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Associations between patient and disease characteristics and severe adverse events during immune checkpoint inhibitor treatment: An observational study

Open AccessPublished:August 18, 2022DOI:https://doi.org/10.1016/j.ejca.2022.07.015

      Highlights

      • 12% of patients receiving anti-PD-1 monotherapy experienced grade ≥3 toxicities.
      • 44% of patients receiving anti-PD-1 + CTLA-4 therapy experienced grade ≥3 toxicities.
      • No clinical factor was associated with toxicities during anti-PD-1 (+CTLA4) therapy.
      • This was found across tumour types, as well as in melanoma and NSCLC patients.

      Abstract

      Aim

      With increasing use of immune checkpoint inhibitors (ICIs) more patients will develop severe and potentially life-threatening immune-related adverse events (irAEs). So far, predictive models for the occurrence of grade ≥3 irAEs are lacking. Therefore, we analysed associations between patient and disease characteristics, and the occurrence of grade ≥3 irAEs.

      Methods

      Patients with cancer who were treated with anti-PD-1 (+/−anti-CTLA-4) between July 2015 and February 2020, and who were prospectively included in the MULTOMAB-trial, were eligible for this cohort study. Time to and occurrence of grade ≥3 irAEs according to CTCAE v5.0 were retrospectively registered. The associations between patient and disease characteristics and irAE occurrence were analysed using the competing risk cox-regression model of Fine and Gray. Analyses were performed separately in patients treated with monotherapy (anti-PD-1) and combination therapy (anti-PD-1 + anti-CTLA-4). Subgroup analyses were performed in tumour types with the highest number of patients; melanoma and NSCLC.

      Results

      Out of 641 patients, 106 patients (17%) experienced grade ≥3 irAEs. None of the analysed factors were associated with grade ≥3 irAE occurrence in the monotherapy (n = 550) or the combination therapy (n = 91) groups, nor in the subgroup analyses. Of interest, none of the patients with NSCLC with a WHO performance status of 0 (n = 34) experienced grade ≥3 irAEs. Most common NSCLC histology types were adenocarcinoma (n = 99/55%) and squamous cell carcinoma (n = 39/22%).

      Concluding statement

      This study shows that patient and disease characteristics are not able to predict the occurrence of serious AEs in patients treated with ICIs.

