Cancer Prevention Month 2021

Transcript

00:00 --> 00:02Support for Yale Cancer Answers
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00:14 --> 00:16Welcome to Yale Cancer Answers with
00:16 --> 00:18your host doctor Anees Chagpar.
00:18 --> 00:20Yale Cancer Answers features the
00:20 --> 00:22latest information on cancer care by
00:22 --> 00:23welcoming oncologists and specialists
00:23 --> 00:26who are on the forefront of the
00:26 --> 00:28battle to fight cancer. This week,
00:28 --> 00:29it's a conversation about outcomes research
00:29 --> 00:32in kidney cancer with Doctor Michaela Dinan.
00:32 --> 00:34Doctor Dinan is an
00:34 --> 00:36associate professor in chronic disease
00:36 --> 00:38Epidemiology at the Yale School of
00:38 --> 00:40Public Health and Doctor Chagpar
00:40 --> 00:42is a professor of surgical oncology
00:42 --> 00:45at the Yale School of Medicine.
00:45 --> 00:47Michaela, maybe we can start
00:47 --> 00:50off by you telling us a little
00:50 --> 00:51bit more about yourself and
00:51 --> 00:52what exactly you do.
00:52 --> 00:55I call myself a cancer outcomes or
00:55 --> 00:56health services researcher so people
00:56 --> 00:58aren't always familiar with cancer
00:58 --> 01:00outcomes or health services research.
01:00 --> 01:03They tend to be more familiar with
01:03 --> 01:05basic or clinical Cancer Research.
01:05 --> 01:06Basic Cancer Research relates to
01:06 --> 01:09studies done in a lab with cancer cells,
01:09 --> 01:12either in a Petri dish or in animals
01:12 --> 01:14where researchers can directly manipulate
01:14 --> 01:16and study cancer cells to learn
01:16 --> 01:18more about basic biology of cancer.
01:18 --> 01:20And then, clinical Cancer Research refers
01:20 --> 01:23to when advances in basic science are
01:23 --> 01:25being translated into actual medical
01:25 --> 01:27tests or treatments and are then
01:27 --> 01:30tested in humans to see if they work.
01:30 --> 01:32My focus of research health services
01:32 --> 01:34is the part that comes
01:34 --> 01:36after this, after a new medical
01:36 --> 01:38treatment or diagnostic tool is
01:38 --> 01:40found to work in clinical trials,
01:40 --> 01:42I study how it actually gets
01:42 --> 01:44used in the real world.
01:44 --> 01:47You have to remember that only around 3% of
01:47 --> 01:50patients are treated on a clinical trial.
01:50 --> 01:52And other people who take part
01:52 --> 01:54in clinical trials are not like
01:54 --> 01:55the general cancer population.
01:55 --> 01:58In order to be enrolled in a clinical trial,
01:58 --> 02:00you have to be healthy enough to
02:00 --> 02:02qualify for participation and every
02:02 --> 02:04clinical trial has a set of very strict
02:04 --> 02:06inclusion and exclusion criteria.
02:06 --> 02:08And if you don't meet every single one,
02:08 --> 02:11you can't participate as you can imagine,
02:11 --> 02:13the vast majority of patients who receive
02:13 --> 02:15treatment are not part of a clinical trial,
02:15 --> 02:17so trial participants don't look
02:17 --> 02:19like everyone else who gets treatment
02:19 --> 02:22for their cancer in the real world.
02:22 --> 02:24Many people that are not included
02:24 --> 02:26in trials are often older adults.
02:26 --> 02:28People who have other medical
02:28 --> 02:30conditions or people who don't live
02:30 --> 02:32near an academic Medical Center or
02:32 --> 02:35who can't make all the extra visits
02:35 --> 02:36that are often required,
02:36 --> 02:39or people that don't otherwise want to
02:39 --> 02:41participate in trials for some reason.
02:41 --> 02:42Health Services Research,
02:42 --> 02:44which is what I do,
02:44 --> 02:45looks at how cancer treatments
02:45 --> 02:48happen quote in the real world.
02:48 --> 02:49So for example,
02:49 --> 02:51we get to ask questions like how is
02:51 --> 02:53cancer treated within the entire
02:53 --> 02:56country as opposed to just one center?
02:56 --> 02:58Who has access to new treatments?
03:01 --> 03:02What are the outcomes associated
03:02 --> 03:04with these new treatments?
03:04 --> 03:06How much does it cost to
03:06 --> 03:07get these treatments?
03:07 --> 03:09And are there racial or economic or
03:09 --> 03:11other disparities in access to cancer care?
