Aging, immune senescence, and immunotherapy: A comprehensive review

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Aging, immune senescence, and immunotherapy: A comprehensive review Rawad Elias a,∗, Kevan Hartshorn b, Osama Rahma c, Nina Lin d, Jennifer E. Snyder-Cappione e,f a

Hartford HealthCare Cancer Institute, Hartford Hospital, Hartford, CT, USA Section of Hematology Oncology, Boston University School of Medicine, Boston, MA, USA c Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA d Department of Medicine, Boston Medical Center, Boston University School of Medicine, MA, USA e Department of Microbiology, Boston University School of Medicine, Boston, MA, USA f Flow Cytometry Core Facility, Boston University School of Medicine, Boston, MA, USA b

a r t i c l e

i n f o

Article history: Received 11 January 2018 Revised 7 July 2018 Accepted 1 August 2018 Available online xxx Keywords: Immunotherapy Checkpoint inhibitors Older adults Immune senescence Frailty

a b s t r a c t The advent of immune checkpoint inhibitors (ICIs) has changed the landscape of cancer treatment. Older adults represent the majority of cancer patients; however, direct data evaluating ICIs in this patient population is lacking. Aging is associated with changes in the immune system known as “immunosenescence” that could impact the efficacy and safety profile of ICIs. In this paper, we review aging-associated changes in the immune system as they may relate to cancer and immunotherapy, with mention of the effect of chronic viral infections and frailty. Furthermore, we summarize the current clinical evidence of ICI effectiveness and toxicity among older adults with cancer. © 2018 Elsevier Inc. All rights reserved.

Introduction Immune Checkpoint Inhibitors (ICIs) showed efficacy in a variety of malignancies [1-13]. The activity of these agents results from unleashing antitumor immunity by blocking inhibitory receptor ligation which under regular physiological conditions aids in self-tolerance and limits immunopathology; however, in the setting of malignancy, this checkpoint inhibition is used by tumors to escape immune responses [14,15]. Immunologic changes seen with aging, known as “immunosenescence,” lead to higher susceptibility to infections, autoimmune diseases, and cancer [16-18]. Due to these changes, the efficacy and safety profile of ICIs in older adults might be different from younger patients. Care of older adults, who represent the majority of cancer patients, is complicated by many variables such as comorbidity, decreased functional status, polypharmacy, and age-related organ dysfunction. Treatment tolerability, quality of life, and survival of older patients are affected by these geriatric variables [19-21]. Despite this, the clinical efficacy of ICIs has not been specifically assessed in older adults to date [22]. We will review immune changes seen in older adults due to biologic aging, chronic viral infections, and frailty. Furthermore, we

∗ Corresponding author. Hartford HealthCare Cancer Institute, Hartford Hospital, Hartford, CT, USA. E-mail address: [email protected] (R. Elias).

https://doi.org/10.1053/j.seminoncol.2018.08.006 0093-7754/© 2018 Elsevier Inc. All rights reserved.

will summarize the current clinical database on effectiveness and toxicity of ICIs in older adults. Aging and immune changes We divide this discussion into 3 sections based on the category of immune cell subsets: (A) innate cells, (B) immune cells that bridge innate and adaptive immune responses, and (C) adaptive cells. Innate cells often serve as the first responders in immune responses, thereby activating the innate-adaptive bridging cells, and both of the latter enable and shape antigen-specific memory B and T cell repertoires. A. Innate immune cells: Neutrophils, monocytes/macrophages, myeloid-derived suppressor cells, and dendritic cells The cellular components of the innate immune system include neutrophils, monocytes/macrophages, Myeloid-Derived Suppressor Cells (MDSCs), and dendritic cells (DCs), among others. Activation of innate immune cells can be triggered by direct phagocytosis of cellular components/debris or via stimulation of Toll-Like Receptors and other surface antigens poised to respond to early activation signals. In this section, we will summarize both the key effects of aging on some of the major cell subsets of the innate immune system and their relevance to cancer.

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Neutrophils Neutrophils can be separated based on their activity profile into N1 or N2 phenotype. N1 neutrophils have an antitumor role through direct toxicity, antibody cell-mediated cytotoxicity, and by stimulation of dendritic and T cells [23-28]. N2 neutrophils promote tumor growth and spread through secretion of cytokines and various growth factors, enhancement of tumor angiogenesis, and inhibition of other components of the immune system [29-34]. The impairment in neutrophil function with aging is considered to be a primary reason for the increased numbers of infections found in older adults as compared with younger counterparts [35]. Neutrophil counts remain unchanged with aging; in fact, hematopoietic stem cell production becomes skewed in favor of myeloid lineage cells in older adults [36]. Data suggest that neutrophils’ chemotactic responses and migratory function become impaired with aging but their adhesive capability remains unaffected [37-39]. Some reports show that phagocytosis and production of reactive oxygen species by neutrophils are compromised with aging [40]. Macrophages/monocytes Monocytes/macrophages mediate antitumor effects via phagocytosis, presentation of tumor antigens to prime T cells, and through the production of type I interferons [41,42]. Macrophages can display functional diversity and are classified into M1 v M2 subsets [43]. M1 macrophages promote effective antitumor immune responses while M2 support immuno-regulatory T cell phenotypes that facilitate tumor growth and metastatic spread. Data regarding macrophage polarization with aging is conflicting, with some publications showing no age-related differences and others reporting skewing toward the M2 phenotype with older age [44-46]. Myeloid-derived suppressor cells MDSCs are a mixed population of cells, including neutrophils and macrophages, that populate the tumor stroma and appear to play key roles in various aspects of cancer development [47,48]. They produce vascular endothelial growth factors and cytokines that promote tumor progression, inhibit protective immune adaptive responses, degrade tumor suppressive molecules, and support cancer invasion [47,49]. The frequency of MDSCs increases with age in both the circulation and tumor stroma, this correlates with higher cancer susceptibility in older mice [50,51]. Older adults who are frail or have a history of cancer have a higher number of MDSCs [51]. Therefore, the accumulation of MDSCs in older adults could play an integral role in cancer onset and progression, and targeted MDSC inhibition is a possible therapeutic intervention to pursue. Dendritic cells DCs are potent antigen presenting cells that are integral for the effective priming and differentiation of T and B cell antigenspecific immune responses [41]. Tumor infiltration by DCs has been associated with reduced metastatic lesions and prolonged survival [52,53]. In mouse studies, the age-related decline in DC function has been linked to an impaired ability to eradicate tumors [54-56]. The activation capacity of DCs is impaired with aging due to dysfunctional toll-like receptor signaling; also their phagocytic and migratory function is reduced secondary to the age-associated decreased activity of the PI3Kinase pathway [57,58]. Evidence regarding changes in T cell priming capacity by DCs with age is scarce; one study suggested that it is impaired in older adults [59]. DC surface expression of CD80 and CD86, both critical for T cell costimulation, is decreased in older adults [56,60]. DCs interact with T cells not only via antigen presentation but also cytokine production. Data regarding changes in the secretion of various cytokines with age by DCs subtypes are conflicting; however, there

