Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

The immune checkpoint inhibitor avelumab increases aortic inflammation on [18F]FDG PET/CT: A retrospective cohort study

  • Anniek Strijdhorst ,

    Contributed equally to this work with: Anniek Strijdhorst, Reindert F. Oostveen, Margot Tesselaar, Hein J. Verberne, Nick van Es

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft

    a.strijdhorst@amsterdamumc.nl

    Affiliations Amsterdam University Medical Center, location University of Amsterdam, Department of Vascular Medicine, Amsterdam, The Netherlands, Cancer Center Amsterdam, Cancer Treatment and Quality of Life, Amsterdam, The Netherlands, Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, The Netherlands

  • Reindert F. Oostveen ,

    Contributed equally to this work with: Anniek Strijdhorst, Reindert F. Oostveen, Margot Tesselaar, Hein J. Verberne, Nick van Es

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Software, Visualization, Writing – original draft

    Affiliations Amsterdam University Medical Center, location University of Amsterdam, Department of Vascular Medicine, Amsterdam, The Netherlands, Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, The Netherlands

  • Mark P.A. Schilder,

    Roles Formal analysis, Investigation, Writing – review & editing

    Affiliation Amsterdam University Medical Center, location University of Amsterdam, Department of Vascular Medicine, Amsterdam, The Netherlands

  • Arthur J.A.T. Braat,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliation Department of Nuclear Medicine, The Netherlands Cancer Institute—Antoni van Leeuwenhoek, Amsterdam, The Netherlands

  • Youssef Chahid,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliation Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands

  • Damini Dey,

    Roles Conceptualization, Software, Writing – review & editing

    Affiliation Department of Medicine (Division of Artificial Intelligence), Cedars-Sinai Medical Center, Los Angeles, California, United States of America

  • Nordin M.J. Hanssen,

    Roles Conceptualization, Writing – review & editing

    Affiliations Amsterdam University Medical Center, location University of Amsterdam, Department of Vascular Medicine, Amsterdam, The Netherlands, Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, The Netherlands

  • Hanneke W.M. van Laarhoven,

    Roles Conceptualization, Writing – review & editing

    Affiliations Cancer Center Amsterdam, Cancer Treatment and Quality of Life, Amsterdam, The Netherlands, Amsterdam University Medical Center, location University of Amsterdam, Department of Medical Oncology, Amsterdam, the Netherlands

  • Anne W. van Schijndel,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliations Department of Intensive Care, The Netherlands Cancer Institute—Antoni van Leeuwenhoek, Amsterdam, The Netherlands, Department of Cardiology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek, Amsterdam, the Netherlands

  • Tom T.P. Seijkens,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliation Division of Medical Oncology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek, Amsterdam, the Netherlands

  • Piotr J. Slomka,

    Roles Conceptualization, Software, Writing – review & editing

    Affiliation Department of Medicine (Division of Artificial Intelligence), Cedars-Sinai Medical Center, Los Angeles, California, United States of America

  • Erik S.G. Stroes,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliations Amsterdam University Medical Center, location University of Amsterdam, Department of Vascular Medicine, Amsterdam, The Netherlands, Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, The Netherlands

  • Margot Tesselaar ,

    Contributed equally to this work with: Anniek Strijdhorst, Reindert F. Oostveen, Margot Tesselaar, Hein J. Verberne, Nick van Es

    Roles Conceptualization, Data curation, Methodology, Writing – review & editing

    Affiliation Division of Medical Oncology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek, Amsterdam, the Netherlands

  • Hein J. Verberne ,

    Contributed equally to this work with: Anniek Strijdhorst, Reindert F. Oostveen, Margot Tesselaar, Hein J. Verberne, Nick van Es

    Roles Conceptualization, Methodology, Supervision, Writing – review & editing

    Affiliation Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands

  • Nick van Es

    Contributed equally to this work with: Anniek Strijdhorst, Reindert F. Oostveen, Margot Tesselaar, Hein J. Verberne, Nick van Es

    Roles Conceptualization, Methodology, Supervision, Writing – review & editing

    Affiliations Amsterdam University Medical Center, location University of Amsterdam, Department of Vascular Medicine, Amsterdam, The Netherlands, Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, The Netherlands

Abstract

Background

Patients with cancer treated with immune checkpoint inhibitors (ICIs) are at increased risk of cardiovascular events. Preclinical studies suggest that this may result from inflammation-induced destabilization of atherosclerotic plaques.

Objective

To evaluate changes in vessel wall inflammation assessed using [18F]FDG positron emission tomography/computed tomography (PET/CT) after ICI initiation.

