The preventive effect of metformin on progression of benign prostate hyperplasia: A nationwide population-based cohort study in Korea.
Yehee HongSanghun LeeSungho WonPublished in: PloS one (2019)
Metformin, a first-line treatment for type 2 diabetes mellitus (T2DM), has recently been recognized for its pleotropic anti-proliferative, anti-cancer, and anti-aging effects. Contrary to the studies characterizing metformin effects in prostate cancer, little is known about these effects in BPH progression. With the Sample Cohort DB data during 2007 and 2017 from the Health Insurance Review and Assessment Service (HIRA) in South Korea, we investigated the preventative effect of metformin on BPH progression. The study population consisted of 211,648 BPH naïve patients that were diagnosed with BPH in 2009 and a follow-up occurrence of prostatectomy until 2017 that was defined as progression of BPH. These patients were divided into three treatment groups: without T2DM, T2DM without metformin, and T2DM with metformin. The hazard ratio in the T2DM with metformin group was 0.86 for prostatectomy compared to the group without T2DM (CI = 0.77-0.96, P value = 0.007) after adjusting for confounding factors such as age, comorbidity, residential area, level of hospital, and category of BPH medications. The T2DM with high-dose metformin group had a significantly lower risk of prostatectomy with hazard ratio of 0.76 (CI = 0.62-0.92, P value = 0.005) in stratified analysis. Our results suggest that metformin may improve BPH progression based on the reduced risk of prostatectomy, although T2DM effects on BPH were unclear. Future observational studies and prospective trials are needed to confirm the effects of metformin on BPH progression.
Keyphrases
- benign prostatic hyperplasia
- lower urinary tract symptoms
- prostate cancer
- health insurance
- end stage renal disease
- glycemic control
- high dose
- newly diagnosed
- chronic kidney disease
- robot assisted
- healthcare
- ejection fraction
- type diabetes
- cardiovascular disease
- mental health
- metabolic syndrome
- risk assessment
- high resolution
- adipose tissue
- emergency department
- machine learning
- stem cell transplantation
- big data
- high speed
- atomic force microscopy
- artificial intelligence