03:16 --> 03:19Wow, I mean that sounds so relevant
03:19 --> 03:21because when you think
03:21 --> 03:24about the subpopulation, as you say,
03:24 --> 03:26who get treated on clinical trials
03:26 --> 03:29being so small and yet the outcomes
03:29 --> 03:31of those clinical trials are
03:31 --> 03:33applied to the entire population,
03:33 --> 03:36it seems to be particularly important
03:36 --> 03:39to see what happens out there in
03:39 --> 03:41the real world on patients who
03:41 --> 03:44may not have looked exactly like
03:44 --> 03:46the people who were in the trials.
03:47 --> 03:48Yes, that's exactly right.
03:48 --> 03:50And the other point about clinical
03:50 --> 03:53trials is that they tend to be
03:53 --> 03:54highly controlled settings, right?
03:54 --> 03:55So patients who are participating
03:55 --> 03:57in a clinical trial not only have
03:57 --> 03:59they gone through the litany
03:59 --> 04:00of inclusion exclusion criteria
04:00 --> 04:02that I've already mentioned,
04:02 --> 04:03just to be enrolled,
04:03 --> 04:05but once they are enrolled they are very
04:05 --> 04:07closely monitored and followed in
04:07 --> 04:09terms of their treatment and their
04:09 --> 04:10outcomes that someone is
04:10 --> 04:12keeping a very watchful eye on them.
04:12 --> 04:15This is very different from a patient
04:15 --> 04:17in the real world who's kind of
04:17 --> 04:19coming into and going out of the
04:19 --> 04:20healthcare system on a regular
04:20 --> 04:22basis and may not be being followed
04:22 --> 04:23as closely.
04:25 --> 04:27So tell us a little bit more about
04:27 --> 04:29your more recent research and what
04:29 --> 04:31you've been doing in this realm.
04:32 --> 04:34Sure, right now
04:34 --> 04:37I currently have a study funded by
04:37 --> 04:39the National Cancer Institute to look
04:39 --> 04:42at oral Anti cancer agent utilization
04:42 --> 04:44in patients with kidney cancer.
04:44 --> 04:47So kidney cancer, like most cancers,
04:47 --> 04:50can either be early stage or
04:50 --> 04:52more advanced stage.
04:52 --> 04:55Stage refers to how far a cancer has
04:55 --> 04:57spread throughout a person's body.
04:57 --> 05:00So for kidney cancer, early stage
05:00 --> 05:03disease is confined to the kidney.
05:03 --> 05:05Whereas for advanced or metastatic disease,
05:05 --> 05:07the disease has learned to travel
05:07 --> 05:09through the bloodstream and has
05:09 --> 05:11spread to other parts of the body,
05:11 --> 05:15such as the lungs, bones or brain.
05:15 --> 05:17So early stage disease is typically treated
05:17 --> 05:20with a surgery or if it's small enough,
05:22 --> 05:24or in an elderly or unhealthy person,
05:24 --> 05:26it is sometimes just observed.
05:26 --> 05:28Advanced kidney cancer for most
05:28 --> 05:30patients is not curable.
05:30 --> 05:31However,
05:31 --> 05:33the treatments for advanced kidney cancer
05:33 --> 05:35have improved dramatically in recent years.
05:35 --> 05:37One of the biggest changes has
05:37 --> 05:40been the development of these oral
05:40 --> 05:42cancer treatments or pills that
05:42 --> 05:44target kidney cancer to help shrink
05:44 --> 05:46or delay its growth.
05:46 --> 05:48These oral cancer treatments have been
05:48 --> 05:51allowing people to live years longer,
05:51 --> 05:53even for people who have what
05:53 --> 05:55traditionally would have been
05:55 --> 05:57considered incurable kidney cancer.
05:57 --> 05:57However,
05:57 --> 06:00these oral treatments are relatively
06:00 --> 06:01new to kidney cancer.
06:01 --> 06:04The first oral agents for kidney
06:04 --> 06:07cancer became available or were
06:07 --> 06:10approved by the FDA in 2005 and 2006,
06:10 --> 06:12but with many similar treatments
06:12 --> 06:14having been discovered since then.
06:14 --> 06:17In fact now
06:17 --> 06:19the 10 first new drugs approved
06:19 --> 06:21for kidney cancer in recent years,
06:21 --> 06:247 out of 10 were oral agents.
06:24 --> 06:26The interesting thing about oral
06:26 --> 06:29anti cancer agents is that they
06:29 --> 06:31represent a shift from how cancer
06:31 --> 06:33treatment used to be delivered.
06:33 --> 06:36So as most folks know, cancer treatment
06:36 --> 06:39used to be almost always intravenous
06:39 --> 06:42or given by injection at the hospital.
