## 4 Discussion  
Predicting the risk of diseases such as PCa is important for both patients and clinicians. Patients can access risk measures to understand their health status and decide whether to visit the hospital. Ultimately, risk calculators are expected to help patients to access additional information. Therefore, this study aimed to develop a risk calculator that can assist patients in acquiring knowledge of PCa risk measures before they become serious, based on their environmental conditions, regular lives, and personal histories.  
Several models have been developed to measure PCa risk [8; 18; 19; 20]. [PERSON] et al. developed risk calculators based on prostate volume and digital rectal examinations [19]. [PERSON] et al. developed a risk calculator to predict low- and high-grade PCa using biopsy data [8]. Many mobile applications function as PCa risk calculators [18; 21; 22; 23; 24; 25; 26]. These apps measure risk scores based on invasive laboratory results, such as PSA and Gleason scores. [PERSON] et al. compared several risk calculators to achieve a better performance [27]. [PERSON] et al. compared MRI-based risk calculators for PCa [28]. Research on lifestyle risk factors was also conducted. [PERSON] et al. developed a prostate cancer risk calculator with additional inputs, such as glucose levels, consumption of meat and alcohol, and family history of cancer [29]. They used lifestyle data and a glucose level test, which is an invasive test.  
Although previous studies aimed to predict the risk level of clinical outcomes, these risk calculators used clinical laboratory results and imaging data obtained from medical tests, highlighting the importance of predicting PCa risk for patients and clinicians. However, accessing the results from such risk calculators is difficult unless patients can access the clinical test results as inputs.  
There were other studies that were conducted to determine the effects of environmental variables on PCa [30; 31; 32; 33; 34; 35; 36]. [PERSON] et al. studied the association between environmental factors and PCa stage [31]. [PERSON] et al. revealed that air pollutants are risk factors of PCa [32]. [PERSON] et al. found that exposure to arsenic and cadmium increased the mortality risk of PCa [30]. These studies have clearly demonstrated that environmental factors affect the risk of developing PCa. The accuracy of risk calculator predictions, even after including environmental factors, can be established by developing novel approaches.  
Despite the significant results, this study has some limitations. First, laboratory test results were not used to develop the risk calculator, which explains the likelihood of 5-year PCa-free survival. However, when individuals discover a high likelihood using a risk calculator, they can decide to visit the hospital and undergo further tests to make appropriate treatment decisions. Second, this study used only Korean data, potentially limiting its application and generalization to other countries. As racial differences may exist [37; 38; 39; 40; 41], future studies should use data from diverse countries. Third, the risk calculator has a low C-index value. In future studies, it may be useful to refer to the previous study by [PERSON] et al. [29] to improve the performance of the risk calculator, and it may also be useful to use family history data for additional input.