Clinical evidence of the effect of bisphosphonates on pregnancy and the infant.
Nikolaos ThomakosGeorgia NtaliParaskevi KouroutouLina MichalaPublished in: Hormone molecular biology and clinical investigation (2019)
Bisphosphonates (BPs) are potent inhibitors of osteoclast mediated bone resorption. These drugs are widely used in the management of osteoporosis and other diseases, characterized by high bone turnover. The effect of BPs on gestation and lactation, when they are used as therapeutic agents in premenopausal women, is yet unknown. We conducted a detailed literature review and identified the cases of BPs use in young women, as well as, the effects of this therapy on the gestation and the embryo. The published data, regarding the use of BPs in premenopausal women and their effects on the pregnancy outcome, are limited. However, we could identify the outcomes of 40 pregnant women, who had received BPs prior to or during pregnancy, that have been documented in the literature. All women had valid indications to receive BPs for serious bone metabolism conditions. We could not identify any prospective trials, which focus on pregnancy outcomes following after the in-utero exposure to BPs. In total, no serious adverse effects were reported. Problems related to the offspring, such as hypocalcemia and a tendency for low body weight (LBW), were self-resolving. In addition, no serious adverse outcomes were reported for women having completed pregnancy. Nevertheless, follow-up was limited for both outcomes suggesting the necessity of national and international registries.
Keyphrases
- pregnancy outcomes
- pregnant women
- bone mineral density
- postmenopausal women
- polycystic ovary syndrome
- breast cancer risk
- body weight
- preterm birth
- bone loss
- preterm infants
- systematic review
- cervical cancer screening
- stem cells
- gestational age
- randomized controlled trial
- body composition
- mesenchymal stem cells
- artificial intelligence
- case report
- electronic health record
- insulin resistance
- metabolic syndrome
- machine learning
- adipose tissue
- deep learning
- early breast cancer