CLL is unique because there is often a significant lag in time between when the diagnosis is made and the first treatment is needed. Since complete blood counts (CBC's) are fairly routine, and CLL sticks out like a sore thumb, patients can often watch their disease for a long time before needing to start on treatment. This can create a dangerous "paralysis by analysis" situation where careful consideration of all options leaves a patient unable to decide on what to do - the downsides of ANY treatment can look really big when they are staring you in the face.
When it comes to treatment decisions, I need to make one an argument for "watch and wait." We are so conditioned to believe that early treatment improves outcomes in cancer that watch and wait feels very counterintuitive. I have been really struck by several recent publications that evaluate "clonal evolution" in CLL. I've written about them in two prior posts linked here and here.
I could quickly sumarize by saying that CLL may start as only one clone, but it can often give rise to several clones over time. If some of the clones that evolve over time are "smarter" (ie. have chemotherapy resistance, faster growth, predisposition to transform - see my post on the "new markers" and "CLL Prognosis") - it may be to your advantage to leave the "stupid" clone alone.
Treatment often eliminates the "stupid" clone and gives more room for the "smarter" clone to take over. In CLL, we take it for granted that high risk markers like 17p, 11q, BIRC3, P53 mutations are more common in relapsed disease. What we haven't considered until recently is that our treatment may be selecting for these higher risk markers.
So I am a big fan of "watch and wait" until treatment is needed. Please see my post on "when to treat CLL" for more of a discussion about when watch and wait is no longer indicated.
But sometimes - we can't wait any longer.....
I've had a fun time serving on a leadership team for a large registry study called the "Connect CLL Disease Registry" sponsored by Celgene. Other leaders on the study include Neil Kay, Michael Keating, Ian Flinn, Mark Weiss, Nicole Lamana, Chris Flowers etc. We've collected a lot of data about how patients with CLL are treated throughout the United States. We've reported some of our data at American Society of Hematology but we've really only just gotten started.
In the United States, most patients treated off of a clinical trial are going to receive either FCR (Fludarabine, Cyclophosphamide, Rituxan), FR (get rid of the cyclophosphamide), or BR (bendamustine, rituxan). Chlorambucil is a respectable option for the elderly population with other medical issues but is generally reserved for patients you just can't treat with chemotherapy (editorial - I think chlorambucil is underutilized as a treatment option in elderly patients - just telling you what the patterns are out there). There is also a surprising amount of single agent rituximab use out there.
Thus far, there have been NO PUBLISHED REPORTS that compare FCR to BR in a prospective randomized study (Gold standard for evidence). The study is being done by the Germans but we don't expect data from that study soon. Chaya Venkat did a very thoughtful evaluation on her blog CLL Topics looking at the data from the single arm phase II study of BR in the front line. I would direct the motivated reader to her post.
To be very clear - when evidence is lacking - opinion abounds. Right now in 2013 we do not know what the best front line therapy actually is. FCR has been the leader of the pack for a number of years, but there are a lot of reasons FCR isn't always the right answer for all patients.
Without a clear answer - opinion is fair game - I will share mine. My first choice for therapy is to consider participation in a clinical trial. That is the "standard answer" in the NCCN guidelines, but it is more true in CLL today than just about any other disease. New investigational treatments like ibrutinib, idelalisib, GA-101, ABT-199, TRU-016 are exploiting the biology of CLL and bringing forward a new generation of treatments for patients with CLL that are currently only available in clinical trials.
The Germans have wonderful terminology that segregates patients into different groups of patients called the "go-go" population, the "slow go" population and the "no go" population for the patients who are young and fit vs the patients in whom you need to have more caution, vs the patients that have a ton of medical issues and the goal is to do no harm. They use a tool called the "cumulative illness rating scale" aka CIRS which has actually been around for quite a few years but gives you a tool to mathematically quantify how many medical problems other than CLL a patient has. The sicker you are - the less intensively you can treat the CLL.
I look at a patient and ask myself if they are "fit" for a fludarabine based regimen. Fludarabine is a good drug - but it has some potential draw backs. It is cleared by the kidneys, so if the kidneys are less than ideal - problems start to increase. Since kidney function declines with age, and CLL is more common in the elderly, the kidneys often guide my decision making. Kidney function can be measured by the "creatinine" which is a standard measure on a chemistry panel. Take age, gender, creatinine and you can calculate a "glomerular filtration rate" or GFR. When that number dips below 60, my caution level goes up quite a bit.