Methods

This was a single-center retrospective cohort study of patients with Merkel cell carcinoma who received at least one cycle of the programmed death ligand 1 (PD-L1) inhibitor avelumab and underwent [18F]FDG PET/CT before initiation of treatment and after 3 months. The primary outcome was the change in the target-to-background ratio (TBRmax) in the descending aorta between baseline and first follow-up scan. Secondary outcomes included the change in TBRmax in the carotid arteries, spleen, and bone marrow, and incidence of major adverse cardiovascular events.

Results

Fifty-three patients were included (66% male; median age 75 years). Most patients had established risk factors for cardiovascular disease (62%). The [18F]FDG TBRmax in the descending aorta increased from 1.52 (IQR, 1.39–1.70) at baseline to 1.64 (IQR, 1.41–1.97) after 3 months of treatment (change 7.8%. p = 0.022). No significant changes were observed in the carotid arteries, bone marrow, and spleen. Statin use was not associated with an attenuated change in TBRmax. During a median follow-up of 2.3 (IQR, 1.5–4.2) years, one nonfatal ischemic stroke occurred.

Conclusion

Avelumab treatment was associated with an increase in [18F]FDG uptake in the descending aorta after 3 months of treatment, which may be a potential marker of inflammation-driven accelerated atherosclerosis in patients receiving ICIs.

Introduction

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment by significantly increasing overall survival in many types of cancer [1]. Monoclonal antibody-mediated inhibition of co-inhibitory proteins located on T cells elicits T cell-mediated anti-tumor immune responses. While ICI enhances the cellular immune response against tumors, it has also been shown to potentially induce T cell mediated adverse effects such as thyroiditis, hepatitis, and colitis [2].

Besides these well-characterized acute side effects, emerging data demonstrate that patients receiving ICI are hallmarked by a 2- to 3-fold increased risk of cardiovascular events, predominantly myocardial infarction and ischemic stroke [3,4]. The underlying pathophysiology has been suggested to relate to an adverse impact of the systemic pro-inflammatory effect of ICI on pre-existing atherosclerotic plaques leading to destabilization and an increased rupture risk [5]. Studies in mice have demonstrated that inhibition of the immune checkpoint proteins cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed death-1 (PD-1) increases atherosclerotic lesion size, accompanied by an inflammatory plaque phenotype with enhanced infiltration of T cells and monocytes into the subendothelial space, leading to a pro-inflammatory milieu in atherosclerotic plaques [68].

Imaging has been used to non-invasively assess changes in atherosclerotic plaques in patients receiving ICI. Small studies using computed tomography (CT) have shown a 3-fold increase in atherosclerotic aortic plaque volume one year after the start of ICI [3,9]. However, changes in plaque volume do not necessarily reflect changes in vascular inflammation. Functional imaging with positron emission tomography CT (PET/CT) could provide valuable insights into whether immune checkpoint inhibitors elicit a pro-inflammatory state in atherosclerotic plaques in patients. The glucose analogue 2-deoxy-2[18F]fluoro-D-glucose ([18F]FDG) is a commonly used tracer that detects an increased metabolic activity, which in the case of the arterial wall has been attributed largely to increased metabolic activity of inflammatory cells, predominantly macrophages [10]. Several large retrospective studies have demonstrated that vascular [18F]FDG uptake can help identify individuals at high risk of cardiovascular events, while it has also been established as a surrogate marker for residual inflammatory risk in intervention studies [11,12].

Therefore, the objective of this study was to evaluate changes in arterial inflammation after initiation of ICI using [18F]FDG PET/CT imaging. We used data from a retrospective cohort of patients with metastatic or irresectable Merkel cell carcinoma treated with the programmed death-ligand 1 (PD-L1) avelumab [13].

