Dyslipidemia in Cancer Patients – Evolving Context, New Challenges

The 2018 American Heart Association/American College of Cardiology (AHA/ACC) multisociety cholesterol guideline invigorated the 2013 risk-adapted approach to the management of dyslipidemia.1 It expanded the spectrum of risk-enhancing factors to include pregnancy-associated complications and chronic inflammatory conditions. The 2018 guideline also defines the role of coronary artery calcium scan in improving the specificity of risk assessment in cases where the health care provider and patient are unclear about whether a person should be on a statin. This integrative consensus statement represents a valuable refinement of the 2013 guideline; however, we may be able to further improve upon it if we deepen our understanding of optimal hypercholesterolemia management in cancer patients.

For many years, a diagnosis of cancer has triggered a shift in the focus from long-term to more acute management. If a rapidly-lethal (cancer) condition was detected, the merit of controlling a generally-latent (atherosclerotic) process was deemed a lower priority. As a result, clinical investigations in cardiovascular medicine were not seen as highly relevant to a large number of patients with cancer. Over the past few decades, however, the trajectory of cancer discovery has allowed for significant improvements in both life expectancy and quality of life. Patients with cancer are now more likely than ever to achieve a remission and become long-term survivors.

Patients with early-stage breast cancer, for example, are currently more likely to die from CVD than from their original neoplasm.2 Patients with Hodgkin lymphoma who are two decades out from treatment experience morbidity and mortality predominantly due to cardiovascular causes and therapy-related malignancies (and much less from their underlying cancer).3 These intriguing statistics are explained by the longer survival of cancer patients and the shared risk-factors of cardiovascular and cancer conditions, as well as the direct and indirect interference of anti-cancer drugs (including cytotoxic and targeted therapies) with numerous cardiac cellular pathways. As cancer and CVD inflict an increasingly greater burden on an aging society, there is a clear need to balance the care of the lipid and metabolic disorders and that of the cancer.

Cholesterol optimization could be considered as universally beneficial, and a case could be made that all cancer patients with a guideline-derived clinical indication should be offered a statin. The reality, however, is more complicated. The management of dyslipidemia requires follow-up blood tests and possible dose titrations, and occasionally leads to adverse effects. As such, routine implementation of lipid-lowering strategies that is disconnected from the clinical context is destined to have limited utility, especially in sub-groups of cancer patients with an expected survival of less than 3 years. (Table 1)

Table 1: Proposed Framework for Integrating CVD- and Cancer-Specific Factors in Lipid-Lowering Decision-Making

Cardiovascular Risk Profile

Cancer-Specific Status

Suggested Recommendation

Low-risk, no ASCVD

Early-stage, definitive treatment

Heart-healthy lifestyle

Low-risk, no ASCVD

Advanced-stage, curative intent

Heart-healthy lifestyle

Low-risk, no ASCVD

Advanced/metastatic, palliative

Heart-healthy lifestyle

Intermediate-risk, no ASCVD

Early-stage, definitive treatment

Lifestyle modification, statin

Intermediate-risk, no ASCVD

Advanced-stage, curative intent

Lifestyle modification, statin

Intermediate-risk, no ASCVD

Advanced/metastatic, palliative

Heart-healthy lifestyle
(pharmacologic intervention in select cases depending on frailty and expected morbidity/mortality)

High-risk, ASCVD

Early-stage, definitive treatment

Lifestyle modification, statins/ezetimibe, plus/minus PCSK9 inhibitors

High-risk, ASCVD

Advanced-stage, curative intent

Lifestyle modification, statins/ezetimibe, plus/minus PCSK9 inhibitors

High-risk, ASCVD

Advanced/metastatic, palliative

Heart-healthy lifestyle
(pharmacologic intervention in select cases depending on frailty and expected morbidity/mortality)

Statins in Cancer Patients – Historical Pitfalls in Study Design and Inclusion

Why haven't we developed clear algorithms for cancer patients that would help determine when lipid lowering is of high value and when it is less valuable? Part of the reason is that, presumably to protect patients from unnecessary interventions, individuals with cancer have been traditionally disqualified from clinical trials in cardiovascular medicine. In addition, the designers of clinical trials understandably wanted to ensure that cancer patients and the non-cardiovascular endpoints they would likely experience were excluded from clinical studies. The historic context of that trial-enrolment pattern is worth noting.

In 1980, when Merck initiated the first clinical trial of lovastatin, the 5-year survival for all cancers was 50%.4 Of those diagnosed with lung cancer, less than one of five patients were alive at the five-year mark.5 Thirty years later, these odds have substantially improved and the aggregate 5-year survival rates for all cancers now approximate 70%.6 A larger subset of patients are cured or achieve prolonged remissions, a phenomenon that has given rise to the survivorship care movement. However, despite the steep improvement in the outcome of cancer patients, clinical trials have not adapted to the new survival landscape.