So what problems can fludarabine cause? It can lower the immune system, cause prolonged supression of the bone marrow, and worsen a hemolytic anemia. Therefore, in a patient with bad lungs from smoking (COPD) who has had pneumonias, has a GFR well under 60, or maybe already has signs of the immune system attacking the red blood cells or the platelets - I avoid fludarabine based chemo and lean toward bendamustine based treatment.
If a patient is "fit" for fludarabine, the choice is either FR or FCR. There is no question that the addition of the cyclophosphamide adds a punch - both to the CLL and to the patient. The Germans have published a study looking at F vs FC (pre-rituximab era). This was also studied in the US by the Eastern Cooperative Oncology Group. The English also looked at this in the CLL4 study. The English did a good job looking at biomarkers in their effort and came to the conclusion that patients with the 11q deletion did a better when they had the cyclophosphamide added to fludarabine. There has been some debate whether the cyclophosphamide is necessary in the absence of 11q deletion. I tend to reserve it for the particulary fit younger patient or the patient with the 11q but I acknowledge this is an opinion and there are plenty of bright CLL docs that would disagree and give it more broadly. It goes without saying that any regimen would include rituxan as shown to us by the German CLL study group.
If a patient is "unfit" for a fludarabine regimen the decision in my mind comes down to Bendamustine versus chlorambucil. Bendamustine is more effective than chlorambucil but perhaps a little more intensive. Bendamustine does not require the kidneys for elimination - so when GFR is a little lower, this can be a good option. For an elderly patient, chlorambucil may still be a good option and should not be disregarded completely. Our patterns of care study indicated that it is the treatment decision of only about 10% of patients over the age 75 and much less common in younger individuals. If I give bendamustine, I virtually always give it with rituximab.
There are some special populations to consider. The biggest one in my mind is the 17p deleted group. We know that cells with the 17p deletion don't respond well to DNA damaging chemotherapy (FCR, BR, etc). I always want to know, "how many 17p deleted cells they have?" Keep in mind that FISH testing gives you a rough percentage of cells with a particular marker. A patient with 5% 17p deleted cells is very different to me than a patient with 85%. The first patient is likely to respond reasonably well to treatment but relapse earlier with a disease that is predominantly 17p deleted. The latter patient is likely to respond very poorly to FCR (short duration of response or limited response at all).Pretty soon we will also be looking at SF3B1 and BIRC3 in this setting and asking the same questions.
For a patient with a large population of 17p deleted cells, there are regimens out there now that use high doses of steroids in combination with either rituximab or campath. We know that campath is one of the few drugs that largely ignores the 17p deletion status but it is not a drug that is easy to use. It definitely lowers the immune system quite a bit and you need to be careful about infections with things that you don't always consider (PCP, CMV, shingles, etc.). Most docs who use campath give preventative antibiotics for each of these - which can definitely be a mouthfull of pills. Campath has recently been taken off the market - but you can still get it. It is a little cumbersome (ie. given three times per week for 12-16 weeks) but it can be quite effective in this setting. Frankly, if I can buy a patient a year or two without really messing up their genome, I think I will be able to get them some of the research drugs that appear quite effective against 17p deletetion CLL including ibrutinib or ABT-199.
Of course, not many patients are appropriate for allogeniec stem cell transplant, but these might be the folks. I am also really intrigued by the "engineered T-Cell" therapies being developed that may be a good option for these patients that don't respond well to typical chemotherapy.
That is the basics of my thinking for patients with untreated CLL that need some form of treatment. This is no substitute for the advice of your own doc, but at least how I think through the issue. There are a number of modifications to what I wrote that would be entirely acceptable. With any luck this will all be outdated in a few years as new options come on line.
Hope that helps.
