Literature DB >> 33653803

Electrocardiographic features of immune checkpoint inhibitor associated myocarditis.

Daniel A Zlotoff1, Malek Z O Hassan2, Amna Zafar2, Raza M Alvi2, Magid Awadalla2, Syed S Mahmood3, Lili Zhang4, Carol L Chen5, Stephane Ederhy6, Ana Barac7, Dahlia Banerji2, Maeve Jones-O'Connor1, Sean P Murphy1, Merna Armanious8, Brian J Forrestal7, Michael C Kirchberger9, Otavio R Coelho-Filho10, Muhammad A Rizvi11, Gagan Sahni12, Anant Mandawat13, Carlo G Tocchetti14, Sarah Hartmann2, Hannah K Gilman2, Eduardo Zatarain-Nicolás15, Michael Mahmoudi16, Dipti Gupta5, Ryan Sullivan17, Sarju Ganatra18, Eric H Yang19, Lucie M Heinzerling20, Franck Thuny21, Leyre Zubiri17, Kerry L Reynolds17, Justine V Cohen22, Alexander R Lyon23, John Groarke24, Paaladinesh Thavendiranathan25, Anju Nohria24, Michael G Fradley8, Tomas G Neilan26,2.   

Abstract

BACKGROUND: Myocarditis is a highly morbid complication of immune checkpoint inhibitor (ICI) use that remains inadequately characterized. The QRS duration and the QTc interval are standardized electrocardiographic measures that are prolonged in other cardiac conditions; however, there are no data on their utility in ICI myocarditis.
METHODS: From an international registry, ECG parameters were compared between 140 myocarditis cases and 179 controls across multiple time points (pre-ICI, on ICI prior to myocarditis, and at the time of myocarditis). The association between ECG values and major adverse cardiac events (MACE) was also tested.
RESULTS: Both the QRS duration and QTc interval were similar between cases and controls prior to myocarditis. When compared with controls on an ICI (93±19 ms) or to baseline prior to myocarditis (97±19 ms), the QRS duration prolonged with myocarditis (110±22 ms, p<0.001 and p=0.009, respectively). In contrast, the QTc interval at the time of myocarditis (435±39 ms) was not increased compared with pre-myocarditis baseline (422±27 ms, p=0.42). A prolonged QRS duration conferred an increased risk of subsequent MACE (HR 3.28, 95% CI 1.98 to 5.62, p<0.001). After adjustment, each 10 ms increase in the QRS duration conferred a 1.3-fold increase in the odds of MACE (95% CI 1.07 to 1.61, p=0.011). Conversely, there was no association between the QTc interval and MACE among men (HR 1.33, 95% CI 0.70 to 2.53, p=0.38) or women (HR 1.48, 95% CI 0.61 to 3.58, p=0.39).
CONCLUSIONS: The QRS duration is increased in ICI myocarditis and is associated with increased MACE risk. Use of this widely available ECG parameter may aid in ICI myocarditis diagnosis and risk-stratification. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  autoimmunity; immune tolerance; immunotherapy; inflammation; self tolerance

Mesh:

Substances:

Year:  2021        PMID: 33653803      PMCID: PMC7929895          DOI: 10.1136/jitc-2020-002007

Source DB:  PubMed          Journal:  J Immunother Cancer        ISSN: 2051-1426            Impact factor:   13.751


Background

Since the introduction of ipilimumab in 2011, immune checkpoint inhibitors (ICIs) have improved oncological care, offering new therapeutic options for a variety of cancers.1 Through activation of the immune system, ICIs can enhance antitumor activity but may also lead to immune-related adverse events (irAEs).2 3 Myocarditis is an uncommon irAE.4 5 The incidence of ICI-associated myocarditis is unclear, with estimates ranging from 0.09% to 1.1%.3 6–10 There are several potential cardiac adverse effects associated with ICIs but the focus on myocarditis is due to the morbidity and mortality associated with that diagnosis.11 12 Specifically, data from multiple groups report a mortality ranging from 17% to 50%.3 6 7 13 In comparison, the mortality of non-ICI myocarditis is far less than 5%.14 15 Therefore, there is a significant need for improved diagnostic and risk-stratification methods in ICI myocarditis, as well as newly recognized cardiac toxicities related to other forms of immune therapy for cancer.16 17 The QRS duration and the QTc interval are standardized measures routinely available from a 12-lead ECG. The QRS duration corresponds to ventricular depolarization, while the QTc interval predominantly represents ventricular repolarization. Monitoring of the QRS duration is employed in the care of patients who are at risk of developing arrhythmias and heart failure.18 19 Measurement of the QTc interval is also routinely used in both oncology trials and routine oncology care.20 However, there are no data on the utility of measurement of the QRS duration and the QTc interval among patients with ICI myocarditis. Therefore, the goal of this study was to evaluate whether the QRS duration and QTc interval increase with ICI myocarditis and whether these parameters associate with the development of subsequent adverse cardiac events.

Methods

Patients

Data on myocarditis cases (n=140) were obtained from a 23-center international registry specifically designed for collating cases of ICI myocarditis.5 7 21 Cases were included between November 2013 and April 2019. Controls (n=179) were selected patients from a Massachusetts General Hospital registry of patients treated with an ICI during the same time interval for whom ECG data were available. Controls were not selected to match on any parameter with the cases.

