Predicting Fertility Treatment Success: Key Factors & Tools

Physicians use data-driven tools like SART’s national database and Shady Grove Fertility’s Richter Predictor to estimate fertility treatment success. These models incorporate factors such as age, hormone levels, and egg source, with SART analyzing over 320,000 U.S. ART cycles to predict live birth probabilities. Shady Grove’s model adds clinical metrics like antral follicle count for more personalized predictions.

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Key Takeaways

SART Patient Predictor: Live Birth Probability Based on National ART Data

The SART Patient Predictor uses national data from 320,000+ U.S. IVF cycles to estimate live birth chances by age, egg source, and medical history. It provides probabilities for one to three treatment cycles but cannot account for clinic-specific protocols or lab techniques.

Richter Predictor: Customized Fertility Success Estimates Using Hormone Levels and Follicle Count

Shady Grove Fertility’s Richter Predictor improves accuracy by integrating AMH, FSH, antral follicle count, and uterine/sperm health. This model predicts live birth rates and surplus embryo availability, leveraging 15,000+ cycles of clinic-specific data since 2009.

Age and Egg Source: Key Determinants in Fertility Treatment Outcomes

When using own eggs, live birth rates decline significantly with age. The Richter Predictor shows donor egg success rates are typically 30-50% higher than using a woman’s own eggs in women over 40, based on Shady Grove’s clinical experience.

ART vs. IUI: Treatment Success Rate Comparisons

ART (IVF) success rates are 4-5x higher than IUI for most patients. The Richter Predictor helps quantify this gap, showing ART achieves ~30-40% live birth rates per cycle versus 8-10% for IUI in similar patient profiles.

Clinic Experience: How 65,000+ Cycles Improve Prediction Accuracy

Shady Grove Fertility’s 65,000+ ART cycles since 1991 enable hyper-personalized protocols. Their research team continuously refines prediction models, allowing physicians to adjust treatment plans for maximum efficacy based on real-world patient outcomes.

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