Reducing Unnecessary Oophorectomies for Benign Ovarian Neoplasms in Pediatric Patients.
Document Type
Article
Publication Date
10-3-2023
Identifier
DOI: 10.1001/jama.2023.17183
Abstract
IMPORTANCE: Although most ovarian masses in children and adolescents are benign, many are managed with oophorectomy, which may be unnecessary and can have lifelong negative effects on health.
OBJECTIVE: To evaluate the ability of a consensus-based preoperative risk stratification algorithm to discriminate between benign and malignant ovarian pathology and decrease unnecessary oophorectomies.
DESIGN, SETTING, AND PARTICIPANTS: Pre/post interventional study of a risk stratification algorithm in patients aged 6 to 21 years undergoing surgery for an ovarian mass in an inpatient setting in 11 children's hospitals in the United States between August 2018 and January 2021, with 1-year follow-up.
INTERVENTION: Implementation of a consensus-based, preoperative risk stratification algorithm with 6 months of preintervention assessment, 6 months of intervention adoption, and 18 months of intervention. The intervention adoption cohort was excluded from statistical comparisons.
MAIN OUTCOMES AND MEASURES: Unnecessary oophorectomies, defined as oophorectomy for a benign ovarian neoplasm based on final pathology or mass resolution.
RESULTS: A total of 519 patients with a median age of 15.1 (IQR, 13.0-16.8) years were included in 3 phases: 96 in the preintervention phase (median age, 15.4 [IQR, 13.4-17.2] years; 11.5% non-Hispanic Black; 68.8% non-Hispanic White); 105 in the adoption phase; and 318 in the intervention phase (median age, 15.0 [IQR, 12.9-16.6)] years; 13.8% non-Hispanic Black; 53.5% non-Hispanic White). Benign disease was present in 93 (96.9%) in the preintervention cohort and 298 (93.7%) in the intervention cohort. The percentage of unnecessary oophorectomies decreased from 16.1% (15/93) preintervention to 8.4% (25/298) during the intervention (absolute reduction, 7.7% [95% CI, 0.4%-15.9%]; P = .03). Algorithm test performance for identifying benign lesions in the intervention cohort resulted in a sensitivity of 91.6% (95% CI, 88.5%-94.8%), a specificity of 90.0% (95% CI, 76.9%-100%), a positive predictive value of 99.3% (95% CI, 98.3%-100%), and a negative predictive value of 41.9% (95% CI, 27.1%-56.6%). The proportion of misclassification in the intervention phase (malignant disease treated with ovary-sparing surgery) was 0.7%. Algorithm adherence during the intervention phase was 95.0%, with fidelity of 81.8%.
CONCLUSIONS AND RELEVANCE: 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. Adoption of this algorithm might prevent unnecessary oophorectomy during adolescence and its lifelong consequences. Further studies are needed to determine barriers to algorithm adherence.
Journal Title
JAMA : the journal of the American Medical Association
Volume
330
Issue
13
First Page
1247
Last Page
1254
MeSH Keywords
Adolescent; Child; Female; Humans; Ovarian Neoplasms; Ovariectomy; Predictive Value of Tests; Retrospective Studies; Unnecessary Procedures; Risk Assessment; Algorithms; Young Adult; Hospitalization; Black or African American; White; Preoperative Care
Keywords
Ovarian Neoplasms; Ovariectomy; Predictive Value of Tests; Retrospective Studies; Unnecessary Procedures; Risk Assessment; Algorithms; Hospitalization; Black or African American; White; Preoperative Care
Recommended Citation
Minneci PC, Bergus KC, Lutz C, et al. Reducing Unnecessary Oophorectomies for Benign Ovarian Neoplasms in Pediatric Patients. JAMA. 2023;330(13):1247-1254. doi:10.1001/jama.2023.17183
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