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Arch Iran Med. 2024;27(2): 96-104.
doi: 10.34172/aim.2024.15
PMID: 38619033
PMCID: PMC11017260
Scopus ID: 85190592211
  Abstract View: 909
  PDF Download: 505

Original Article

A New Model Including AMH Cut-off Levels to Predict Post-treatment Ovarian Function in Early Breast Cancer: A Prospective Cohort Study

Ramesh Omranipour 1,2,3 ORCID logo, Fatemeh Ahmadi-Harchegani 4 ORCID logo, Azin Saberi 5 ORCID logo, Ashraf Moini 1,6,7 ORCID logo, Mostafa Shiri 8 ORCID logo, Amirmohsen Jalaeefar 2 ORCID logo, Arvin Arian 9 ORCID logo, Akram Seifollahi 10 ORCID logo, Mahshad Madani 11 ORCID logo, Bita Eslami 1* ORCID logo, Sadaf Alipour 1,5* ORCID logo

1 Breast Diseases Research Center (BDRC), Cancer Institute, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Oncologic Surgery, Cancer Institute, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
3 Cancer Control Research Center, Cancer Control Foundation, Iran University of Medical Sciences, Tehran, Iran
4 Department of Biostatistics, Faculty of Health, Tehran University of Medical Sciences, Tehran, Iran
5 Department of Surgery, Arash Women’s Hospital, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
6 Department of Infertility, Arash Women’s Hospital, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
7 Department of Endocrinology and Female Infertility at Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran
8 Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
9 Department of Radiology, Cancer Institute, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Tehran, Iran
10 Department of Pathology, Arash Women’s Hospital, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
11 Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
*Corresponding Authors: Bita Eslami, Email: dr.bes.96@gmail.com; Sadaf Alipour, Email: sadafalipour@yahoo.com

Abstract

Background: Breast cancer (BC) treatment decreases fertility capacity, but unnecessary fertility preservation procedures in women who would not be infertile after treatment would be a waste of time and resources and could cause the unwarranted exposure of cancer cells to exogenous sex hormones. It has been largely shown that post-treatment ovarian reserve is directly associated with pre-treatment anti-mullerian hormone levels (AMH0). A threshold for AMH0, or a model including AMH0 and patient characteristics that could distinguish the patients who will be infertile after treatments, still needs to be defined. Accordingly, this study was performed to specifically target this high-priority concern.

Methods: Women≤45 years old with newly diagnosed non-metastatic BC were entered in this multicenter prospective cohort study. AMH0 and two-year post-treatment AMH (AMH2) were measured, and hormonal patient features were recorded as well. Receiver operating characteristic (ROC) curve analysis, decision tree (DT), and random forest analyses were performed to find a cut-off point for AMH0 and define a model involving related features for the prediction of AMH2.

Results: The data from 84 patients were analyzed. ROC curve analysis revealed that AMH0>3 ng/mL (Area under the curve=0.69, 95% CI: 0.54‒0.84) was the best indicator for predicting AMH2≥0.7 (sensitivity=79%, specificity=60%). The best model detected by DT and random forest for predicting an AMH2>0.7 with a probability of 93% consisted of a combination of AMH0>3.3, menarche age<14, and age<31.

Conclusion: This combination model can be used to withhold fertility preservation procedures in BC patients. Performing larger studies is suggested to further test this model.


Cite this article as: Omranipour R, Ahmadi-Harchegani F, Saberi A, Moini A, Shiri M, Jalaeefar A, et al. A new model including AMH cut-off levels to predict post-treatment ovarian function in early breast cancer: a prospective cohort study. Arch Iran Med. 2024;27(2):96-104. doi: 10.34172/aim.2024.15
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Submitted: 06 Sep 2023
Accepted: 24 Dec 2023
ePublished: 01 Feb 2024
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