06:42 --> 06:44So you know it required patients to
06:44 --> 06:47come to a cancer hospital or clinic
06:47 --> 06:49in order to receive treatment.
06:49 --> 06:49However,
06:49 --> 06:51oral agents are picked up by the
06:51 --> 06:53patient from the pharmacy and taken home,
06:53 --> 06:55and unlike intravenous treatments,
06:55 --> 06:57these oral agents are not taken
06:57 --> 06:59in front of a medical staff.
06:59 --> 06:59Instead,
06:59 --> 07:01they are taken at home by the patients
07:01 --> 07:04when patients come to a cancer clinic
07:04 --> 07:06and receive an intravenous chemotherapy,
07:06 --> 07:07obviously, the doctors know that
07:07 --> 07:09they're getting the treatment there.
07:09 --> 07:11The same is not necessarily
07:11 --> 07:12true for oral agents,
07:12 --> 07:13however.
07:13 --> 07:14Patients can forget to take
07:14 --> 07:15their medications.
07:15 --> 07:17They can forget or delay
07:17 --> 07:18refilling their prescriptions.
07:18 --> 07:19They may not follow the
07:19 --> 07:21instructions as to when and how
07:21 --> 07:23to take their medications exactly,
07:23 --> 07:25or they may choose to stop taking
07:25 --> 07:26their medication altogether,
07:26 --> 07:28particularly if they are concerned that
07:28 --> 07:31they might be having side effects from it,
07:31 --> 07:33or if the cost of filling the
07:33 --> 07:35prescription is too high.
07:35 --> 07:36So my current research has been
07:36 --> 07:39looking at the use of these oral anti
07:39 --> 07:41cancer agents and kidney cancer.
07:41 --> 07:43I'm looking at things like
07:43 --> 07:44who are receiving them.
07:44 --> 07:46Are there any racial or economic
07:46 --> 07:48disparities in access to these drugs?
07:48 --> 07:50Are patients doing as well as they did in
07:50 --> 07:52clinical trials when taking these drugs?
07:52 --> 07:54Because like we were just talking about,
07:54 --> 07:57when a patient when these drugs were
07:57 --> 07:59being first studied in a clinical trial,
07:59 --> 08:01they were being studied in a
08:01 --> 08:02highly controlled setting,
08:02 --> 08:04whereas now in the real world,
08:04 --> 08:05patients are on their own,
08:05 --> 08:07taking them at home,
08:07 --> 08:08and then finally,
08:08 --> 08:09I'm interested in questions
08:09 --> 08:11like can patients
08:11 --> 08:13afford to continue taking these
08:13 --> 08:14drugs based on the cost?
08:15 --> 08:17Those all sound like really
08:17 --> 08:17interesting questions.
08:17 --> 08:22What have you found?
08:22 --> 08:24What's interesting is that we have
08:24 --> 08:27found that by 2015 a little over 1/3
08:27 --> 08:29of patients with kidney cancer with
08:29 --> 08:32renal cell carcinoma specifically,
08:32 --> 08:35which is a subset of kidney cancer,
08:35 --> 08:37were receiving an oral anti cancer
08:37 --> 08:40agent for their advanced kidney cancer.
08:40 --> 08:43We know that previous studies have
08:43 --> 08:45shown that black patients have
08:45 --> 08:48had about a 10% worse mortality
08:48 --> 08:49associated with kidney cancer,
08:49 --> 08:52and we know that this
08:52 --> 08:54difference is not improved with
08:54 --> 08:55the introduction of these
08:55 --> 08:56oral anti cancer agents.
08:56 --> 08:59We wanted to see if access to these drugs
08:59 --> 09:02was a potential driver of these disparities.
09:02 --> 09:03Surprisingly,
09:03 --> 09:06when we looked we didn't see any difference
09:06 --> 09:08in access to these drugs by race,
09:08 --> 09:10ethnicity or any other indicators
09:10 --> 09:11of socioeconomic status.
09:11 --> 09:12However,
09:12 --> 09:14we did see decreased use in these
09:14 --> 09:17oral agents in patients who were
09:17 --> 09:19unmarried, patients who were living
09:19 --> 09:21in the South, and patients who
09:21 --> 09:24were in older age groups and in
09:24 --> 09:25this specific patient population
09:25 --> 09:28that means patients who
09:29 --> 09:32were in the age group 80 plus.
09:32 --> 09:34We were surprised to see that
09:34 --> 09:36access to these drugs was not
09:36 --> 09:38different by race or ethnicity,
09:38 --> 09:40so we next wanted to see if something
09:40 --> 09:42else could be driving disparities in
09:42 --> 09:45kidney cancer outcomes that we know exist.