      Keywords

      1. Introduction

      Immune checkpoint inhibitors (ICIs) blocking programmed cell death 1 (PD-1) or cytotoxic T lymphocyte-associated antigen (CTLA-4) such as nivolumab, pembrolizumab, and ipilimumab can cause immune-related adverse events (irAEs). Examples of irAEs are dermatitis, hepatitis, colitis, pneumonitis, hypophysitis, and thyroiditis [
      • Haanen J.
      • Carbonnel F.
      • Robert C.
      • Kerr K.M.
      • Peters S.
      • Larkin J.
      • et al.
      Management of toxicities from immunotherapy: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.
      ,
      • Basak E.A.
      • van der Meer J.W.M.
      • Hurkmans D.P.
      • Schreurs M.W.J.
      • Oomen-de Hoop E.
      • van der Veldt A.A.M.
      • et al.
      Overt thyroid dysfunction and anti-thyroid antibodies predict response to anti-PD-1 immunotherapy in cancer patients.
      ], although virtually every organ system may be affected. Despite anti-PD-1 monotherapy being tolerated by the majority of patients, around 7–20% of the patients experience grade 3 or higher adverse events (SAEs) graded according to Common Terminology Criteria for Adverse Events (CTCAE) [
      • Brahmer J.
      • Reckamp K.L.
      • Baas P.
      • Crino L.
      • Eberhardt W.E.
      • Poddubskaya E.
      • et al.
      Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer.
      ,
      • Weber J.S.
      • Hodi F.S.
      • Wolchok J.D.
      • Topalian S.L.
      • Schadendorf D.
      • Larkin J.
      • et al.
      Safety profile of nivolumab monotherapy: a pooled analysis of patients with advanced melanoma.
      ,
      • Robert C.
      • Long G.V.
      • Brady B.
      • Dutriaux C.
      • Maio M.
      • Mortier L.
      • et al.
      Nivolumab in previously untreated melanoma without BRAF mutation.
      ,
      • Larkin J.
      • Chiarion-Sileni V.
      • Gonzalez R.
      • Grob J.J.
      • Cowey C.L.
      • Lao C.D.
      • et al.
      Combined nivolumab and ipilimumab or monotherapy in untreated melanoma.
      ,
      • Borghaei H.
      • Paz-Ares L.
      • Horn L.
      • Spigel D.R.
      • Steins M.
      • Ready N.E.
      • et al.
      Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer.
      ,
      • Ribas A.
      • Puzanov I.
      • Dummer R.
      • Schadendorf D.
      • Hamid O.
      • Robert C.
      • et al.
      Pembrolizumab versus investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): a randomised, controlled, phase 2 trial.
      ]. When anti-PD-1 therapy is combined with anti-CTLA-4, up to 55% of the patients experience grade ≥3 irAEs [
      • Larkin J.
      • Chiarion-Sileni V.
      • Gonzalez R.
      • Grob J.J.
      • Cowey C.L.
      • Lao C.D.
      • et al.
      Combined nivolumab and ipilimumab or monotherapy in untreated melanoma.
      ].
      SAEs may have various serious consequences. First, in a small fraction of patients, SAEs may lead to mortality. Second, SAEs may require life-long treatment, e.g. hydrocortisone replacement therapy in adrenal failure or hypophysitis. Third, anti-cancer treatment may be delayed or permanently discontinued due to SAEs, precluding further treatment with a potentially effective drug. Fourth, patients may also experience a significant impact on quality of life due to irAE consequences. This might become more relevant, now that ICIs are used in lower disease stages (e.g. in an adjuvant setting), where patients already received treatment with curative intent. Also, immunosuppressants such as prednisone or infliximab may be necessary to resolve irAEs [
      • Haanen J.
      • Carbonnel F.
      • Robert C.
      • Kerr K.M.
      • Peters S.
      • Larkin J.
      • et al.
      Management of toxicities from immunotherapy: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.
      ], which may be accompanied by (potentially long-term) side effects of their own. Moreover, for infliximab, a negative impact on treatment outcomes has been described for patients with melanoma [
      • Verheijden R.J.
      • May A.M.
      • Blank C.U.
      • Aarts M.J.B.
      • van den Berkmortel F.
      • van den Eertwegh A.J.M.
      • et al.
      Association of anti-TNF with decreased survival in steroid refractory ipilimumab and anti-PD1-treated patients in the Dutch melanoma treatment registry.
      ]. Finally, fatal irAEs may occur in a small number of patients: from 0.36% in patients receiving anti-PD-1 monotherapy up to 1.23% when receiving combination therapy [
      • Wang D.Y.
      • Salem J.E.
      • Cohen J.V.
      • Chandra S.
      • Menzer C.
      • Ye F.
      • et al.
      Fatal toxic effects associated with immune checkpoint inhibitors: a systematic review and meta-analysis.
      ]. Therefore, predictive models to identify patients who do not tolerate ICIs are urgently needed.
      Some biomarkers are associated with a higher risk of irAEs during anti-PD-1 therapy, such as high tumour mutational burden, possibly due to differences in neoantigenic load between cancer types [
      • Bomze D.
      • Hasan Ali O.
      • Bate A.
      • Flatz L.
      Association between immune-related adverse events during anti-PD-1 therapy and tumor mutational burden.
      ]. Moreover, for example, the neutrophil-to-lymphocyte ratio was associated with irAEs in solid tumours [
      • Eun Y.
      • Kim I.Y.
      • Sun J.M.
      • Lee J.
      • Cha H.S.
      • Koh E.M.
      • et al.
      Risk factors for immune-related adverse events associated with anti-PD-1 pembrolizumab.
      ]. Recently, activated CD4 memory T cells and TCR diversity has been linked to severe irAE occurrence [
      • Lozano A.X.
      • Chaudhuri A.A.
      • Nene A.
      • Bacchiocchi A.
      • Earland N.
      • Vesely M.D.
      • et al.
      T cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanoma.
      ]. Also, the occurrence of specific irAEs differs between cancer types. Possibly due to different neoantigen profiles between those tumour types [
      • Khoja L.
      • Day D.
      • Wei-Wu Chen T.
      • Siu L.L.
      • Hansen A.R.
      Tumour- and class-specific patterns of immune-related adverse events of immune checkpoint inhibitors: a systematic review.
      ]. However, since most biomarkers have yet failed to sufficiently predict the onset of severe irAEs [
      • Hommes J.W.
      • Verheijden R.J.
      • Suijkerbuijk K.P.M.
      • Hamann D.
      Biomarkers of checkpoint inhibitor induced immune-related adverse events-a comprehensive review.
      ], we aimed to investigate the association of readily available clinical parameters with the occurrence of severe irAEs. Therefore, we studied associations between SAEs and patient and disease characteristics in a large real-life cohort of patients receiving anti-PD-1 therapy with or without anti-CTLA-4 therapy.

      2. Materials and methods

      2.1 Patient selection

      Patients with cancer starting anti-PD-1 treatment with or without anti-CTLA-4 between July 2015 and February 2020, who were prospectively included in the MULTOMAB-trial (Dutch Trial Register Number NTR7015; trialsearch.who.int), and treated at the Erasmus Medical Center (Rotterdam, the Netherlands) were eligible for this cohort study. The local ethics committee of the Erasmus Medical Center approved the study (METC 16-011). The only exclusion criteria for the MULTOMAB-trial is the inability to draw blood for study purposes. All patients were followed for the occurrence of grade ≥3 irAEs until loss of follow-up, death, or data lock point (August 2020).

      2.2 Data classification and outcome definition

      All data were retrospectively collected from the hospitals' electronic patient record system. The following baseline characteristics were collected: tumour type, sex, age at treatment start, type of administered ICI, World Health Organisation (WHO) performance status, lactate dehydrogenase (LDH) level, number of organ sites with metastases, the presence of brain metastases, number of prior treatment lines, treatment setting (e.g. adjuvant therapy), and non-small cell lung cancer (NSCLC) histology. Missing data were not imputed.
      The presence of an SAE, defined as a grade ≥3 irAEs, was based on the grading by the clinician and was recorded from the electronic patient record system from the start of treatment until the end of follow-up. Grades of irAEs were scored using CTCAE v5.0. Furthermore, time from treatment start until onset of the first SAE was noted. To characterise each SAE, the type of clinical management was noted (e.g. prednisone), as well as its consequence regarding ICI therapy (e.g. temporary discontinuation) and outcome (recovered, ongoing, or fatal). Only SAEs related to ICI therapy and that were not pre-existent were included.

