Use of Preoperative Algorithm may prevent unnecessary oophorectomy during adolescence: JAMA

In the intervention phase, the algorithm demonstrated impressive test performance. It exhibited a sensitivity of 91.6%, meaning it accurately identified benign lesions in over 91% of cases. The specificity was equally impressive at 90%, indicating it correctly identified malignant cases 90% of the time. Moreover, the algorithm boasted a positive predictive value of 99.3% and a negative predictive value of 41.9%.

Overall, the algorithm was able to significantly reduce misclassification during the intervention phase, with only 0.7% of malignant cases being treated with ovary-sparing surgery. Algorithm adherence during this phase was also high, at 95%, with a fidelity rate of 81.8%.

These findings are highly promising as the authors suggest that the adoption of this algorithm could prevent unnecessary oophorectomies during adolescence, sparing young patients from potential lifelong consequences. While the results are encouraging, further research will be needed to explore any barriers to algorithm adherence and ensure its widespread implementation.

Reference:

Minneci, P. C., Bergus, K. C., Lutz, C., Aldrink, J., Bence, C., Breech, L., Dillon, P. A., Downard, C., Fraser, J. D., Grabowski, J., Hirschl, R. B., Kabre, R., Lal, D. R., … Landman, M. (2023). Reducing Unnecessary Oophorectomies for Benign Ovarian Neoplasms in Pediatric Patients. In JAMA (Vol. 330, Issue 13, p. 1247). American Medical Association (AMA). https://doi.org/10.1001/jama.2023.17183