Predicting Sperm DNA Fragmentation Markers using Basic Semen Parameters and Age: A Preliminary Data Analysis

Sperm DNA fragmentation is a critical factor in male infertility assessment, often evaluated using tests such as the Sperm Chromatin Structure Assay (SCSA) and the TUNEL assay. Despite their diagnostic importance, these tests are expensive, resource-intensive, and not universally accessible, creating a need for alternative, cost-effective approaches. This study uniquely investigates the feasibility of predicting DNA fragmentation markers using only basic semen parameters and male age. Utilizing a dataset of6,000 patients, we applied a range of regression models, from linear models to tree-based methods and neural network approaches, to predict the continuous values of TUNEL and SCSA. Feature importance analysis of the best-performing model identified the interaction between immotile sperm and male age as the most significant predictor. While the predictive accuracy of these models requires further refinement, this novel approach demonstrates the potential to reduce reliance on expensive testing methods. Our findings lay the foundations for developing accessible risk models, advancing cost-effective diagnostics and clinical decision-making in male infertility assessment.