09:45 --> 09:47So we looked at adherence to these
09:47 --> 09:48medications and what we observed
09:48 --> 09:51was that about half of the patients
09:51 --> 09:53we studied were adhering to the
09:53 --> 09:54medication during the first
09:54 --> 09:56three months of their treatment.
09:56 --> 09:58So we were interested in the patients
09:58 --> 10:00who live in areas with
10:00 --> 10:02high levels of poverty were much less
10:02 --> 10:04likely to take their medication almost
10:04 --> 10:07half as likely as those who did not
10:07 --> 10:09live in high poverty neighborhoods.
10:09 --> 10:09Also,
10:09 --> 10:12we found that patients that had to pay more
10:12 --> 10:14than $200 a month for their medications
10:14 --> 10:16they were about 30% less likely
10:16 --> 10:18to be adherent as compared to
10:18 --> 10:20patients paying less than $200
10:20 --> 10:22a month for their medication.
10:22 --> 10:25So when we take a step back from all this,
10:25 --> 10:27what we think we're seeing is
10:27 --> 10:29that although poor patients are
10:29 --> 10:31able to start these drugs because
10:31 --> 10:33we're not seeing any difference
10:33 --> 10:34in their initiation,
10:34 --> 10:38they may not be able to continue to
10:38 --> 10:41take them or to continue to take them
10:41 --> 10:43as often as they are prescribed,
10:43 --> 10:45because we're seeing decreases in
10:45 --> 10:48the adherence to these drugs and
10:48 --> 10:51that could be affecting the
10:51 --> 10:52differential outcomes that
10:52 --> 10:54we know exist in patients with kidney cancer.
10:54 --> 10:58So when you control
10:58 --> 11:00for socioeconomic status and
11:00 --> 11:03you look at the impact on race
11:03 --> 11:07did you find that that was a
11:07 --> 11:09driver that
11:09 --> 11:11mediated the relationship
11:11 --> 11:13between race and outcomes?
11:15 --> 11:20I think that
11:20 --> 11:21is a good interpretation of
11:21 --> 11:23what we're seeing, right?
11:23 --> 11:25So I think what you're asking is,
11:25 --> 11:27when you look at everything
11:27 --> 11:30in the same model,
11:30 --> 11:32we're seeing that yes,
11:32 --> 11:34poverty is driving this measure
11:34 --> 11:36of adherence, but we're not
11:36 --> 11:37seeing an association with race,
11:38 --> 11:40but I think what you're
11:40 --> 11:41getting at, which is correct,
11:41 --> 11:44is that the kind of
11:44 --> 11:46interaction between race and poverty,
11:46 --> 11:49those are two very closely
11:49 --> 11:52related.
11:52 --> 11:54So yes, seeing an association
11:54 --> 11:57in one might be attenuating
11:57 --> 11:59the association in the other.
12:00 --> 12:03Did you look at that?
12:03 --> 12:06The reason I ask is
12:06 --> 12:09because we've seen a similar thing
12:09 --> 12:12across a number of disease sites.
12:12 --> 12:15I did a study just recently
12:15 --> 12:17looking at breast cancer survivors
12:17 --> 12:20and their use of endocrine therapy,
12:20 --> 12:23which is also an oral agent that
12:23 --> 12:27women take for at least five years
12:27 --> 12:30and very similar to your findings,
12:30 --> 12:32did not find that there was
12:32 --> 12:34necessarily a difference by race,
12:34 --> 12:37which we had thought might have been
12:37 --> 12:39a factor when looking at whether
12:39 --> 12:41people took these medications,
12:41 --> 12:44but we we were looking at the question
12:44 --> 12:47of did you not take this medication
12:47 --> 12:50as prescribed due to cost and we
12:50 --> 12:53thought there may be a
12:53 --> 12:55racial disparity in terms of that.
12:55 --> 12:58But when we looked at it,
12:58 --> 13:01we didn't find a racial disparity
13:01 --> 13:02but really found a
13:02 --> 13:04difference very much as you say
13:04 --> 13:08in terms of poverty and in terms of
13:08 --> 13:10whether or not people had insurance.
13:10 --> 13:14I'm wondering if
13:14 --> 13:16you controlled for poverty
13:16 --> 13:18and whether we still see a
13:18 --> 13:20difference in outcomes between black
13:20 --> 13:22patients and Caucasian patients.
13:22 --> 13:25So in our city we did not
13:25 --> 13:27see a difference by race,
13:27 --> 13:31but we did see a difference by poverty.
13:31 --> 13:34So by both indicators of poverty and
13:34 --> 13:37race were in the model and the
13:37 --> 13:40association by race, as you said,
13:40 --> 13:43for your city was not significant where it
13:43 --> 13:47was for the indicators of poverty level.
