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How Do You Make the Best Cancer Choices for Older Loved Ones?
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Jul 25, 2025
This video explores the intricacies of medical decision making in oncology, particularly for elderly patients. Understanding geriatric assessment is key to providing appropriate care. It emphasizes the importance of considering the patient's overall health and well-being when making choices about cancer treatments and palliative medicine. LinkedIn https://www.linkedin.com/in/arminshahrokni?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app X https://x.com/GeriOncologist?t=QMpM6F9KTB9_2W66OiEOzw&s=09 Instagram https://www.instagram.com/aging_cancer/profilecard/?igsh=MXI3eTBieTNhNjJucg== Google Scholar https://scholar.google.com/scholar?hl=en&as_sdt=0%2C33&q=armin+shahrokni+&btnG=
View Video Transcript
0:05
How do we make the absolute best
0:06
decisions? Especially when it's about
0:08
something as critical, as complex as
0:10
cancer treatment for the people we care
0:13
about most, you know, as they get older.
0:15
It's a really profound challenge. Many
0:16
of us face it or probably will. So,
0:19
today we're doing a deep dive into
0:21
medical decisionm specifically for older
0:24
adults who have cancer. And uh this
0:26
isn't just about picking treatments.
0:27
It's much more about balancing hopes,
0:29
fears, and all those nuances, the
0:31
realities of individual lives. To help
0:34
us navigate this, we're looking at
0:35
insights from a conceptual review. It
0:37
was published in the Journal of Clinical
0:38
Oncology. The article is called
0:40
Decision-M in Older Adults with Cancer
0:43
by Clark Dumontier and colleagues. It
0:45
synthesizes a lot of evidence and
0:47
importantly proposes a framework to help
0:49
steer through these tough choices.
0:51
Yeah. And the mission really for this
0:53
deep dive is to give you a clearer
0:55
picture of all the complexities involved
0:58
and uh to introduce this principled
1:00
framework that's designed to help
1:01
optimize these really critical
1:03
decisions. It's all about trying to
1:05
minimize both under treatment and overt
1:07
treatment, making sure care actually
1:09
aligns with what an individual needs and
1:11
crucially what they value. What's quite
1:14
fascinating here is how it tries to
1:15
bridge that gap between, you know, what
1:17
we know from clinical trials and the
1:19
real world situation for older patients
1:21
who are often frankly frailer.
1:23
Okay, so let's unpack that central
1:25
challenge then. The article really
1:26
highlights a significant gap, doesn't
1:28
it? Clinical trials, well, they often
1:30
enroll healthier, maybe younger
1:31
patients, which leaves oncologists,
1:33
especially in community practices, with
1:35
a lot of uncertainty when they're
1:37
treating older maybe frailer adults.
1:40
Exactly. If you think about the bigger
1:42
picture, it means the hard evidence we
1:44
have.
1:45
Well, it isn't always directly
1:47
generalizable to the majority of older
1:50
patients we see in clinics. So, that
1:52
raises a pretty fundamental question.
1:54
How do we make properly informed
1:56
decisions when the rule book, so to
1:58
speak, doesn't quite cover everyone?
2:01
Right? And adding another layer here, uh
2:03
the article points out the involvement
2:05
of caregivers, other key people, their
2:08
influence on how decisions are
2:09
structured, the actual choice made that
2:11
can vary a whole lot. It's rarely just
2:13
the patient alone.
2:14
Mhm. That whole system.
2:16
So navigating this complex landscape, it
2:19
sounds like you really need a guide. And
2:20
that's what the authors offer, right? A
2:22
decision framework.
2:23
Precisely. They propose this uh pretty
2:26
powerful framework built right on the
2:27
foundation of evidence-based medicine.
2:29
And it's not just theory. It's designed
2:31
as a practical guide.
2:32
Okay. So, what's at the core of it?
2:34
Well, it optimizes decisions based on
2:36
three key principles. First, figuring
2:38
out the patients age related
2:39
vulnerability. That's done using
2:42
something called a geriatric assessment
2:43
or GA.
2:44
Okay, GA. Got it.
2:45
Second, you consider the overall
2:47
benefits and importantly the harms of
2:49
treatment specifically in light of that
2:51
vulnerability score. And third, you
2:54
absolutely have to incorporate the
2:56
patients own values and preferences.
