Increased breast cancer risk in in vitro fertilisation treated women with a multiple pregnancy: A new hypothesis based on historical in vitro fertilisation treatment data

Transiently increased risk of breast cancer after childbirth: implications for fertility treatments and surrogacy

Whereas longstanding dogma has purported that pregnancies protect women from breast cancer, a recent meta-analysis now mandates reconsideration since it reported an actual higher breast cancer risk for more than two decades after childbirth before the relative risk turns negative. Moreover, the risk of breast cancer appears higher for women having their first birth at an older age and with a family history and it is not reduced by breastfeeding. The process of obtaining informed consent for all fertility treatments, therefore, must make patients aware of the facts that every pregnancy, to a small degree, will increase the short-term breast cancer risk. This observation may be even more relevant in cases of surrogacy where women agree to conceive without deriving benefits of offspring from assuming the risk, thus creating a substantially different risk-benefit ratio. Consequently, it appears prudent for professional societies in the field to update recommendations regarding consent information for all fertility treatments but especially for treatments involving surrogacy.

State of the evidence 2017: an update on the connection between breast cancer and the environment

BACKGROUND

In this review, we examine the continually expanding and increasingly compelling data linking radiation and various chemicals in our environment to the current high incidence of breast cancer. Singly and in combination, these toxicants may have contributed significantly to the increasing rates of breast cancer observed over the past several decades. Exposures early in development from gestation through adolescence and early adulthood are particularly of concern as they re-shape the program of genetic, epigenetic and physiological processes in the developing mammary system, leading to an increased risk for developing breast cancer. In the 8 years since we last published a comprehensive review of the relevant literature, hundreds of new papers have appeared supporting this link, and in this update, the evidence on this topic is more extensive and of better quality than that previously available.

CONCLUSION

Increasing evidence from epidemiological studies, as well as a better understanding of mechanisms linking toxicants with development of breast cancer, all reinforce the conclusion that exposures to these substances - many of which are found in common, everyday products and byproducts - may lead to increased risk of developing breast cancer. Moving forward, attention to methodological limitations, especially in relevant epidemiological and animal models, will need to be addressed to allow clearer and more direct connections to be evaluated.

[Does fertility treatment increase the risk of breast cancer? Current knowledge and meta-analysis]

OBJECTIVE

The objective of this review was to assess the level of risk of breast cancer for women exposed to ovulation-inducing therapy (OIT).

METHODS

The 25 selected studies were extracted from the PUBMED database from January 2000 until March 2016 with the following key-words: "fertility agents", "infertility treatments", "clomiphene citrate", "buserelin", "ovarian stimulation", "assisted reproductive technology" and "breast cancer". Our meta-analysis was performed using Review Manager software, Cochrane Collaboration, 2014. The results were calculated by type of OIT, as well as globally.

RESULTS

The analysis of these published epidemiological studies confirms that exposition to OIT is not a breast cancer risk factor, but the results are contradictory. Two studies have shown a significantly increased risk of breast cancer in a population of infertile women, while two others have found a significant decrease of this risk. The twenty others did not show any impact of IOT over this risk. Our meta-analysis of 20 selected studies has not identified a significant association between exposition to OIT and breast cancer risk (relative risk=0,96; IC 95: (0,81-1,14) for cohort studies and odds ratio=0,94; IC 95% (0,81-1,10) for case-control studies).

CONCLUSION

Exposition to OIT is not an identified risk factor for breast cancer. A message reassuring about a possible risk of OIT-related breast cancer should be given to these women. Exposition to OIT is therefore not an indication of increased breast surveillance.

The Association Between Body Size and Breast Cancer in Han Women in Northern and Eastern China

INTRODUCTION

Although obesity has been reported worldwide as a risk factor for breast cancer, there are still some inconsistencies regarding the association between obesity and breast cancer. Body mass index (BMI) is used most to assess the extent of obesity; however, the association of other body size characteristics, such as waist and hip circumference, with susceptibility to breast cancer in Chinese Han women needs to be better assessed.

PATIENTS AND METHODS

Female Chinese Han patients (N = 2,800) were recruited from 21 hospitals in northern and eastern China from April 2012 to April 2013 for a case-control study. The significant differences of factors related to body size between the breast-cancer case and control groups were determined by Student's t test and chi-square tests.

RESULTS

Premenopausal women with breast cancer had higher BMI and larger waist and hip circumferences (p = 2 × 10-4, <1 × 10-6, and 2 × 10-5, respectively). However, these body-size factors were not associated with postmenopausal breast cancer (p = .45, 0.32, and 0.12, respectively). BMI between 28 and 30 kg/m2 or greater than 32 kg/m2 was related to breast cancer incidence in the overall study population and in premenopausal women but not in the postmenopausal group.

CONCLUSION

Obesity is significantly associated with breast cancer in Chinese Han premenopausal women but not in postmenopausal women. Thus, it is important to realize that weight control, as well as avoiding abdominal obesity, should be considered as one of the most effective methods of reducing breast cancer risk.

IMPLICATIONS FOR PRACTICE

To better understand the characteristics and risk factors for breast cancer in Han women in northern and eastern China, a case-control study of 2,800 Chinese Han women was conducted. Obesity was significantly associated with breast cancer in Chinese Han premenopausal women but not in postmenopausal women. Consequently, controlling body weight and avoiding abdominal obesity should be considered as one of the most effective methods of reducing breast cancer susceptibility. However, the diversity between this study's finding among Chinese Han women and other data previously reported among European and American populations still needs further investigation.

Selecting the embryo with the highest implantation potential using a data mining based prediction model

BACKGROUND

Embryo selection has been based on developmental and morphological characteristics. However, the presence of an important intra-and inter-observer variability of standard scoring system (SSS) has been reported. A computer-assisted scoring system (CASS) has the potential to overcome most of these disadvantages associated with the SSS. The aims of this study were to construct a prediction model, with data mining approaches, and compare the predictive performance of models in SSS and CASS and to evaluate whether using the prediction model would impact the selection of the embryo for transfer.

METHODS

A total of 871 single transferred embryos between 2008 and 2013 were included and evaluated with two scoring systems: SSS and CASS. Prediction models were developed using multivariable logistic regression (LR) and multivariate adaptive regression splines (MARS). The prediction models were externally validated with a test set of 109 single transfers between January and June 2014. Area under the curve (AUC) in training data and validation data was compared to determine the utility of the models.

RESULTS

In SSS models, the AUC declined significantly from training data to validation data (p < 0.05). No significant difference was detected in CASS derived models. Two final prediction models derived from CASS were obtained using LR and MARS, which showed moderate discriminative capacity (c-statistic 0.64 and 0.69 respectively) on validation data.

CONCLUSIONS

The study showed that the introduction of CASS improved the generalizability of the prediction models, and the combination of computer-assisted scoring system with data mining based predictive modeling is a promising approach to improve the selection of embryo with the highest implantation potential.