Methods

Study design and study group

This was a single-center retrospective cohort study conducted in the Antoni van Leeuwenhoek hospital, a referral center for the treatment of Merkel cell carcinoma, a rare cancer of the skin. Patients were eligible for inclusion if they had a confirmed diagnosis of metastatic or irresectable Merkel cell carcinoma, received at least one cycle of the PD-L1 inhibitor avelumab, and underwent a 18F-FDG PET/CT before the initiation of avelumab and at least one scan after initiation, between July 1, 2017, and November 30, 2023. Patients were identified using the hospital’s electronic health records. Avelumab 600 mg was given every 2 weeks until disease progression, intolerable side effects, or death. The most recent PET/CT performed prior to the start of avelumab treatment was designated the baseline scan (T0). As per local protocol, the first evaluation scan was performed approximately 3 months after treatment initiation (T1). The following data were collected from the electronic health records: age, sex, risk factors for cardiovascular disease (i.e., obesity, hypertension, dyslipidemia, diabetes mellitus, and smoking), medication (i.e., prior chemotherapy, lipid lowering therapy, glucose lowering agents, antihypertensive drugs, anticoagulation, antiplatelet therapy, and immunosuppressive agents), previous cardiovascular events, immune-related adverse events, major cardiovascular events, and all-cause death. Patients were followed until death, loss to follow-up, or last date of data collection (January 3, 2025). Hypertension was defined as the use of blood pressure lowering medication. Dyslipidemia was defined as the use of lipid lowering therapy. The study protocol was approved by the Investigational Review Board of the Netherlands Cancer Institute (NKI) (Approval number IRB23–288) and all patients provided informed consent. This report adheres to the Strengthening of Reporting of Observational Studies (STROBE) statement (see checklist in S1 File).

Image acquisition and reconstruction

PET/CT scans were performed on a Philips Gemini TF 16 or the Philips Gemini TF big-bore PET/CT scanner (Philips, Cleveland, USA) using 3.5 MBq/kg [18F]FDG activity. Patients were required to fast for a minimum of 4 hours prior to imaging. In addition, patients were instructed to drink at least 500 mL of fluids prior to the scan. Imaging was performed approximately 60 minutes after tracer administration. The total scan time varied depending on the number of bed positions, with each bed position being imaged for 1–3 minutes. The scan coverage was tailored based on the primary tumor localization and was either from skull base to the inguinal region, or total body. A low-dose, non-contrast CT scan was performed with the following parameters: 40 mAs, 140 kV, and slice thickness ranging from 2 to 5 mm. Routine clinical PET image reconstruction was used for standardized uptake value (SUV) measurements.

Image analysis

The analysis of [18F]FDG PET/CT scans was conducted using specialized research software (FusionQuant, Cedars-Sinai Medical Center, CA, USA) by MS and RFO. The assessors were blinded to patient information, as all scans were anonymized and assigned a random study ID. To evaluate the uptake of [18F]FDG in the aorta and carotid artery, we employed the maximum target-to-background ratio (TBRmax), which is calculated by dividing the maximum standardized uptake value (SUVmax) of the target tissue by the SUVmean of the background blood in the superior vena cava (SVC) [13,25]. For measuring tracer uptake in the carotid artery, a region of interest (ROI) with a diameter of 4 mm was positioned around the right common carotid artery, extending from the division of the brachiocephalic artery to the bifurcation. For the analysis of the descending aorta, the ROI diameter was set to the aortic wall diameter plus an additional 4 mm to accommodate spatial resolution. The descending aorta was assessed from the apex of the descending segment until the spleen appeared in the transverse plane of the CT scan.

For assessing bone marrow and splenic uptake we adopted methods as published previously [14]. In short, the SUVmax in the spleen was evaluated by outlining a cylindrical volume of interest (VOI) with a 5 mm diameter around the region of highest uptake. The bone marrow SUVmax was calculated by placing a VOI across six thoracic vertebrae, with the reported value representing the average SUVmax of these vertebrae. All SUV calculations were according to a body weight corrected formula.

Study outcomes

The primary outcome was the change in [18F]FDG (expressed as TBRmax) uptake in the descending aorta between the baseline (T0) and first follow-up scan (T1). Secondary outcomes included the change in [18F]FDG uptake in the carotid arteries, spleen, and bone marrow. Uptake in spleen and bone marrow indicates hematopoietic activity. We also assessed the incidence of major cardiovascular events, defined as the composite of nonfatal ischemic stroke, nonfatal myocardial infarction, and cardiovascular death, and immune related adverse events (irAE) graded according to Common Terminology Criteria for Adverse Events, version 5.0 [13].

Statistical analysis

Standard descriptive statistics were used. Change in TBRmax between T0 and T1 was assessed by the Wilcoxon signed-rank test. Factors associated with change in TBRmax in the descending aorta were evaluated using linear regression models. All baseline variables were first evaluated for association with TBRmax in an univariable regression analysis, and only variables associated with TBRmax at P ≤ 0.20 were subsequently included in the exploratory multivariable model. We also assessed the potential effect of statins on arterial inflammation, as previous studies suggested a protective role of these drugs [1517]. Long-term changes in [18F]FDG uptake in the aorta were explored in patients with at least four PET/CT scans by performing a trend analysis. Two-sided P-values below 0.05 were considered to indicate statistical significance. No sample size calculation was performed; all eligible patients between July 2017 and November 2023 were included. All statistical analyses were performed in R, version 4.3.2 (www.R-project.org), and Figures were created with GraphPad Prism version 10.0.0 for Windows (GraphPad Software, Boston, Massachusetts USA, www.graphpad.com).