Translating basic science and clinical breakthroughs into language we all can understand
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Tuesday, March 26, 2013
Saturday, March 16, 2013
Molecular Prognosis in DLBCL
There is a new test for patients with diffuse large B cell lymphoma (DLBCL) that has the potential to alter the way we manage the disease. R-CHOP is very good treatment for approximately 2/3 of patients with DLBCL who are cured - but that still leaves quite a bit of room for improvement. What we really need is a way to identify the patients who are high risk right from the outset. That will enable us to concentrate our efforts to improve R-CHOP in the high risk group - and perhaps even consider ways to make therapy less intense for the low risk patients (in clinical trials only for now).
As you probably know from my prior posts - there are a bunch of different types of lymphoma. My post about telling them all apart has been the most frequently visited page on my blog.
What makes lymphoma interesting to manage is that a two cases of a specific disease like DLBCL that may look identical under the microscope can be very different biologically. Those differences may have consequences for treatment, prognosis, etc. We are now in an era where we can begin to measure those biologic differences and figure out what to do about it.
In the past DLBCL was DLBCL was DLBCL. If you looked into the microscope and saw larger cells (centroblasts) and they infiltrated the lymph node in a "diffuse" pattern and applied a few extremely simple tests to prove it was of B cell origin - the diagnosis was DLBCL. We really didn't understand that cases had fundamental biologic differences and they were pretty much treated all the same. You gave them all CHOP (rituxan wasn't around yet) and about half of patients did well and half didn't.
Understandably docs and patients want to be able to predict how an individual patient will do right from the outset. Researchers looked at large data sets and realized several "clinical variables" (i.e. easy lab tests or patient characteristics) could segregate patients into risk categories. By looking at a patients age, stage, ldh (blood test), patient functional status (ECOG score), and the number of places where the lymphoma affected the body outside of the lymph nodes - you could calculate a score called the international prognostic index (IPI). After rituxan improved things - the IPI was revised - giving the R-IPI which can be calculated online.
IPI and the R-IPI were good for their day, but in 2000 a new technology called "Gene expression profiling" was applied to a large group of DLBCL samples. A buddy of mine from Stanford named Ash Alizadeh (the smartest I've ever known) published a paper in the journal Nature that helped identify two subgroups of DLBCL called "germinal center DLBCL" (GCB) or "activated B cell DLBCL" (ABC).
This technology measures a differential quantities of a specific type of RNA called mRNA. mRNA is called "messenger" RNA because it is synthesized in the nucleus of the cell by being copied off the DNA template. It then goes to the cytoplasm where it serves as a "messenger"for the protein synthesis machinery. Different types of lymphoma need to make different proteins. By measuring the mRNA you can tell these lymphomas apart.
One of the cool aspects of this technology is that you can simultaneously measure THOUSANDS of mRNA's at once. You can let the data sort itself out into patterns (unsupervised analysis) or you can ask questions of the data (supervised analysis). One thing to shake out of letting the patterns sort themselves out was that there are two main types of DLBCL - the Activated B Cell (ABC) and the Germinal Center B Cell (GCB) subtypes. Understanding that there are two main types of DLBCL has been a big advancement in the disease. We are now learning that underneath this differential expression are unique mutations that probably cause the diseases in the first place.
The main categories of DLBCL to emerge from this was the Germinal Center B Cell / Activated B cell subtypes. The GCB subtype do a lot better than the ABC subtype. Since those patients with ABC generally do not do as well, there have already been a number of clinical trials focusing on that subgroup specifically (such as the addition of velcade to R-CHOP for this group).
The were two big headaches with this technology that prevented it from becoming a standard test. The first is that it has required a chunk of tissue that was taken directly from the patient and put into the freezer instead of being immersed in paraffin which is the standard in most pathology labs. The only "frozen" samples were pretty much the domain of major research centers (these specialized freezers are expensive). That meant that the vast majority of patients who had a biopsy to get the diagnosis might have to have a second biopsy if you wanted to get the expression profile. The second problem is that the "chips" that enabled you to measure thousands of genes at once were expensive. Those barriers essentially kept this knowledge out of routine practice.
There have been a number of efforts to substitute a commonly used technology called "immunohistochemistry" which is pretty inexpensive and readily available. Unfortunately several groups have developed different testing criteria, it can be hard at times to get labs to agree on the results etc. Even with these limitations though, more and more people are getting this testing done as part of their work-up.