13:47 --> 13:48Does that make sense?
13:48 --> 13:50So even though they were
13:50 --> 13:51both in the model race,
13:51 --> 13:53we did not find an association with race,
13:53 --> 13:55but we did with poverty,
13:55 --> 13:57and I guess the point that I was
13:57 --> 13:59trying to make earlier is that
13:59 --> 14:00we know you that
14:00 --> 14:03unfortunately, in this country,
14:03 --> 14:07poverty differentially impacts folks
14:11 --> 14:13by race and ethnicity.
14:13 --> 14:16This is such an
14:16 --> 14:16interesting conversation,
14:16 --> 14:19but we need to take a short
14:19 --> 14:21break for a medical minute.
14:21 --> 14:23Please stay tuned to learn more
14:23 --> 14:25about cancer prevention with
14:25 --> 14:26my guest Doctor Michaela Dinan.
14:26 --> 14:28Support for Yale Cancer Answers
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14:34 --> 14:37Learn more at astrazeneca-us.com.
14:37 --> 14:39This is a medical minute
14:39 --> 14:40about colorectal cancer.
14:40 --> 14:42When detected early,
14:42 --> 14:44colorectal cancer is easily treated
14:44 --> 14:47on highly curable and as a result
14:47 --> 14:49it's recommended that men and women
14:49 --> 14:52over the age of 50 have regular
14:52 --> 14:54colonoscopies to screen for the disease.
14:54 --> 14:56Tumor gene analysis has helped
14:56 --> 14:58improve management of colorectal
14:58 --> 15:00cancer by identifying the patients
15:00 --> 15:02most likely to benefit from
15:02 --> 15:04chemotherapy and newer targeted agents,
15:04 --> 15:06resulting in more patient
15:06 --> 15:07specific treatments.
15:07 --> 15:09More information is available
15:09 --> 15:10at yalecancercenter.org.
15:10 --> 15:14You're listening to Connecticut Public Radio.
15:14 --> 15:15Welcome
15:15 --> 15:17back to Yale Cancer Answers.
15:17 --> 15:20This is doctor Anees Chagpar and
15:20 --> 15:23I'm joined tonight by my guest Doctor
15:23 --> 15:25Michaela Dinan and we're talking
15:25 --> 15:28about cancer prevention and more,
15:28 --> 15:30specifically, right before the break
15:30 --> 15:32Michaela you were telling
15:32 --> 15:34us about your research
15:34 --> 15:36looking at disparities that we
15:36 --> 15:38see in outcomes between African
15:38 --> 15:40American patients and Caucasian
15:40 --> 15:42patients with regards to kidney
15:42 --> 15:44cancer and renal cell cancer.
15:44 --> 15:46In particular,
15:46 --> 15:48you were looking specifically
15:48 --> 15:52then at oral agents and found that really
15:52 --> 15:56race was not a driver of adherence,
15:56 --> 15:59but really poverty was, so a
15:59 --> 16:00couple of questions.
16:00 --> 16:04Has anybody gone back and looked at the
16:04 --> 16:06correlation between race and outcomes?
16:06 --> 16:10That kind of drove your research to
16:10 --> 16:14begin with and took a step back and said
16:14 --> 16:17uncoupling that from poverty is
16:17 --> 16:19it really poverty
16:19 --> 16:22that is the driver of those outcomes,
16:22 --> 16:26or is it really race and the poverty
16:26 --> 16:28by association with nonadherence
16:28 --> 16:30is a separate issue?
16:33 --> 16:36Yeah, so the overall question of
16:36 --> 16:39why is there differential outcomes for
16:39 --> 16:42patients of black race with kidney cancer?
16:42 --> 16:44That's a bigger question and the studies
16:44 --> 16:47that have looked at that question
16:47 --> 16:49some of them have certainly
16:49 --> 16:52included measures of poverty in them and
16:52 --> 16:55have still found a significant association
16:55 --> 16:57between race and outcomes as well.
16:57 --> 16:59You're right and
16:59 --> 17:00our study was specifically a
17:02 --> 17:05subset of that question.
17:05 --> 17:07Because we were specifically
17:07 --> 17:08interested in
17:08 --> 17:12how are oral anti cancer agents either
17:12 --> 17:15contributing or not contributing to this
17:15 --> 17:18kind of pre observed disparity that
17:18 --> 17:21we've seen in kidney cancer patients?
17:21 --> 17:24So because oral anti cancer agents
17:24 --> 17:26were a relatively knew technology
17:26 --> 17:29in the kidney cancer space,
17:29 --> 17:32we wanted to see whether or not
17:32 --> 17:35they were contributing
17:35 --> 17:37to an attenuation of
17:37 --> 17:39this disparity in outcomes,
17:39 --> 17:41or whether it was contributing
17:41 --> 17:43to a potential widening of
17:43 --> 17:45these disparities in outcomes.