Results

Between July 2017 and November 2023, 62 patients with metastatic Merkel cell carcinoma (MCC) and 7 with locally advanced irresectable MCC received at least one cycle of first-line treatment with avelumab of whom 53 (77%) had both baseline and follow-up scans. The median age was 75 years (interquartile range [IQR], 70–81) and 66% of patients were male (see Table 1 for baseline characteristics). The majority of patients had one or more established risk factors for cardiovascular disease (62%). The median number of completed cycles at three months was 7. There was no difference in median plasma glucose between baseline (5.8 mmol/L) and 3-month follow-up (5.9 mmol/L). During the median follow-up period of 2.3 (IQR, 1.5–4.2) years, eighteen patients (34%) died and seven (13%) were lost to follow-up after the second PET/CT scan was performed due to treatment in other hospitals or best supportive care after progressive disease.

Imaging results

The median time between the baseline (T0) and first follow-up scan (T1) was 120 days (IQR, 101−132), and the median time between the start of avelumab and T1 was 90 days (IQR, 78−107). There was a significant increase in TBRmax in the descending aorta from 1.52 (IQR, 1.39–1.70) at T0 to 1.64 (IQR, 1.41–1.97) at T1 (p = 0.022) (Fig 1). No difference was observed in the TBRmax in the carotid arteries between T0 and T1 (1.31 vs 1.37; p = 0.27). Also, no change in splenic TBRmax (1.48 vs 1.57; p = 0.66) and bone marrow TBRmax was observed (1.26 vs 1.31; p = 0.28). Results were similar when patients who were treated with glucocorticoid between T0 and T1 because ofirAEs were excluded. In a subgroup analysis of patients who completed all 7 cycles between baseline and the follow-up PET/CT at 3 months, similar results were found for the increase in aortic TBRmax (p = 0.01, S1 Table)

thumbnail
Fig 1. Change in [18F]FDG uptake between baseline and follow-up PET-CT.

(A) Descending aorta. (B) Carotid arteries. (C) Spleen. (D) Bone marrow.

https://doi.org/10.1371/journal.pone.0339671.g001

Factors associated with changes in TBRmax

Between T0 and T1, six patients (11%) developed grade ≥3 irAE for which they received immunosuppressive agents. Development of irAE was not associated with a change in aortic TBRmax (p = 0.72). In univariable linear regression analysis, age was significantly associated with a reduction in TBRmax between T0 and T1 at P < 0.05, while body mass index was associated with a reduction in TBRmax at P < 0.20 (Table 2). These variables were then included in a multivariable linear regression in which age remained negatively associated with change in TBRmax at P < 0.05. Pre-existing statin use was not associated with a change in TBRmax following avelumab initiation after adjusting for age, sex, and baseline TBRmax (P = 0.58). Subgroup analysis did not reveal a significant difference in the change in TBRmax uptake between smokers and non-smokers (p = 0.81) nor between patients with and without type 2 diabetes (p = 0.88) (S1 Table).

thumbnail
Table 2. Univariable and multivariable regression model of baseline predictors on ΔTBRmax in the descending aorta.

https://doi.org/10.1371/journal.pone.0339671.t002

Long term changes in TBRmax

Eight patients underwent four or more PET/CT scans for disease monitoring during follow-up. The median intervals between baseline (T0) and the third (T2) and fourth follow-up scans (T3) were 6 and 9 months, respectively. TBRmax at 9 months appeared to be higher than at baseline, but no further increase was observed thereafter (Ptrend = 0.27; S1 Fig).

Cardiovascular events

During the median follow-up period of 2.3 (IQR, 1.5–4.2) years, one (2%) patient developed a nonfatal ischemic stroke. Four patients developed non-major cardiovascular events including a transient ischemic attack (n = 2; 4%), below-knee amputation due to ischemic peripheral artery disease (n = 1; 2%), and percutaneous transluminal angioplasty and stent placement for a stenosis in an aorto-bifurcated prosthesis (n = 1; 2%). Change in TBRmax between T0 and T1 was not associated with major or non-major cardiovascular events (p= 0.85).