In an effort to make the expression profiling technology more applicable to clinical samples, the Ron Levy laboratory (where I proved I have no business working in the laboratory) went back to the ABC / GCB expression profiling data sets and asked the question - which markers best predicted prognosis - both good and bad (supervised analysis). They pulled out six genes that helped determine which patients had high or low risk.
Unfortunately these samples came from the pre-rituxan era and it was unclear if the gene would hold their value in the rituxan era. Researchers then went and rounded up a bunch of clinical samples from patients treated with either CHOP or R-CHOP. They found that a few of the markers were not as good but two main markers stood out in their ability to predict outcome - those were LMO2 (which helped segregate GCB/ABC pretty well and TNFRSF9 (aka CD137 or 4-1BB) which served as a marker of the surrounding immune system. By focusing on just two markers - you could run the test without using an entire gene expression chip (making it a lot less expensive). Furthermore, they were able to use a newer technology to extract the mRNA from samples embedded in paraffin. This allowed access to the test for routine clinical samples. The results come from a mathematical formula that converts expression into a score and spits out high / intermediate / low risk.
Finally - a test that can be run on routine clinical samples, that is relatively easy, and reflects tumor biology instead of just clinical variables. The next question was what happens to IPI. Fortunately the results enhanced each other instead of just replicating one another. They found that you could combine the IPI and the biologic score to further refine the prediction model.
So where does this go from here?
Right now, a lot of frontline DLBCL studies require certain IPI in order to enroll (commonly an IPI score of 3 or higher) I think this test could be integrated into clinical trials to enlarge the population of eligible patients. It is also useful for the newly diagnosed patients who wants to understand their prognosis better. Right now, outside of a clinical trial, I am not totally sure what to do for the patient who has a high score. Do I give them R-CHOP or do I try to intensify their therapy. At this point, I am unclear what alternative therapy to choose - perhaps R-EPOCH?
Anyhow, I think this is a step forward in DLBCL. Hopefully we will see more data sets that validate the test. It can be ordered today. I am optimistic that this will take a lot of science developed over the last 13 years and adjust our management of DLBCL - particularly for that group that isn't cured with R-CHOP.
Thanks for reading.
(Disclosure- I worked in Ron Levy's lab and I personally know Izidore Lossos - I think they are great researchers so I tend to believe their conclusions - I have no financial relationship pertaining to this test to disclose)
As you probably know from my prior posts - there are a bunch of different types of lymphoma. My post about telling them all apart has been the most frequently visited page on my blog.
What makes lymphoma interesting to manage is that a two cases of a specific disease like DLBCL that may look identical under the microscope can be very different biologically. Those differences may have consequences for treatment, prognosis, etc. We are now in an era where we can begin to measure those biologic differences and figure out what to do about it.
In the past DLBCL was DLBCL was DLBCL. If you looked into the microscope and saw larger cells (centroblasts) and they infiltrated the lymph node in a "diffuse" pattern and applied a few extremely simple tests to prove it was of B cell origin - the diagnosis was DLBCL. We really didn't understand that cases had fundamental biologic differences and they were pretty much treated all the same. You gave them all CHOP (rituxan wasn't around yet) and about half of patients did well and half didn't.
Understandably docs and patients want to be able to predict how an individual patient will do right from the outset. Researchers looked at large data sets and realized several "clinical variables" (i.e. easy lab tests or patient characteristics) could segregate patients into risk categories. By looking at a patients age, stage, ldh (blood test), patient functional status (ECOG score), and the number of places where the lymphoma affected the body outside of the lymph nodes - you could calculate a score called the international prognostic index (IPI). After rituxan improved things - the IPI was revised - giving the R-IPI which can be calculated online.
IPI and the R-IPI were good for their day, but in 2000 a new technology called "Gene expression profiling" was applied to a large group of DLBCL samples. A buddy of mine from Stanford named Ash Alizadeh (the smartest I've ever known) published a paper in the journal Nature that helped identify two subgroups of DLBCL called "germinal center DLBCL" (GCB) or "activated B cell DLBCL" (ABC).
This technology measures a differential quantities of a specific type of RNA called mRNA. mRNA is called "messenger" RNA because it is synthesized in the nucleus of the cell by being copied off the DNA template. It then goes to the cytoplasm where it serves as a "messenger"for the protein synthesis machinery. Different types of lymphoma need to make different proteins. By measuring the mRNA you can tell these lymphomas apart.
