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Central precocious puberty in girls: an evidence-based diagnosis tree to predict central nervous system abnormalities
Martin Chalumeau1, Wassim Chemaitilly, Christine Trivin
1INSERM U149, Epidemiological Research Unit on Women's and Children's Health, Paris, France.
Insights
Predictors like early puberty onset and high estradiol levels can help identify girls with central precocious puberty (CPP) who may have central nervous system (CNS) abnormalities, guiding the need for brain imaging.
Area of Science:
- Pediatric Endocrinology
- Neuroendocrinology
Background:
- Central precocious puberty (CPP) involves early onset of puberty due to central nervous system (CNS) activation.
- Identifying CNS abnormalities in girls with CPP is crucial for appropriate diagnosis and management.
Purpose of the Study:
- To identify predictors of CNS abnormalities in girls diagnosed with CPP.
- To develop a diagnostic tool for selecting girls with CPP who require neuroimaging.
Main Methods:
- Retrospective cohort study of girls under 8 years with CPP.
- Evaluation of existing guidelines (Lawson Wilkins Pediatric Endocrine Society) and assessment of clinical, radiological, and biological predictors.
- Development and validation of a diagnostic tree for CNS abnormalities.
Main Results:
- Age at puberty onset <6 years, lack of pubic hair, and estradiol >110 pmol/L were independent predictors of CNS abnormalities.
- The developed diagnostic tree demonstrated 100% sensitivity in detecting CNS abnormalities in the validation cohort.
- Existing guidelines potentially missed 2 out of 11 girls with CNS abnormalities requiring imaging.
Conclusions:
- Simple predictors including age and estradiol levels can aid in identifying girls with CPP who need cerebral imaging.
- Further testing of this diagnostic approach in diverse populations is warranted.
Objective:
To identify predictors of central precocious puberty (CPP) that reveal central nervous system (CNS) abnormalities in girls with CPP.
Methods:
A retrospective cohort study was conducted of all girls younger than 8 years with breast development related to CPP, seen between 1982 and 2000, in a university pediatric hospital in Paris, France. For a pilot population (186 idiopathic, 11 revealing CNS abnormalities), the accuracy of the Lawson Wilkins Pediatric Endocrine Society recommendations were evaluated. Potential clinical, radiological, and biological predictors of CNS abnormalities were assessed by univariate and multivariate analyses. A diagnosis tree aiming for 100% sensitivity for the detection of CNS abnormalities was constructed and was tested on a validation population (39 idiopathic, 3 revealing CNS abnormalities).
Results:
Applying the Lawson Wilkins Pediatric Endocrine Society recommendations, 2 of 11 girls with CPP that revealed CNS abnormalities would not have been considered to require brain imaging. Independent predictors of CNS abnormalities were age at onset of puberty <6 years (adjusted odds ratio [AOR]: 6.7; 95% confidence interval [CI]: 1.5-29), lack of pubic hair at diagnosis (AOR: 7.7; 95% CI: 1.8-33), and estradiol >110 pmol/L (AOR: 4.1, 95% CI: 1.0-17). The diagnosis tree that was constructed on the basis of these predictors had 100% sensitivity and 56% specificity for the validation population.
Conclusion:
The identification of girls who have CPP and require cerebral imaging seems possible on the basis of validated, simple, and reproducible predictors: age and estradiol. However, this process needs to be tested on other populations.