ECG data

ECGs were obtained at various timepoints relative to ICI initiation and to the development of myocarditis (among cases). The acquisition of an ECG was not protocol-specified and was performed at the discretion of the medical care team. ECGs were recorded using the preferred system at each registry site and the parameters were derived automatically by those systems. Forty randomly selected ECGs (20 from controls and 20 from myocarditis cases) were also manually interpreted by a reader (DAZ) blinded to the case/control identity and the automated measurements. These manually measured values were then compared with those which had been automatically derived. The primary measures of interest included the PR interval, QRS duration, and the QTc interval. The PR interval represents the time delay between atrial depolarization and ventricular depolarization and was included in the analysis to assess which measures of intracardiac conduction were affected in ICI myocarditis. QT interval correction for heart rate was calculated using the Fridericia formula22 as this is more accurate than the commonly used Bazett formula and considered the most appropriate strategy by the US Food and Drug Administration.23 24 Based on standardized criteria, a QRS duration greater than 110 ms was considered prolonged.25 Similarly, based on standardized criteria, a QTc interval greater than 450 ms in men and 460 ms in women was considered prolonged.26

Clinical data

Clinical data of interest obtained retrospectively from electronic medical records included patient demographics, medications, prior medical conditions, lab values, and cardiovascular risk factors. Data relevant to cancer included the cancer type, prior cancer therapies, and specific ICI treatments.

Definitions and outcomes of interest

Myocarditis was diagnosed through one of the following standardized approaches: (1) histopathological features on endomyocardial biopsy or autopsy or (2) a clinically accepted scoring system designed for suspected myocarditis that uses clinical findings, biomarkers, and imaging features.27 This latter clinical diagnostic algorithm relies on the presence of one or more clinical features (chest pain, heart failure, arrhythmias, or cardiogenic shock) plus one or more diagnostic findings (ECG abnormalities, elevated troponin levels, functional or structural abnormalities on cardiac imaging, or evidence of edema or late gadolinium enhancement on cardiac MRI) occurring in the absence of significant coronary disease or known alternative causes.27 This standardized scoring system was devised because an endomyocardial biopsy is typically performed in less than 15% of myocarditis cases.28 The main outcome of interest was major adverse cardiac events (MACE), which was a composite of cardiovascular death,29 cardiac arrest,30 cardiogenic shock,31 and hemodynamically significant complete heart block.7

Statistical analysis

Continuous variables were summarized as either the mean±SD or as the median and IQR, as appropriate, and categorical variables were presented as percentages. Comparisons between myocarditis cases and controls were made with Fisher’s exact test for categorical variables or with the Wilcoxon rank sum test for continuous variables (age and body mass index (BMI), both of which demonstrated non-Gaussian distribution). Comparisons of ECG parameters by case and ICI exposure status used the Kruskal-Wallis test with Dunn’s correction for multiple comparisons. The relationship between measured ECG parameters and left ventricular ejection fraction (EF) or left ventricular end-diastolic volume (LVEDV) was analyzed with simple linear regression and the associations were tested with the Pearson correlation coefficient. HRs for the association of dichotomized ECG parameters with MACE were determined using Cox proportional hazard models with follow-up time used as the time scale. The assumption of proportionality was verified by the method of Therneau and Grambsch.32 Kaplan-Meier curves and the log-rank test were used to analyze the relationship between QRS duration or QTc interval and MACE-free survival. The χ2 test was used to compare the frequencies of MACE component endpoints among myocarditis cases and subgroups. Multivariable logistic regression was used to address the relationship between multiple covariates, including ECG parameters at the time of myocarditis, and MACE risk. All statistical tests were two-sided and p<0.05 was considered significant. Statistical analysis was performed using R V.3.5.1 (R Foundation for Statistical Computing, Vienna, Austria) and SPSS V.26 (IBM Corporation).

Results

Patient characteristics

One hundred and forty patients with ICI myocarditis and 179 controls were included in the analysis. The median time between ICI initiation and myocarditis diagnosis was 58 days, and 91 cases (65.0%) occurred within the first 90 days of ICI therapy. Of the 140 cases, 70 (50.0%) were diagnosed based on clinical criteria, 58 patients (41.4%) were diagnosed by pathology from an endomyocardial biopsy, and 12 patients (8.6%) were diagnosed based on autopsy pathology. The median duration of follow-up for myocarditis cases was 69 days (IQR 19–153). Myocarditis patients had a higher BMI than controls (28±6.1 vs 26±5.8, p=0.002); otherwise, cases and controls had similar rates of cardiovascular risk factors (table 1). The most common cancer in both groups was melanoma. Renal cell cancer was more common among myocarditis cases (8.6% vs 2.2%, p=0.02). The use of atezolizumab was higher among cases (7.1% vs 1.7%, p=0.02). There was a lower frequency of anti-programmed cell death 1 (PD-1) therapy use in the myocarditis group (87.1% vs 96.1%, p=0.005); conversely, there was a greater frequency of anti-programmed death ligand 1 (PD-L1) therapy use in the myocarditis group (11.4% vs 2.2%, p=0.001). The use of ipilimumab/nivolumab combination therapy was also more common in the myocarditis group (25.7% vs 11.2%, p=0.001). The rates of pneumonitis (24.3% vs 12.3%, p=0.007) and neurological adverse events (8.6% vs 2.2%, p=0.02) were higher in the myocarditis group.
Table 1