Discussion

Using [18F]FDG PET/CT, the PD-L1 immune checkpoint inhibitor avelumab was associated with an increase in aortic TBRmax within 3 months after treatment initiation in patients with metastatic or irresectable Merkel cell carcinoma. These findings support the concept that systemic immune checkpoint inhibition results in vascular inflammation, which may contribute to the increased risk of cardiovascular events observed in patients receiving immune checkpoint inhibitors.

Atherosclerosis is characterized by chronic low-grade inflammation of the arterial wall, in which T cells are the most abundant immune cells present in the atherosclerotic plaques [18,19]. Murine studies have demonstrated that ICI leads to pro-inflammatory changes in the plaques, characterized by an increase in CD4+ and CD8+ T cells, macrophage content, and a larger necrotic core [6,7,20]. Upregulation of the adhesion molecules ICAM-1 and VCAM-1 on the endothelial lining was also observed, confirming activation of the endothelium with enhanced recruitment of immune cells to the atherosclerotic plaques [7,20,21]. An adverse effect of inhibition of immune checkpoint proteins on atherogenesis is further supported by a decrease in plaque size and more stable phenotype when, conversely, CTLA-4 and PD-1 are stimulated [2224]. To our knowledge, no other studies to date have evaluated the effects of a PD-L1 inhibitor, specifically avelumab, on arterial inflammation.

The significant increase in aortic TBRmax after 3 months of treatment with avelumab in patients with metastatic or irresectable Merkel cell carcinoma aligns with previous studies. In a retrospective cohort study of 96 melanoma patients, Polomski and colleagues found a significant increase in [18F]FDG uptake in large arteries was observed within the first 6 months of ICI treatment, while no further increase was observed beyond 6 months [15]. Three other small retrospective cohort studies also observed increased [18F]FDG uptake in large arteries within 6–9 months of treatment with PD-1 and/or CTLA-4 inhibitors [14,23,24]. In contrast, a small PET-imaging pilot study [7] including 10 relatively young melanoma patients without a history of cardiovascular disease did not find a difference in FDG uptake after 6 weeks of PD-1 and/or CTLA-4 treatment. This population may not have been at high risk for accelerated atherosclerosis, and the short interval between scans may have limited the ability to detect changes in vascular inflammation. We did not observe changes in TBRmax beyond 3 months in eight patients with multiple PET/CT scans during follow-up, suggesting that the pro-inflammatory effects of ICIs are most pronounced in the first months after initiation of treatment [17]. However, a recent study by Bacmeister and colleagues found an significant increase in FDG uptake of 2.5% annually up to 2 years after initiation of ICI [15]. This discrepancy underscores the need for longitudinal studies to determine the long-term vascular effects of ICI.

We focused on an elderly population with metastatic or irresectable Merkel cell carcinoma. These patients may have different characteristics than younger cancer patients, and a higher proportion may have pre-existent atherosclerotic plaques with a different phenotype. In the risk factor analysis, we found that age was negatively correlated with change in TBRmax, also when adjusted for baseline TBRmax. Whether this inverse association is causal or due to residual confounding is unclear. A potential explanation may be that elderly patients with extensive vascular calcifications exhibit a smaller [18F]FDG increase due to reduced baseline inflammatory activity of plaques, as shown in previous studies in patients who received ICI [17,25]. This is in line with data demonstrating that calcified plaques have less [18F]FDG uptake than metabolically active lesions [26]. Further studies are needed to assess the association of increased arterial [18F]FDG uptake and the incidence of cardiovascular events in patients receiving ICI.

In contrast to the increase in TBRmax in the descending aorta, we found no changes in carotid TBRmax after the initiation of avelumab. The images were obtained from scanners with limited spatial resolution, which hampered accurate carotid measurements on non-contrast enhanced scans. However, this finding may also reflect low baseline carotid plaque inflammation in this cohort. Notably, we also observed no significant changes in [18F]FDG uptake in the spleen or bone marrow, consistent with findings from Calabretta et al., suggesting that avelumab-induced vascular inflammation is not merely the result of increased hematopoietic activity [16].