      2.3 Data analysis

      The relationship between baseline clinical parameters and the risk of SAEs was retrospectively studied by means of the proportional hazards model for the sub-distribution as described by Fine & Gray [
      • Fine J.P.
      • Gray R.J.
      A proportional hazards model for the subdistribution of a competing risk.
      ] where the occurrence of death before SAE onset was regarded as a competing risk. As the risk of SAEs varies substantially between mono- and combination ICI therapy, analyses were conducted separately for these groups. As SAE occurrence might also differ between tumour types, further subgroup analyses were performed for tumour types with the highest number of patients in our cohort: NSCLC and melanoma in the monotherapy cohort and melanoma in the combination therapy cohort.
      The following variables were included in the analysis for all cohorts: age, sex, number of prior treatment lines, WHO performance status, type of anti-PD-1, number of organ sites with metastases, and presence of brain metastases. Additionally, tumour type was included as a variable for the monotherapy and combination therapy cohorts, histological type of NSCLC for the monotherapy cohort, whereas treatment setting (i.e. adjuvant treatment versus treatment for metastatic disease) was included for the melanoma monotherapy cohort, and LDH level for the melanoma monotherapy and combination therapy cohorts.
      All variables were univariably tested for their association with the occurrence of first SAEs. Variables with a p-value <0.1 in univariable analyses were selected for multivariable analyses where backward selection was applied with a threshold of p <0.05. Categories with <10 patients were excluded.
      A sensitivity analysis was performed to investigate any interference of follow-up time in patients with SAEs versus those without SAEs, therefore all analyses were duplicated excluding patients with <3 months of follow-up. Furthermore, treatment duration between patients with and without SAEs was compared using the Mann–Whitney U test.
      All clinical data were captured using OpenClinica. Statistical analyses were performed using IBM SPSS Statistics, v25 (Chicago, IL) and STATA (v 16.1 StataCorp.; College Station, TX). A p-value <0.05 was considered statistically significant.

