Research Brief

New data model reveals novel infertility treatment recommendations

Flat illustration depicting communication between doctor and patient regarding reproductive health.
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A novel data analysis model developed in part by University of Minnesota faculty is shedding more light on potential treatment for women facing infertility issues, offering possibilities for the future of health recommendation tools.

In a forthcoming study in the Journal of the American Statistical Association, Carlson School of Management Assistant Professor Xuan Bi and his colleagues examine existing data on 1,376 women with polycystic ovary syndrome (PCOS). The condition is one of the most common causes of infertility, but it is not well understood. Why? The dataset shrinks.

In PCOS studies, three stages — ovulation, pregnancy and live birth — are usually analyzed separately. However, fewer women progress to each stage and only a small number reach live birth. Despite the challenge, the researchers developed a series of algorithms and revealed effects existing across all three stages.

“Our model bridges the three stages to look at the whole pregnancy process to see how different factors, like treatment or alcohol use, may affect the chance of a live birth,” said Bi. “The analysis shows how doctors could better identify a treatment at the start of the ovulation stage based on those factors.”

The model highlighted novel infertility treatment recommendations that improved the chances of a live birth. For example, clomiphene citrate — also known as Clomid — was more effective for older women. The team also confirmed existing clinical research, such as the negative impact of smoking on pregnancy rates. Bi says while the treatment recommendations should go through more rigorous clinical trials and FDA approval, the findings are promising.

Researchers believe the new method could be applied to other clinical research of sequential processes that face similar diminishing data issues. Bi says the model could eventually be developed into a medical artificial intelligence tool used by doctors as a second opinion.

“This could be a step toward a potential software in a doctor’s office, where a patient could enter risk factors and other information to help augment a doctor’s decision for treatment,” said Bi.

Bi’s collaborators on the paper included Assistant Professor Long Feng at the City University of Hong Kong, Assistant Professor Cai Li at the St. Jude Children’s Research Hospital, and Professor Heping Zhang of the Yale School of Public Health.

About the Carlson School of Management
Located on the University of Minnesota Twin Cities campus, the Carlson School of Management exemplifies a commitment to excellence through a focus on experiential learning and international education, and by maintaining strong ties with the Minneapolis/Saint Paul business community. Through its undergraduate and graduate programs, the Carlson School offers access to world-renowned faculty members and an alumni network of 55,000 people. Learn more at carlsonschool.umn.edu.

Media Contacts

Rose Semenov

Carlson School of Management, Twin Cities

Andria Waclawski

University Public Relations
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