is an agreement that secretion of the critical cytokine IFNα is reduced in aged DCs [59-64]. In sum, alterations of the innate immune system (neutrophils, monocytes/macrophages, MDSCs, and DCs) with age may contribute to the increased likelihood of cancer onset in older as compared to younger individuals. The increase in MDSCs with age could represent an important target for immunotherapy as both MDSCs and DCs express checkpoint inhibitor targets (ie, PD-1, PDL1, or TIM-3) [41,42,65]. An essential way in which ICIs may work in older adults could be by specifically blocking the immunesuppressive effects of innate immune cells. B. Immune cells that bridge innate and adaptive responses: Natural Killer cells, invariant Natural Killer T cells, and γ δ T cells Immune cell subsets that do not clearly reside in the “innate” or “adaptive” categories include Natural Killer (NK) cells, invariant Natural Killer T (iNKT) cells, and gamma delta (γ δ T) cells. NK, iNKT, and γ δ T cells all possess qualities of innate cells, including the ability to respond to inflammatory cytokines and danger signals without antigen-specific priming, yet they also possess adaptive immune cell characteristics, such as the generation of memory cell populations (NK cells) and the possession of rearranged T cell receptors (iNKT and γ δ T cells). NK, iNKT, and γ δ T cells also serve as important immuno-modulatory cells, responding to signals from innate cells (ie, monocytes/macrophages, DCs) to then promote and direct the generation of adaptive (memory) T and B cell responses. Changes in these cell subsets with age could impact responses to ICIs and other immunotherapies in older individuals with cancer. Natural Killer cells NK cells exert direct cytotoxic activity by various means, including via recognition of infected or transformed cells with altered expression of MHC Class I; this is known as the ‘missing self’ pathway of recognition [66,67]. NK cells secrete cytokines including IFN-γ , TNF-α , and IL-10 that directly impact both innate immune cells and help drive adaptive responses. Significant evidence links NK cells to effective antitumor responses. In mouse models, NK cells exhibit antitumor activity against methylcholanthreneinduced sarcomas [68,69]. In humans, there is evidence that harnessing NK cell activity via ‘missing self’ activation could provide clinical benefit to leukemic patients [70]. With healthy aging, NK cells expand in frequency in peripheral blood [71]. NK cell activation in response to cytokines and intracellular perforin content have been reported to remain intact with age from some groups [72,73] yet others report impairment of cytotoxic activity on a per cell basis and decreased proliferation in response to in vitro activation of NK cells from older compared with younger individuals [71,74]. However, circulating NK cell subsets shift with age, with a decrease in the CD56bright population and an increase in the CD56dim and CD16+ CD56- populations [71,75,76]. Also, age and/or cytomegalovirus (CMV) status track with altered expression of the NK cell activating receptors NKp30, NKp46, and DNAM-1 (involved in recognition of and cytolytic response to tumor cells) [77]. To what extent the subset shifts and altered receptor expression of circulating NK cells in older adults impact cancer incidence or response to immunotherapies is unknown. Invariant Natural Killer cells iNKT cells are a unique T cell population that can be activated by glycolipid antigens via its T cell receptor; however, it is likely that its primary mode of stimulation is in response to cytokines and other danger signals in the microenvironment [78]. NKT cells secrete inflammatory and/or immunoregulatory cytokines and thereby help direct the functional signature of the adaptive immune response. Specific stimulation of iNKT cells inhibited metastases or suppressed tumor development in multiple

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mouse models and enhanced priming of tumor-specific memory T cell responses [79-83]. Also, iNKT cells suppress the activity of MDSCs, a cell subset known for its protumor activity [84]. Little is known to date about alterations of iNKT cells with aging. Using a precise gating strategy for iNKT cells (Vα 24+ and CD1d-PBS57 tetramer+) we found that circulating iNKT cell frequencies and absolute counts are higher in older compared with younger subjects (unpublished observations), similar to a report where NKT cells were defined using less precise markers [85], and in disagreement with others [86,87]. In another study, iNKT cell levels were significantly higher in older females compared with older males with no significant differences based on sex found in younger age groups; also, iNKT subsets of the males but not the females shifted with age, with lower CD4- and CD8- double negative and higher CD4+ cells reported for older compared with younger male subjects [88]. It is unknown if these sex-specific differences of iNKT cells from older individuals are associated with the onset and progression of cancer or other age-related diseases.