Randomized controlled investigations of lipid-modifying agents largely exclude patients with any form of non-cutaneous, invasive malignancy. By doing so, we lack critical data regarding the utility of cardio-protective interventions in cancer patients at various levels of atherosclerotic risk. As the bulk of cancer patients who achieve long-term remissions continues to grow, the pool of individuals with both a malignancy and an elevated atherosclerotic risk proportionately increases.

In addition, clinical trials in preventive cardiology report the number and percentage of participants according to several standard clinical strata: those with hypertension, diabetes mellitus, history of myocardial infarction and history of stroke, but not history of cancer. The scientific rationale for characterizing study groups according to cardiovascular risk factors is to define the baseline cardiovascular risk profile of the cohort and to ensure that there are no confounding factors between the intervention and control arms. However, some of these routinely-reported cardiovascular entities carry 5-year mortality rates that are even higher than that of various malignancies. Myocardial infarction, for instance, was associated with mortality rates of 24% at 1 year, 51% at 5 years and 65% at 8 years of follow up in a large Medicare cohort treated from 2001 to 2006.7 Heart failure has been estimated to have a median overall survival of 2.1 years.8 These survival figures are inferior to those of indolent forms or early and resectable stages of cancer.

Multiple risk factors – obesity, sedentary lifestyle, nicotine use and diabetes mellitus – are shared by both classes of disorders. Secondly, we have learned that inflammation serves as a dual biologic mediator of both carcinogenesis and arterial thrombosis. As CANTOS (Canakinumab Anti-Inflammatory Thrombosis Outcomes Study) illustrated, biochemical suppression of inflammation lowers the incidence of cardiovascular events (and also cancer mortality) independent of the lipid status.9 Lastly, the cancer-CVD pathobiological overlap is also evident in hematologic neoplasms with peculiar somatic mutations in myeloid cells – termed clonal hematopoiesis of indeterminate potential (CHIP) – serving as the harbinger of both acute leukemia and CVD, possibly via expression of inflammatory chemokines.

Assessing Statin Effectiveness – The Case of Elderly and Renal Dysfunction

What other patient populations have been under-represented in clinical trials testing the efficacy of statins, presumably due to a desire to avoid endpoints not mitigated by statins that may render the study to be statistically insignificant? One such group is the elderly. Under-inclusion in clinical trials has been a major deficit in this group at high risk of cardiovascular events. Most trials have excluded patients above the age of 75, and there are only few, mostly retrospective, statin studies that focus on senior populations.

Individuals with renal dysfunction represent another patient population where the evidence for statin benefit continues to evolve. Statins and ezetimibe do not provide significant benefit in patients with end-stage renal disease (ESRD) on hemodialysis.10 This is likely due to high competing risks in that population which statins do not have a chance to prevent. However, patients with mild renal impairment do benefit from statins which is due to their cumulative lipid-lowering (and possibly pleiotropic) effects in a milieu known for its high vascular risk. There is a conceivable renal function limit, therefore, beyond which lipid-lowering interventions fail to reduce the cardiovascular event rate (as survival free of major comorbidity is simply not long enough to accrue the benefits of lipid control).

Similar to renal function and age, cancer should be viewed as a spectrum. Setting age and creatinine clearance thresholds is necessary to protect clinical trial participants and maximize a study's ability to address a clinical hypothesis. Defining an individual patient 'cancer survival score' (based on patient age, performance status and comorbidities; cancer stage and biology; tumor response to treatment, etc.) could help quantify the merit of preventive cardiovascular interventions in view of the patient's neoplasm. This is important because, while the prognosis of some cancers (i.e., breast, colon) is good in most cases, other cancers (i.e., pancreas, leukemia) still have a very poor prognosis in most patients.

The published research about the observational association of statins on the clinical outcomes of cancer patients is methodologically problematic. Several population-based cohorts suggested a survival benefit but others failed to show the same.11-13 These investigations are plagued by the observational or retrospective nature of most of the sub-studies, the significant unadjusted confounding factors (i.e., cancer stage, ASCVD risk), and the healthy-adherer bias (healthy patients are more likely to initiate and comply with statins). Longitudinal prospective studies with careful accounting of baseline comorbid conditions that could contribute to CVD and cancer mortality are unfortunately lacking.

Enhancing our Knowledge Base – Steps Forward

Formulating a practical roadmap, based on the current knowledge gaps in the understanding of dyslipidemia in cancer patients, is essential. First, clinical trialists should reverse the sweeping cancer-as-exclusion-criteria policy. It would be reasonable to allow inclusion of patients with early-stage disease, those who have completed definitive, "curative-intent" treatments, and those with a stable, low-grade metastatic cancer (i.e., neuroendocrine, prostate). Data about the effect of lipid-lowering in cancer patients should be retrospectively collected from existing national and institution-specific registries. In addition, prospective studies of PCSK9 inhibitors or small interfering RNA molecules should recruit patients with a history of cancer but good prognoses and report the degree of inclusion, type/stage of cancer, and the cancer-specific efficacy and safety.

