Literature DB >> 33789879

Prediction of severe immune-related adverse events requiring hospital admission in patients on immune checkpoint inhibitors: study of a population level insurance claims database from the USA.

Mark Kalinich1, William Murphy1,2,3, Shannon Wongvibulsin3,4, Vartan Pahalyants1,2,3, Kun-Hsing Yu5, Chenyue Lu5, Feicheng Wang5, Leyre Zubiri6, Vivek Naranbhai6,7, Alexander Gusev7, Shawn G Kwatra4, Kerry L Reynolds6, Yevgeniy R Semenov8.   

Abstract

BACKGROUND: Immune-related adverse events (irAEs) are a serious side effect of immune checkpoint inhibitor (ICI) therapy for patients with advanced cancer. Currently, predisposing risk factors are undefined but understanding which patients are at increased risk for irAEs severe enough to require hospitalization would be beneficial to tailor treatment selection and monitoring.
METHODS: We performed a retrospective review of patients with cancer treated with ICIs using unidentifiable claims data from an Aetna nationwide US health insurance database from January 3, 2011 to December 31, 2019, including patients with an identified primary cancer and at least one administration of an ICI. Regression analyses were performed. Main outcomes were incidence of and factors associated with irAE requiring hospitalization in ICI therapy.
RESULTS: There were 68.8 million patients identified in the national database, and 14 378 patients with cancer identified with at least 1 administration of ICI in the study period. Patients were followed over 19 117 patient years and 504 (3.5%) developed an irAE requiring hospitalization. The incidence of irAEs requiring hospitalization per patient ICI treatment year was 2.6%, rising from 0% (0/71) in 2011 to 3.7% (93/2486) in 2016. Combination immunotherapy (OR: 2.44, p<0.001) was associated with increased odds of developing irAEs requiring hospitalization, whereas older patients (OR 0.98 per additional year, p<0.001) and those with non-lung cancer were associated with decreased odds of irAEs requiring hospitalization (melanoma OR: 0.70, p=0.01, renal cell carcinoma OR: 0.71, p=0.03, other cancers OR: 0.50, p<0.001). Sex, region, zip-code-imputed income, and zip-code unemployment were not associated with incidence of irAE requiring hospitalization. Prednisone (72%) and methylprednisolone (25%) were the most common immunosuppressive treatments identified in irAE hospitalizations.
CONCLUSIONS: We found that 3.5% of patients initiating ICI therapy experienced irAEs requiring hospitalization and immunosuppression. The odds of irAEs requiring hospitalization were higher with younger age, treatment with combination ICI therapy (cytotoxic T lymphocyte-associated 4 and programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1)), and lower for other cancers compared with patients on PD-1 or PD-L1 inhibitors with lung cancer. This evidence from the first nationwide study of irAEs requiring hospitalization in the USA identified the real-world epidemiology, risk factors, and treatment patterns of these irAEs which may guide treatment and management decisions. © 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:  Immunotherapy

Mesh:

Substances:

Year:  2021        PMID: 33789879      PMCID: PMC8016099          DOI: 10.1136/jitc-2020-001935

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


Background

Immune checkpoint inhibitors (ICIs) are medications increasingly used to treat cancer that modulate the endogenous immune response. These medications block interaction of checkpoint proteins on tumor cells binding to T-cells, and include inhibition of programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PDL-1), and cytotoxic T lymphocyte-associated 4 (CTLA-4) thus allowing immune activation.1–3 ICIs strengthen antitumor immunity, resulting in enhanced progression free survival and in many cases also overall survival in numerous cancer types.4 Expanding indications for ICIs have rapidly increased ICI use among patients with advanced malignancies, as the percentage of US patients with cancer eligible for ICI therapy has risen from 1.5% in 2011 to 38.5% in 2019.5 6 Activation of the immune system by ICIs can also result in complications of treatment known as immune-related adverse events (irAEs).7 irAEs commonly affect the skin, liver, gastrointestinal tract, and endocrine organs, and although the majority are mild, irAEs may range in severity from mild to life threatening and may require hospitalization with immunosuppression.3 8–13 irAEs are stratified by a clinical grading system which guides treatment decisions including whether to continue therapy, suspend therapy, or treat with immunosuppression.3 14–18 irAEs represent a considerable source of morbidity and mortality for the patient due to the adverse event itself, holding or discontinuing ICI therapy, and possible blunting of the ICI stimulated immune response through systemic immunosuppression.11 19 20 Predicting which patients are at risk of severe irAEs is challenging due to multiple factors: wide variability and lack of standardization in clinical definition of irAEs, lack of a specific International Classification of Disease (ICD) code to denote irAEs, and significant discordance among providers in classifying irAEs in clinical practice.10 21 22 Additionally, the data required to use the Common Terminology Criteria for Adverse Events grading system are frequently unavailable in Insurance Claims databases. Further, reporting of irAEs in clinical trials of ICIs has been shown to be inconsistent and suboptimal, indicating a need for standardized methodology to assess irAEs.23 Understanding which patients are at high risk prior to initiation of therapy would allow for early diagnosis and treatment of irAEs.24 Although there have been efforts to model the risk of irAEs among different classes of ICI therapy, previous studies have focused on clinical trial data,23 used single center data,24 or did not report detailed patient demographics for risk factors.25–27 Here, we propose a definition of irAE requiring hospitalization as hospitalization with new or escalated immunosuppression within 2 years of ICI therapy initiation, and identify factors associated with risk of irAEs requiring hospitalization using an Aetna national claims database from the USA.