γ δ T cells

Like iNKT cells, γ δ T cells are activated via T cell receptor recognition of specific antigens as well as from cytokines and other inflammatory factors. γ δ T cells within tumors were a prognostically favorable factor in melanoma, but inversely correlated with patient survival in breast cancer highlighting potentially integral but varying roles of this unique T cell subset in tumor outcome [89,90]. The ability of γ δ T cells to kill tumor cells in a non-MHC restricted fashion has underscored their putative role in tumor immune surveillance and the potential for dramatic antitumor activity if γ δ T cells are effectively therapeutically targeted. γ δ T cell alterations with aging are not fully elucidated; however, lower circulating γ δ T cell frequencies in older compared with younger subjects has been reported by several groups, and a higher percentage of γ δ T cells from older subjects produced TNFα as compared with γ δ T cells from younger counterparts in one study [91-97]. Shifts in Vδ 1:Vδ 2 subset frequencies, maturation markers, and inhibitory receptors occur with aging as well [92-96]. In 1 study of melanoma patients taking ipilimumab, a worse overall survival (OS) and a lower rate of clinical benefit of the checkpoint inhibitor was significantly associated with decreases of the Vδ 2 γ δ T cell subset in the circulation since treatment initiation [98]. C. The adaptive immune system: CD4± T cells (including T regulatory cells), CD8± T cells, B cells Immune cells classified as ‘adaptive’ undergo receptor gene rearrangement and are primed upon antigen presentation to differentiate into memory cells. Adaptive cells include CD4+ T cells, CD8+ T cells, and B cells. CD4± and CD8± T cells Significant changes are seen in the CD4+ and CD8+ T cell compartments with aging. There is a selective loss of naïve (CD45RA+) T cells with age, particularly within the CD8+ T cell compartment [99-101]. In addition, there is a noted inversion of the CD4:CD8 ratio; the decline in CD4+ T cell numbers in older individuals is a marker of immunosenescence and is a predictor of mortality [102104]. The percentage of circulating T cells expressing the costimulatory antigen CD28 is lower in older subjects [105]. Higher percentages of circulating T cells express CD57 is observed with increased age, a cell surface antigen associated with functional defects and senescence [106]. Intrinsic defects are noted in the memory T cell compartment of aged individuals, such as evidence of a reduced ability to move kinase substrates and coupling factors into the region of TcR-antigen presenting cells contact as well as defects in cytoskeletal organization both of which may contribute to the noted defects in TcR signal transduction in older CD4+ T cells

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[107,108]. Defects in cell signaling of memory CD4+ and CD8+ T cells may explain the incomplete restoration of T cell responses upon PD-1: PD-1L checkpoint blockade of T cells from aged mice [109]. T regulatory cells T regulatory cells (Tregs) is a suppressive T cell subset that dampens immune responses to prevent immunopathology and is actively involved in the prevention of autoimmune diseases. In humans, naturally occurring Tregs are CD4+, CD25med-hi , CD127lo , and express the transcription factor FOXP3. In cancer patients, presence of higher numbers of Tregs or lower CD8+ T/Treg ratios within the tumor microenvironment is associated with a worse prognosis [109-112]. Antitumor immune responses are enhanced if the Treg activity is diminished [113-115]. Reports discussing age-associated changes circulating Treg frequencies are conflicting [116-121]. However, in other anatomic sites such as the human skin, there are apparent accumulations of Tregs with age [117,121,122]. In vitro, the functional capacity of aged Tregs is similar or enhanced as compared with cells from younger counterparts [116,117]. CD4- CD25- T cells from aged mice are hyporesponsive to stimulation and suppress T cells from younger mice in vitro, thereby appearing to acquire a Treg functional phenotype [123]. Taken together, data suggest that with aging, traditional Tregs are redistributed from the circulation to accumulate in other anatomic sites and that the aged immune environment promotes the alternative differentiation of non-Treg T cells to acquire immunosuppressive functional activity. B cells It is well established that older individuals exhibit lower antibody responses after vaccination and infection compared with younger counterparts [124,125]. This is attributed to diminished germinal center reactions (reduced in number and size with aging), T follicular helper cell-defects, and to aberrations intrinsic to B cells such as decreased class switch recombination and somatic hypermutation [126]. Other alterations of the B cell compartment with age include higher frequencies of naïve B cells and lower class-switched memory B cells [127], lower total B cell receptor diversity [128], and impaired plasma cell differentiation/antibody production after in vitro culture [129]. How these B cell changes with aging impact cancer onset, progression, and response to immunotherapies are not yet known. In summary, the frequencies and functions of the innate-toadaptive ‘immune bridging’ populations (NK, iNKT, and γ δ T cells) appear to be better preserved with age than both the innate (neutrophils, monocytes/macrophages, MDSC, and DCs) and the adaptive immune cells (CD4+ and CD8+, B cells). Given this stability with age and their direct roles in antitumor immunity, these immune bridging subsets should be given more attention as putative therapeutic targets to boost responses to ICIs and other immunotherapies in older cancer patients. Frailty and adaptive immune changes Aging is a heterogeneous process that varies from one individual to another. In fact, different organ-systems within the same individual age differently [138]. “Physiologic aging” is influenced by multiple variables such as the environment, comorbidities, and genetics. Immune changes seen with aging are not consistent across older adults; evidence suggests that there is an association between degree of frailty and immune-competency. Frailty is a state of vulnerability that reflects decreased physiological reserves resulting from the interaction of biological aging and the manifestations of age-related diseases [139]. Several methods have been developed to measure frailty. Fried’s criteria define frailty as the presence of three out of 5 criteria (unintentional weight