Baseline characteristics

CharacteristicControls, n (%)(n=179)Myocarditis, n (%)(n=140)P value
Age at ICI Initiation64.1±13.965.9±14.70.02
Sex
 Male118 (65.9)99 (70.7)0.40
 Female61 (34.1)41 (29.3)0.40
Body mass index, kg/m225.8±5.827.8±6.10.002
Cardiovascular risk factors and disease
 Hypertension109 (60.9)81 (57.9)0.65
 Diabetes mellitus29 (16.2)31 (22.1)0.20
 CKD29 (16.2)9 (8.5)*0.07
 COPD26 (14.5)19 (17.6)*0.51
 Coronary artery disease23 (12.8)20 (14.3)0.74
 Stroke20 (11.2)7 (5.0)0.07
 Heart failure12 (6.7)8 (5.7)0.82
Pre-ICI cardiovascular medications
 Statin45 (25.1)45 (32.1)0.17
 Aspirin43 (24.0)33 (23.6)1.00
 Beta-blocker56 (31.3)33 (23.6)0.13
 ACE-I or ARB34 (19.0)37 (26.4)0.14
 CCB31 (17.3)16 (11.4)0.15
Primary cancer type
 Melanoma86 (48.0)57 (40.7)0.21
 Non-small cell lung cancer36 (20.1)24 (17.1)0.56
 Head and neck13 (7.3)6 (4.3)0.34
 Small cell lung cancer7 (3.9)1 (0.7)0.08
 Renal cell carcinoma4 (2.2)12 (8.6)0.02
 Hodgkin’s lymphoma2 (1.1)2 (1.4)1.00
 Glioblastoma2 (1.1)2 (1.4)1.00
 Other29 (16.2)36 (25.7)0.05
ICI type (monotherapy or combination)
 Nivolumab100 (55.9)67 (47.9)0.18
 Pembrolizumab72 (40.2)55 (39.3)0.91
 Ipilimumab65 (36.3)49 (35.0)0.82
 Atezolizumab3 (1.7)10 (7.1)0.02
 Durvalumab1 (0.6)3 (2.1)0.32
 Tremelimumab1 (0.6)4 (2.9)0.17
 Avelumab0 (0.0)3 (2.1)0.08
 Any anti-PD-1172 (96.1)122 (87.1)0.005
 Any anti-CTLA-466 (36.9)53 (37.9)0.91
 Any anti-PD-L14 (2.2)16 (11.4)0.001
Type of combined ICI
 Ipilimumab+nivolumab20 (11.2)36 (25.7)0.001
 Ipilimumab+pembrolizumab0 (0.0)2 (1.4)0.19
 Tremelimumab+avelumab0 (0.0)1 (0.7)0.44
 Tremelimumab+durvalumab0 (0.0)2 (1.4)0.19
Other adverse events
 None108 (60.3)64 (45.7)0.01
 Colitis24 (13.4)13 (9.3)0.29
 Pneumonitis22 (12.3)34 (24.3)0.007
 Pituitary/adrenal axis disorder13 (7.3)7 (5.0)0.49
 Hepatitis10 (5.6)16 (11.4)0.07
 Dermatitis5 (2.8)10 (7.1)0.11
 Neurological4 (2.2)12 (8.6)0.02
 Other6 (3.4)7 (5.0)0.57
Prior cancer therapies
 Anthracycline chemotherapy3 (1.7)8 (5.7)0.07
 VEGF inhibitor7 (3.9)1 (0.7)0.08

Values are n (%) or mean±SD (for age and BMI only).

*Certain patients with incomplete data were not included in analysis for some variables in the myocarditis group; percentages were derived from lower denominators in these rows (106 for CKD and 108 for COPD).

ACE-I, Angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; BMI, body mass index; CCB, calcium channel blocker; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; ICI, immune checkpoint inhibitor; PD-1, programmed cell death 1; PD-L1, programmed death ligand 1; VEGF, vascular endothelial growth factor.

Baseline characteristics Values are n (%) or mean±SD (for age and BMI only). *Certain patients with incomplete data were not included in analysis for some variables in the myocarditis group; percentages were derived from lower denominators in these rows (106 for CKD and 108 for COPD). ACE-I, Angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; BMI, body mass index; CCB, calcium channel blocker; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; ICI, immune checkpoint inhibitor; PD-1, programmed cell death 1; PD-L1, programmed death ligand 1; VEGF, vascular endothelial growth factor.