2:59
That includes understanding the
3:00
trade-offs they're willing or unwilling
3:02
to make.
3:03
Right. And this is where it gets really
3:04
interesting. You mentioned the geriatric
3:06
assessment, the GA. That seems central.
3:08
It's not just about how old someone is
3:10
in years.
3:10
No, not at all.
3:11
It's about figuring out who's well
3:14
resilient enough for maybe more
3:15
intensive treatments and who's frail and
3:18
really at high risk for toxicity.
3:20
Exactly. It even helps estimate life
3:22
expectancy, which is crucial for
3:24
context.
3:25
And the article notes, efforts are
3:27
ongoing to build up the evidence. space
3:28
for this. You've got policies now like
3:30
the NIH's inclusion across the lifespan
3:33
that requires older adults to be
3:34
included in funded clinical studies.
3:36
Plus, there's a real push for more
3:38
rigorous observational studies,
3:40
especially for those frailer patients
3:41
often left out of trials.
3:43
Okay, so let's dig into the first
3:44
principle, understanding the benefits of
3:46
cancer treatment. The article says the
3:49
first step is estimating if the cancer
3:50
is even likely to cause symptoms within
3:52
the patients remaining lifespan.
3:54
Right? You have to look at the cancer
3:56
itself. How aggressive is it? and
3:58
estimate their life expectancy
4:00
independent of the cancer.
4:01
Makes sense.
4:02
So for instance, the article contrasts
4:04
uh say an indolent slow growing early
4:07
stage prostate cancer.
4:09
Mhm.
4:09
In a fit 55year-old, he's likely to live
4:12
long enough for it to become a problem.
4:14
But maybe in a more vulnerable
4:15
72-year-old with lots of other health
4:17
issues, well, their risk of dying from
4:19
something else in the next 5 or 10 years
4:21
might be much higher. So the cancer
4:23
might not actually affect them. How do
4:25
clinicians estimate that non-cancer life
4:27
expectancy?
4:28
They can use prognostic calculators.
4:30
There are tools available like on the
4:31
prognosis website, things like the Lee
4:33
Shawnberg index and these rely heavily
4:36
on those geriatric assessment variables
4:38
like functional status, coorbidities,
4:41
cognition.
4:41
I see. So, okay, beyond just general
4:44
life expectancy, how do we look at the
4:46
evidence for specific treatments? What
4:48
questions should we ask?
4:49
Good question. You need to ask was this
4:51
kind of patient actually represented in
4:53
the study you know their age their
4:55
health status that's generalizability
4:57
right
4:58
then does the benefit of the treatment
5:00
change based on those age related
5:03
factors that's called heterogeneity of
5:05
treatment effect
5:06
okay
5:06
and maybe the most crucial one is the
5:09
outcome measured in the study like tumor
5:11
shrinkage or delaying progression is
5:14
that outcome actually important to this
5:16
particular older patient
5:17
that's a really key point because most
5:19
trials cells focus on survival or maybe
5:22
tumor response.
5:23
Exactly. But how does shrinking a tumor
5:25
actually translate? Does it improve
5:27
their function, their quality of life?
5:29
Does it help them live better, not just
5:31
longer?
5:31
So, we need more trials looking at those
5:33
things.
5:34
Absolutely. The article really stresses
5:35
the need for more patient- centered
5:37
outcomes in trials, function, quality of
5:40
life, things that matter dayto-day. It
5:42
also suggests that multiddisciplinary
5:44
teams bringing in geriatricians,
5:45
paliotative care experts, they can
5:47
really improve those patient- centered
5:49
outcomes, especially when the evidence
5:51
from trials is a bit thin.
5:52
Okay, so that's benefits. Now let's flip
5:54
the coin. Principle two is considering
5:55
the harms of cancer treatment. So if a
5:58
treatment does offer a benefit that
6:00
matters to the patient, we then have to
6:01
weigh that against the risks, the
6:03
toxicities,
6:04
right? And these harms, they're
6:06
definitely not oneizefits-all. They vary
6:09
hugely depending on how intensive the
6:11
treatment is and critically the
6:13
patient's underlying health status.
