Development and validation of a clinical prediction model for poor ovarian response in assisted reproductive technology - Takeaways - MDSpire

Development and validation of a clinical prediction model for poor ovarian response in assisted reproductive technology

  • By

  • Xin Xin

  • Zhaoxia Cheng

  • Ting Hu

  • Yi Guo

  • Nan Li

  • Junbo Zhao

  • Shuaishuai Guo

  • June 15, 2026

  • 0 min

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  • 1

    A predictive model for poor ovarian response (POR) in assisted reproductive technology (ART) was developed and validated using data from 1,789 patients.

  • 2

    The final model identified AMH, basal FSH, BMI, and antral follicle count as significant predictors of POR.

  • 3

    The model demonstrated high discriminatory ability and good calibration across training, internal validation, and test datasets.

  • 4

    A nomogram was created from the model to provide an intuitive tool for individualized risk prediction in ART.

  • 5

    This study addresses the need for a systematic prediction model for POR, incorporating a wide range of clinical and ovarian reserve markers.

Original Source(s)

Development and validation of a clinical prediction model for poor ovarian response in assisted reproductive technology

  • by Xin Xin, Zhaoxia Cheng, Ting Hu, Yi Guo, Nan Li, Junbo Zhao, Shuaishuai Guo

  • June 15, 2026

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