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loss, self-reported exhaustion, weakness, slow gait speed, and decreased physical activity); the presence of 1 or 2 criteria defines prefrailty status [140]. Rockwood’s frailty index is another tool that measures frailty based on the accumulation of medical, functional, and cognitive deficits [141]. Multiple other simple tools exist to measure frailty such as The Canadian Study of Health and Aging Clinical Frailty Scale, the FRAIL scale, and the Study of Osteoporotic Fractures tool [142-144]. Geriatric assessment remains the most thorough tool to measure aging-related syndromes [145]. Frailty has been associated with immune changes including increased neutrophil:lymphocyte ratios in cancer patients and increased MDSCs. Few papers have investigated the relationship between frailty and the adaptive immune cells with conflicting findings, possibly due to the heterogeneity of tools used to measure frailty and study population, therefore limiting any definitive conclusions. However, evidence suggests that such a relationship exists with papers showing either negative or positive correlation between frailty and different immune phenotype markers. Details of these studies are summarized in Table 1. Aging, immunity and the chronic viral infections CMV and human immunodeficiency virus The presence of chronic viral infections in an aging immune system can dramatically impact the immune-competency of the host. In particular, infection with CMV or human immunodeficiency virus (HIV) each seem to further progress the inflammatory state found in aged individuals and thereby contribute to the further aberration of the immune system. CMV infection is associated with all-cause mortality as well as several chronic diseases associated with aging, including cancer, cardiovascular disease, cognitive decline, and frailty [130-134]. CMV impacts the cellular composition of the aged immune system; for example, lower frequencies of naïve CD4+ T cells with older age was significant among CMV+ subjects but not uninfected counterparts [101]. CMV seropositivity is considered a marker of immunosenescence, similar to IL-6 and C-reactive protein levels in plasma. While CMV has a dramatic impact on the aging immune system; how this virus impacts the functionality of immune cells and the downstream effects of CMVinduced immune changes are unclear to date. Although improvements to antiretroviral therapy (ART) regimens have dramatically decreased HIV-associated morbidity and mortality within the last 2 decades, virologically suppressed HIV-infected individuals are at an increased risk of presenting with many age-associated diseases, including cardiovascular atherosclerosis, neurocognitive degeneration, diabetes mellitus, cancer, and osteoporosis, referred to as Serious Non-AIDS conditions (SNAs) [135-137]. These HIV-induced age-related morbidities occur throughout the course of infection, in 1 study the distribution of the number of SNAs per person in different age groups resembled the distribution for controls who were 5 years older [136]. It remains unclear whether HIV contributes to the accelerated onset of these SNA conditions through the same mechanism as normal aging or through other distinct processes. Our analysis of inhibitory receptor (IR) expression, including PD-1, on a variety of immune cell subsets from both younger (≤35yo) and older (≥50yo) uninfected and ART-suppressed HIV+ subjects have revealed that overall, the lowest percentages of IR+ cells are found in the young uninfected subjects as compared with the other three groups (uninfected older, ART-suppressed HIV+ younger, and ART-suppressed HIV+ older) (unpublished observations). These data suggest that the alteration of immune cells, including activation or immune exhaustion, that occurs with aging may be accelerated in HIV+ individuals. In summary, further understanding of how CMV and HIV promote age-related diseases could elucidate the biological processes

that drive age-associated morbidities in the general population and thereby reveal novel therapeutic avenues for immune maintenance in older adults. Efficacy of checkpoint inhibitors in older adults There is limited evidence on the efficacy of ICIs among older adults. The impact of age on immunotherapy outcomes in metastatic melanoma was reviewed in a patient population treated at 2 academic cancer centers with anti-PD1 or anti-PD-L1 therapy [146]. Among 254 patients included in this paper, 112 were ≥65 years (44%). The authors showed no difference based on age in regards of OS or progression-free survival (PFS). Data from the Italian Expanded Access Program (EAP) was reviewed for the efficacy of ipilimumab, and anti-CTLA-4 therapy, in 855 patients with metastatic melanoma [147]. The disease control rate was 33% in patients ≤70 years, 38% in patients >70 years, and 31% in those ≥80 years. There was no statistically significant difference in PFS or OS between different age groups. A clinical prediction scale for response to anti-PD-1 therapy was developed and validated based on a population of 315 patients that included 138 (44%) aged ≥65 years with advanced melanoma [148]. Age <65 years was found to be predictive of a lower response to anti-PD-1 monotherapy with an odds ratio (OR) 0.55 (95% confidence interval [CI] 0.30– 0.98, P = .04). Other negative predicting factors determined in this paper were female sex (OR: 0.51, CI: 0.27–0.94), previous ipilimumab treatment (OR: 0.38, CI: 0.20–0.69), elevated LDH (OR: 0.48, CI: 0.25–0.90), and liver metastasis (OR: 0.34, 0.17–0.66). A retrospective analysis of 50 patients treated with nivolumab monotherapy in Japan did not find age to be predictive of response to treatment in adults younger versus ≥70 years (OR: 0.69; 95% CI: 0.12–3.81, P = 1.0 0 0) [149]. Data from the Netherlands and United Kingdom EAP did not find significant correlations between age and survival [150]. Efficacy of checkpoint inhibitors in older adults—Data from randomized trials We performed a Pubmed database search using terms “atezolizumab,” “avelumab,” “durvalumab,” “ipilimumab,” “pembrolizumab,” “nivolumab,” and “tremelimumab.”. In addition, we reviewed the “Drugs @FDA” database published by the Food and Drug Administration (FDA) for randomized studies that did not report subgroup analysis for OS, PFS, or response rate (RR) by age in the published manuscript. We present the data below based on an efficacy outcome. A. Efficacy of checkpoint inhibitors in older adults—Overall survival Overall survival analysis based on an age cutoff was reported in 22 studies (Table 2). We used “Drugs @FDA” to obtain information about OS results by age subgroups for 2 trials (POPLAR, CheckMate-017) [4,10,151,152]. Nine studies were with a CTLA-4 antibody (ipilimumab = 7, tremelimumab = 2), 8 with a PD-1 antibody (nivolumab = 3, pembrolizumab = 5), 2 with a PD-L1 antibody (atezolizumab), and 3 with the combination of nivolumab plus ipilimumab. A total of 12,860 patients were included in the analysis, with 5,299 ≥65 years (41%). All trials with a PD-1 or PD-L1 inhibitor showed positive results overall for all subjects enrolled. No notable differences were detected based on an age cutoff of 65 years except for the CheckMate-141 trial that evaluated nivolumab in patients with recurrent squamous-cell carcinoma of the Head and Neck [153]. The hazard ratio (HR) for OS in patients aged ≥65– <75 years was 0.93 (95% CI: 0.56–1.54) compared to a HR of 0.64 (95% CI: 0.45–0.89) in patients <65 years. Survival analysis for patients ≥75 years was reported in 4 of the trials [3-6]. However, only 8% of patients included in these studies were ≥75 years, and