6:15
The GA vulnerability score again
6:17
precisely. And what's fascinating or
6:20
perhaps concerning is that even if the
6:22
chance of controlling the cancer is
6:23
similar, the harms can differ
6:25
significantly by age or frailty.
6:29
The source gives some pretty stark
6:30
examples.
6:30
Yeah. for frail older nursing home
6:33
residents having breast cancer surgery.
6:35
One study found 30 to 40% one-year
6:37
mortality.
6:38
Wow.
6:38
And among the survivors, over half
6:40
experienced functional decline, lost
6:42
independence.
6:43
That's huge.
6:44
Another example, primary CNS lymphoma.
6:46
In a subgroup of adults, median age 73
6:49
receiving treatment,
6:50
25% died within 6 months. And largely
6:53
that was due to complications from their
6:54
other health issues and treatment
6:56
toxicity, not necessarily the lymphoma
6:58
itself. So the treatment itself caused
7:00
major problems.
7:01
It can especially in vulnerable
7:02
patients. One more acute myoid leukemia
7:06
AML. For patients aged 70 or older
7:09
getting intensive chemo. One study
7:12
reported 35% mortality at just 8 weeks.
7:15
And that's despite reasonable cancer
7:17
response rates. It really highlights
7:19
that just because the cancer responds or
7:21
progression-free survival looks okay, it
7:23
doesn't always mean better overall
7:25
survival if the treatment toxicity or
7:27
other health problems are overwhelming.
7:29
So, this really underscores the need for
7:31
better ways to predict who's going to
7:33
run into trouble with toxicity.
7:35
Exactly. And that's where the geriatric
7:36
assessment comes in. Again, it actually
7:38
performs better at predicting toxicity
7:40
than traditional measures like just
7:42
performance status.
7:43
Are there specific tools based on the
7:45
GA?
7:45
Yes. The ASCO guideline, for instance,
7:48
recommends tools like the Chi score
7:50
cancer and aging research group or the
7:52
TR score. These use GA components to
7:55
predict the risk of severe
7:56
chemotoxicity.
7:57
And can using the GA actually help
7:59
reduce harm?
8:00
It seems so. The article mentions recent
8:02
trials suggesting that GA guided care,
8:05
where treatment decisions are adjusted
8:07
based on the GA results, can actually
8:09
mitigate toxicity and reduce things like
8:11
unplanned hospital visits.
8:12
Yeah. and importantly often without
8:15
sacrificing the treatment's benefit for
8:17
the cancer itself.
8:19
That's really promising. So it raises
8:20
the question, doesn't it? How do we make
8:22
sure these assessments become standard
8:24
practice to really minimize harms
8:27
effectively?
8:28
That's the implementation challenge.
8:29
Absolutely.
8:29
Okay. So we've estimated benefits, we've
8:31
estimated harms in light of
8:33
vulnerability. Now the third principle,
8:35
incorporating values, preferences, and
8:38
those tricky trade-offs.
8:39
This is where it all comes together.
8:41
balancing the pros and cons within the
8:43
context of what that specific older
8:45
adult truly values.
8:47
And this is where it gets really
8:48
interesting, you said earlier, because
8:49
what's important can shift significantly
8:52
with age.
8:52
Generally speaking, yes, younger adults
8:55
might be willing to tolerate more risks,
8:57
more side effects for a chance at a
8:59
longer life expectancy. Older patients
9:02
often are less willing to trade quality
9:04
of life for just quantity of life.
9:07
Maintaining independence, function,
9:09
staying out of the hospital, those often
9:11
become paramount.
9:12
So, how do oncologists actually figure
9:14
this out? Is it just asking?
9:16
It's more than just asking. The article
9:19
points to validated tools and resources
9:21
that can help structure these
9:22
conversations. Websites like patient
9:24
priorities care or prepare for your
9:26
care. They offer conversation guides.
9:28
They help patients actually list
9:29
specific priorities like I want to be
9:32
able to attend my grandchild's wedding
9:33
or keep gardening.
9:35
Concrete things.
9:36
Yes. And fears too like I'm afraid of
9:38
not being able to care for myself. And
9:40
importantly, these tools help gauge
9:42
whether quality or quantity of life is
9:44
the main driver for them.