17:45 --> 17:46Because
17:47 --> 17:49previous research of both mine
17:49 --> 17:52and other folks looking at the
17:52 --> 17:54emergence of medical technologies
17:54 --> 17:57and cancers has shown that
17:57 --> 18:00sometimes it can go either way.
18:00 --> 18:03It can either help mitigate disparities
18:03 --> 18:06or sometimes it can help widen disparities
18:06 --> 18:07if there's
18:07 --> 18:09an additional element of decreased
18:09 --> 18:11access for certain populations.
18:12 --> 18:14The other question that
18:14 --> 18:17I had was when we were talking earlier
18:17 --> 18:19before the break about the whole
18:19 --> 18:22concept of health services research,
18:22 --> 18:24one of the really important points you
18:24 --> 18:27made is that health services
18:27 --> 18:30research really looks at real world
18:30 --> 18:33outcomes as opposed to trials.
18:33 --> 18:37And clinical trials sadly do not necessarily
18:37 --> 18:40include the population at large,
18:40 --> 18:45and so when we think about clinical trials,
18:45 --> 18:48particularly with oral agents
18:48 --> 18:50for kidney cancer,
18:50 --> 18:53did those include African American patients,
18:53 --> 18:58and were the outcomes in those
18:58 --> 19:01African American patients equivalent
19:01 --> 19:03to Caucasian patients?
19:03 --> 19:06I mean, could that partly explain
19:06 --> 19:08some of these disparities as well?
19:08 --> 19:11That's a great question,
19:11 --> 19:14and again, it points to a broader
19:14 --> 19:17issue where clinical trials in
19:17 --> 19:20general struggle to be representative
19:20 --> 19:23of the general population,
19:23 --> 19:25and there are certainly efforts
19:25 --> 19:28to make those clinical trials more
19:28 --> 19:31representative of the general population.
19:31 --> 19:34But that's something that continues to be
19:38 --> 19:40addressed and certainly race is 1
19:40 --> 19:42area where there have been efforts
19:42 --> 19:45to make them more representative.
19:45 --> 19:48I think 1 area where trials continue to
19:48 --> 19:50struggle with their representativeness
19:50 --> 19:52is with older populations,
19:52 --> 19:55and I think that's something that's
19:55 --> 19:57particularly relevant to cancer
19:57 --> 20:00patients because a lot of cancers tend
20:00 --> 20:02to have median age of diagnosis
20:02 --> 20:06for the 65 plus patient population,
20:06 --> 20:10and yet those people tend to be very
20:10 --> 20:12under represented in trials.
20:12 --> 20:13For instance,
20:13 --> 20:17I think one great example of this is
20:18 --> 20:21with an you emerging medical
20:21 --> 20:23technology which is relevant to
20:23 --> 20:26kidney cancer but also other
20:26 --> 20:29cancers are immunotherapies
20:29 --> 20:31or immune checkpoint inhibitors.
20:31 --> 20:32And again,
20:32 --> 20:34older folks in those clinical
20:34 --> 20:37trials are under represented and
20:37 --> 20:40yet there's this kind of assumption
20:40 --> 20:42that these immune checkpoint inhibitors
20:42 --> 20:45are going to be less toxic than
20:45 --> 20:48the standard or previously
20:48 --> 20:50used cytotoxic chemotherapies.
20:50 --> 20:52And so you know,
20:52 --> 20:55a lot of physicians have been operating
20:55 --> 20:58under the assumption that the toxicity
20:58 --> 21:01profiles of these immune oncology
21:01 --> 21:04agents is less than traditional
21:04 --> 21:06therapies and so have been more
21:06 --> 21:08willing to give these therapies
21:08 --> 21:11to older patients and yet it's
21:11 --> 21:13not really based on clinical trial
21:13 --> 21:15data because that clinical trial
21:15 --> 21:17data doesn't readily exist,
21:17 --> 21:20and so one of the things I'm interested
21:20 --> 21:23in potentially looking at in the
21:23 --> 21:26future is real world utilization of
21:26 --> 21:29these drugs in patients who were again
21:29 --> 21:32not going to be represented and in
21:32 --> 21:34standard trials and whose outcomes,
21:34 --> 21:36whose toxicity profiles may look very
21:36 --> 21:38different than what is typically
21:38 --> 21:40seen in a trial.
21:40 --> 21:43I think that
21:43 --> 21:44it's so important,
21:44 --> 21:47especially when we think about the
21:47 --> 21:49fact that these drugs may affect
21:49 --> 21:51different people differently, right?