Methods

Using unidentifiable Aetna insurance national claims data from January 2011 to December 2019, all patients receiving ICI treatment were identified by Current Procedural Terminology (CPT) procedure codes, and separated into three treatment groups, PD-1 or PD-L1, CTLA-4, and combination (CTLA-4 and PD-1/PD-L1) therapy. Combination therapy was defined as receiving ICI in two classes on the same day. Patient cancer diagnoses were identified using ICD codes, and stratified into major cancer groups: melanoma, lung cancer, renal cell carcinoma (RCC), bladder cancer, colon cancer, head and neck squamous cell carcinoma, Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, breast cancer, prostate cancer, or Merkel cell carcinoma. ICD codes denoting a “personal history,” “cancers in situ,” or “benign” conditions were removed by searching the ICD code text for those strings. Patients with only one cancer diagnosis in the month preceding their first ICI treatment and who had at least three diagnosis codes with that cancer over the study period were included in the study population to minimize contribution from ICD coding errors. Patients with a primary cancer diagnosis of breast and prostate cancer were excluded, as these indications were not Food and Drug Administration (FDA) approved (except those with microsatellite instability-high) for the majority of the study duration28–30). For the analysis, cancers were grouped into melanoma, lung cancer, RCC, and other, which included bladder cancer, colon cancer, head and neck squamous cell carcinoma, Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, or Merkel cell carcinoma. Demographic data, including age, gender, region, zip-code-imputed income, and zip-code-imputed unemployment from 2010 census data, were calculated for each patient. Charlson Comorbidity Index (CCI) score without contribution from cancer (as all patients had advanced cancer) was calculated for each patient using ICD codes prior to initiation of immunotherapy.31 irAEs requiring hospitalization were defined as any inpatient hospitalization associated with commencement of a new immunosuppressive drug not present in a claim in the 14 days prior to admission, or a dose escalation of an immunosuppressive medication that was present in a claim in the 14 days prior to admission (list of medications in online supplemental table 1) within 2 years after initiation of ICI. Combination ICI was defined as administration of two ICIs administered on the same day, and were codified into Nivolumab combination therapy (Nivolumab and any other ICI) and pembrolizumab combination therapy (pembrolizumab and any other ICI). All occurrences of combination therapy were with these two medications. Inpatient hospitalization was defined as place of service being coded as inpatient, with length of stay defined as the discharge date minus the admission date. Medication type and dose were identified by Healthcare Common Procedure Coding System (HCPCS) and National Drug Code (NDC) code. For each hospitalization, new immunosuppressive medications or a dose escalation of prior immunosuppressive medications were identified, and the highest treatment dose given of each was codified. When dosing was “up to” a certain dose, the maximum dose was used.

Study outcomes

The primary study outcome is incidence of irAE, requiring hospitalization as defined as a hospitalization with new or dose escalation of immunosuppression within 2 years of ICI initiation. The secondary outcomes are hospitalizations without immunosuppression, intensive care unit (ICU) admission, and immunosuppressant treatment in irAE hospitalizations.

Statistical analysis

Analyses were performed in R V.3.6.3 (R Statistical Software). Continuous variables were compared with a t-test, and categorical variables were compared with the Pearson’s χ2. Linear regressions were performed on continuous variables, and logistic regressions performed on categorical variables. Where data were non-normal (eg, income), variables were normalized using the scale function in R.