One of the cool aspects of this technology is that you can simultaneously measure THOUSANDS of mRNA's at once. You can let the data sort itself out into patterns (unsupervised analysis) or you can ask questions of the data (supervised analysis). One thing to shake out of letting the patterns sort themselves out was that there are two main types of DLBCL - the Activated B Cell (ABC) and the Germinal Center B Cell (GCB) subtypes. Understanding that there are two main types of DLBCL has been a big advancement in the disease. We are now learning that underneath this differential expression are unique mutations that probably cause the diseases in the first place.
The main categories of DLBCL to emerge from this was the Germinal Center B Cell / Activated B cell subtypes. The GCB subtype do a lot better than the ABC subtype. Since those patients with ABC generally do not do as well, there have already been a number of clinical trials focusing on that subgroup specifically (such as the addition of velcade to R-CHOP for this group).
The were two big headaches with this technology that prevented it from becoming a standard test. The first is that it has required a chunk of tissue that was taken directly from the patient and put into the freezer instead of being immersed in paraffin which is the standard in most pathology labs. The only "frozen" samples were pretty much the domain of major research centers (these specialized freezers are expensive). That meant that the vast majority of patients who had a biopsy to get the diagnosis might have to have a second biopsy if you wanted to get the expression profile. The second problem is that the "chips" that enabled you to measure thousands of genes at once were expensive. Those barriers essentially kept this knowledge out of routine practice.
There have been a number of efforts to substitute a commonly used technology called "immunohistochemistry" which is pretty inexpensive and readily available. Unfortunately several groups have developed different testing criteria, it can be hard at times to get labs to agree on the results etc. Even with these limitations though, more and more people are getting this testing done as part of their work-up.
In an effort to make the expression profiling technology more applicable to clinical samples, the Ron Levy laboratory (where I proved I have no business working in the laboratory) went back to the ABC / GCB expression profiling data sets and asked the question - which markers best predicted prognosis - both good and bad (supervised analysis). They pulled out six genes that helped determine which patients had high or low risk.
Unfortunately these samples came from the pre-rituxan era and it was unclear if the gene would hold their value in the rituxan era. Researchers then went and rounded up a bunch of clinical samples from patients treated with either CHOP or R-CHOP. They found that a few of the markers were not as good but two main markers stood out in their ability to predict outcome - those were LMO2 (which helped segregate GCB/ABC pretty well and TNFRSF9 (aka CD137 or 4-1BB) which served as a marker of the surrounding immune system. By focusing on just two markers - you could run the test without using an entire gene expression chip (making it a lot less expensive). Furthermore, they were able to use a newer technology to extract the mRNA from samples embedded in paraffin. This allowed access to the test for routine clinical samples. The results come from a mathematical formula that converts expression into a score and spits out high / intermediate / low risk.
Finally - a test that can be run on routine clinical samples, that is relatively easy, and reflects tumor biology instead of just clinical variables. The next question was what happens to IPI. Fortunately the results enhanced each other instead of just replicating one another. They found that you could combine the IPI and the biologic score to further refine the prediction model.
So where does this go from here?
Right now, a lot of frontline DLBCL studies require certain IPI in order to enroll (commonly an IPI score of 3 or higher) I think this test could be integrated into clinical trials to enlarge the population of eligible patients. It is also useful for the newly diagnosed patients who wants to understand their prognosis better. Right now, outside of a clinical trial, I am not totally sure what to do for the patient who has a high score. Do I give them R-CHOP or do I try to intensify their therapy. At this point, I am unclear what alternative therapy to choose - perhaps R-EPOCH?
Anyhow, I think this is a step forward in DLBCL. Hopefully we will see more data sets that validate the test. It can be ordered today. I am optimistic that this will take a lot of science developed over the last 13 years and adjust our management of DLBCL - particularly for that group that isn't cured with R-CHOP.
Thanks for reading.
(Disclosure- I worked in Ron Levy's lab and I personally know Izidore Lossos - I think they are great researchers so I tend to believe their conclusions - I have no financial relationship pertaining to this test to disclose)