9:45
Can you give us an example of how this
9:46
plays out?
9:47
Sure. The article gives a couple.
9:49
Imagine a uh vulnerable older man with
9:52
prostate cancer. Maybe his biggest fear
9:54
is the cancer spreading metastasis. So
9:58
he might prioritize definitive treatment
10:00
even if it means accepting immediate
10:01
risks like incontinence or impetence.
10:04
Okay.
10:04
Or flip side maybe he deeply values
10:07
maintaining his current function and
10:08
independence right now. In that case he
10:10
might prefer active surveillance just
10:12
watching the cancer closely even if it
10:15
means accepting a slightly higher risk
10:16
of metastasis down the road.
10:18
So same diagnosis potentially very
10:20
different choices based on values.
10:22
Exactly. Or think of a fit older woman
10:25
with stage three colon cancer. Maybe she
10:27
really wants to maximize her chances of
10:29
living longer without recurrence. So she
10:31
desires intensive adgivant therapy. But
10:33
another woman in the same situation
10:34
might say, "You know what? The side
10:36
effects of that intensive chemo really
10:37
scare me. I prioritize my quality of
10:40
life today." So she might offer a less
10:42
intensive option, consciously balancing
10:44
the potential survival gains against the
10:46
toxicity risks.
10:47
It's about making the trade-offs
10:48
explicit.
10:49
Yes. And there's another tool mentioned,
10:51
the best case, worst case scenario. It's
10:54
gaining popularity.
10:55
How does that work?
10:56
It helps patients visualize potential
10:58
outcomes more concretely instead of just
11:01
talking percentages. For instance, one
11:03
study used breast cancer trial data to
11:05
show patients, okay, with this chemo,
11:08
best case, here's what survival looks
11:10
like. Worst case, considering side
11:12
effects and other factors, here's what
11:14
it might look like. Makes it much more
11:15
tangible.
11:16
That sounds incredibly helpful. But you
11:18
know these decisions they rarely happen
11:20
in isolation just between the doctor and
11:22
patient. There's often family caregivers
11:25
a whole social context. Let's unpack
11:27
that layer.
11:28
Absolutely vital point. Real life
11:30
decision-m is embedded in relationships.
11:32
Family members, caregivers, the whole
11:34
healthcare team, they all provide input
11:36
and that can get complicated, right?
11:38
What happens if family members try to
11:39
maybe shield the older person from bad
11:41
news?
11:42
That definitely happens. attempting to
11:43
withhold information, especially about
11:46
prognosis. The article highlights that
11:48
family influence tends to be higher
11:50
among older individuals and also
11:51
sometimes in certain racial and ethnic
11:53
groups.
11:54
And the article makes a critical point
11:56
about the research itself here, doesn't
11:57
it?
11:58
It does. It notes that many studies on
11:59
shared decision-m have primarily
12:02
involved non-Hispanic white
12:04
participants,
12:04
meaning the models might not fit
12:06
everyone.
12:06
Exactly. They might not generalize well.
12:09
And the article is very clear on this.
12:11
While culture absolutely can influence
12:13
preferences, physicians should never
12:15
stereotype patients based on their
12:17
background.
12:18
So what's the alternative?
12:19
Active engagement. Physicians need to
12:22
actively engage both the patient and
12:23
their caregivers. Work on communication
12:26
skills. Build trust. It's about
12:28
understanding the individual's
12:29
perspective, not making assumptions.
12:32
The article also introduces this idea of
12:34
a decision-making unit. What's that
12:36
about? Yeah, it's a concept borrowed, I
12:38
think, initially from policy decisions,
12:39
but applied here to families or groups
12:42
making a health decision. It helps
12:44
categorize how the group works together.
12:46
Is there one dominant leader calling the
12:48
shots? Does everyone act together as a
12:50
single group or are there sort of
12:52
coalitions or alliances within the
12:54
family?
12:54
Ah, okay. Understanding the family
12:56
dynamic,
12:57
right? Understanding those dynamics and
13:00
also the prevailing values within that
13:02
unit. Maybe they really value equality
13:04
or individual choice. Or perhaps there's
13:06
a sense of fatalism understanding that
13:09
can really guide the shared
13:11
decision-making process towards an
13:13
outcome that feels satisfactory for
13:15
everyone involved.