ECG characteristics

We compared computer-derived ECG parameters between controls and myocarditis cases at three different time-points: prior to initiation of ICI (“pre-ICI”), after the initiation of ICI but prior to development of myocarditis (“on-ICI”), and at the time of presentation with myocarditis. For validation of this approach, we also manually measured the parameters from 40 random ECGs (20 control and 20 cases) and found these values to be similar to the computer-derived values (online supplemental file 1). The median time intervals between pre-ICI baseline ECG and initiation of ICI were 103 days (IQR 24–215) and 82 days (IQR 35–172), controls and cases, respectively. The median time intervals between initiation of ICI and on-ICI ECG were 165 days (IQR 41–379) and 44 days (IQR 11–152), controls and cases, respectively. The pre-ICI baseline PR interval, QRS duration, and QTc (corrected for heart rate with the Fridericia formula, subsequently designated QTc-F) interval were similar between controls and cases (figure 1A–C). The on-ICI (prior to development of myocarditis for cases) PR interval, QRS duration, and QTc-F did not change from baseline and were similar between cases and controls. Additionally, among cases prior to the development of myocarditis, there was no increase in these parameters between the pre-ICI values and the on-ICI values. With the development of myocarditis, the PR interval did not increase. In contrast, the QRS duration at the time of myocarditis (110±22 ms) did increase and was greater than the QRS duration of cases pre-ICI (99±20 ms, p=0.001), controls on-ICI (93±19 ms, p<0.001), and cases on-ICI prior to the development of myocarditis (97±19, p=0.009). Cases were stratified by QRS duration using the cut-off of 110 ms, the upper limit of normal in adults.25 A normal QRS duration of ≤110 ms was observed in 74 cases (52.8%), while 66 (47.1%) had a prolonged QRS duration >110 ms. A similar testing strategy was adopted for the QTc-F interval. The QTc-F interval at time of myocarditis (435±39 ms) was increased when compared with controls on ICI (419±28 ms, p=0.02) but not when compared with values from cases prior to the development of myocarditis (422±27 ms, p=0.42). Of 99 male cases, 29 (29.3%) had a normal QTc-F≤450 ms, while 70 (70.7%) had a prolonged QTc-F>450 ms. Among women with myocarditis, 25 (61.0%) had a normal QTc-F≤460 ms, while 16 (39.0%) had a prolonged QTc-F>460 ms. We also analyzed the QTc interval across time points using the Bazett formula to correct for heart rate (subsequently designated QTc-B). With this approach, the QTc-B interval at the time of myocarditis (460±36 ms) was increased when compared with either on-ICI controls (440±28 ms, p<0.001) or on-ICI cases (440±29 ms, p=0.007) (online supplemental file 2).
Figure 1

Changes in ECG parameters with ICI myocarditis. (A) PR interval, (B) QRS duration, and (C) QTc-F interval values were derived from ECGs obtained pre-ICI therapy (“baseline or pre-ICI”), after initiating ICI therapy (“on-ICI”), or at the time of myocarditis (for cases only; “myocarditis”). Shown are box-and-whisker plots with the central line indicating the median value, the margins of the box indicating the 25th/75th percentiles, and the whiskers indicating the 5th/95th percentiles. ICI, immune checkpoint inhibitor.

Changes in ECG parameters with ICI myocarditis. (A) PR interval, (B) QRS duration, and (C) QTc-F interval values were derived from ECGs obtained pre-ICI therapy (“baseline or pre-ICI”), after initiating ICI therapy (“on-ICI”), or at the time of myocarditis (for cases only; “myocarditis”). Shown are box-and-whisker plots with the central line indicating the median value, the margins of the box indicating the 25th/75th percentiles, and the whiskers indicating the 5th/95th percentiles. ICI, immune checkpoint inhibitor.

Sensitivity of QRS duration for the diagnosis of ICI myocarditis

Given the significantly prolonged QRS duration observed during myocarditis, the sensitivity and specificity of QRS duration towards myocarditis diagnosis was determined. Applying a cut-off of >110 ms achieved a sensitivity of 48.6% and specificity of 87.0% for the diagnosis of myocarditis; the application of a higher cut-off of >130 ms yielded a sensitivity of 16.4% and a specificity of 92.6% (online supplemental table 1). A receiver-operating characteristic curve applying QRS duration towards myocarditis diagnosis had an area under the curve of 0.73 (online supplemental figure 3). Using the change in QRS duration (ΔQRS; equal to the QRS duration at time of myocarditis minus the QRS duration at baseline prior to myocarditis) yielded a sensitivity of 51.7% when applying a diagnostic threshold of >10 ms; this decreased to 31.0% and 21.6% for >20 ms and >30 ms, respectively.

Association of ECG parameters with left ventricular size and function

We analyzed the relationship between the measured ECG parameters and left ventricular EF and LVEDV among myocarditis cases (figure 2A–C). The QRS duration was not related to either echocardiographic EF (r=−0.10, 95% CI −0.27 to 0.07, p=0.25) or MRI-derived EF (r=−0.095, 95% CI −0.29 to 0.11, p=0.35), but was directly related to the LVEDV (r=0.32, 95% CI 0.13 to 0.49, p=0.001). The QTc-F interval was inversely associated with the echocardiographic EF (r=−0.20, 95% CI −0.36 to −0.02, p=0.026) and the MRI-derived EF (r=−0.20, 95% CI −0.039 to −0.01, p=0.044), but was not related to the LVEDV (r=0.16, 95% CI −0.04 to 0.35, p=0.12).
Figure 2

Relationship between ECG parameters, ejection fraction, and left ventricular volumes. (A) Scatter-plots of QRS duration (left) or QTc-F interval (right) versus echocardiographic left ventricular EF. Shown are the linear regression lines with their 95% CI. (B) Scatter-plots of QRS duration (left) or QTc-F interval (right) versus EF. (C) Scatter-plots of QRS duration (left) or QTc-F interval (right) versus LVEDV. EF, ejection fraction; LVEDV, left ventricular end-diastolic volume.

Relationship between ECG parameters, ejection fraction, and left ventricular volumes. (A) Scatter-plots of QRS duration (left) or QTc-F interval (right) versus echocardiographic left ventricular EF. Shown are the linear regression lines with their 95% CI. (B) Scatter-plots of QRS duration (left) or QTc-F interval (right) versus EF. (C) Scatter-plots of QRS duration (left) or QTc-F interval (right) versus LVEDV. EF, ejection fraction; LVEDV, left ventricular end-diastolic volume.

Association of QRS duration with MACE

Overall, 69 of the 140 cases (49%) experienced a MACE. The median time to a MACE was 34 days (IQR 12–103) and 68% of MACE occurred within the first 90 days after diagnosis of myocarditis. A non-sinus rhythm at presentation with myocarditis was associated with an HR for MACE of 1.94 relative to sinus rhythm at presentation (95% CI 1.27 to 3.43, log-rank p=0.01) (online supplemental figure 4). Using an unadjusted Cox proportional hazard model, a QRS duration >110 ms was associated with a HR for MACE of 3.28 relative to a QRS duration ≤110 ms (95% CI 1.98 to 5.62, p<0.001) (figure 3A). Increased QRS duration at the time of myocarditis was associated with increased MACE risk after adjustment for age, sex, and cardiovascular comorbidities (table 2). Specifically, an increase in the QRS duration of 10 ms conferred a 1.30-fold increase in the odds of MACE (95% CI 1.07 to 1.61, p=0.011). We also assessed the prognostic utility of troponin in ICI myocarditis. Troponin data were available for 138 of the 140 patients. Of these 138, 125 (90.6%) had an elevated troponin. Of the 125 patients with elevated troponins, 68 (54.4%) experienced a MACE, while of the 13 patients with normal troponins, only 1 (7.7%) had a MACE (p=0.002). An elevated troponin was common and was not associated with increased MACE risk in the multivariable model (OR 2.54, 95% CI 0.69 to 10.83, p=0.17).
Figure 3

Association between QRS duration or QTc-F interval and MACE. (A) Kaplan-Meier curves indicate the occurrence of MACE over 120 days from time of diagnosis for myocarditis patients stratified by QRS duration. Similar analyses were performed for male (B) and female (C) myocarditis patients stratified by QTc-F interval as indicated. P value obtained from the log-rank test. MACE, major adverse cardiac events.

Table 2

Association with major adverse cardiac events (MACE) by multivariable analysis

VariableOR95% CIP value
QRS duration1.301.07 to 1.610.011
Age1.010.98 to 1.040.61
Male sex0.550.21 to 1.400.22
Hypertension0.620.24 to 1.550.31
Diabetes mellitus1.320.48 to 3.730.59
Coronary artery disease0.340.07 to 1.360.14
Ejection fraction <50%4.201.80 to 10.380.001
Elevated troponin2.540.69 to 10.830.17

QRS duration was determined at the time of myocarditis diagnosis. For the QRS duration row, the OR reflects the MACE risk for an increase of 10 ms from the mean value across the myocarditis cohort. For the age row, the OR reflects the MACE risk for an increase of 1 year. For all other rows, the ORs reflect the MACE risk comparing those with the designated condition compared with those without.

OR, odds ratio.

Association between QRS duration or QTc-F interval and MACE. (A) Kaplan-Meier curves indicate the occurrence of MACE over 120 days from time of diagnosis for myocarditis patients stratified by QRS duration. Similar analyses were performed for male (B) and female (C) myocarditis patients stratified by QTc-F interval as indicated. P value obtained from the log-rank test. MACE, major adverse cardiac events. Association with major adverse cardiac events (MACE) by multivariable analysis QRS duration was determined at the time of myocarditis diagnosis. For the QRS duration row, the OR reflects the MACE risk for an increase of 10 ms from the mean value across the myocarditis cohort. For the age row, the OR reflects the MACE risk for an increase of 1 year. For all other rows, the ORs reflect the MACE risk comparing those with the designated condition compared with those without. OR, odds ratio. Rates for each of the four MACE components (cardiovascular death, cardiac arrest, cardiogenic shock, and complete heart block) were higher among patients with a QRS duration >110 ms than among those with a QRS duration ≤110 ms (figure 4). The most common MACE component in each was cardiovascular death (16.2% among those with QRS ≤110 ms, and 39.4% among those with QRS >110 ms).
Figure 4

Frequency of MACE components. Frequencies of the indicated outcome among all myocarditis patients stratified by QRS duration are shown. Numbers at the end of each bar indicate the fraction of patients in each stratum with the indicated event. MACE, major adverse cardiac events.

Frequency of MACE components. Frequencies of the indicated outcome among all myocarditis patients stratified by QRS duration are shown. Numbers at the end of each bar indicate the fraction of patients in each stratum with the indicated event. MACE, major adverse cardiac events.

Association of QTc interval with MACE

In contrast, a prolonged QTc-F interval was not associated with increased risk for MACE among men (HR 1.33, 95% CI 0.70 to 2.53, p=0.38) or women (HR 1.48, 95% CI 0.61 to 3.58, p=0.39) (figure 3B, C). We also tested the association using QTc interval values corrected for heart rate using the Bazett formula. With this approach, among men, a QTc-B of >450 ms was associated with an increased risk of MACE (HR 2.81, 95% CI 1.42 to 5.38, p=0.002) (online supplemental file 5A). Among women, a QTc-B duration of >460 ms was also associated with an increased risk of MACE (HR 3.00, 95% CI 1.08 to 8.32, log-rank p=0.03) (online supplemental file 5B).

