Elizabeth Wayne, Ph.D.
When we talk about cancer research we are probably just thinking about scientists in lab coats, gloves, and safety goggles looking at test tubes full of cancer cells. While this is true, cancer research doesn’t just happen in a test tube or broadly, in a laboratory. The practice of studying cancer from an epidemiological, social, and outcomes perspective is equally valuable and imperative for improving patients’ lives and outcomes.
We can look at cancer from the genetic level, but we can also scale-up and look at cancer from the population level. Social scientists study how disease travels in specific populations. What social, economic, and behavioral factors affect patient treatment and outcomes? What can we do to improve cancer success rates on a public health level?
To understand this, we have to look at what happens when people get diagnosed with cancer. Where do they go for treatment and what type of treatment do they get? The National Cancer Institute maintains a database called SEER which stands for Surveillance Epidemiological and End Result. SEER is the largest and most comprehensive database about cancer statistics in the U.S. Because SEER information links the insurance claims with patient demographic information we can determine with accuracy the treatments received and the final outcomes.
The work from Amanda Kong at the University of Wisconsin explored whether socioeconomic status (SES) and treatment type affected the outcome of elderly breast cancer patients. Studying breast cancer in the senior population is significant because the majority of people who are diagnosed with breast cancer are elderly.
In this study, Kong and her colleagues drew data from nearly 28,000 women diagnosed with incident breast cancer. Within this cohort of people, they summarized the characteristics of the group: the majority were white, over one-third were above 80 years old, most had no comorbidities, and most were also in the medium-to-high SES bracket.
Kong used a special analysis method to determine which factors about the patient were the most significant determinants of outcome which in this case was being alive or dead after 5-years. In this analysis, the researchers found 18 distinct patterns ranging from best survival probability to worst. They found the patterns that were associated with the worst likelihood of survival were having three or more lymph nodes with traces of cancer, being older (in this case being above the age of 80), having one or more pre-existing conditions, having an advanced stage diagnosis, or being negative for the two most commonly treatable types of breast cancer.
The study also found patient survival depended on the type of treatment received. Patients who received radiation or hormonal therapy, even those that had one of the attributes linked to poor survival such as the spread of the tumor to lymph nodes, had better survival rates than those who had received no treatments at all.
Interestingly, women whose treatment was associated with the patterns of lower survival also had longer wait times (the time between diagnosis and administration of the first treatment).
Intuitively, these findings make sense. If you are already suffering from another illness before your cancer diagnosis or if you present with a large tumor that has been to other parts of the body, it will be much harder to treat. Likewise, receiving treatment may have more benefit than doing nothing at all. These are all factors about cancer that make it more difficult to treat and that can be directly attributed to the biology of the disease.
However, what may not be as well-known are some of the lived experiences of these patients. Who is more likely to receive the treatments that are correlated with greater or worse survivorship? And if there are differences then why?
In comparison to high SES women (middle to upper class), women who are poor are almost FOUR times more likely to be in the patterns associated with worse survival. They are almost only half as likely to be in the patterns associated with the best survival (31.7% vs. 52.9%). Put another way, poor women are more likely to have pre-existing conditions and receive no radiation or hormonal therapies.
The persistence of a disparity here is shocking considering that all the patients sampled had the same Medicare coverage which provides access to the same types of treatments. Other researchers have suggested this may be due to high copays and differences in treatment options at low-volume hospitals where women who are poor are more likely to seek treatment from. To receive radiation therapy, a patient must be able to travel to the hospital almost daily for 3-6 weeks. Depending on where you live, the treatment needed may not be available locally and can require long travel times. This alone can present time and financial barrier.
Studies like this are important because they alert medical practitioners to areas where improvement in existing treatments can lead to better survival outcomes. They also help policymakers understand how resources are being utilized and where resources should be distributed to ensure equal access. In my role as a scientist, studies like this help me understand how therapies that I develop get implemented into patient care. More personally, as someone who hopes one day to be an elderly woman and has been supported by the love and strength of many elderly women, studies like this help me appreciate the obstacles they may face.
Kong, A. L., Nattinger, A. B., McGinley, E., & Pezzin, L. E. (2018). The relationship between patient and tumor characteristics, patterns of breast cancer care, and 5-year survival among elderly women with incident breast cancer. Breast Cancer Res Treat. doi: 10.1007/s10549-018-4837-4
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