      3. Results

      A total of 641 patients who started ICI therapy between July 2015 and February 2020 were prospectively included (see Table 1). The indication for ICI therapy was melanoma in 293 (46%) patients, NSCLC in 181 (28%), mesothelioma in 71 (11%), renal cell carcinoma in 65 (10%), and urothelial cell carcinoma (UCC) in 31 (5%) patients. Overall, 226 (35%) patients were female, and the median age at treatment initiation was 66 (IQR: 58–72) years. A total of 550 patients (86%) were treated with nivolumab (n = 393) or pembrolizumab (n = 157) monotherapy, and 91 (14%) patients were treated with nivolumab–ipilimumab combination therapy, of whom 62 patients (68%) were treated with ipilimumab 3 mg/kg and 29 (32%) with ipilimumab 1 mg/kg. Out of all patients treated in the palliative setting, for 319 (59%) patients ICI therapy was the first line of treatment. A total of 58 melanoma patients received ICI monotherapy in an adjuvant setting. Patients with NSCLC were frequently treated with one or more prior lines of systemic therapy (146 out of 181; 81%), and had a WHO performance status of 2 or higher in 10% of cases (n = 18). Median follow-up time was 10.3 months (IQR: 5.6–18.9).
      Table 1Baseline characteristics of study population (n = 641).
      Total cohort (n = 641)MonotherapyCombination therapy
      Total (n = 550)NSCLC (n = 181)Melanoma (n = 231)Total (n = 91)Melanoma (n = 62)
      Sex, n (%)
      Male415 (65%)356 (65%)103 (57%)140 (61%)59 (65%)37 (60%)
      Female226 (35%)194 (35%)78 (43%)91 (39%)32 (35%)25 (40%)
      Age at start of treatment
      ≤65 years316 (49%)252 (46%)92 (51%)110 (48%)64 (70%)48 (77%)
      >65 years325 (51%)298 (54%)89 (49%)121 (52%)27 (30%)14 (23%)
      Drug treatment, n (%)
      Nivolumab393 (61%)393 (72%)128 (71%)170 (74%)0 (0%)0 (0%)
      Pembrolizumab157 (24%)157 (29%)53 (29%)61 (26%)0 (0%)0 (0%)
      Nivolumab + ipilimumab91 (14%)0 (0%)0 (0%)0 (0%)91 (100%)62 (100%)
      WHO performance status
      0258 (40%)214 (39%)34 (19%)145 (63%)44 (48%)33 (53%)
      1287 (45%)247 (45%)100 (55%)64 (28%)40 (44%)25 (40%)
      234 (5%)29 (5%)17 (9%)4 (2%)5 (6%)2 (3%)
      3+1 (0.2%)1 (0%)1 (1%)0 (0%)0 (0%)0 (0%)
      Unknown61 (10%)59 (11%)29 (16%)18 (8%)2 (2%)2 (3%)
      LDH
      ≤1× ULN345 (54%)300 (55%)42 (23%)166 (72%)45 (49%)25 (40%)
      >1× ULN166 (26%)120 (22%)40 (22%)60 (26%)46 (51%)37 (60%)
      Unknown130 (20%)130 (24%)99 (55%)5 (2%)0 (0%)0 (0%)
      No. of organ sites with metastasis
      0118 (18%)114 (21%)13 (7%)62 (27%)4 (4%)2 (3%)
      1169 (26%)146 (27%)53 (29%)51 (22%)23 (25%)11 (18%)
      2166 (26%)147 (27%)64 (35%)56 (24%)19 (21%)12 (19%)
      3120 (19%)100 (18%)39 (22%)42 (18%)20 (22%)15 (24%)
      445 (7%)32 (6%)8 (4%)15 (7%)13 (14%)11 (17%)
      ≥522 (3%)10 (2%)4 (2%)5 (2%)12 (13%)11 (17%)
      Unknown1 (0%)1 (0%)0 (0%)0 (0%)0 (0%)0 (0%)
      Brain metastasis
      Yes52 (8%)35 (6%)19 (11%)15 (7%)17 (19%)17 (27%)
      No588 (92%)514 (94%)161 (89%)216 (94%)74 (81%)45 (73%)
      Unknown1 (0%)1 (0%)1 (1%)0 (0%)0 (0%)0 (0%)
      No. of prior treatment lines
      0319 (50%)245 (45%)34 (19%)204 (88%)74 (81%)45 (73%)
      1252 (39%)235 (43%)120 (66%)25 (11%)17 (19%)17 (27%)
      261 (10%)61 (11%)23 (13%)2 (1%)0 (0%)0 (0%)
      38 (1%)8 (2%)3 (2%)0 (0%)0 (0%)0 (0%)
      Unknown1 (0%)1 (0%)1 (1%)0 (0%)0 (0%)0 (0%)
      Treatment setting
      Adjuvant58 (9%)58 (11%)0 (0%)58 (25%)0 (0%)0 (0%)
      Overall, 106 patients developed a total of 129 CTCAE grade 3 or higher irAEs during follow-up, most frequently gastro-intestinal toxicity (n = 37), hepatotoxicity (n = 21), skin toxicity (n = 15), pneumonitis (n = 13), and renal toxicity (n = 11) (see Table 2). One event of myocarditis had a fatal outcome and five events concerned grade 4 irAEs (including colitis [n = 2], hepatitis, hyperglycemia and myositis). Details of grade ≥4 irAEs are shown in Supplementary Table 1. The remaining 123 (95%) events were grade 3 irAEs. The median time to onset was 2.1 months, and ranged by type of reaction from a median of 0.9 months (neurological autoimmune disease) to a median of 7.5 months (rheumatic disease; see Fig. 1).
      Table 2Number and type of grade ≥3 adverse reactions observed during immune checkpoint inhibitor therapy.
      Type of reactionTotal number of eventsMedian time to onset,
      Median time to onset taking into account the concerning events.
      months (range)
      Number of events, n (%)
      MonotherapyCombination therapy
      Total (n = 550)Melanoma (n = 231)NSCLC (n = 181)Total (n = 91)
      Colitis, diarrhoea371.8 (0.2–21)22 (4.0%)13 (5.6%)8 (4.4%)15 (16%)
      Hepatitis, ALAT and/or ASAT increase212.2 (0.6–14.8)10 (1.8%)2 (0.9%)7 (3.9%)11 (12%)
      Dermatitis, rash151.3 (0.2–13.8)9 (1.6%)4 (1.7%)3 (1.7%)6 (7%)
      Pneumonitis132.8 (0.2–20.6)9 (1.6%)2 (0.9%)5 (2.8%)4 (4%)
