2285 141 1,619,563 2512 165 1,523,573 2501 129 1,941,960 1953 103 1,897,420 1730 78 2,204,698 948 45 2,111,877 376 18 2,122,997 2020 49 4 1,122,008 570 47 1,225,107 1,785 114 1,562,539 2584 156 1,652,449 2604 173 1,506,688 2348 127 1,852,902 1941 102 1,901,418 1695 79 2,156,068 951 44 2,147,074 321 15 2,092,130 2021 42 4 1,139,096 523 45 1,152,557 1,528 100 1,520,709 2096 126 1,665,042 2228 147 1,515,957 2036 116 1,753,790 1716 89 1,929,716 1409 68 2,082,435 824 38 2,194,596 270 13 2,037,429 total 417 32 20,129,626 5092 359 22,514,546 15,076 951 23,666,225 26,421 1575 25,261,583 35,549 2005 26,990,070 30,611 1534 30,202,964 23,248 1129 31,269,351 18,785 873 32,107,646 9902 485 30,345,340 3567 197 26,376,597 Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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Journal of Clinical Medicine. 2026; 15(12):4411. https://doi.org/10.3390/jcm15124411 Chicago/Turabian Style Yoon, Hyonjee, Kyung-Hee Chae, Hyunkyung Kim, Youngseo Jang, Chaewon Kim, Sukil Kim, and Jeong Namkung. 2026. "Incidence, Treatment Patterns, and Associated Clinical Conditions of Hyperprolactinemia Identified via Nationwide Claims Data in Korea: A 13-Year Population-Based Study" Journal of Clinical Medicine 15, no. 12: 4411. https://doi.org/10.3390/jcm15124411 APA Style Yoon, H., Chae, K.-H., Kim, H., Jang, Y., Kim, C., Kim, S., & Namkung, J. (2026). Incidence, Treatment Patterns, and Associated Clinical Conditions of Hyperprolactinemia Identified via Nationwide Claims Data in Korea: A 13-Year Population-Based Study. Journal of Clinical Medicine, 15(12), 4411. https://doi.org/10.3390/jcm15124411 Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details . 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