Discussion

In this paper, we present novel findings describing increases in the QRS duration that may aid the diagnosis and risk-stratification of ICI myocarditis. This study has several unique and widely generalizable findings. First, we found that ICI myocarditis is associated with an unchanged PR interval but an increased QRS duration when compared with controls or cases at earlier timepoints (both prior to the initiation of ICI therapy and on ICI therapy but prior to the development of myocarditis). The QTc-F interval was prolonged compared with on-ICI controls but not on-ICI cases. Second, the increase in ECG intervals correlated with structural (LVEDV) and functional (EF) changes in the heart. Third, prolongations of QRS duration but not QTc-F interval at the time of myocarditis diagnosis were associated with an increased risk of MACE; specifically, a QRS duration >110 ms was associated with a 3.28-fold increased risk of MACE. This association between prolonged QRS duration and MACE persisted after adjustment for several cardiovascular covariates. Fourth, each of the individual components of MACE occurred more frequently in myocarditis patients with a prolonged QRS duration, with cardiovascular death the most common. Despite its high morbidity, the diagnosis of ICI myocarditis can be challenging.21 33–36 First, the presentation can be non-specific, both in terms of clinical symptoms and testing abnormalities.7 13 21 34–36 Second, the utility of standard cardiac testing in the diagnosis and risk-stratification of ICI myocarditis is not yet well established.21 35 36 Serum troponin levels, typically a hallmark of myocardial injury/myocarditis, may be only modestly elevated, may be elevated for other reasons, or, in rare cases, even normal.7 13 Collectively, the available non-invasive diagnostic tests (including serum troponin levels, electrocardiography, and echocardiography) all fail to provide high specificity.4 21 34 35 37 Third, the gold standard diagnostic test, endomyocardial biopsy, confers procedural risk that may be prohibitive for some patients and is not commonly performed.35 38 Our study now provides novel data that the QRS duration and QTc interval may be used as part of a diagnostic algorithm. However, changes in these ECG parameters can too have limited specificity, highlighting the fact that no test can be interpreted in isolation. Rather, surveillance of these values may be an effective and rapid means of identifying ICI recipients who should receive additional, more specific, cardiovascular testing. Prospective data will be needed to demonstrate the efficacy of this approach. Our study also suggests that the QRS duration may be used to risk-stratify ICI myocarditis patients. Prolongations of these values are associated with poor outcomes in a variety of conditions, including heart failure and acute myocardial infarction.39 40 The prognostic significance of a prolonged QRS duration or QTc interval in non-ICI myocarditis is not clear. One study of patients with suspected myocarditis reported that a prolonged QRS duration or QTc interval were each associated with poor outcomes, though only a prolonged QRS duration was found to be an independent predictor after adjustment for covariates.41 However, a more recent study of non-ICI myocarditis patients failed to find an association between QRS duration or QTc interval and adverse outcomes, though the sensitivity to detect an association was limited by a markedly lower adverse event rate.42 As background, ICI myocarditis has a higher adverse event rate compared with other irAEs or non-ICI lymphocytic myocarditis, and therefore the prognostic associations of prolonged ECG parameters may be more easily identified.3 14 15 Cardiac inflammation alters intracardiac conduction patterns and can promote arrhythmogenesis.43 44 This may occur through several non-mutually exclusive mechanisms: (1) interplay between immune cells and cardiac fibroblasts and/or cardiomyocytes, leading to fibrosis45; (2) direct participation of immune cells, namely macrophages, in cardiac conduction46; and (3) the effects of autoantibodies and cytokines on cardiomyocyte ion channels.47 In addition, patients with chronic inflammatory conditions have increased rates of conduction abnormalities, demonstrating that even inflammation outside the heart can affect cardiac conduction.48 49 In our analysis, the QT interval was corrected for heart rate using the Fridericia formula as this is more accurate than the commonly used Bazett formula and considered the most appropriate strategy by the US Food and Drug Administration.22–24 50 The Bazett formula, however, remains frequently used in clinical practice, so we performed the same analysis using the Bazett-corrected QTc interval. With these values, an association between QTc-B interval and MACE was observed for both men and women, suggesting a potential role for the Bazett-corrected QTc interval towards ICI myocarditis risk stratification. These findings should be interpreted within the overall limitations of the retrospective study design. First, the clinical data collection was not protocolized and was instead derived from medical records at each participating center, which in some cases led to incomplete data. Second, the timing of ECGs relative to ICI therapy initiation was not standardized, thereby leading to variability within each cohort. Third, we identified differences in the use of anti-PD-1 agents, anti-PD-L1 agents, and combination therapy between the control and myocarditis groups which may have confounded our results. Fourth, all controls were derived from a single center. In summary, we observed prolongation of the QRS duration in the setting of ICI myocarditis. A QRS duration, but not QTc-F interval, greater than normal was associated with increased risk of MACE. These findings illustrate the potential diagnostic and prognostic value of easily obtained ECG parameters in ICI myocarditis.
  48 in total

Review 1.  AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: part III: intraventricular conduction disturbances: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society. Endorsed by the International Society for Computerized Electrocardiology.

Authors:  Borys Surawicz; Rory Childers; Barbara J Deal; Leonard S Gettes; James J Bailey; Anton Gorgels; E William Hancock; Mark Josephson; Paul Kligfield; Jan A Kors; Peter Macfarlane; Jay W Mason; David M Mirvis; Peter Okin; Olle Pahlm; Pentti M Rautaharju; Gerard van Herpen; Galen S Wagner; Hein Wellens
Journal:  J Am Coll Cardiol       Date:  2009-03-17       Impact factor: 24.094

2.  Cardiovascular toxicities associated with immune checkpoint inhibitors: an observational, retrospective, pharmacovigilance study.