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Table 1 Summary of studies exploring the relationship between frailty and immune changes. Study

Population

Johnstone 2017

• Nursing Home residents (n = 1,072) • Median age: 86 years

Bailur 2017

• Older females with breast cancer (n = 56) • Median age:

No correlation

Negative Correlation Higher percentage of: - Naïve CD4+ T cells - Effector memory CD8+ T cells

Positive Correlation Higher percentage of: - CD8+ Central memory T-Cells

Higher frequency of granulocytic cells Lower frequency of MDSCs Lower frequency of Tregs

- control group: 75 years (70–88) - chemotherapy group: 73 years (70–80) Lu 2016

• Participants from SLAS-2 • Mean age: 68.41 years • Age range: 55-84 years

Higher frequency of: - CD3+ cells - CD4+ CD27+ CD45RA- cells - CD45RA+ CD8+ T cells

α /β T cells:

- Altered CD4/CD8 ratio in CD28+ T cells - Frequency of Terminal Effector CD8+ T cells (CD27- CD45RA+)

γ /δ T cells: - Decreased frequency of CD27 and CD57 expression - Increased expression of IFN G + TNF A in highly differentiated γ /δ 2+ cells - Increased expression of IFN G - TNF A + in highly differentiated γ /δ 2- CD3+ T cells -

Increased frequency of CD38+ B cells Increased frequency of exhausted B cells Decreased frequency of IgD+ B cells Decreased frequency of CD14+ CD16+ inflammatory monocytes

Valdiglesias 2015

• Community-dwelling older adults (n = 144) • Age range: 65-95 years

-

Ng 2015

- Participants from SLAS-2 (n = 421) - Mean age: 74.5 years

- CD57 expression

Adriaensen 2014

• Community-dwelling older adults (n = 235) • Mean age: 86.7 years

- CD4/CD8 ratio > 5 in CMV seropositive individuals

Johnstone 2014

• Nursing Home Residents (n = 262) • Median Age: 87 years • Range: 65-98 years

- Higher T regulatory expression

Bucci 2014

• Centenarians (n = 116) • Mean age: 100.7 years • Range: 99-111 years

-

CD3+ T lymphocytes CD4+ T cells CD8+ T cells CD19+ B cells CD3- CD16+ CD56+ NK cells Expression of: - CD8+ CD28- CD27+ cells - CD4+ CD28- CD27+ cells - CD8+ CD28- cells - Higher CD4/CD8 ratio

A cluster of immune parameters that includes: Leucocytes count Lymphocytes count Monococytes count CD3+ T lymphocytes CD4+ T helper CD8+ T cells IgM level

Collerton 2012

• Participants from the Newcastle 85+ Study (n = 811)

Martin-Ruiz 2011

• Participants from the Newcastle 85+ Study (n = 778)

Ratio of memory / naïve B cells < 10

De Fanis 2008

• Community-dwelling older adults (n = 26) • Mean age: 83.8 years • Range: 72–94

Higher expression of: - CD8+ T cells - CCR5+ CD8+ T Cells - CCR5+ CD45RO- T Cells

- Lymphocytes - Memory / naïve CD8 T cell ratio - Memory / naïve B cell ratio

Malignancy

Study arms

Distribution by age (years)

General HR OS

HR OS younger adults

Fehrenbacher 2016 (FDA BLA) Rittmeyer 2016

Atezolizumab

2

NSCLC

Atezolizumab v Docetaxel

<65: 61% ≥65: 39%

HR: 0.68; CI: 0.51–0.89

Atezolizumab

3

NSCLC

Atezolizumab v Docetaxel

<65: 53.29% ≥65: 46.70%

Bellmunt 2017

Pembrolizumab

3

Pembrolizumab

2/3

Pembrolizumab v Chemotherapy Pembrolizumab 2 mg/kg v Pembrolizumab 10 mg/kg v Docetaxel

<65: 42% ≥65: 58%

Herbst 2016

Urothelial Carcinoma NSCLC

≥65 years: HR: 0.65; CI: 0.42–0.99 ≥65 years: HR: 0.66; CI: 0.52–0.83 ≥65 years: HR: 0.76; CI: 0.56–1.02 ≥65 years: Pooled Pembrolizumab HR: 0.76; CI: 0.56–1.02