      Nephritis, acute kidney injury112.7 (0.7–5.8)5 (0.9%)2 (0.9%)1 (0.6%)6 (7%)
      Neurological autoimmune disease90.9 (0.2–11.5)5 (0.9%)4 (1.7%)4 (4%)
      Pancreatitis
      Pancreatitis/hyperglycemia: 2 patients experienced both pancreatitis and hyperglycemia.
      55.8 (3.4–22.0)3 (0.5%)1 (0.4%)1 (0.6%)2 (2%)
      Hyperglycemia
      Pancreatitis/hyperglycemia: 2 patients experienced both pancreatitis and hyperglycemia.
      51.6 (0.6–22.6)4 (0.7%)2 (0.9%)1 (1%)
      Rheumatic disease47.5 (2.6–23.7)4 (0.7%)4 (1.7%)
      Thyroiditis21.7 (0.7–2.8)2 (0.4%)1 (0.4%)1 (0.6%)
      Other
      Other events included (all reported once): hemophagocytic lymphohistiocytosis, graft versus host disease, infusion reaction, febrile neutropenia, metabolic acidosis, fever, and myocarditis.
      70.6 (0.3–1.3)4 (0.7%)2 (0.9%)3 (3%)
      Total number of SAEs1291.9 (0–23.7)75352651
      Number of patients with SAEs10666 (12%)31 (13%)25 (13%)40 (44%)
      a Median time to onset taking into account the concerning events.
      b Pancreatitis/hyperglycemia: 2 patients experienced both pancreatitis and hyperglycemia.
      c Other events included (all reported once): hemophagocytic lymphohistiocytosis, graft versus host disease, infusion reaction, febrile neutropenia, metabolic acidosis, fever, and myocarditis.
      Fig. 1
      Fig. 1Time to onset of SAEs since treatment initiation. Box represents 25 to 75th percentile, whiskers represent 5th to 95th percentile. The dots show the outliers.
      The overall incidence of SAEs was higher among patients receiving combination therapy with ipilimumab (40 out of 91 patients; 44%) as compared to patients receiving monotherapy (66 out of 550 patients; 12%). Of the 62 patients receiving ipilimumab 3 mg/kg, 31 patients experienced SAEs (50%), whereas 9 out 29 patients receiving ipilimumab 1 mg/kg had an SAE (31%). Of all patients treated with anti-PD-1 monotherapy or anti-PD-1 and anti-CTLA-4 combination therapy, no variables were significantly associated with the occurrence of SAEs (Table 3). In the subgroup analysis, no variables were associated with the occurrence of SAEs in patients with melanoma or NSCLC receiving monotherapy (Supplementary Table 2) or melanoma patients receiving combination therapy (Supplementary Table 3). However, out of 34 patients with NSCLC with a WHO performance score of 0 none developed SAEs. Whereas of 118 patients with NSCLC with a WHO performance score above 0, 20 developed SAEs (17%). Therefore, this variable could not be analysed in NSCLC patients. One category contained <10 patients and was therefore excluded from analysis (being giant-cell NSCLC histology).
      Table 3Investigated variables and their correlation with the occurrence of a first ≥grade 3 irAEs in the total monotherapy cohort and total combination therapy cohort.
      VariablesTotal monotherapy cohort (n = 550)Total combination therapy cohort (n = 91)
      Events/total (%)UnivariableEvents/total (%)Univariable
      sHR (95% CI)P-valuesHR (95% CI)P-value
      Tumour type
      Melanoma30/231 (13%)Ref31/62 (50%)Ref
      NSCLC25/181 (14%)1.07 (0.63–1.82)0.792
      Mesothelioma5/71 (7%)0.55 (0.22–1.43)0.222
      RCC2/36 (6%)0.42 (0.10–1.74)0.2319/29 (31%)0.54 (0.26–1.10)0.091
      UCC4/31 (13%)0.99 (0.34–2.89)0.980
      Age
      ≤65 years25/252 (10%)Ref29/64 (45%)Ref
      >65 years41/298 (14%)1.43 (0.87–2.34)0.15911/27 (41%)0.90 (0.45–1.80)0.763
      Sex
      Male37/356 (10%)Ref25/59 (42%)Ref
      Female29/194 (15%)1.49 (0.92–2.43)0.10515/32 (47%)0.98 (0.48–2.03)0.966
      No. of prior treatment lines
      In steps of one0.74 (0.46–1.19)0.2150.87 (0.39–1.92)0.732
      WHO status
      021/214 (10%)Ref17/44 (39%)Ref
      ≥137/277 (13%)1.40 (0.82–2.38)0.22022/45 (49%)1.32 (0.65–2.68)0.436
      Type of anti-PD1
      Nivolumab40/393 (10%)Ref
      Pembrolizumab26/157 (17%)1.57 (0.96–2.58)0.073
      No. of organ sites with metastasis
      0–127/260 (10%)Ref13/27 (48%)Ref
      2–337/247 (15%)1.40 (0.85–2.30)0.18218/39 (46%)0.74 (0.32–1.71)0.485
      4–52/41 (5%)0.41 (0.10–1.69)0.2187/21 (33%)0.60 (0.23–1.57)0.299
      Brain metastasis
      No60/514 (12%)Ref31/74 (42%)Ref
      Yes5/35 (14%)1.11 (0.46–2.68)0.8099/17 (53%)1.04 (0.50–2.18)0.904
      LDH range
      Normal38/300 (13%)Ref20/45 (44%)Ref
      >1× ULN16/120 (13%)1.02 (0.57–1.82)0.95020/46 (43%)0.92 (0.50–1.69)0.779
      In the sensitivity analysis, no variables were significantly associated with SAEs. Median treatment duration between patients with and without SAEs were comparable in both the monotherapy (5.1 versus 5.0 months, p = 0.883) and combination therapy cohorts (2.5 versus 2.8 months, p = 0.474).
      Most SAEs were treated with prednisone (dose range 0.1–2.0 mg/kg; 106 out of 129; 82%), and led to temporary discontinuation of ICI treatment (in 45% of the cases). Furthermore, most irAEs fully recovered (75%; Supplementary Table 4).

      4. Discussion

      Our analysis shows that patient and disease characteristics are not able to predict the occurrence of SAEs in patients treated with ICIs. Of the patients with melanoma treated with anti-PD-1 monotherapy, 31 patients (13%) developed SAEs, which is consistent with earlier findings (5–19%) [
      • Verheijden R.J.
      • May A.M.
      • Blank C.U.
      • van der Veldt A.A.M.
      • Boers-Sonderen M.J.
      • Aarts M.J.B.
      • et al.
      Lower risk of severe checkpoint inhibitor toxicity in more advanced disease.
      ,
      • Weber J.S.
      • D'Angelo S.P.
      • Minor D.
      • Hodi F.S.
      • Gutzmer R.
      • Neyns B.
      • et al.
      Nivolumab versus chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial.
      ]. Regarding NSCLC, SAE occurrence in our cohort (n = 25; 13%) was comparable to earlier studies (7–27%) [
      • Brahmer J.
      • Reckamp K.L.
      • Baas P.
      • Crino L.
      • Eberhardt W.E.
      • Poddubskaya E.
      • et al.
      Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer.
      ,
      • Borghaei H.
      • Paz-Ares L.
      • Horn L.
      • Spigel D.R.
      • Steins M.
      • Ready N.E.
      • et al.
      Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer.
      ,
      • Herbst R.S.
      • Baas P.
      • Kim D.W.
      • Felip E.
      • Perez-Gracia J.L.
      • Han J.Y.
      • et al.
      Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial.
      ,
      • Reck M.
      • Rodriguez-Abreu D.
      • Robinson A.G.
      • Hui R.
      • Csoszi T.
      • Fulop A.
      • et al.
      Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer.
      ]. The number of SAEs in the melanoma combination therapy groups was close to those reported in the CheckMate-067 phase 3 clinical trial (50% versus 55%) [
      • Larkin J.
      • Chiarion-Sileni V.
      • Gonzalez R.
      • Grob J.J.
      • Cowey C.L.
      • Lao C.D.
      • et al.
      Combined nivolumab and ipilimumab or monotherapy in untreated melanoma.
      ]. In all our cohorts, gastro-intestinal irAEs were the most occurring severe irAEs. While skin toxicities have been reported as the most occurring irAEs in literature, gastro-intestinal irAEs were shown to be the most occurring severe irAEs [
      • Haanen J.
      • Carbonnel F.
      • Robert C.
      • Kerr K.M.
      • Peters S.
      • Larkin J.
      • et al.
      Management of toxicities from immunotherapy: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.
      ]. The median time until onset of most types of irAEs was within three months, as is described earlier [
      • Haanen J.
      • Carbonnel F.
      • Robert C.
      • Kerr K.M.
      • Peters S.
      • Larkin J.
      • et al.
      Management of toxicities from immunotherapy: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.
      ]. However, small discrepancies exist regarding median time to onset in our cohort compared to literature for some irAEs, e.g. neurological AEs and nephritis [
      • Hassel J.C.
      • Heinzerling L.
      • Aberle J.
      • Bahr O.
      • Eigentler T.K.
      • Grimm M.O.
      • et al.
      Combined immune checkpoint blockade (anti-PD-1/anti-CTLA-4): evaluation and management of adverse drug reactions.
      ,
      • Martins F.
      • Sofiya L.
      • Sykiotis G.P.
      • Lamine F.
      • Maillard M.
      • Fraga M.
      • et al.
      Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance.
      ]. This is possibly due to a different distribution across monotherapy and combination therapy in our cohort and low numbers of cases experiencing those irAEs.
      Studies using real-world data generated conflicting results regarding the association between age and irAEs. A previous analysis regarding patients with melanoma treated with anti-PD-1 monotherapy showed no association between age and SAEs [
      • Verheijden R.J.
      • May A.M.
      • Blank C.U.
      • van der Veldt A.A.M.
      • Boers-Sonderen M.J.
      • Aarts M.J.B.
      • et al.
      Lower risk of severe checkpoint inhibitor toxicity in more advanced disease.
      ]. Other studies also did not demonstrate a significant relationship between age and irAEs [
      • de Glas N.A.
      • Bastiaannet E.
      • van den Bos F.
      • Mooijaart S.P.
      • van der Veldt A.A.M.
      • Suijkerbuijk K.P.M.
      • et al.
      Toxicity, response and survival in older patients with metastatic melanoma treated with checkpoint inhibitors.
      ,
      • Kartolo A.
      • Sattar J.
      • Sahai V.
      • Baetz T.
      • Lakoff J.M.
      Predictors of immunotherapy-induced immune-related adverse events.
      ,
      • Cathcart-Rake E.J.
      • Sangaralingham L.R.
      • Henk H.J.
      • Shah N.D.
      • Riaz I.B.
      • Mansfield A.S.
      A population-based study of immunotherapy-related toxicities in lung cancer.
      ,
      • Mikami T.
      • Liaw B.
      • Asada M.
      • Niimura T.
      • Zamami Y.
      • Green-LaRoche D.
      • et al.
      Neuroimmunological adverse events associated with immune checkpoint inhibitor: a retrospective, pharmacovigilance study using FAERS database.
      ]. However, two studies found significantly more AEs in either older or younger patients, depending on which type of AEs was investigated [
      • Baldini C.
      • Martin Romano P.
      • Voisin A.L.
      • Danlos F.X.
      • Champiat S.
      • Laghouati S.
      • et al.
      Impact of aging on immune-related adverse events generated by anti-programmed death (ligand)PD-(L)1 therapies.
      ,
      • Huang X.
      • Tian T.
      • Zhang Y.
      • Zhou S.
      • Hu P.
      • Zhang J.
      Age-associated changes in adverse events arising from anti-PD-(L)1 therapy.
      ]. Looking at the association between sex and AEs, two studies found an increased risk for either men or women for specific types of AEs [
      • Bai X.
      • Chen X.
      • Wu X.
      • Huang Y.
      • Zhuang Y.
      • Chen Y.
      • et al.
      Immune checkpoint inhibitor-associated pituitary adverse events: an observational, retrospective, disproportionality study.
      ,
      • Zamami Y.
      • Niimura T.
      • Okada N.
      • Koyama T.
      • Fukushima K.
      • Izawa-Ishizawa Y.
      • et al.
      Factors associated with immune checkpoint inhibitor-related myocarditis.
      ]. However, again, many other studies have found no association between sex and AEs at all [
      • Verheijden R.J.
      • May A.M.
      • Blank C.U.
      • van der Veldt A.A.M.
      • Boers-Sonderen M.J.
      • Aarts M.J.B.
      • et al.
      Lower risk of severe checkpoint inhibitor toxicity in more advanced disease.
      ,
      • Cathcart-Rake E.J.
      • Sangaralingham L.R.
      • Henk H.J.
      • Shah N.D.
      • Riaz I.B.
      • Mansfield A.S.
      A population-based study of immunotherapy-related toxicities in lung cancer.
      ,
      • Mikami T.
      • Liaw B.
      • Asada M.
      • Niimura T.
      • Zamami Y.
      • Green-LaRoche D.
      • et al.
      Neuroimmunological adverse events associated with immune checkpoint inhibitor: a retrospective, pharmacovigilance study using FAERS database.