Results

There were 68.8 million patients identified in the national database. Fourteen thousand three hundred seventy-eight patients were identified as having received an ICI administration, an identified primary cancer, and complete demographic information. A summary of demographic characteristic is reported in table 1. The most commonly identified cancer for patients receiving an ICI was lung cancer (N=7393, 51.4%), followed by melanoma (N=3157, 22.0%), RCC (N=1486, 10.3%), and other cancers (N=2342, 16.3%) a group which includes bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma (table 1). The cumulative follow-up time in years after ICI commencement in the 14 378 ICIs recipients was 19 177 (median follow-up, 927 days for patients with irAE, 736 for patients without irAE), and the total number of irAE admissions identified during those years was 504. The overall incidence rate of irAEs requiring hospital admission per patient year was 2.6%, ranging from 0% in 2011 to 3.7% in 2016 (figure 1, table 2). The most common ICI drug exposure was to pembrolizumab, with 7574 (39.5%) patient years, followed by nivolumab with 7367 (38.4%) patient years, and ipilimumab 1561 (8.1%) patient years (table 2).
Table 1

Demographic, treatment, and outcome characteristics of patients with and without severe immune-related adverse event (irAE)

Patients without irAEPatients with severe irAEP value
Number (%)13 874 (96.5%)504 (3.5%)
Men (%)8172 (58.9%)298 (59.1%)0.96
Women (%)5702 (41.1%)206 (40.9%)0.96
Avg age (years)66.763.5<0.001
Avg follow-up time (days)735.5926.5<0.001
Average time to hospitalization (days)172.0148.7<0.001
Immune checkpoint inhibitor use
 PD-110 815 (78.0%)372 (73.8%) 0.03
 PD-L11052 (7.6%)12 (2.4%)<0.001
 CTLA-41022 (7.4%)42 (8.3%)0.47
 CTLA4/PD-1 or CTLA-4/PD-L1 combination985 (7.1%)78 (15.5%)<0.001
 Average ICI treatment Length163.0 days168.2 days0.58
Underlying conditions
 Lung cancer7114 (51.3%)279 (55.4%)0.08
 Melanoma3036 (21.9%)121 (24.0%)0.28
 Renal cell carcinoma1430 (10.3%)56 (11.1%)0.61
 Other cancer2294 (16.5%)48 (9.5%)<0.001
 Average Charlson Comorbidity Index1.51.50.90
Secondary outcomes
 Number of hospitalizations13.1<0.001
 Hospital length (days)3.16<0.001
 Proportion in ICU0.020.056<0.001
Regional information
 Average zip code unemployment0.060.060.33
 Average zip code income63 168.164 332.80.32
 East North Central2123 (15.3%)80 (15.9%)0.77
 East South Central445 (3.2%)14 (2.8%)0.68
 Mid-Atlantic3272 (23.6%)110 (21.8%)0.39
 Mountain626 (4.5%)24 (4.8%)0.88
 New England661 (4.8%)38 (7.5%) 0.01
 Pacific1089 (7.8%)30 (6.0%)0.14
 South Atlantic3261 (23.5%)107 (21.2%)0.26
 West North Central470 (3.4%)25 (5.0%)0.08
 West South Central1927 (13.9%)76 (15.1%)0.49

Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma.

CTLA-4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor; ICU, intensive care unit; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1.

Figure 1

Incidence of immune-related adverse event (irAE) hospitalizations and total hospitalizations in patients on ICI therapy. CRC, colorectal cancer; HNSCC, head and neck squamous cell carcinoma; Merkel, Merkel Cell Carcinoma; RCC, renal cell carcinoma.

Table 2

Immune checkpoint inhibitor usage and immune-related adverse event (irAE) incidence over time

EventTherapy class201120122013201420152016201720182019Total
Number of patients 19 177% of total
 Pembrolizumab PD-1113393134123423385757439.5%
 Nivolumab PD-14221702165219221669736738.4%
 Ipilimumab CTLA-471193196319306205140745715618.1%
 Nivolumab combination therapy1712921947856614097.3%
 Atezolizumab PD-L15720727865812006.3%
 Avelumab PD-L163126630.3%
 Pembrolizumab combination therapy2130.0%
Number of irAEs 504
 Pembrolizumab PD-11336675016632.9%
 Nivolumab PD-1105852543220640.9%
 Ipilimumab CTLA-424617661428.3%
 Nivolumab combination therapy1611302178
 Atezolizumab PD-L145211
 Avelumab PD-L111
irAE/patient year 0.0%1.0%2.0%1.9%3.1%3.7%3.1%3.1%1.7%2.6%

CTLA-4, cytotoxic T lymphocyte-associated 4; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1.