Robert 2015

Pembrolizumab

3

Melanoma

Pembrolizumab every 2 weeks v Pembrolizumab every 10 weeks v Ipilimumab

<65: 56% ≥65: 44%

Borghaei 2015

Nivolumab

3

NS-NSCLC

Nivolumab v Docetaxel

<65: 58% ≥65–<75: 34% ≥75: 7%

HR: 0.73; CI: 0.62–0.87; P = .0 0 03 HR: 0.73; CI: 0.59–0.91; P = .002 Pembrolizumab 2 mg/kg HR: 0.71; CI: 0.58–0.88 P = .0 0 08 Pembrolizumab 10 mg/kg HR: 0.61; CI: 0.49–0.75; P < .0 0 01 Pembrolizumab every 2 weeks HR: 0.63; CI: 0.47–0.83; P < .0 0 05 Pembrolizumab every 3 weeks HR: 0.69; CI: 0.52–0.90; P = .0036 HR: 0.73; CI: 0.59–0.89; P = .002

<65 years: HR: 0.70; CI: 0.48–1.01 <65 years: HR: 0.80; CI: 0.64–1.00 <65 years: HR: 0.75; CI: 0.53–1.05 <65 years: Pooled Pembrolizumab HR: 0.63; CI: 0.53–1.05

<65 years: Pembrolizumab every 2 weeks HR: 0.65; CI: 0.44–0.95 Pembrolizumab every 3 weeks HR: 0.77; CI: 0.53–1.12 <65 years: HR: 0.81; CI: 0.62–1.04

Brahmer 2015

Nivolumab

3

S-NSCLC

Nivolumab v Docetaxel

<65: 56% ≥65–<75: 33% ≥75: 11%

HR: 0.59; CI: 0.44–0.79; P = .0 0 0 025

<65 years: HR: 0.52; CI: 0.35–0.76

Ferris 2016

Nivolumab

3

Head & Neck

Nivolumab v Chemotherapy

Motzer 2015

Nivolumab

3

Renal Cell Carcinoma

Nivolumab v Everolimus

<65: 68.69% ≥65–<75: 26.31% ≥75: 5% <65: 60.53% ≥65–<75: 30.45% ≥75: 9%

HR: 0.70; CI: 0.51–0.96; P = .01 HR: 0.73; CI: 0.57–0.93; P = .002

<65 years: HR: 0.64; CI: 0.45–0.89 <65 years: HR: 0.78; CI: 0.60–1.01

Robert 2015

Nivolumab

3

Melanoma

Nivolumab v Dacarbazine

<65: 47.84% ≥65–<75: 36.12% ≥75: 16%

HR: 0.42; CI: 0.25–0.73; P < .001

<65 years: HR: 0.52; CI: 0.32–0.85

Hodi 2016

Nivolumab & Ipilimumab Nivolumab & Ipilimumab

2

Melanoma

<65: 48% ≥65: 52%

2

Melanoma

HR: 0.74; CI: 0.43–1.26; P = .2619 HR: 0.48; CI: 0.29–0.80

<65 years: HR: 0.52; CI: 0.24–1.12 <65 years: HR: 0.54; CI: 0.29–1.01

3

Melanoma

Nivolumab + Ipilimumab v Ipilimumab Nivolumab then Ipilimumab v Ipilimumab then Nivolumab Nivolumab + Ipilimumab VS Nivolumab v Ipilimumab

≥65 years: Pembrolizumab every 2 weeks HR: 0.56; CI: 0.36–0.87 Pembrolizumab every 3 weeks HR: 0.66; CI: 0.44–1.01 ≥65–<75 years: HR: 0.63; CI: 0.45–0.89 ≥75 years: HR: 0.90; CI: 0.43–1.87 ≥65 years: HR: 0.70; CI: 0.46–1.06 ≥65–<75 years: HR: 0.56; CI: 0.34–0.91 ≥75 years: HR: 1.85; CI: 0.76–4.51 ≥65–<75 years: HR: 0.93; CI: 0.56–1.54 ≥65–<75 years: HR: 0.64; CI: 0.45–0.91 ≥75 years: HR: 1.23; CI: 0.66–2.31 ≥65–<75 years: HR: 0.44; CI: 0.24–0.81 ≥75 years: HR: 0.25; CI: 0.10–0.61 ≥65 years: HR: 0.95; CI: 0.45–2.02 ≥65 years: HR: 0.40; CI: 0.16–0.97

Nivolumab + Ipilimumab v Ipilimumab: HR: 0.55; CI: 0.45–0.69 Nivolumab v Ipilimumab: HR: 0.65; CI: 0.53–0.80 Nivolumab + Ipilimumab v Nivolumab: HR: 0.85; CI: 0.68–1.07

<65 years: Nivolumab + Ipilimumab v Ipilimumab: HR: 0.48; CI: 0.36–0.64 Nivolumab v Ipilimumab: HR: 0.62; CI: 0.48–0.81 Nivolumab + Ipilimumab v Nivolumab: HR: 0.78; CI: 0.58–1.05

Weber 2016

Wolchok 2017

Nivolumab & Ipilimumab

<65: 58.47% ≥65: 41.52%

<65: 59% ≥65: 41%

<65: 60% ≥65: 40%

HR OS older adults

≥65 years: Nivolumab + Ipilimumab v Ipilimumab: HR: 0.69; CI: 0.49–0.95 Nivolumab v Ipilimumab: HR: 0.71; CI: 0.51–0.99 Nivolumab + Ipilimumab v Nivolumab: HR: 0.96; CI: 0.68–1.38 (continued on next page)

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Table 2 Overall survival in patients treated with checkpoint inhibitors by age group: data from randomized trials.

