In addition to the genetic and lifestyle factors examined in the study, several other genetic and environmental factors may interact to influence prostate cancer prognosis. For instance, variations in genes related to inflammation, hormone regulation, and DNA repair mechanisms can impact disease progression and treatment response. Environmental factors such as exposure to carcinogens, pollution, and dietary components may also play a role in shaping prostate cancer outcomes.
To incorporate these additional factors into risk prediction models, researchers can conduct comprehensive genome-wide association studies to identify novel genetic variants associated with prostate cancer risk and aggressiveness. Integrating data on environmental exposures, such as occupational hazards or air quality, into risk assessment tools can provide a more holistic view of individual risk profiles.
Furthermore, leveraging advanced computational techniques like machine learning and artificial intelligence can help analyze complex interactions between genetic and environmental factors to improve the accuracy of risk prediction models. By expanding the scope of genetic and environmental factors considered in risk assessment, healthcare providers can offer more personalized and precise recommendations for prostate cancer screening, treatment, and lifestyle interventions.