Demographic, treatment, and outcome characteristics of patients with and without severe immune-related adverse event (irAE) Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma. CTLA-4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor; ICU, intensive care unit; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1. Incidence of immune-related adverse event (irAE) hospitalizations and total hospitalizations in patients on ICI therapy. CRC, colorectal cancer; HNSCC, head and neck squamous cell carcinoma; Merkel, Merkel Cell Carcinoma; RCC, renal cell carcinoma. Immune checkpoint inhibitor usage and immune-related adverse event (irAE) incidence over time CTLA-4, cytotoxic T lymphocyte-associated 4; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1. The incidence of irAEs requiring hospitalization as defined by hospitalization with new or escalated immunosuppression within 2 years of ICI initiation was 504/14 378 patients (3.5%) (table 2). irAEs requiring hospitalization were identified in 372 (3.3%) patients on PD-1 therapy, 12 (1.1%) on PD-L1 therapy, 42 (3.9%) on CTLA-4 therapy, and 78 (7.3%) on combination CTLA-4 and PD-1 or PD-L1 therapy. The average time from start date of ICI treatment to irAE requiring hospitalization was 168.2 days (range: 1–722). Seven thousand five hundred eighty-seven (53%) patients were hospitalized in 16 053 hospitalizations within 2 years of immunotherapy initiation. The total number of patients that were hospitalized more than once was 3888 (27%). Patients with irAE requiring hospitalization had more total hospitalizations than those without irAE requiring hospitalization in the 2 years after ICI initiation (3.1 vs 1 hospitalizations, p<0.001). Length of stay was greater for patients with irAEs requiring hospitalization than those without irAE requiring hospitalization (6 vs 3.1 days, p<0.001). Patients with irAE requiring hospitalization were more likely to be in the ICU than those without (0.06 vs 0.02 ICU visits per patient, p<0.001).

Multivariable modeling

Regressions were performed on the incidence of irAEs requiring hospitalization, all cause hospitalizations, and ICU stay (tables 3–5). In each regression, female patients with lung cancer on PD-1/PD-L1 therapy were used as the reference group. Multivariate regression results for incidence of severe immune-related adverse event Note: reference group is female patients on programmed cell death protein 1 or programmed death-ligand 1 therapy with lung cancer in East North Central Region. Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma. CTLA-4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor. Multivariate regression results for incidence of hospitalization Note: reference group is female patients on programmed cell death protein 1 or programmed death-ligand 1 therapy with lung cancer in East North Central Region. Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma. CTLA4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor. Multivariate regression results for incidence of intensive care unit admission Note: reference group is female patients on programmed cell death protein 1or programmed death-ligand 1 therapy with Lung Cancer in East North Central Region. Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma. CTLA4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor. Severe irAE incidence regression (table 3): compared with the reference group, combination ICI therapy (anti-PD-1/PD-L1 and CTLA-4) was associated with increased odds of irAE requiring hospitalization (OR: 2.44, p<0.001). Older patients (OR 0.98 per additional year, p<0.001), patients with other cancers (OR 0.50, p<0.001), patients with melanoma (OR 0.71, p=0.01) and patients with RCC (OR 0.71, p=0.03) were associated with decreased odds of a irAE requiring hospitalization than the reference group.
Table 3

Multivariate regression results for incidence of severe immune-related adverse event

EstimateSEStatisticP valueOROR SE
Patient characteristics
 Age−0.020.00−5.49<0.0010.980.05
 Male gender0.070.090.760.451.070.15
 Charlson Comorbidity Index (excluding cancer)0.030.021.610.111.030.23
Immune checkpoint inhibitor use
 CTLA-4 therapy0.290.21.420.161.340.2
 Combination ICI therapy0.890.146.18<0.0012.440.11
Underlying conditions
 Other cancer−0.690.16−4.29<0.0010.50.03
 Melanoma−0.350.14−2.45 0.01 0.710.21
 Renal cell carcinoma−0.350.16−2.17 0.03 0.710.11
Regional information
 Zip code average income (normalized)0.040.050.740.461.040.17
 Zip code average unemployment (normalized)−0.020.05−0.390.70.980.16
 East South Central−0.250.3−0.830.410.780.02
 Mid-Atlantic−0.170.15−1.090.280.850.14
 Mountain−0.080.24−0.320.750.930.19
 New England0.350.211.710.091.420.34
 Pacific−0.370.22−1.680.090.690.14
 South Atlantic−0.180.15−1.180.240.840.2
 West North Central0.230.240.960.341.260.12
 West South Central−0.040.17−0.230.820.960.14

Note: reference group is female patients on programmed cell death protein 1 or programmed death-ligand 1 therapy with lung cancer in East North Central Region.

Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma.

CTLA-4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor.

Hospitalization incidence regression (table 4): compared with the reference group, anti-CTLA-4 therapy (OR: 2.34, p<0.001), combination ICI therapy (OR: 1.70, p<0.001), and higher non-cancer CCI (OR: 1.06, p<0.001) were associated with increased odds of all cause hospitalization. Patients with melanoma were associated with decreased odds of all cause hospitalization compared with the reference group (OR: 0.55, p<0.001). Region was also associated with all cause hospitalization, notably decreased in the Pacific region (OR: 0.69, p<0.001).
Table 4

Multivariate regression results for incidence of hospitalization

VariableEstimateSEStatisticP valueOROR SE
Patient characteristics
 Age0.000.000.810.421.000.01
 Male gender−0.020.03−0.710.480.980.07
 Charlson Comorbidity Index (excluding cancer)0.060.017.19<0.0011.060.02
Immune checkpoint inhibitor use
 CTLA4 therapy0.850.0810.81<0.0012.340.04
 Combination ICI therapy0.530.077.55<0.0011.70.03
Underlying conditions
 Other cancer−0.080.05−1.590.110.930.06
 Melanoma−0.60.05−11.39<0.0010.550.03
 Renal cell carcinoma−0.280.06−4.75<0.0010.750.07
Regional information
 Zip code average income (normalized)0.040.021.94 0.05 1.040.01
 Zip code average unemployment (normalized)0.040.022.28 0.02 1.050.07
 East South Central
 Mid-Atlantic−0.120.06−2.11 0.04 0.890.03
 Mountain−0.330.09−3.63<0.0010.720.05
 New England−0.160.09−1.80.070.850.04
 Pacific−0.370.08−4.93<0.0010.690.04
 South Atlantic−0.270.06−4.89<0.0010.760.07
 West North Central−0.190.1−1.870.060.830.04
 West South Central−0.190.06−2.96<0.010.830.05

Note: reference group is female patients on programmed cell death protein 1 or programmed death-ligand 1 therapy with lung cancer in East North Central Region.

Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma.

CTLA4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor.

ICU stay incidence regression (table 5): compared with the reference group, older patients were associated with decreased odds of all cause admission to the ICU (OR: 0.97 per additional year, p<0.001). Patients with an irAE hospitalization (OR: 2.60, p<0.001), higher non-cancer CCI (OR: 1.07, p=0.01), and higher zip code average income (OR: 1.19, p=0.01) were associated with increased odds of all cause ICU admission than the reference group.
Table 5

Multivariate regression results for incidence of intensive care unit admission

EstimateSEStatisticP valueOROR SE
Patient characteristics
Age−0.030.00−5.41<0.0010.970.00
Male gender0.110.120.890.371.120.28
Charlson Comorbidity Index (excluding cancer)0.060.032.36 0.02 1.060.07
Immune checkpoint inhibitor use
CTLA4 therapy0.360.251.470.141.440.29
Combination ICI therapy0.210.220.960.341.230.46
Underlying conditions
Other cancer0.110.170.670.51.120.24
Melanoma−0.070.19−0.380.70.930.19
Renal cell carcinoma0.110.20.550.581.120.03
Regional information
Zip code average income (normalized)0.170.062.72 0.01 1.190.08
Zip code average unemployment (normalized)0.050.070.680.51.050.37
East South Central
Mid-Atlantic−0.080.2−0.390.70.920.16
Mountain0.210.290.70.481.230.25
New England−0.580.37−1.560.120.560.21
Pacific0.150.250.60.551.160.14
South Atlantic−0.10.21−0.480.630.910.17
West North Central0.110.350.310.761.110.27
West South Central0.220.2210.321.240.37

Note: reference group is female patients on programmed cell death protein 1or programmed death-ligand 1 therapy with Lung Cancer in East North Central Region.

Other cancers include: bladder cancer, colon cancer, head and neck squamous cell carcinoma Hodgkin’s lymphoma, gastric cancer, liver cancer, cervical cancer, and Merkel cell carcinoma.

CTLA4, cytotoxic T lymphocyte-associated 4; ICI, immune checkpoint inhibitor.

Immunosuppressant use in hospitalizations

Of the immunosuppressants identified in online supplemental table 1), prednisone (72%) and methylprednisolone (25%) accounted for the majority of immunosuppressant medications found in irAE hospitalizations. The remaining identified immunosuppressants each accounted for less than 1% immunosuppressive medications identified during an irAE hospitalization: azathioprine, cyclosporine, everolimus, infliximab, methotrexate, mycophenolate, sirolimus, and tacrolimus (table 6).
Table 6

Number of immune-related adverse events hospitalizations with administration of immunosuppressants

ImmunosuppressantNumber of hospitalizations
Prednisone454 (71.8%)
Methylprednisolone160 (25.3%)
Mycophenolate5 (0.8%)
Tacrolimus3 (0.5%)
Cyclosporine2 (0.3%)
Everolimus2 (0.3%)
Infliximab2 (0.3%)
Sirolimus2 (0.3%)
Azathioprine1 (0.2%)
Methotrexate1 (0.2%)
Basiliximab0
IVIG0
Leflunomide0
Rituximab0
Tocilizumab0
Vedolizumab0

IVIG, Intravenous immunoglobulin.

Number of immune-related adverse events hospitalizations with administration of immunosuppressants IVIG, Intravenous immunoglobulin.

Discussion/conclusion

ICIs have shown great promise in treating a variety of advanced cancers. However, activation of the immune system during treatment frequently leads to immune-related adverse events in many patients. This study describes the experience of ICI use and the incidence of irAEs requiring hospitalization for patients in a national Aetna insurance database, and proposes an algorithm to identify and study irAEs requiring hospitalization using claims data. The results of this study can be used to identify patients at higher risk of being admitted with irAE and enable analysis of other large claims databases to compare experience across payors and institutions. Our study showed that the absolute incidence of irAEs requiring hospitalization in the study population increased over time from 2011 to 2019, a finding that is consistent with the increased use of ICI over that time period. We demonstrate that combination therapy is associated with increased odds of irAE requiring hospitalization, which is in agreement with prior findings that combination therapy32 and CTLA-4 therapy23 33–35 are associated with higher incidence of irAEs relative to PD-1 or PD-L1 treatment. The incidence of irAEs requiring hospitalization in this study was 3.5% overall, with 3.3% for patients receiving PD-1, 1.1% for patients receiving PD-L1, 3.9% for patients receiving CTLA-4 therapy, and 7.3% for patients on combination therapy. These figures are lower compared with early estimates of clinical trial data, which reported high-grade irAEs in 6.3% of patients with PDL-1, 7.1% of patients taking PD-1, 21.5% of patients taking CTLA-4, and 54.8% in CLTA-4 and PD-1 combination therapy.34 Similarly, a meta-analysis of phases II and III clinical trials showed incidence of grade 3 or 4 immune-related adverse events for atezolizumab, nivolumab, pembrolizumab, and ipilimumab of 15.1%, 14.1%, 19.8%, and 28.6%, respectively.36 However, a recent publication identified a similar rate (3.6%) of high-grade (grade 3+) irAEs in a single-center experience with PD-1 therapy.24 The lower rate found in our population relative to clinical trial data may be representative of less toxic ICI treatment regimens or reflect real-world treatment patterns and identification of high-grade events outside of clinical trial settings. Additionally, our study would not include irAE admissions where immunosuppression is not indicated for treatment, such as endocrinopathies. In our study, average hospitalization length of stay for irAE patients was 6 days, which is consistent with previous study results.32 Our study reports that patients with severe irAEs were more likely to have an ICU admission (OR 2.60, p<0.001), which is not a widely reported outcome in large scale ICI studies.34 As ICI indications have expanded and use of ICIs has continued to grow, the percentage of patients with cancer eligible for ICI therapy has been estimated at up to 38.5% in 2019, representing up to 233 790 potential US ICI patients treated with standard of care therapy alone.6 If, as in our study population, 3.5% of patients receiving ICI therapy experience irAEs requiring hospitalization, that would represent approximately 8200 hospitalizations if all eligible patients received therapy—a population that is expected to grow.6 This increasing incidence of irAEs requiring hospitalization necessitates greater knowledge and training among emergency department, primary care, internal medicine, and specialty providers to accurately diagnose and treat severe immune-related adverse events.37 If these irAEs are not treated appropriately, there is risk of substantially increased morbidity and mortality.26 Additionally, these data show that older age is protective of both irAEs requiring hospitalization and ICU stay. Previous studies have shown mixed results between age and the risk of irAE in ICI recipients, with alternate studies finding no association between age and irAEs,7 higher incidence with older patients38 and higher incidence with younger patients.39 With regards to the likelihood of ICU stay, our findings are similar to a single center study showing that patients <70 years old have a higher likelihood of an ICU stay as well as longer ICU stays than older patients.38 This may be due to relatively less severe irAEs, immune senescence in older patients, differing goals of care, more cautious treatment in the elderly, lower proportion of combination ICI therapy in the elderly, or a combination of all. Male gender was not predictive of irAE, hospitalization, or ICU stay in our study. A study reviewing PD-1 therapy found a greater incidence of all grade irAEs in women, but no gender difference in high-grade irAEs, which is more similar to the irAE definition in this study.40 This study also showed that severe irAEs are more frequent among patients with lung cancer than patients with RCC, melanoma, or other primary cancers. The difference in incidence may be due different provider experience using ICI therapy among these cancer types. Although previous studies have shown differences in type of irAEs for different primary cancers,33 the current analysis of irAEs requiring hospitalization defines the overall likelihood of developing an irAE requiring hospitalization by primary cancer. We show that by far the most frequent immunosuppressive treatments used with patients on ICIs in this study are prednisone (72%) and methylprednisolone (25%), with limited use of other immunosuppressants. This is consistent with guidance that grade 3+irAEs should be treated with prednisone or methylprednisolone, and other immunosuppressants such as infliximab should be reserved for those who do not respond to initial therapy.3 This result signifies that few (3%) hospitalizations for severe irAEs require immunosuppressive medication other than prednisone or methylprednisolone. These data imply that in our population, refractory irAEs requiring second line immunosuppression are not common, and incidence of such refractory toxicities is likely low. This analysis is limited by a retrospective study design, lack of comprehensive mortality data, and inability to review chart-level data to determine clinician interpretation of suspected irAEs. As a result, our definition of severe irAEs is likely overly strict and limited to patients with more severe events than what has been previously reported in literature. In particular, this definition of severe irAE used in this analysis would not include low-grade toxicities that did not result in hospitalization with new or escalated immunosuppression, and as such the results may not be generalizable to low-grade irAE and the overall number is likely underestimated. Additionally, the definition of severe irAE in this analysis is impacted by regional, hospital system, and individual provider capabilities and practice patterns; for example, the ability of a hospital to provide emergency care for an irAE in the inpatient setting. Also, as our inclusion criteria involve selecting for patients with cancer diagnosis codes in a post-treat matter, it may incur collider bias. In this first, population-level analysis of immunotherapy toxicities in the USA, we describe a method of querying large, insurance claims databases for suspected high-grade irAEs and identify the incidence, risk factors, and outcomes associated with severe irAEs. We further identified patient factors that can be used to predict the likelihood of severe irAEs and lay the methodological basis for future research on this topic utilizing insurance claims data. Additionally, we described that patients with an identified irAE hospitalization have more total hospitalizations in the 2 years after starting ICI (3.1 vs 1 hospitalizations), and the length of stay for irAE hospitalizations is double that for non-irAE hospitalizations (6 vs 3.1 days). This, coupled with the increasing incidence of ICI use, underscore the importance of understanding the likelihood of and factors related to severe irAEs and large, population-level databases will enable researchers to answer important questions regarding risk factors and outcomes for severe irAEs that cannot be answered in clinical trials or with individual studies. It is critical that we build on this study to further refine queries and that open-access is granted to replicate these important findings across other databases.
  38 in total

Review 1.  Pathogenesis, clinical manifestations and management of immune checkpoint inhibitors toxicity.

Authors:  Alessandro Inno; Giulio Metro; Paolo Bironzo; Antonio M Grimaldi; Elisabetta Grego; Vincenzo Di Nunno; Virginia Picasso; Francesco Massari; Stefania Gori
Journal:  Tumori       Date:  2017-05-10       Impact factor: 2.098

Review 2.  Dermatomyositis in a patient undergoing nivolumab therapy for metastatic melanoma: a case report and review of the literature.

Authors:  Cory Kosche; Molly Stout; Jeffrey Sosman; Rimas V Lukas; Jennifer N Choi
Journal:  Melanoma Res       Date:  2020-06       Impact factor: 3.599

3.  Association of age with differences in immune related adverse events and survival of patients with advanced nonsmall cell lung cancer receiving pembrolizumab or nivolumab.

Authors:  Doran Ksienski; Elaine S Wai; Nicole S Croteau; Ashley T Freeman; Angela Chan; Leathia Fiorino; Zia Poonja; David Fenton; Tiffany Patterson; Sarah Irons; Mary Lesperance
Journal:  J Geriatr Oncol       Date:  2020-01-11       Impact factor: 3.599

4.  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

5.  Performance Status and Age as Predictors of Immunotherapy Outcomes in Advanced Non-Small-Cell Lung Cancer.

Authors:  Tamjeed Ahmed; Thomas Lycan; Andy Dothard; Paul Ehrlichman; Jimmy Ruiz; Michael Farris; Umit Topaloglu; Beverly Levine; Stefan Grant; Heidi D Klepin; W Jeffrey Petty
Journal:  Clin Lung Cancer       Date:  2020-01-23       Impact factor: 4.785

Review 6.  Tumour- and class-specific patterns of immune-related adverse events of immune checkpoint inhibitors: a systematic review.

Authors:  L Khoja; D Day; T Wei-Wu Chen; L L Siu; A R Hansen
Journal:  Ann Oncol       Date:  2017-10-01       Impact factor: 32.976

Review 7.  Management of adverse events related to checkpoint inhibition therapy.

Authors:  Jakob Daniel Rudzki
Journal:  Memo       Date:  2018-06-12

8.  Comparative safety of immune checkpoint inhibitors in cancer: systematic review and network meta-analysis.

Authors:  Cheng Xu; Yu-Pei Chen; Xiao-Jing Du; Jin-Qi Liu; Cheng-Long Huang; Lei Chen; Guan-Qun Zhou; Wen-Fei Li; Yan-Ping Mao; Chiun Hsu; Qing Liu; Ai-Hua Lin; Ling-Long Tang; Ying Sun; Jun Ma
Journal:  BMJ       Date:  2018-11-08

Review 9.  Immune-related adverse events and anti-tumor efficacy of immune checkpoint inhibitors.