ARTICLE IN PRESS

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<65: 69% ≥65: 31% 3 Tremelimumab Ribas 2017

Melanoma

2b Tremelimumab Maio 2017

Mesothelioma

Melanoma 3 Robert 2011

Ipilimumab

Tremelimumab v Chemotherapy

<65: 41% ≥65: 58%

≥65 years: Log HR: –0.09; CI: −0.44 to 0.25 ≥65 years: HR: 0.99; CI: 0.77–1.26 ≥65 years: HR: 0.87; CI: 0.64–1.19 <65 years: Log HR: –0.36; CI: −0.60 to −0.13 <65 years: HR: 0.87; CI: 0.64–1.20 <65 years: HR: 0.88; CI: 0.71–1.1 HR: 0.72; CI: 0.59–0.84; P < .001 HR: 0.92; CI: 0.76–1.12; P = .41 HR: 0.88; CI: 0.76–1.12; P = .1267 <65: 68% ≥65: 32%

≥70 years: HR: 0.88; CI: 0.69–1.13 <70 years: HR: 0.81; CI: 0.64–1.01 Prostate Ipilimumab Kwon 2014

3

Ipilimumab v Placebo after radiation in patients with Metastatic CRPC that progressed after Docetaxel. Ipilimumab + Dacarbazine v Dacarbazine Tremelimumab v Placebo

<65: 56% ≥65: 44%

HR: 0.64; 1-sided 90% repeated CI: not applicable – 0.90; P = .01 HR: 0.85; CI: 0.72–1.00; P = .053 Melanoma 2 Ipilimumab Hodi 2014

Melanoma 3 Ipilimumab Hodi 2010

S-NSCL 3 Ipilimumab Govindan 2017

Prostate Cancer Ipilimumab Beer 2017

3

Ipilimumab + Sargramostin v Ipilimumab

<65: 56% ≥65: 44%

<65 years: Ipilimumab + gp100 v gp100: HR: 0.70; CI: 0.54–0.90 Ipilimumab v gp100: HR: 0.65; CI: 0.47–0.90 <65 years: HR: 0.52; CI: 0.24–1.12 Ipilimumab + gp100 v gp100: HR: 0.69; CI: 0.56–0.85 Ipilimumab v gp100: HR: 0.64; CI: 0.49–0.84 <65: 71% ≥65: 29%

Ipilimumab + Chemotherapy v Chemotherapy Ipilimumab + gp100 v Ipilimumab v gp100

<65: 51% ≥65–<75: 40% ≥75: 9%

≥65 years: HR: 0.99; CI: 0.77–1.28 ≥70 years: HR: 1.02; CI: 0.57–1.37 ≥65––<75 years: HR: 1.06; CI: 0.81–1.37 ≥75 years: HR: 0.85; CI: 0.51–1.43 ≥65 years: Ipilimumab + gp100 v gp100: HR: 0.69; CI: 0.47–1.01 Ipilimumab v gp100: HR: 0.61; CI: 0.38–0.99 ≥65 years: HR: 0.95; CI: 0.45–2.02 <65 years: HR: 0.78; CI: 0.62–0.97 <70 years: HR: 1.16; CI: 0.85–1.57 <65 years: HR: 0.82; CI: 0.64–1.04 HR: 0.84; CI: 0.70–0.99; P = .04 HR: 1.11; CI: 0.88–1.39; P = .3667 HR: 0.91; CI: 0.77–1.07; P = .25 <65: 59% ≥65: 41% Melanoma Ipilimumab Ascierto 2017

3

Ipilimumab 10 mg/kg v Ipilimumab 3 mg/kg Ipilimumab v Placebo

<65: 32% ≥65: 78%

HR OS older adults HR OS younger adults General HR OS Malignancy Trial phase Agent Study

Table 2 (continued)

Study arms

Distribution by age (years)