21:51 --> 21:54I mean, I think we've seen this even
21:54 --> 21:57in the cardiology world back in the
21:57 --> 22:00day when only men were included in
22:00 --> 22:03some of the the heart attack trials
22:03 --> 22:06and we realized that women's
22:06 --> 22:08heart attacks present differently
22:08 --> 22:11than men's heart attacks and
22:11 --> 22:12drugs may affect different
22:12 --> 22:13genders differently,
22:13 --> 22:16and similarly we may find that
22:16 --> 22:18there are differences based
22:18 --> 22:20on race and other things,
22:20 --> 22:23and so trying to tease out what really
22:23 --> 22:27is at the root of these disparities,
22:27 --> 22:31it really does require some as you call
22:31 --> 22:34it real world kind of investigation.
22:34 --> 22:39Yes, and this is all
22:39 --> 22:42so relevant right now in the times
22:42 --> 22:45of COVID-19 where we have this very big need
22:48 --> 22:51to get vaccines approved and treatments
22:51 --> 22:54approved as quickly as possible.
22:54 --> 22:57But again, we already know that COVID-19
22:57 --> 22:58is affecting
23:01 --> 23:04minority racial and ethnic patients
23:04 --> 23:08differently than it is white patients.
23:08 --> 23:11We know that there's differential
23:11 --> 23:15outcomes.
23:15 --> 23:18we know that there are differential outcomes.
23:27 --> 23:31Covid is affecting
23:31 --> 23:33minority patients much more severely
23:33 --> 23:36than it is Caucasian patients.
23:36 --> 23:39What I think is really important,
23:39 --> 23:41thinking about COVID-19 is that
23:41 --> 23:43you know the clinical trials
23:43 --> 23:46that were done really did have a
23:46 --> 23:48reasonably robust representation of
23:48 --> 23:51minority patients
23:51 --> 23:54and so it's led us to believe
23:54 --> 23:58that the vaccines should work equally
23:58 --> 24:01efficaciously for minority patients.
24:01 --> 24:03For African American patients,
24:03 --> 24:06as it should for Caucasian patients.
24:06 --> 24:09But bringing it back to kind
24:09 --> 24:10of health services
24:10 --> 24:14research and real world science is
24:14 --> 24:16this vaccine hesitancy
24:16 --> 24:20and the fact that we're seeing,
24:20 --> 24:22at least by anecdote, that
24:22 --> 24:25there may be more reluctance
24:25 --> 24:27to really embrace the vaccine
24:27 --> 24:29amongst African Americans,
24:29 --> 24:34who sadly are the most affected and who
24:34 --> 24:38probably could use the vaccine the most.
24:40 --> 24:42So how do you
24:42 --> 24:45address that in terms
24:45 --> 24:49of trying to understand
24:49 --> 24:51data from clinical trials
24:51 --> 24:53are applied in the real
24:53 --> 24:55world?
24:55 --> 24:57Yeah, it's an interesting
24:57 --> 24:58conundrum.
24:58 --> 25:02I think that in terms of people's
25:02 --> 25:05willingness to take a vaccine,
25:05 --> 25:08their willingness to kind of accept data
25:08 --> 25:11from clinical trials as relevant to them
25:11 --> 25:14I think that that largely depends on the
25:14 --> 25:16messaging and inconsistent messaging.
25:16 --> 25:20I think that part of the problem is that
25:20 --> 25:23some of these issues
25:23 --> 25:26are incredibly entrenched and
25:26 --> 25:28systemic issues that are longstanding
25:28 --> 25:31for some of these populations, right?
25:31 --> 25:33And so
25:33 --> 25:35they're not specific to necessarily
25:35 --> 25:37one vaccine or one trial,
25:37 --> 25:40but generations of a health care
25:40 --> 25:42system that hasn't necessarily always acted
25:42 --> 25:45in their best interest, right?
25:45 --> 25:48So I think just going forward
25:48 --> 25:51a consistent message of
25:51 --> 25:52representation for everyone
25:52 --> 25:53concerned for everyone,
25:53 --> 25:57I think is going to be really important
25:57 --> 26:00and I think that that's true of Covid.
26:00 --> 26:02I think that's true of cancer,
26:03 --> 26:06because one of the issues that we're
26:06 --> 26:08talking about today is cancer
26:08 --> 26:11prevention and some of the most important
26:11 --> 26:13factors for cancer prevention are things
26:13 --> 26:16that have been long known as perhaps
26:16 --> 26:19one area where there's not been a
26:19 --> 26:22ton of really large steps and advances, but
26:23 --> 26:26things like not smoking things like
26:27 --> 26:29maintaining a healthy weight,
26:29 --> 26:30eating a healthy diet
26:30 --> 00:-01these are kind of the standards of
26:33 --> 26:35cancer prevention across the board,
26:35 --> 26:38and again, it's certain
26:38 --> 26:40messaging to different
26:40 --> 26:42populations to make sure that
26:42 --> 26:44they are receiving the message.
