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Algorithm Cuts Unnecessary Oophorectomy in Children, Teens

Medically reviewed by Drugs.com.

By Lori Solomon HealthDay Reporter

TUESDAY, Oct. 24, 2023 -- Adoption of a preoperative risk stratification algorithm might prevent unnecessary oophorectomy in pediatric and adolescent patients with benign ovarian disease, according to a study published in the Oct. 3 issue of the Journal of the American Medical Association.

Peter C. Minneci, M.D., from Nationwide Children’s Hospital in Columbus, Ohio, and colleagues assessed whether implementation of a consensus-based, preoperative risk stratification algorithm reduces unnecessary oophorectomies in 519 pediatric and adolescent patients with benign ovarian disease. The analysis included patients (aged 6 to 21 years) undergoing surgery for an ovarian mass in 11 U.S. children’s hospitals between August 2018 and January 2021.

The researchers found that benign disease was present in 96.9 percent in the preintervention cohort and 93.7 percent in the intervention cohort. There was an absolute reduction of 7.7 percent in the percentage of unnecessary oophorectomies (decreasing from 16.1 percent preintervention to 8.4 percent during the intervention). For identifying benign lesions, the algorithm test performance in the intervention cohort had a sensitivity of 91.6 percent, a specificity of 90.0 percent, a positive predictive value of 99.3 percent, and a negative predictive value of 41.9 percent. In the intervention phase, the proportion of misclassification (malignant disease treated with ovary-sparing surgery) was 0.7 percent.

“Unnecessary oophorectomies decreased with use of a preoperative risk stratification algorithm to identify lesions with a high likelihood of benign pathology that are appropriate for ovary-sparing surgery,” the authors write.

Several authors disclosed ties to industry.

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Disclaimer: Statistical data in medical articles provide general trends and do not pertain to individuals. Individual factors can vary greatly. Always seek personalized medical advice for individual healthcare decisions.

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