Estimating the risk of breast cancer in relation to the interval since last term pregnancy

P Cummings1, N S Weiss, B McKnight

  • 1Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, USA.

We review the analytical methods of studies that asked whether a term pregnancy transiently increases a woman's risk of breast cancer. These analyses must separate the possible influence of a recent pregnancy from that of two other correlated variables, attained age and age at last pregnancy. Most analyses have compared women of the same parity. To determine, however, whether the risk of breast cancer is different than it would have been had the last pregnancy never occurred, it is necessary to compare the risk of breast cancer over time among women of parity N+1 with women of parity N, which has been done in a few studies. To generate relative risk estimates that are independent of arbitrary coding decisions, we show that the analytical models must be more complex than those in published studies. We used these models to compare women of parity N and N+1 for breast cancer occurrence, using data from the U.S. Cancer and Steroid Hormone Study. For the first 6 years after delivery, first term pregnancy was associated with lower or unchanged risk of breast cancer, second pregnancy with higher risk, third pregnancy with lower risk, and fourth pregnancy with both lower and higher risk depending on age at delivery. Given the inconsistent findings between adjoining levels of parity and the wide confidence intervals around the estimates, we could not find clear evidence for or against the theory that term pregnancy is transiently associated with an increased risk of breast cancer.

Related Concept Videos

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Relative Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
Odds Ratio01:09

Odds Ratio

The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Hazard Rate01:11

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...