Development of a fertility risk calculator to predict individualized chance of ovarian failure after chemotherapy
| Autor: | Kelly S. Acharya, Esther H. Chung, Chaitanya R. Acharya, Benjamin S. Harris |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Adult
Oncology medicine.medical_specialty Pediatrics medicine.medical_treatment Primary ovarian insufficiency Reproductive medicine Primary Ovarian Insufficiency Risk Assessment law.invention Cancer Survivors law Neoplasms Surveys and Questionnaires Internal medicine Antineoplastic Combined Chemotherapy Protocols Fertility risk Genetics medicine Humans Ovarian Diseases Fertility preservation Precision Medicine Genetics (clinical) Oncofertility Chemotherapy Models Statistical business.industry Ovarian failure Fertility Preservation Obstetrics and Gynecology General Medicine United States Random forest Cross-Sectional Studies Reproductive Medicine Calculator Female business Infertility Female Developmental Biology |
| Zdroj: | J Assist Reprod Genet |
| ISSN: | 1573-7330 1058-0468 |
| Popis: | PURPOSE: To develop an innovative machine learning (ML) model that predicts personalized risk of primary ovarian insufficiency (POI) after chemotherapy for reproductive-aged women. Currently, individualized prediction of a patient’s risk of POI is challenging. METHODS: Authors of published studies examining POI after gonadotoxic therapy were contacted, and six authors shared their de-identified data (N = 435). A composite outcome for POI was determined for each patient and validated by 3 authors. The primary dataset was partitioned into training and test sets; random forest binary classifiers were trained, and mean prediction scores were computed. Institutional data collected from a cross-sectional survey of cancer survivors (N = 117) was used as another independent validation set. RESULTS: Our model predicted individualized risk of POI with an accuracy of 88% (area under the ROC 0.87, 95% CI: 0.77–0.96; p |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink