ASH 2024 | The importance of assessing frailty in patients with hematological malignancies

So this was actually a presentation that I presented as part of the aging workshop at the ASH annual meeting. In this presentation, I discussed the tools to assess frailty, both clinical and objective biomarkers of frailty. And initially, I discussed that age increases the risk of both frailty and increases the risk of having a hematological malignancy. But also having a hematological malignancy increases the risk of frailty. And this is because of the disease itself, but also because of the treatments and side effects associated with that disease. So hematological malignancies do accelerate biological aging. And when patients have frailty, it has been demonstrated that they experience increased risk of adverse events with treatment, they can experience functional dependence, increased healthcare utilization, and an important issue is that a lot of the patients will end up getting dose reductions and have to discontinue treatment prematurely, and this can compromise the efficacy of treatment. So in order to improve the outcomes of older patients, it’s very important to distinguish frail from non-frail patients because we do not want to over-treat the frail patients and at the same time don’t want to under-treat the non-frail patients. And this is where it’s important to be aware of the various tools to measure frailty. In the clinical setting, there are really different models to measure frailty, and most of them will depend on functional status. The gold standard to measure frailty in oncology and hematology, and endorsed by ASCO, is actually the Comprehensive Geriatric Assessment. And this is a multidimensional assessment of functional status, social support, psychological state, cognition, nutrition, comorbidities, and polypharmacy. In clinical practice, because time is a major barrier to conducting a comprehensive geriatric assessment, a lot of tools have been proposed in order to just be used in the clinical trial and also in the clinical setting in order to measure frailty and divide patients into one, into two or three or more groups of fitness, whether frail, non-frail or frail, intermediate, and fit. And what I showed is that we don’t have any shortage of tools. In multiple myeloma itself, we have more than six tools. We also have tools which are specific to other hematological malignancies or lymphoma, and we have some tools which are generalizable to all malignancies. For example, the Fried frailty phenotype and the cumulative deficit frailty index, which is really just summing all the deficits that a patient has in terms of cognition, nutrition, comorbidities, and providing a score based on a number of deficits. Now, despite the fact that we have so many tools available to measure frailty in the clinical setting, it is very uncommon to see those tools actually being used. And this is also because of the time constraints. There have been recent studies using virtual assessment, using patient-reported data in order to increase uptake of those tools. We also have online calculators available, but the uptake is still low. It would be ideal if we can find objective biomarkers that we can use to quickly decide if a patient is frail and non-frail. Some people have looked at sarcopenia, which is a measure of muscle mass and strength and physical function. It’s very important for me to highlight that sarcopenia is actually very different from frailty. There is an overlap between the two conditions, but as I discussed earlier, frailty is more of a multidimensional assessment that includes functional status in addition to other geriatric domains. So those two concepts should not be used interchangeably. It’s also important for me to highlight that most studies have defined sarcopenia as low muscle mass, but sarcopenia is actually a composite measure of both muscle mass and function. While some studies have shown sarcopenia to be associated with adverse outcomes in patients with hematological malignancies, this has not been consistent across the studies. We actually conducted a study where we looked at the impact of muscle mass on outcomes of patients with multiple myeloma and we measured muscle mass using CT images. What we found is that in this population, muscle mass was not associated with outcomes, but the muscle radiodensity, where low radiodensity means more fat in the muscle and therefore low muscle quality was associated with decreased survival. Another objective biomarker that has been evaluated recently is the senescence-associated secretory phenotype. The rationale behind that is accelerated cellular senescence is thought to be one of the mechanisms of frailty. And this is also something that is induced by cancers. One of the ways to measure cellular senescence in the blood is to measure this secretory phenotype, which is a collection of molecules which create an inflammatory state in the body. I shared with the group data from one of the aging labs at Mayo Clinic looking at the senescence-associated secretory phenotype in non-cancer patients. I shared that the senescence-associated secretory phenotype was indeed associated with age, with frailty, and adverse health outcomes. I then discussed a pilot study which I conducted with Dr Megan Weivoda at Mayo Clinic looking at the senescence-associated secretory phenotype in older patients with multiple myeloma. We divided patients into frail and non-frail at the time of diagnosis using a cumulative deficit index. We looked at the biomarkers which were previously studied in a non-cancer population and compared that profile between frail and non-frail patients. And we did actually find a statistically significant difference in the concentration of those specific molecules, which I can name, activin A, interleukin-15, FAS, osteopontin, among a few others, to be associated with frailty. Now, this is just a pilot study. The sample size was small, but it does provide a signal that perhaps those markers can have a role in the future to predict frailty. So at this time, we don’t really know what is the best way to measure frailty, whether patient-reported data, whether it is the clinical assessments, the sarcopenia, the objective biomarkers. But it is definitely not what we call the eyeball test, which is when a clinician judges frailty based on a brief encounter with the patient without actually delving into functional status, whether with questionnaires or with objective measures. I also highlighted that frailty should be repeated at different intervals throughout the treatment journey. Because at the time of diagnosis, frailty can be either due to the disease itself, or the patient may actually be frail. And if we assign treatment based on the frailty status at the time of diagnosis, then patients who do end up improving after treatment has started are at risk of being undertreated. And I also shared the results of a recent study by Dr Zwiegman and her group showing that a lot of patients change their frailty status throughout treatment. And this could be either improvement or worsening due to the side effects of treatment. So I think this is a very important step to highlight that whichever way or tool we use to measure frailty, it’s important to do that continuously throughout the treatment.

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