Several limitations of this study should be acknowledged. First, the sample size was small because Merkel cell carcinoma is a rare tumor type, which limited statistical power. Second, coronary arterial inflammation could not be assessed since the [18F]FDG PET/CT scans were not cardiac-gated. Third, only eight patients had multiple follow-up scans available hampering the analysis of long-term changes. Fourth, the European Association of Nuclear Medicine (EANM) recommends acquiring PET images 2 hours after tracer injection to ensure reliable quantification of arterial wall FDG uptake, and prescan blood glucose levels below 130 mg/dL [27]. In our retrospective study, PET/CT scans were acquired for oncological purposes, with image acquisition performed between 52 and 74 minutes after tracer injection, which may not have been optimized for assessing tracer uptake in the arterial wall. Additionally, 80% of patients at baseline and 87% at 3 months had prescan glucose levels below 130 mg/dL, and there was no significant difference in glucose levels between scans (p = 0.71). While these factors may have introduced some variability, the majority of scans met the recommended glucose threshold, and the timing reflects standard clinical practice for oncology patients. Fifth, as this was a retrospective study with considerable loss to follow-up, outcome events may have been missed.

The observed increase in 18FDG uptake in large arteries in elderly patients with metastatic or irresectable Merkel cell carcinoma receiving avelumab supports the concept of ICI-induced arterial wall inflammation, which has been shown to lead to plaque destabilization in murine studies. Although our sample size was too small to evaluate the association between changes in arterial wall inflammation and cardiovascular events, previous studies have demonstrated that arterial wall inflammation predicts major cardiovascular events [10]. Therefore, with the expanding use of ICIs, also in the neoadjuvant or adjuvant setting, identifying patients at high risk for cardiovascular events is becoming increasingly relevant. The European Society of Cardiology (ESC) Cardio-Oncology guidelines advocate routine cardiovascular assessment every 6–12 months in patients requiring ICI for more than one year, with more intensive surveillance recommended for those classified as being at high risk of CVD [28]. However, this recommendation ignores the increased risk of major cardiovascular events observed shortly after starting ICI in other studies [3,4], and it does not provide guidance on the optimal risk stratification nor risk mitigation strategies.

Whether arterial wall inflammation detected by PET/CT-scans could serve as a biomarker for cardiovascular risk in this setting remains an open question, requiring future larger studies. The observed changes in FDG uptake after ICI initiation suggest that this imaging marker, reflecting macrophage activity, could be valuable in future studies investigating risk mitigation strategies. Previous studies have shown that increased vascular FDG uptake is associated with a increased risk for ASCVD [29]. Therefore, future studies should evaluate whether and how these routinely available PET/CT data can be used to better identify patients at high risk of ASCVD. In addition, FDG PET or newer tracers such as DOTATATE [30] may help to evaluate the effect of interventions aimed at reducing vascular inflammation in this population.

Exploring alternative imaging modalities, such as coronary CT angiography, may offer a more accessible approach. Surrogate markers of arterial inflammation, like the fat attenuation index, strongly correlate with future cardiovascular events [31]. However, its integration into routine clinical practice remains challenging due to the need for dedicated ECG-gated scans. Furthermore, whether patients with ICI-induced arterial inflammation could benefit from prophylactic treatment with statins or anti-inflammatory therapies has not yet been studied.

Overall, our findings support previous concerns regarding the potential adverse cardiovascular effects of ICI. As ICI use expands, future research should determine whether PET/CT-detected arterial inflammation can predict cardiovascular events and whether alternative imaging techniques could provide a more practical risk assessment tool. Investigating targeted interventions to mitigate ICI-induced cardiovascular disease will be crucial to optimizing cardiovascular outcomes in this patient population.

Supporting information

S1 Table. Subgroup analyses of the change in TBRmax in the descending aorta between baseline and 3 months, stratified by cardiovascular risk factors and treatment characteristics.

https://doi.org/10.1371/journal.pone.0339671.s001

(DOCX)

S1 Fig. Change in TBRmax in the descending aorta over time in eight patients with multiple follow-up scans.

Timepoints: T0, baseline; T1, + /- 3 months; T2, + /- 6 months; T3, + /- 9 months. Abbreviations: TBRmax, target-to-background ratio.

https://doi.org/10.1371/journal.pone.0339671.s002

(TIF)