      ,
      • Grouthier V.
      • Lebrun-Vignes B.
      • Moey M.
      • Johnson D.B.
      • Moslehi J.J.
      • Salem J.E.
      • et al.
      Immune checkpoint inhibitor-associated primary adrenal insufficiency: WHO VigiBase Report Analysis.
      ,
      • Kalinich M.
      • Murphy W.
      • Wongvibulsin S.
      • Pahalyants V.
      • Yu K.H.
      • Lu C.
      • et al.
      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.
      ,
      • Zhai Y.
      • Ye X.
      • Hu F.
      • Xu J.
      • Guo X.
      • Zhuang Y.
      • et al.
      Endocrine toxicity of immune checkpoint inhibitors: a real-world study leveraging US Food and Drug Administration adverse events reporting system.
      ]. Those conflicting outcomes per investigated type of AEs underline the caution that should be taken when interpreting relationships between AEs and patient characteristics. Our study showed no association with age or sex and SAE occurrence, confirming that they are not to be used for clinical decision-making in daily practice.
      Contradicting results regarding the relationship between tumour burden or disease stage and the risk of irAEs have been described for different tumour types [
      • Weber J.S.
      • D'Angelo S.P.
      • Minor D.
      • Hodi F.S.
      • Gutzmer R.
      • Neyns B.
      • et al.
      Nivolumab versus chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial.
      ,
      • Sakata Y.
      • Kawamura K.
      • Ichikado K.
      • Shingu N.
      • Yasuda Y.
      • Eguchi Y.
      • et al.
      The association between tumor burden and severe immune-related adverse events in non-small cell lung cancer patients responding to immune-checkpoint inhibitor treatment.
      ,
      • Weber J.
      • Mandala M.
      • Del Vecchio M.
      • Gogas H.J.
      • Arance A.M.
      • Cowey C.L.
      • et al.
      Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma.
      ]. For patients with melanoma, a lower disease stage was associated with more severe irAEs [
      • Verheijden R.J.
      • May A.M.
      • Blank C.U.
      • van der Veldt A.A.M.
      • Boers-Sonderen M.J.
      • Aarts M.J.B.
      • et al.
      Lower risk of severe checkpoint inhibitor toxicity in more advanced disease.
      ]. While a pooled analysis showed no association between NSCLC disease stage and AEs due to ICIs [
      • Suazo-Zepeda E.
      • Bokern M.
      • Vinke P.C.
      • Hiltermann T.J.N.
      • de Bock G.H.
      • Sidorenkov G.
      Risk factors for adverse events induced by immune checkpoint inhibitors in patients with non-small-cell lung cancer: a systematic review and meta-analysis.
      ]. Furthermore, more AEs were seen in the adjuvant setting compared to anti-PD-1 treatment in advanced disease [
      • Weber J.S.
      • D'Angelo S.P.
      • Minor D.
      • Hodi F.S.
      • Gutzmer R.
      • Neyns B.
      • et al.
      Nivolumab versus chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial.
      ,
      • Weber J.
      • Mandala M.
      • Del Vecchio M.
      • Gogas H.J.
      • Arance A.M.
      • Cowey C.L.
      • et al.
      Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma.
      ]. On the contrary, for NSCLC, a high tumour burden was associated with severe irAEs [
      • Sakata Y.
      • Kawamura K.
      • Ichikado K.
      • Shingu N.
      • Yasuda Y.
      • Eguchi Y.
      • et al.
      The association between tumor burden and severe immune-related adverse events in non-small cell lung cancer patients responding to immune-checkpoint inhibitor treatment.
      ]. To compare, in our analyses, no association was found between SAEs and disease stage or LDH level in melanoma, or number of organs with metastases in any cohort. In patients with NSCLC with a WHO performance status of 0, no SAEs occurred. While this finding might be a coincidence, it might also be a reflection of an earlier result describing an association between tumour burden and irAEs in patients with NSCLC [
      • Sakata Y.
      • Kawamura K.
      • Ichikado K.
      • Shingu N.
      • Yasuda Y.
      • Eguchi Y.
      • et al.
      The association between tumor burden and severe immune-related adverse events in non-small cell lung cancer patients responding to immune-checkpoint inhibitor treatment.
      ].
      Limitations of our study are the retrospective collection of SAEs from the patient's electronic recording system. Especially for lower-grade irAEs, clinicians might be less inclined to record mild symptoms and aetiology of mild symptoms is more difficult to assess. Therefore, we only collected grade ≥3 irAEs. In that way, we assessed predictors for the more relevant irAEs for daily clinical practice. However, SAEs relatable to subjective standards might still be less reliable compared to laboratory values. Furthermore, the heterogeneity in the analysed cohort (monotherapy versus combination therapy, tumour type, treatment setting) may lead to small subgroups reducing the power of the analysis. Also, data regarding (familiar) history of autoimmune disease is absent, therefore it might be that in some cases a flare of a pre-existing condition was considered an SAE. However, we excluded SAEs that were pre-existent, limiting the influence of pre-existing conditions on study outcomes. Despite careful selection of irAEs from the electronic patient record system, bias may exist. Clinical frailty in older patients with melanoma might lead to treatment with monotherapy instead of combination therapy, leading to a higher a-priori risk of irAEs in older patients treated with monotherapy. It would have been interesting to investigate the association between SAEs and efficacy. However, our cohort consists of different tumour types, treatment regimens, and disease stages, reducing the reliability of such analysis. IrAEs may occur after a long time, e.g. one patient experienced colitis after 21 months, while some patients are followed for a short period, e.g. due to death caused by disease progression. To account for any time bias, we conducted a competing risk cox-regression analysis, in which death was considered a competing risk. Moreover, we compared the treatment duration between patients with and without SAEs. Also, when excluding patients with <3 months of follow-up, no differences were found compared to the main analyses. Moreover, data lock point was >6 months after inclusion of the last patient, allowing for sufficient follow-up time. These findings suggest that study outcomes are not due to varying follow-up times.
      In conclusion, no associations were found between patient and disease characteristics and SAEs in the total monotherapy and total combination therapy cohorts, nor in the separate NSCLC and melanoma cohorts. Of interest, despite results from earlier publications, we found no association between disease severity measured as treatment setting, LDH level and number of organ sites with metastases and the occurrence of SAEs. Therefore, future analyses should focus on other possible predictors of adverse events.