Authors:  Satya Das; Douglas B Johnson
Journal:  J Immunother Cancer       Date:  2019-11-15       Impact factor: 13.751

10.  Immune-Related Adverse Events Requiring Hospitalization: Spectrum of Toxicity, Treatment, and Outcomes.

Authors:  Aanika Balaji; Jiajia Zhang; Beatriz Wills; Kristen A Marrone; Hany Elmariah; Mark Yarchoan; Jacquelyn W Zimmerman; Khalid Hajjir; Deepti Venkatraman; Deborah K Armstrong; Daniel A Laheru; Ranee Mehra; Won Jin Ho; Joshua E Reuss; Joseph Heng; Paz Vellanki; Ross C Donehower; Matthias Holdhoff; Jarushka Naidoo
Journal:  J Oncol Pract       Date:  2019-08-06       Impact factor: 3.714

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  10 in total

1.  Identification of cutaneous immune-related adverse events by International Classification of Diseases codes and medication administration.

Authors:  Wenxin Chen; Guihong Wan; Nga Nguyen; Bonnie Leung; Jun Wen; Michael R Collier; Shawn G Kwatra; Yevgeniy R Semenov
Journal:  JAAD Int       Date:  2022-08-18

Review 2.  Harnessing big data to characterize immune-related adverse events.

Authors:  Ying Jing; Jingwen Yang; Douglas B Johnson; Javid J Moslehi; Leng Han
Journal:  Nat Rev Clin Oncol       Date:  2022-01-17       Impact factor: 65.011

3.  Adverse Cardiovascular Complications following prescription of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) inhibitors: a propensity-score matched Cohort Study with competing risk analysis.

Authors:  Jiandong Zhou; Sharen Lee; Ishan Lakhani; Lei Yang; Tong Liu; Yuhui Zhang; Yunlong Xia; Wing Tak Wong; Kelvin King Hei Bao; Ian Chi Kei Wong; Gary Tse; Qingpeng Zhang
Journal:  Cardiooncology       Date:  2022-03-17

4.  Large-scale real-world data analysis identifies comorbidity patterns in schizophrenia.

Authors:  Chenyue Lu; Di Jin; Nathan Palmer; Kathe Fox; Isaac S Kohane; Jordan W Smoller; Kun-Hsing Yu
Journal:  Transl Psychiatry       Date:  2022-04-11       Impact factor: 6.222

Review 5.  Risk Factors and Biomarkers for Immune-Related Adverse Events: A Practical Guide to Identifying High-Risk Patients and Rechallenging Immune Checkpoint Inhibitors.

Authors:  Adithya Chennamadhavuni; Laith Abushahin; Ning Jin; Carolyn J Presley; Ashish Manne
Journal:  Front Immunol       Date:  2022-04-26       Impact factor: 8.786

6.  Monitoring Endocrine Complications of Immunotherapy: A Screening Tool.

Authors:  Priyanka Majety; Anna Groysman; Virginia Seery; Meghan Shea; Runhua Hou
Journal:  Cureus       Date:  2022-07-14

7.  Impact of gender on response to immune checkpoint inhibitors in patients with non-small cell lung cancer undergoing second- or later-line treatment.

Authors:  Myeong Geun Choi; Chang-Min Choi; Dae Ho Lee; Sang-We Kim; Shinkyo Yoon; Wonjun Ji; Jae Cheol Lee
Journal:  Transl Lung Cancer Res       Date:  2022-09

8.  Hospitalized cancer patients with comorbidities and low lymphocyte counts had poor clinical outcomes to immune checkpoint inhibitors.

Authors:  Richard Benjamin Young; Hemali Panchal; Weijie Ma; Shuai Chen; Aaron Steele; Andrea Iannucci; Tianhong Li
Journal:  Front Oncol       Date:  2022-09-14       Impact factor: 5.738

9.  Immune Checkpoint Inhibitor-Induced Myositis/Myocarditis with Myasthenia Gravis-like Misleading Presentation: A Case Series in Intensive Care Unit.

Authors:  François Deharo; Julien Carvelli; Jennifer Cautela; Maxime Garcia; Claire Sarles; Andre Maues de Paula; Jérémy Bourenne; Marc Gainnier; Amandine Bichon
Journal:  J Clin Med       Date:  2022-09-23       Impact factor: 4.964

Review 10.  Overcoming the cardiac toxicities of cancer therapy immune checkpoint inhibitors.

Authors:  Omoruyi Credit Irabor; Nicolas Nelson; Yash Shah; Muneeb Khan Niazi; Spencer Poiset; Eugene Storozynsky; Dinender K Singla; Douglas Craig Hooper; Bo Lu
Journal:  Front Oncol       Date:  2022-09-16       Impact factor: 5.738

  10 in total

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