What led to a decline in US breast cancer mortality between 1975 and 2019?

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In a recent study published in JAMA Network Open, researchers simulated breast cancer mortality rates among United States (US) women aged 30-79 years between 1975 and 2019 using simulation models developed by the Cancer Intervention and Surveillance Modeling Network (CISNET).

Study: Analysis of Breast Cancer Mortality in the US—1975 to 2019. Image Credit: Gorodenkoff/Shutterstock.comStudy: Analysis of Breast Cancer Mortality in the US—1975 to 2019. Image Credit: Gorodenkoff/Shutterstock.com


Between 1975 and 2019, age-adjusted breast cancer mortality rates in the US declined from 48 to 27 per 100,000 women. Since 2000, outcomes for metastatic breast cancer patients improved further. 

ClinicalTrials.gov registered more than 2,000 phase III clinical trials for breast cancer during this duration, and the US Food and Drug Administration (FDA) approved 30 breast cancer drugs between 2010 and 2020, of which four were for stage I-III breast cancer treatments and 26 for metastatic cancer.

While advancements in breast cancer treatment and screening likely led to the observed decline in US breast cancer mortality rates, its consequences remain unquantified.

In particular, the association of changes in metastatic breast cancer treatment with improved breast cancer mortality remains unclear.

About the study

In the present study, researchers used the updated CISNET models to estimate the associations of stage I-III and metastatic breast cancer treatments and screening mammography with age-adjusted breast cancer mortality rates in the US between 1975 and 2019.

They used four breast cancer simulation models, each with a unique approach, formulated through analytic framework, microsimulation, or both. For instance, Model S used tumor size and progression of cancer stages to model cancer detection.

It also applied treatment benefits to baseline survival curves based on estrogen receptor (ER)/ERBB2 status, stage, and age at detection.

In addition, these models simulated metastatic recurrence and post-metastatic survival, separately focusing on ER/ERBB2 statuses, ER+/ERBB2+, ER+/ ERBB2−, ER−/ERBB2−, and ER−/ERBB2+.

They assessed measures of breast cancer–specific median survival from diagnosis to metastatic recurrence and metastatic recurrence to death.

These models used the distribution of post-metastasis baseline survival curves stratified by age and ER/ERBB2 status to evaluate the treatment of metastatic breast cancer.

They used data from 82,252 breast cancer patients, of which 7,740 had metastatic recurrence, retrieved from the National Comprehensive Cancer Network Outcomes (NCCNO) database.

The model's reported mortality reduction was the difference between the estimated age-adjusted mortality rate under an intervention scenario and their absence, divided by the mortality rate in the absence of any intervention.

These estimates were means of the four models, weighted equally. There were eight intervention scenarios, and models simulated patients with de novo stage IV and recurrent metastatic disease could receive metastatic treatments.

They reported the relative proportion of the mortality reduction attributed to each intervention; this approach was consistent with prior work and estimated the relative proportion of the mortality reduction attributed to each intervention.

In other words, it was approximately equal to the median of other feasible approaches. 

Finally, the team compared model results with actual age-adjusted breast cancer mortality rates reported from death record data in the Surveillance, Epidemiology, and End Results Program (SEER) registry.

Results and conclusion

At the end of 2019, the study model simulations showed a 58% reduction in US breast cancer mortality, of which ~29%, 47%, and 25% were attributable to treatment for metastatic breast cancer, treatment of stage I-III breast cancer, and mammography screening.

The authors also noted the highest mortality reduction in ER+/ERBB2+ breast cancer and the smallest in ER−/ERBB2− breast cancer. 

Further, the models simulated improvements in survival after metastatic recurrence between 2000 and 2019, with survival improving by 2.5 and 0.5 years for ER+/ERBB2+ breast cancer and ER−/ERBB2− breast cancer, respectively. These differences show varying efficacy of treatments for ER+ and ERBB2+ cancers.

It is also important to note that while survival estimates may vary according to the time of diagnosis of cancer or recurrence, mortality rates remain unaffected.

However, the population-level breast cancer mortality reductions may be uniquely associated with novel treatments, necessitating their continual introduction to sustain the observed mortality reduction over time.

Another notable finding of this trial was that screening mammography accounted for a higher proportion of breast cancer mortality reduction in ER−/ERBB2−breast cancer, while treatment had the least.

However, cancers diagnosed without screening were associated with poorer outcomes that modern treatments could not surmount.

Overall, both breast cancer screening and treatments showed associations with US breast cancer mortality rates.

Compared to interventions in 1975, they decreased breast cancer mortality in the US by ~58%. In addition, survival after metastatic recurrence improved the most between 2000 and 2019.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.


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