13:16
Makes sense. Now, shifting slightly, the
13:18
article also talks about the psychology
13:20
of decision-m biases and things like
13:22
that.
13:23
Yes, this is crucial. It turns out both
13:25
oncologists and patients can be
13:27
influenced by various cognitive biases
13:29
during this whole process.
13:31
How does that happen? M it often comes
13:32
down to a failure to properly balance
13:35
two types of thinking. What
13:37
psychologists call type one thinking.
13:39
That's the fast intuitive gut reaction
13:41
kind.
13:41
Okay.
13:42
And type two thinking which is slow,
13:44
deliberate, analytical.
13:45
And we need both.
13:46
Ideally, yes.
13:47
Yeah.
13:48
But emotions can sometimes hijack the
13:50
process. There's something called the
13:51
affect heristic.
13:51
What affect her?
13:52
Yeah. Basically, strong emotions
13:54
clouding judgment. A patients intense
13:57
anxiety or depression might lead them to
13:59
push for choices that aren't necessarily
14:01
evidence-based. Or conversely, an
14:04
oncologist's own fear of the cancer
14:06
spreading might unconsciously push them
14:08
towards more intensive treatment, even
14:10
if the evidence for benefit in that
14:12
specific patient is limited. A healthy
14:14
mix using both intuition and
14:16
deliberation usually leads to better
14:18
decisions.
14:19
And there's one bias specifically
14:21
mentioned regarding older adults. Agism.
14:24
Yes, a really important one. Negative
14:26
attitudes, stereotypes about aging. It's
14:28
insidious.
14:29
How does it affect care?
14:31
It can lead to clinicians or even
14:32
patients themselves deciding against
14:35
beneficial therapies simply because of
14:36
age. It can lead to poorer access to
14:38
care, worse communication, maybe a more
14:41
paternalistic approach where the doctor
14:42
just decides what's best without real
14:45
discussion.
14:45
And patients can internalize it, too.
14:47
Absolutely. Self- aism. An older adult
14:49
might think, "Oh, I'm too old for this
14:51
treatment." And not even seek it out.
14:53
The article is emphatic. Decisions
14:55
should never be based on chronological
14:57
age alone. Never.
14:58
So given all these potential pitfalls,
15:02
biases, communication challenges, how do
15:05
we ensure true informed consent?
15:07
That's the goal. And true informed
15:09
consent requires promoting
15:10
understanding. Understanding the
15:12
disease, the treatment options, the
15:14
likely outcomes, both good and bad, and
15:17
the prognosis.
15:18
But understanding prognosis can be
15:19
difficult.
15:20
Very difficult. Studies show a really
15:23
high percentage, like 50 to 73% of older
15:26
adults with advanced cancer either have
15:28
a poor understanding of their prognosis
15:30
or their understanding is very different
15:32
from their oncologist's view.
15:34
And that matters because
15:35
because poor prognostic understanding is
15:37
linked to choosing more aggressive
15:39
burdensome care towards the end of life.
15:42
Care that might not align with their
15:43
overall goals.
15:44
Is there anything that helps improve
15:45
that understanding? Paliative care
15:47
involvement has been shown to
15:49
significantly improve disease
15:51
understanding and alignment of care with
15:53
preferences.
15:54
Okay. And then there's the fundamental
15:55
question of capacity, right? Can the
15:57
patient actually make the decision?
15:59
Essential. We need to confirm decision-m
16:02
capacity. That generally involves four
16:05
things.
16:06
Can they understand the information? Can
16:08
they express a choice? Do they
16:10
appreciate how the information applies
16:12
to their own situation? And can they
16:14
reason through the options? And just
16:16
having some cognitive impairment doesn't
16:18
automatically mean they lack capacity.
16:20
Correct. That's a crucial distinction.
16:22
Cognitive impairment alone isn't
16:23
incapacity. But if a patient does lack
16:26
capacity, then a designated healthcare
16:28
proxy or surrogate decision maker needs
16:30
to be involved.
16:30
One last point on this section.
16:33
How much should the doctor guide the
16:35
decision?
16:36
Ah yes, the article touches on that
16:39
debate. How much help should the
16:41
clinician give with the final choice?
