In an interview with Targeted Oncology, study investigator David Dawe, MD, BASc, MSC, FRCPC, discussed the impact of age, comorbidities, and polypharmacy on cancer care in greater detail.
As a patient ages rise, so do incidences of cancer, comorbidities, and polypharmacy. However, how these factors interplay and affect the receipt of systemic therapy in advanced malignances has not been thoroughly studied.
A retrospective cohort study looked at this relationship in greater detail. The study included patients 18 years of age or older diagnosed between 2004 to 2015 with multiple myeloma, non-Hodgkin lymphoma, breast cancer, colorectal cancer, prostate cancer, or ovarian cancer. In total, 17,228 participants were included.
The cancer breakdown included, colorectal cancer (29%), lung cancer (28%), prostate cancer (13%), breast cancer (12%), non-Hodgkin lymphoma (10%), multiple myeloma (5%), and ovarian cancer (4%). Non-Hodgkin lymphoma and multiple myeloma were the only hematologic malignancies included.
In an interview with Targeted OncologyTM , study investigator David Dawe, MD, BASc, MSC, FRCPC, an assistant professor in the Max Rady College of Medicine, discussed the impact of age, comorbidities, and polypharmacy on cancer care in greater detail.
TARGETED ONCOLOGY: Can you give a brief overview of the impact of age, comorbidities and polypharmacy on receipt of systemic therapy in advanced cancers?
DAWE: While we certainly know that systemic therapy for cancers decrease with increasing age, and that's due to a whole variety of factors. We also know that comorbidities are probably part of that, performance status is part of that, and possibly the number of additional medications is part of that as well. And while there have certainly been studies that have explored each of those factors, there hasn't really been much that's looked at the interaction between those components. And so, we were trying to use real world data from the Canadian Province of Manitoba to look in both areal-world setting and a population-based setting, how those factors interacted.
And the population-based part is important here, because if we were simply looking at patients referred to a cancer center, you would end up losing a lot of the patients with the highest rate of comorbidities, highest age. Ultimately, we looked at about 17,000 patients, or more specifically 17,228 patients, with a variety of cancers. we pick the common solid tumors, so colorectal cancer, lung cancer, breast cancer, and prostate cancer, and then supplemented that with a selection of cancers from other areas such as ovarian, non-Hodgkin lymphoma, and multiple myeloma. And what we found was that, as expected, treatment rates with systemic therapy, which would include things like hormonal therapy, those dropped off with age as we might expect. But also, those drop offs were more were both earlier and more substantial for cytotoxic chemotherapy.
The drop offs are most notable in the cancers where non-cytotoxic systemic therapy options don't really exist or didn't exist a whole lot between 2004 and 2015, which was the time frame of diagnosis in our study. And we found, for example, lung cancer, stage IV lung cancer was treated with systemic therapy 24% of the time, which dropped off starting with people in their 60s, from 58% in those less than 50 to 4% in those over 80. And then, conversely, cancers with a large amount of hormonal associate therapy such as prostate cancer or breast cancer, maintain their rates of treatment for people into their 70s, and even a greater extent than other cancers into their 80s.
We also saw treatment dropped off with a higher number of medications, or polypharmacy specifically defined as 6 or more prescription medications, and also dropped off with comorbidity, though that was a bit more complex relationship, because we had 2 different measures of comorbidity. One was the Charlson Comorbidity Index, which is a selection of other health conditions. And the other was what's called a resource utilization band, determined using the software from Johns Hopkins University. While it can be used as a comorbidity score, is really more of a interactions with the healthcare system, going from 0 where there's no interactions all the way up to 5, whether these are the highest users of the health care system. And in that resource utilization band, interestingly, we found treatment rates were comparatively lower with the people who never interacted with the health care system, potentially because those are people who have concerns about interacting with the healthcare system. And that most people had an RUB of 2 or 3. Charlson comorbidity score behaves more as we would typically think of it in clinic where higher comorbidity score lead to lower likelihood of survival.
As far as interaction between the factors, we actually found that age did not interact with comorbidity or with polypharmacy. And by that, I mean the relationship between those factors did not change over the course of age. But there were interactions with age and stage of cancer, as well as agent type of cancer. So, as an example, where stage 3 and 4 cancers both dropped off with age, at the earlier ages, stage3 rate of treatment was much higher. And with unknown stage it was lower throughout. Whereas amongst different cancers, we saw significantly different patterns with something like lung cancer starting low and then going down. Whereas prostate cancer formed an interesting kind of "S" curve, since it's all hormonal, there was a fairly stable rate of treatment. We saw that survival rates did stratify out by age, and comorbidity, and stage, and polypharmacy. And then again, the interaction here was between age and type of cancer or age and stage of cancer. There wasn't again, a differing relationship across age with comorbidity or with medication counter polypharmacy. So, it does seem as though those are independent factors that predict both receipt of treatment and survival.
Did you see a difference between like solid tumors and hematologic tumors?
The types of cancer with hormonal therapies like breast cancer or prostate cancer, we saw much less in the way of drop off as people age. Others like lung cancer, or colon cancer, where it's pretty much strictly cytotoxic chemotherapy. We saw significant drop offs really starting in either your 60s or 70s, especially 70s, and 80s. And then for hematologic tumors, like non-Hodgkin lymphoma, or multiple myeloma, which were the two hematologic cancers included, we again saw less drop off it until people were in their 80s. And again, I think that's because those are highly responsive cancers to the treatment. And in the case of non-Hodgkin lymphoma, you're aiming for cure. So regardless of stage you are aiming for cure. So, I think those are probably some of the underlying reasons.
What steps can community oncologists take to mitigate some of these comorbid factors in their patients in order for them to get the best therapy or to have the best response possible?
In terms of mitigating comorbidities, I think it's more managing comorbidities and trying to make sure whatever other health conditions someone has are being managed as well as possible. So, whether that's heart failure or diabetes or previous stroke, I think there's perhaps more that can be done at the point of care, if you will, with regards to number of medications. So, we know that as people's number of medications goes up, there's a higher risk of potentially inappropriate medications. And so, I think being aware of that, and looking for potentially inappropriate medications and trying to deprescribe those medications. You can potentially reduce the number of medications.
We do see, that perhaps not surprisingly, we see a big drop off in treatment and a reduction in survival with increasing age. But we do know that appropriately selected older adults can still benefit from treatment. As we get older, our health conditions become more complex. And we know that there can be issues with tolerance. But we should still be trying to think of ways to both improve other health conditions, even with cancers that may have a limited life expectancy, but also that we should be looking at ways to reduce the number of medications.