Breast cancer cases in the United States could increase by 50% by 2030, according to new analysis conducted by the National Cancer Institute (NCI). Philip S. Rosenberg, PhD, a senior investigator at the NCI, announced the findings Monday at the American Assoication for Cancer Research annual meeting.

The total number of new breast cancer cases in the U.S. in 2030 is expected to be 441,000, a substantial jump from the 283,000 new cases found in 2011. These numbers include both invasive cancers and non-invasive cancers such as ductal carcinoma in-situ (DCIS).

"Managing this clinical burden will present a huge challenge," Rosenberg said in a press release. "The one silver lining is that we expect fewer estrogen receptor (ER)-negative tumors, which include the most difficult-to-treat HER2-positive and triple-negative subtypes."

The analysis found that much of the increase is expected to be due to new cases in women 70 years and older. The proportion of new cases among women ages 70 to 84 is expected to be 35% in 2030, up from 24% in 2011. On the other hand, the proportion of new cases among women ages 50 to 69 is expected to be 44% in 2030, down from 55% in 2011.

In addition, the NCI study suggests the proportion of ER-negative cancers will drop to 9% of all cases, down from 17% in 2011. The proportion of ER-positive cancers, which respond to endocrine therapy, is a little more complicated. The proportion of ER-positive invasive cancers is expected to stay roughly the same, but the proportion of ER-positive non-invasive cancers is expected to rise to 29% in 2030, up from 19% in 2011.

“In sum, our results suggest that although breast cancer overall is going to increase, different subtypes of breast cancer are moving in different directions and on different trajectories,” Rosenberg said in a press release. “These distinct patterns within the overall breast cancer picture highlight key research opportunities that could inform smarter screening and kinder, gentler, and more effective treatment.”

The NCI used existing data, population projections, mathematical models and estimates about patient behavior to reach its conclusions.