Authors:  Joe-Elie Salem; Ali Manouchehri; Melissa Moey; Bénédicte Lebrun-Vignes; Lisa Bastarache; Antoine Pariente; Aurélien Gobert; Jean-Philippe Spano; Justin M Balko; Marc P Bonaca; Dan M Roden; Douglas B Johnson; Javid J Moslehi
Journal:  Lancet Oncol       Date:  2018-11-12       Impact factor: 41.316

3.  Global Longitudinal Strain and Cardiac Events in Patients With Immune Checkpoint Inhibitor-Related Myocarditis.

Authors:  Magid Awadalla; Syed S Mahmood; John D Groarke; Malek Z O Hassan; Anju Nohria; Adam Rokicki; Sean P Murphy; Nathaniel D Mercaldo; Lili Zhang; Daniel A Zlotoff; Kerry L Reynolds; Raza M Alvi; Dahlia Banerji; Shiying Liu; Lucie M Heinzerling; Maeve Jones-O'Connor; Rula B Bakar; Justine V Cohen; Michael C Kirchberger; Ryan J Sullivan; Dipti Gupta; Connor P Mulligan; Sachin P Shah; Sarju Ganatra; Muhammad A Rizvi; Gagan Sahni; Carlo G Tocchetti; Donald P Lawrence; Michael Mahmoudi; Richard B Devereux; Brian J Forrestal; Anant Mandawat; Alexander R Lyon; Carol L Chen; Ana Barac; Judy Hung; Paaladinesh Thavendiranathan; Michael H Picard; Franck Thuny; Stephane Ederhy; Michael G Fradley; Tomas G Neilan
Journal:  J Am Coll Cardiol       Date:  2020-02-11       Impact factor: 24.094

Review 4.  Myocarditis.

Authors:  Sandeep Sagar; Peter P Liu; Leslie T Cooper
Journal:  Lancet       Date:  2011-12-18       Impact factor: 79.321

Review 5.  The Quest for New Approaches in Myocarditis and Inflammatory Cardiomyopathy.

Authors:  Stephane Heymans; Urs Eriksson; Jukka Lehtonen; Leslie T Cooper
Journal:  J Am Coll Cardiol       Date:  2016-11-29       Impact factor: 24.094

6.  Cardiovascular Events Among Adults Treated With Chimeric Antigen Receptor T-Cells (CAR-T).

Authors:  Raza M Alvi; Matthew J Frigault; Michael G Fradley; Michael D Jain; Syed S Mahmood; Magid Awadalla; Dae Hyun Lee; Daniel A Zlotoff; Lili Zhang; Zsofia D Drobni; Malek Z O Hassan; Emmanuel Bassily; Isaac Rhea; Roohi Ismail-Khan; Connor P Mulligan; Dahlia Banerji; Aleksandr Lazaryan; Bijal D Shah; Adam Rokicki; Noopur Raje; Julio C Chavez; Jeremy Abramson; Frederick L Locke; Tomas G Neilan
Journal:  J Am Coll Cardiol       Date:  2019-12-24       Impact factor: 24.094

7.  Fulminant Myocarditis with Combination Immune Checkpoint Blockade.

Authors:  Douglas B Johnson; Justin M Balko; Margaret L Compton; Spyridon Chalkias; Joshua Gorham; Yaomin Xu; Mellissa Hicks; Igor Puzanov; Matthew R Alexander; Tyler L Bloomer; Jason R Becker; David A Slosky; Elizabeth J Phillips; Mark A Pilkinton; Laura Craig-Owens; Nina Kola; Gregory Plautz; Daniel S Reshef; Jonathan S Deutsch; Raquel P Deering; Benjamin A Olenchock; Andrew H Lichtman; Dan M Roden; Christine E Seidman; Igor J Koralnik; Jonathan G Seidman; Robert D Hoffman; Janis M Taube; Luis A Diaz; Robert A Anders; Jeffrey A Sosman; Javid J Moslehi
Journal:  N Engl J Med       Date:  2016-11-03       Impact factor: 91.245

8.  Prevalence, correlates, and prognostic significance of QRS prolongation in heart failure with reduced and preserved ejection fraction.

Authors:  Lars H Lund; Juliane Jurga; Magnus Edner; Lina Benson; Ulf Dahlström; Cecilia Linde; Urban Alehagen
Journal:  Eur Heart J       Date:  2012-10-04       Impact factor: 29.983

9.  Electrocardiographic Predictors of Morbidity and Mortality in Patients With Acute Myocarditis: The Importance of QRS-T Angle.

Authors:  Shmuel Chen; Sarah Hoss; Vicki Zeniou; Ayelet Shauer; Dan Admon; Donna R Zwas; Chaim Lotan; Andre Keren; Israel Gotsman
Journal:  J Card Fail       Date:  2017-11-20       Impact factor: 5.712

10.  Fatal Toxic Effects Associated With Immune Checkpoint Inhibitors: A Systematic Review and Meta-analysis.

Authors:  Daniel Y Wang; Joe-Elie Salem; Justine V Cohen; Sunandana Chandra; Christian Menzer; Fei Ye; Shilin Zhao; Satya Das; Kathryn E Beckermann; Lisa Ha; W Kimryn Rathmell; Kristin K Ancell; Justin M Balko; Caitlin Bowman; Elizabeth J Davis; David D Chism; Leora Horn; Georgina V Long; Matteo S Carlino; Benedicte Lebrun-Vignes; Zeynep Eroglu; Jessica C Hassel; Alexander M Menzies; Jeffrey A Sosman; Ryan J Sullivan; Javid J Moslehi; Douglas B Johnson
Journal:  JAMA Oncol       Date:  2018-12-01       Impact factor: 31.777

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  11 in total

1.  Defining cardiovascular toxicities of cancer therapies: an International Cardio-Oncology Society (IC-OS) consensus statement.