References

  1. 1. Haslam A, Gill J, Prasad V. Estimation of the Percentage of US Patients With Cancer Who Are Eligible for Immune Checkpoint Inhibitor Drugs. JAMA Netw Open. 2020;3(3):e200423. pmid:32150268
  2. 2. Chen TW, Razak AR, Bedard PL, Siu LL, Hansen AR. A systematic review of immune-related adverse event reporting in clinical trials of immune checkpoint inhibitors. Ann Oncol. 2015;26(9):1824–9. pmid:25888611
  3. 3. Drobni ZD, Alvi RM, Taron J, Zafar A, Murphy SP, Rambarat PK, et al. Association Between Immune Checkpoint Inhibitors With Cardiovascular Events and Atherosclerotic Plaque. Circulation. 2020;142(24):2299–311. pmid:33003973
  4. 4. Ma Z, Sun X, Zhang Y, Li H, Sun D, An Z, et al. Risk of Thromboembolic Events in Cancer Patients Treated with Immune Checkpoint Inhibitors: A Meta-analysis of Randomized Controlled Trials. Thromb Haemost. 2022;122(10):1757–66. pmid:35772727
  5. 5. Vuong JT, Stein-Merlob AF, Nayeri A, Sallam T, Neilan TG, Yang EH. Immune Checkpoint Therapies and Atherosclerosis: Mechanisms and Clinical Implications: JACC State-of-the-Art Review. J Am Coll Cardiol. 2022;79(6):577–93.
  6. 6. Bu D, Tarrio M, Maganto-Garcia E, Stavrakis G, Tajima G, Lederer J, et al. Impairment of the programmed cell death-1 pathway increases atherosclerotic lesion development and inflammation. Arterioscler Thromb Vasc Biol. 2011;31(5):1100–7. pmid:21393583
  7. 7. Poels K, van Leent MMT, Boutros C, Tissot H, Roy S, Meerwaldt AE, et al. Immune Checkpoint Inhibitor Therapy Aggravates T Cell-Driven Plaque Inflammation in Atherosclerosis. JACC CardioOncol. 2020;2(4):599–610. pmid:34396271
  8. 8. Strijdhorst A, Vos WG, Bosmans LA, Dzobo KE, Kusters PJH, Hanssen NMJ, et al. Accelerated atherosclerosis associated with immune checkpoint inhibitors: a systematic review and meta-analysis of pre-clinical studies. Atherosclerosis. 2025;405:119219. pmid:40354680
  9. 9. Drobni ZD, Gongora C, Taron J, Suero-Abreu GA, Karady J, Gilman HK, et al. Impact of immune checkpoint inhibitors on atherosclerosis progression in patients with lung cancer. J Immunother Cancer. 2023;11(7):e007307. pmid:37433718
  10. 10. Ogawa M, Nakamura S, Saito Y, Kosugi M, Magata Y. What can be seen by 18F-FDG PET in atherosclerosis imaging? The effect of foam cell formation on 18F-FDG uptake to macrophages in vitro. J Nucl Med. 2012;53(1):55–8. pmid:22128324
  11. 11. Moon SH, Cho YS, Noh TS, Choi JY, Kim B-T, Lee K-H. Carotid FDG Uptake Improves Prediction of Future Cardiovascular Events in Asymptomatic Individuals. JACC Cardiovasc Imaging. 2015;8(8):949–56. pmid:26189117
  12. 12. Pirro M, Simental-Mendía LE, Bianconi V, Watts GF, Banach M, Sahebkar A. Effect of Statin Therapy on Arterial Wall Inflammation Based on 18F-FDG PET/CT: A Systematic Review and Meta-Analysis of Interventional Studies. J Clin Med. 2019;8(1):118. pmid:30669380
  13. 13. D’Angelo SP, Lebbé C, Mortier L, Brohl AS, Fazio N, Grob J-J, et al. First-line avelumab in a cohort of 116 patients with metastatic Merkel cell carcinoma (JAVELIN Merkel 200): primary and biomarker analyses of a phase II study. J Immunother Cancer. 2021;9(7):e002646. pmid:34301810
  14. 14. Oostveen RF, Kaiser Y, Ståhle MR, Nurmohamed NS, Tzolos E, Dweck MR, et al. Atorvastatin lowers 68Ga-DOTATATE uptake in coronary arteries, bone marrow and spleen in individuals with type 2 diabetes. Diabetologia. 2023;66(11):2164–9. pmid:37581619
  15. 15. Bacmeister L, Hempfling N, Maier A, Weber S, Buellesbach A, Heidenreich A, et al. Longitudinal Assessment of Subclinical Arterial Inflammation in Patients Receiving Immune Checkpoint Inhibitors by Sequential [18F]FDG PET Scans. Circ Cardiovasc Imaging. 2025;18(2):e016851. pmid:39902567