16:43
Extremes are generally avoided being
16:44
totally paternalistic. I know best or
16:47
completely handsoff. It's all up to you.
16:48
I offer nothing.
16:49
Somewhere in the middle.
16:50
Usually, a patient absolutely has the
16:53
right to ask for a recommendation. And
16:55
if they do, the physician should provide
16:57
one thoughtfully grounding it in that
16:59
patients stated values and preferences.
17:02
Some argue actually that stronger
17:04
clinician recommendations are often
17:05
preferred, especially when uncertainty
17:07
is really high. Patients can't be
17:09
expected to be experts in navigating all
17:11
the complex medical evidence.
17:12
themselves.
17:13
Okay, so bringing this all together,
17:15
what's the ultimate goal? What does this
17:17
mean for the big picture?
17:19
Well, the article concludes by really
17:21
highlighting that biased, uninformed, or
17:24
poorly communicated decision-making too
17:26
often leads to those two bad outcomes we
17:28
mentioned at the start, under treatment
17:30
or over treatment.
17:31
Denying beneficial care or giving
17:33
harmful or pointless care.
17:34
Exactly. and ASCO, the American Society
17:36
of Clinical Oncology. Their research
17:38
priorities back in 2021 specifically
17:41
included investigating personalized care
17:43
guided by the geriatric assessment
17:45
precisely to minimize these problems.
17:47
Their article also points out that the
17:48
terms themselves under treatment
17:50
overtreatment can be tricky.
17:51
Yes, they can carry their own biases and
17:54
lack precision. Sometimes labeling
17:57
something as potential overt treatment
17:59
might paradoxically lead to
18:00
undertreatment if clinicians become
18:03
overly cautious. So how do we fix that?
18:05
The authors propose shifting the
18:06
definitions moving away from purely
18:09
disease-centric criteria like just
18:11
focusing on survival towards truly
18:14
patient centered criteria
18:15
which means including
18:16
including function and quality of life
18:18
as core outcomes when judging whether
18:20
care was appropriate. Was it aligned
18:22
with what mattered to the patient not
18:24
just what happened to the tumor?
18:25
Makes sense.
18:26
So in the end the source really
18:27
emphasizes that sound shared decision-m
18:30
is just essential. It's a principled
18:32
approach. It actively engages the
18:34
patient, their caregiver, allows for
18:35
both that intuitive gut feeling
18:37
reasoning and the careful deliberative
18:39
thinking. And this process itself, just
18:42
having that good communication, shared
18:43
understanding, even regardless of the
18:45
final impact on survival or function, it
18:47
significantly improves communication and
18:49
patient satisfaction with their care.
18:51
And that's a profoundly important
18:53
outcome in its own right.
18:54
So, as we wrap up this deep dive, it's
18:57
just so clear, isn't it? decision-making
18:59
in older adults with cancer is this
19:01
incredibly complex tapestry. It's woven
19:04
with medical evidence. Yes. But also
19:06
deeply personal values, family dynamics,
19:09
those subtle cognitive biases we
19:11
discussed.
19:12
Absolutely. And the framework we've
19:13
explored today, the one centered on that
19:15
geriatric assessment, it really offers a
19:17
powerful lens, a structured way to
19:19
approach these choices. It helps ensure
19:21
that the intensity of treatment aligns
19:22
with the patients vulnerability and that
19:25
the expected outcomes align with what
19:26
that individual actually prefers and
19:28
really highlights that the process of
19:30
deciding how that conversation happens
19:32
that is an outcome of profound
19:33
importance itself.
19:35
Definitely. So here's a final maybe
19:37
provocative thought for you to consider.
19:38
How might actively incorporating
19:40
something like a geriatric assessment
19:42
and having these explicit discussions
19:44
about patient values, how might that
19:47
transform healthcare beyond just cancer
19:49
treatment? Could it improve
19:50
decision-making across all complex
19:52
medical fields for older adults?
19:54
Something to think about. What stands
19:56
out most to you from today's deep dive?
19:58
We really hope this exploration has
19:59
given you a valuable shortcut to being
20:01
well informed on this critical topic and
20:03
maybe uh maybe even sparked some new
20:05
questions for you.
#Aging & Geriatrics
#Cancer