Authors:  Joerg Herrmann; Daniel Lenihan; Saro Armenian; Ana Barac; Anne Blaes; Daniela Cardinale; Joseph Carver; Susan Dent; Bonnie Ky; Alexander R Lyon; Teresa López-Fernández; Michael G Fradley; Sarju Ganatra; Giuseppe Curigliano; Joshua D Mitchell; Giorgio Minotti; Ninian N Lang; Jennifer E Liu; Tomas G Neilan; Anju Nohria; Rupal O'Quinn; Iskra Pusic; Charles Porter; Kerry L Reynolds; Kathryn J Ruddy; Paaladinesh Thavendiranathan; Peter Valent
Journal:  Eur Heart J       Date:  2022-01-31       Impact factor: 35.855

2.  Immune checkpoint inhibitors for cancer and venous thromboembolic events.

Authors:  Jingyi Gong; Zsofia D Drobni; Raza M Alvi; Sean P Murphy; Ryan J Sullivan; Sarah E Hartmann; Hannah K Gilman; Hang Lee; Leyre Zubiri; Vineet K Raghu; Rebecca S Karp-Leaf; Amna Zafar; Daniel A Zlotoff; Matthew J Frigault; Kerry L Reynolds; Tomas G Neilan
Journal:  Eur J Cancer       Date:  2021-10-15       Impact factor: 10.002

3.  Electrocardiographic Manifestations of Immune Checkpoint Inhibitor Myocarditis.

Authors:  Javid Moslehi; Joe-Elie Salem; John R Power; Joachim Alexandre; Arrush Choudhary; Benay Ozbay; Salim Hayek; Aarti Asnani; Yuichi Tamura; Mandar Aras; Jennifer Cautela; Franck Thuny; Lauren Gilstrap; Dimitri Arangalage; Steven Ewer; Shi Huang; Anita Deswal; Nicolas L Palaskas; Daniel Finke; Lorenz Lehman; Stephane Ederhy
Journal:  Circulation       Date:  2021-11-01       Impact factor: 29.690

4.  Bradyarrhythmias in Cardio-Oncology.

Authors:  Marta Fonseca; Evaline Cheng; Duc Do; Shouvik Haldar; Shelby Kutty; Eric H Yang; Arjun K Ghosh; Avirup Guha
Journal:  South Asian J Cancer       Date:  2021-10-15

5.  Symptomatic Young Adults with ST-Segment Elevation-Acute Coronary Syndrome or Myocarditis: The Three-Factor Diagnostic Model.

Authors:  Paulina Wieczorkiewicz; Katarzyna Przybylak; Karolina Supel; Michal Kidawa; Marzenna Zielinska
Journal:  J Clin Med       Date:  2022-02-10       Impact factor: 4.241

Review 6.  The Diagnosis and Management of Immune Checkpoint Inhibitor Cardiovascular Toxicity: Myocarditis and Beyond.

Authors:  Dan Gilon; Zaza Iakobishvili; David Leibowitz
Journal:  Vaccines (Basel)       Date:  2022-02-16

7.  Multi-organ Immune-Related Adverse Event Is a Risk Factor of Immune Checkpoint Inhibitor-Associated Myocarditis in Cancer Patients: A Multi-center Study.

Authors:  Xiaohong Xie; Liqiang Wang; Yingqing Li; Yan Xu; Jianhui Wu; Xinqing Lin; Wen Lin; Qicong Mai; Zhanhong Chen; Jiexia Zhang; Zhanhong Xie; Yinyin Qin; Ming Liu; Mingjun Lu; Bihui Luo; Chengzhi Zhou
Journal:  Front Immunol       Date:  2022-07-18       Impact factor: 8.786

8.  Echocardiographic and Cardiac MRI Comparison of Longitudinal Strain and Strain Rate in Cancer Patients Treated with Immune Checkpoint Inhibitors.

Authors:  Jibran Mirza; Sunitha Shyam Sunder; Badri Karthikeyan; Sharma Kattel; Saraswati Pokharel; Brian Quigley; Umesh C Sharma
Journal:  J Pers Med       Date:  2022-08-19

9.  Cardiovascular adverse events induced by immune checkpoint inhibitors: A real world study from 2018 to 2022.

Authors:  Si Wu; Hansheng Bai; Ling Zhang; Jiamin He; Xiangru Luo; Shiyi Wang; Guangjun Fan; Na Sun
Journal:  Front Cardiovasc Med       Date:  2022-08-10

10.  Case Report: Treatment for steroid-refractory immune-related myocarditis with tofacitinib.

Authors:  Qian Xing; Zhongwei Zhang; Biao Zhu; Qionghua Lin; Lihua Shen; Fangfang Li; Zhili Xia; Zhiyong Zhao
Journal:  Front Immunol       Date:  2022-09-15       Impact factor: 8.786

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