A valuable contribution to CVD prevention in cancer patients could be in the form of dedicated cardio-oncology teams. Such teams would evaluate each cancer patient individually, assess their cancer prognosis alongside with CVD risk, and very important, integrate patient's preferences into the treatment plan. They would then provide individualized recommendations on the mid- and long-term CVD preventive management of each cancer patient. The involvement of such teams would be in at least at two key time points: at the time the cancer is first diagnosed, and at the time of cancer control or progression so that the updated risk assessment accounts for the fact that the patient has survived the cancer as well the previous lines of cancer therapies. The fact that randomized clinical trial evidence is currently unavailable makes this expert team approach a good alternative.

As we gain more insights into the overlapping biology of inflammation, dyslipidemia, atherosclerosis and cancer, we should take a step back and appreciate how far we have gone. In both cardiology and oncology, we have refined our diagnostic capabilities, enhanced the sensitivity of predictive circulating and radiographic markers and pushed treatment options beyond all expectations. Yet, perhaps as a result of the incredible progress, we have neglected to notice a demographic shift in cancer survival that strongly impacts the prevention and treatment of cardiovascular conditions. It is time we learn how to better inform our lipid management decisions to patients with a history of cancer.

References

  1. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2019;73:e285-350.
  2. Park NJ, Chang Y, Bender C, et al. Cardiovascular disease and mortality after breast cancer in postmenopausal women: results from the Women's Health Initiative. PLoS One 2017;12:e0184174.
  3. van Leeuwen FE, Ng AK. Late sequelae in Hodgkin lymphoma survivors. Hematol Oncol 2017;35:60-6.
  4. U.S. Department of Health and Human Services National Cancer Institute. SEER Cancer Statistics Review 1973-1999. https://seer.cancer.gov/archive/csr/1973_1999/allsites.pdf. Accessed Jul 30, 2019.
  5. U.S. Department of Health and Human Services National Institutes of Health. NIH Fact Sheet: Cancer. https://report.nih.gov/nihfactsheets/viewfactsheet.aspx?csid=75. Accessed June 30, 2019.
  6. U.S. Department of Health and Human Services National Cancer Institute. SEER Cancer Statistics Review 1975-2015. https://seer.cancer.gov/archive/csr/1975_2015/index.html#contents. Accessed June 30, 2019.
  7. Kochar A, Chen AY, Sharma PP, et al. Long-term mortality of older patients with acute myocardial infarction treated in US clinical practice. J Am Heart Assoc 2018;7:e007230.
  8. Shah KS, Xu H, Matsouaka RA, et al. Heart failure with preserved, borderline, and reduced ejection fraction: 5-year outcomes. J Am Coll Cardiol 2017;70:2476-86.
  9. Ridker PM, Everett BM, Thuren T, et al. Antiinflammatory therapy with canakinumab for atherosclerotic disease. N Engl J Med 2017;377:1119-31.
  10. Baigent C, Landray MJ, Reith C, et al. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial. Lancet 2011;377:2181-92.
  11. Murtola TJ, Visvanathan K, Artama M, Vainio H, Pukkala E. Statin use and breast cancer survival: a nationwide cohort study from Finland. PLoS One 2014;9:e110231.
  12. Cardwell CR, Hicks BM, Hughes C, Murray LJ. Statin use after diagnosis of breast cancer and survival: a population-based cohort study. Epidemiology 2015;26:68-78.
  13. Mc Menamin UC, Murray LJ, Hughes CM, Cardwell CR. Statin use and breast cancer survival: a nationwide cohort study in Scotland. BMC Cancer 2016;16:600.

Keywords: Dyslipidemias, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hypercholesterolemia, Risk Factors, American Heart Association, Life Expectancy, Hodgkin Disease, Coronary Vessels, Follow-Up Studies, Quality of Life, Cholesterol, Risk Assessment, Morbidity, Antineoplastic Agents, Hematologic Tests, Breast Neoplasms, Health Personnel, Retrospective Studies, Retrospective Studies, Lovastatin, RNA, Small Interfering, Creatinine, Survival Rate, Sedentary Behavior, Cardiovascular Diseases, Antibodies, Monoclonal, Myocardial Infarction, Stroke, Heart Failure, Thrombosis, Registries, Leukemia, Diabetes Mellitus, Carcinogenesis, Renal Dialysis, Obesity, Inflammation, Hematologic Neoplasms, Chemokines, Kidney Failure, Chronic, Myeloid Cells, Lipids, Algorithms, Hypertension, Biological Products, Cardiotoxicity


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