  16. 16. Calabretta R, Hoeller C, Pichler V, Mitterhauser M, Karanikas G, Haug A, et al. Immune Checkpoint Inhibitor Therapy Induces Inflammatory Activity in Large Arteries. Circulation. 2020;142(24):2396–8. pmid:32894978
  17. 17. Polomski EAS, Kapiteijn EW, Heemelaar JC, van der Kolk AV, Kalisvaart TM, van de Burgt A, et al. Arterial inflammation on [(18)F]FDG PET/CT in melanoma patients treated with and without immune checkpoint inhibitors: CHECK-FLAME I. Atherosclerosis. 2024;398:118595.
  18. 18. Barcia Durán JG, Das D, Gildea M, Amadori L, Gourvest M, Kaur R, et al. Immune checkpoint landscape of human atherosclerosis and influence of cardiometabolic factors. Nat Cardiovasc Res. 2024;3(12):1482–502. pmid:39613875
  19. 19. Saigusa R, Winkels H, Ley K. T cell subsets and functions in atherosclerosis. Nat Rev Cardiol. 2020;17(7):387–401. pmid:32203286
  20. 20. Poels K, van Leent MMT, Reiche ME, Kusters PJH, Huveneers S, de Winther MPJ, et al. Antibody-Mediated Inhibition of CTLA4 Aggravates Atherosclerotic Plaque Inflammation and Progression in Hyperlipidemic Mice. Cells. 2020;9(9):1987. pmid:32872393
  21. 21. Lou L, Detering L, Luehmann H, Amrute JM, Sultan D, Ma P. Visualizing immune checkpoint inhibitors derived inflammation in atherosclerosis. Circ Res. 2024;135(10):990–1003.
  22. 22. Ewing MM, Karper JC, Abdul S, de Jong RCM, Peters HAB, de Vries MR, et al. T-cell co-stimulation by CD28-CD80/86 and its negative regulator CTLA-4 strongly influence accelerated atherosclerosis development. Int J Cardiol. 2013;168(3):1965–74. pmid:23351788
  23. 23. Grievink HW, Verwilligen RAF, Smit V, Kleijn MNAB, Smeets DN, Binder CJ, et al. Stimulation of the PD-1 pathway decreases atherosclerotic lesion development in Ldlr deficient mice. Eur J Immunol. 2021;51:80.
  24. 24. Matsumoto T, Sasaki N, Yamashita T, Emoto T, Kasahara K, Mizoguchi T, et al. Overexpression of Cytotoxic T-Lymphocyte-Associated Antigen-4 Prevents Atherosclerosis in Mice. Arterioscler Thromb Vasc Biol. 2016;36(6):1141–51. pmid:27055906
  25. 25. Calabretta R, Staber PB, Kornauth C, Lu X, Binder P, Pichler V, et al. Immune Checkpoint Inhibitor Therapy Induces Inflammatory Activity in the Large Arteries of Lymphoma Patients under 50 Years of Age. Biology (Basel). 2021;10(11):1206. pmid:34827199
  26. 26. Dunphy MPS, Freiman A, Larson SM, Strauss HW. Association of vascular 18F-FDG uptake with vascular calcification. J Nucl Med. 2005;46(8):1278–84. pmid:16085583
  27. 27. Bucerius J, Hyafil F, Verberne HJ, Slart RHJA, Lindner O, Sciagra R, et al. Position paper of the Cardiovascular Committee of the European Association of Nuclear Medicine (EANM) on PET imaging of atherosclerosis. Eur J Nucl Med Mol Imaging. 2016;43(4):780–92. pmid:26678270
  28. 28. Lyon AR, López-Fernández T, Couch LS, Asteggiano R, Aznar MC, Bergler-Klein J, et al. 2022 ESC Guidelines on cardio-oncology developed in collaboration with the European Hematology Association (EHA), the European Society for Therapeutic Radiology and Oncology (ESTRO) and the International Cardio-Oncology Society (IC-OS). Eur Heart J. 2022;43(41):4229–361. pmid:36017568
  29. 29. Rominger A, Saam T, Wolpers S, Cyran CC, Schmidt M, Foerster S, et al. 18F-FDG PET/CT identifies patients at risk for future vascular events in an otherwise asymptomatic cohort with neoplastic disease. J Nucl Med. 2009;50(10):1611–20. pmid:19759117
  30. 30. Tarkin JM, Joshi FR, Evans NR, Chowdhury MM, Figg NL, Shah AV, et al. Detection of Atherosclerotic Inflammation by 68Ga-DOTATATE PET Compared to [18F]FDG PET Imaging. J Am Coll Cardiol. 2017;69(14):1774–91. pmid:28385306
  31. 31. Oikonomou EK, Marwan M, Desai MY, Mancio J, Alashi A, Hutt Centeno E, et al. Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data. Lancet. 2018;392(10151):929–39. pmid:30170852