      Author contributions

      All authors contributed to the final approval of the manuscript and are accountable for all aspects of the work. EAB, NSV, KdJ, DPH, AJ, RHJM contributed to the concept and design of the manuscript. EAB, NSV, DEMV, AAMvdV, JGJVA, AJ, RHJM contributed to data acquisition. EAB, NSV, kdJ, EOH, MWJS, SB, SLWK, RD, AAMvdV, JGJVA, AJ, RHJM contributed to data analysis and interpretation. EAB, NSV, AJ contributed to drafting the manuscript. KdJ, DPH, DEMV, EOH, MWJS, SB, SLWK, RD, AAMvdV, JGJVA, AJ, RHJM contributed to critical revision of the manuscript. EAB, NSV, EOH, AJ contributed to the statistical analysis. DEMV provided administrative support.

      Funding

      This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

      Conflict of interest statement

      The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
      EAB, NSV, KdJ, DPH, DEMV, EOH, MWJS, SB, SLWK declares having no relevant conflict of interest. RD has received research support from MSD and Bayer, personal fees from Bluebird Bio, Genticel, other support from Pan Cancer T outside the submitted work (all paid to the Erasmus MC Cancer Institute), as well as European patent application no's. 21152822.9 and 21184727.2. AAMvdV declares having received consultancy fees (paid to the institute) from BMS, MSD, Merck, Eisai, Ipsen, Pfizer, Pierre Fabre, Novartis, Roche, Sanofi. JGJVA declares having received consulting fees from MSD, BMS, Boehringer Ingelheim, Amphera, Eli-Lilly, Takeda, Bayer, Roche, Astra Zeneca, BIOCAD, payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from MSD, BMS, Boehringer Ingelheim, Amphera, Eli-Lilly, Takeda, Bayer, Roche, Astra Zeneca, BIOCAD, having patents planned, issued or pending regarding biomarkers for immunotherapy, allogenic tumour cell lysates. AJ declares having received support for attending meetings and/or travel from Ipsen. RHJM declares having received grants or contracts (paid to the institute) from Astellas, Bayer, Cristal Therapeutics, Novartis, Pamgene, Pfizer, Roche, Sanofi, Servier.

      Acknowledgements

      We thank Katie S. Hensley for providing additional language revision.

      Appendix A. Supplementary data

      The following is the Supplementary data to this article:

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