26:44 --> 26:46Make sure that they understand
26:46 --> 26:48how important it is.
26:48 --> 26:50It is something that needs to be considered.
26:53 --> 26:55I think your point about
26:55 --> 26:57systemic racism and the
26:57 --> 26:59absolutely important tragedies that
26:59 --> 27:02have happened in the US health
27:02 --> 27:04care system over centuries really,
27:04 --> 27:07that has propagated the lack
27:07 --> 27:10of trust for minority populations
27:10 --> 27:12in clinical trials is going to
27:12 --> 27:15be a hard mountain to climb,
27:15 --> 27:18but I think it is so important,
27:18 --> 27:21particularly when we think about not
27:21 --> 27:24only therapeutics and but as you say,
27:24 --> 27:25about prevention.
27:25 --> 27:28Whether we're talking about Covid
27:28 --> 27:30or whether we're talking about
27:30 --> 27:33cancer and so really thinking about all
27:33 --> 27:37of the ways that we can prevent cancer,
27:37 --> 27:39February being Cancer Prevention Month,
27:39 --> 27:42have we seen any impact in terms
27:42 --> 27:45of really driving forward
27:45 --> 27:47some of those behaviors?
27:47 --> 27:50Some of those primary prevention
27:50 --> 27:52techniques that all of us know about
27:52 --> 27:55in terms of cancer prevention.
27:55 --> 27:58Are we making a dent?
27:59 --> 28:01I think so.
28:03 --> 28:05There's a long way
28:05 --> 28:07to go and I think there's a lot more
28:07 --> 28:09to be done in those
28:09 --> 28:11primary areas that you mentioned.
28:11 --> 28:14But for a lot of cancers we do see
28:14 --> 28:17that the incidence of cancer is going down,
28:17 --> 28:19not for all of them, but
28:19 --> 28:21for some of them. Smoking
28:21 --> 28:23related cancers to some extent
28:23 --> 28:25it kind of fluctuates a little bit,
28:25 --> 28:27but for sure we're seeing
28:27 --> 28:28some improvements there.
28:30 --> 28:32One of the easiest things to do
28:32 --> 28:34for younger boys and girls is
28:34 --> 28:36to make sure that they received
28:36 --> 28:37their HPV vaccinations in
28:37 --> 28:39the terms of cancer prevention,
28:39 --> 28:42and certainly since
28:42 --> 28:44the HPV vaccination has come on the scene,
28:44 --> 28:46we've certainly seen decreases
28:46 --> 28:48in HPV related cancers associated
28:48 --> 28:50with utilization of that vaccine.
28:50 --> 28:52And then the other area is that
28:52 --> 28:56we're seeing this kind of
28:56 --> 28:58increase in the number of cancer survivors,
28:58 --> 29:01so even folks who are unfortunate to
29:01 --> 29:03receive a diagnosis, cancer survival
29:03 --> 29:06for many cancers is going up as well,
29:06 --> 29:09and I think some of that you
29:09 --> 29:11know a lot of that,
29:11 --> 29:13is attributable to these advances
29:13 --> 29:15in diagnostic or treatment technologies.
29:15 --> 29:18But to some extent as well
29:18 --> 29:19people trying to,
29:19 --> 29:22you know, reduce or quit smoking,
29:22 --> 29:23eat healthier diets,
29:23 --> 29:25maintaining a healthy body weight.
29:25 --> 29:27All of these things are
29:27 --> 29:28only going to help.
29:29 --> 29:31Doctor Michaela Dinan is an associate
29:31 --> 29:33professor of chronic disease Epidemiology
29:33 --> 29:35at the Yale School of Public Health.
29:35 --> 29:37If you have questions,
29:37 --> 29:38the address is canceranswers@yale.edu
29:38 --> 29:41and past editions of the program
29:41 --> 29:43are available in audio and written
29:43 --> 29:44form at yalecancercenter.org.
29:44 --> 29:47We hope you'll join us next week to
29:47 --> 29:49learn more about the fight against
29:49 --> 29:52cancer here on Connecticut Public Radio.

Information

Cancer Prevention Month 2021 with guest Dr. Michaela Dinan February 14, 2021 Yale Cancer Center visit: http://www.yalecancercenter.org email: canceranswers@yale.edu call: 203-785-4095