Pediatric Ovarian Teratoma Biomarker Data for 82 Patients

82 pediatric patients with ovarian teratomas were analyzed to evaluate diagnostic biomarkers. The dataset includes serum levels of alpha-fetoprotein and lactate dehydrogenase, along with Ki-67 proliferation indices, for 45 mature and 37 immature cases. Results from multivariate logistic regression and ROC analyses show a combined model achieved an AUC of 0.96 for distinguishing tumor types.

Use Cases

• Building a classifier to distinguish mature from immature ovarian teratomas based on biomarker levels.
• Analyzing the correlation between Ki-67 index and pathological tumor grade.
• Evaluating the prognostic value of combined biomarkers for recurrence-free survival prediction.

Strengths

• Includes data from 82 pediatric patients with histologically confirmed diagnoses.
• Provides specific biomarker thresholds identified as independent predictors (e.g., Ki-67 > 30%, AFP > 500 ng/mL).
• Reports a high diagnostic accuracy with an AUC of 0.96 for the combined biomarker model.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The dataset is small at 17.4 KB, which may limit the scope of machine learning applications.
• Data may reflect temporal and institutional bias inherent to the single retrospective study design.

Provenance

Source

figshare, authored by Xiazhe Li.

Collection Method

Retrospective analysis of pediatric patients with histologically confirmed ovarian teratomas.

Time Range

Study includes a median follow-up of 38 months; specific collection dates are not provided.

Freshness

Last updated 2026-04-21 04:10:56; freshness should be verified.