R. Elias et al. / Seminars in Oncology 000 (2018) 1–14

[mUS5Gb;October 24, 2018;22:17] 7

therefore data were not sufficient to draw definitive conclusions except for the CheckMate-066 study (HR: 0.25; 95% CI: 0.10–0.61) [6]. Among the trials we reviewed that evaluated an anti-CTLA4 antibody, only 4 out of 9 showed positive results. These studies showed consistent efficacy across age groups except for one that compared ipilimumab 10 mg/kg v 3 mg/kg (<65 years: HR: 0.78; 95% CI: 0.62–0.97 v ≥65 years: HR: 0.99; 95% CI: 0.77–1.28) [154]. Among 4 trials that explored the combination nivolumab plus ipilimumab, only CheckMate-067 did not show consistent efficacy across age groups (nivolumab + ipilimumab v single agent nivolumab: <65 years HR: 0.78; 95% CI: 0.58–1.05 v ≥65 years: HR: 0.96; 95% CI: 0.68–1.38) [155]. Nine randomized trials were included in a meta-analysis that reviewed the efficacy of PD-1 and PD-L1 inhibitors in patients younger versus ≥65 years [156]. The overall estimated random-effects HR for death was 0.68 (95% CI: 0.61–0.75) in patients <65 years versus 0.64 (95% CI: 0.54–0.76) in patients ≥65 years. A second meta-analysis included studies with both anti-CTLA-4 and anti-PD-1 agents (4 with anti-CTLA4 and 5 with anti-PD1) [157]; the authors showed a comparable OS benefit for ICIs in younger (HR: 0.75, 95% CI: 0.68–0.82) and older adults (HR: 0.73, 95% CI: 0.62–0.78). B. Efficacy of checkpoint inhibitors in older adults—Progression-free survival Ten of the reviewed papers reported PFS survival analysis by age (Table 3). Six papers were with a PD-1 antibody (nivolumab = 2, pembrolizumab = 4), 1 with a PD-L1 antibody (durvalumab), 2 with the combination nivolumab plus ipilimumab, and 1 with the CTLA-4 antibody ipilimumab. Included in these studies were a total of 5,611 patients among which 2,411 (43.5%) were ≥65 years. Survival outcomes were similar in adults younger versus ≥65 years. Two trials reported PFS analysis for patients ≥75 years [3,4]. No difference in PFS benefit was seen based on age in CheckMate-057 (<65 years: HR: 0.89; 95% CI: 0.70–1.13 v 65–75: HR: 0.94; 95% CI: 0.69–1.27 v ≥75: 0.97; CI: 0.49–1.95), while in CheckMate-017 HR PFS was not significant in patients ≥75 years (HR: 1.76; 95% CI: 0.77–4.05) versus ≥65–<75 years (HR: 0.51; CI: 0.32–0.82) and <65 years (HR: 0.62; 95% CI: 0.44–0.89) although most likely this was secondary to the small number of patients ≥75 enrolled (n = 29/272; 11%). The combination nivolumab plus ipilimumab demonstrated superior PFS compared to single-agent ipilimumab in 2 trials; however, this was not shown versus single agent nivolumab in CheckMate-067 (<65 years: HR 0.73; 95% CI 0.56–0.94 v ≥65 years: HR: 0.90; 95% CI: 0.65–1.24) [155,158]. Four trials were included in a meta-analysis that explored the efficacy of PD-1 and PD-L1 inhibitors in patients <65 versus ≥65 years [156]. The overall estimated random-effects for HR for progression was 0.74 (95% CI: 0.60–0.92) in patients ≥65 years versus 0.73 (95% CI: 0.61–0.88) in patients <65 years. A PFS benefit for adults ≥65 years was not demonstrated in a second meta-analysis that included trials with both anti-CTLA-4 and anti-PD-1 agents (HR: 0.77, 95% CI: 0.58–1.01) versus a favorable HR in patients <65 years (HR: 0.58, 95% CI: 0.40–0.84) [157]. C. Efficacy of checkpoint inhibitors in older adults—Response Rate RR based on age subgroups was obtained for 11 trials, including 4 where information was obtained from the “Drugs @FDA” database [10,151,159-164]. Details of these studies are in Table 4. Seven studies used a PD-1 antibody (nivolumab = 3, pembrolizumab = 4), 3 used a PD-L1 antibody (atezolizumab = 2, avelumab = 1), and 1 used the combination of nivolumab plus ipilimumab. Nine studies reported patient demographics based on age cutoff of 65 years, 46.75% were ≥65 years. RRs in all trials were similar regardless of age except for in 1 study; this was likely due to the small number of patients enrolled (15 patients <65 years v 20 patients ≥65 years) [165].

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Table 3 Progression-free survival in patients treated with checkpoint inhibitors by age group: data from randomized trials. Malignancy

Study arms

Distribution by age (years)

General HR PFS

HR PFS younger adults

Antonia 2017

Durvalumab

3

NSCLC

Durvalumab v Placebo

<65: 55% ≥65: 45%

Herbst 2016

Pembrolizumab

2/3

NSCLC

Pembrolizumab 2 mg/kg v Pembrolizumab 10 mg/kg v Docetaxel

<65: 58.47% ≥65: 41.52%

<65 years: HR: 0.43; CI: 0.32–0.57 <65 years: Pooled Pembrolizumab HR: 0.84; CI: 0.69–1.02

≥65 years: HR: 0.74; CI: 0.54–1.01 ≥65 years: Pooled Pembrolizumab HR: 0.93; CI: 0.72–1.19

Reck 2016

Pembrolizumab

3

NSCLC

<65: 46.22% ≥65: 53.77%

HR: 0.61; CI: 0.40–0.92

HR: 0.45; CI: 0.29–0.70

Ribas 2015

Pembrolizumab

3

Melanoma

Pembrolizumab v Chemotherapy Pembrolizumab 2 mg/kg v Pembrolizumab 10 mg/kg v Chemotherapy

<65 years: Pembrolizumab 2 mg/kg HR: 0.47; CI: 0.34–0.66 Pembrolizumab 10 mg/kg HR: 0.42; CI: 0.30–0.59

≥65 years: Pembrolizumab 2 mg/kg HR: 0.70; CI: 0.48–1.01 Pembrolizumab 10 mg/kg HR: 0.60; CI: 0.41–0.88

Robert 2015

Pembrolizumab

3

Melanoma

Pembrolizumab every 2 weeks v Pembrolizumab every 10 weeks v Ipilimumab

<65: 56% ≥65: 44%

Borghaei 2015

Nivolumab

3

NS-NSCLC

Nivolumab v Docetaxel

<65: 58% ≥65–<75: 34% ≥75: 7%

HR: 0.52; CI: 0.42–0.65; P < .001 Pembrolizumab 2 mg/kg HR: 0.88; CI: 0.74–1.05; P = .07 Pembrolizumab 10 mg/kg HR: 0.79; CI: 0.66–0.94; P = .004 HR: 0.50; CI: 0.37–0.68; P < .0 0 01 Pembrolizumab 2 mg/kg HR: 0.57; CI: 0.45–0.73; P<.0 0 01 Pembrolizumab 10 mg/kg HR: 0.50; CI: 0.39–0.64; P < .0 0 01 Pembrolizumab every 2 weeks HR: 0.58; CI: 0.46–0.72; P < .001 Pembrolizumab every 3 weeks HR: 0.58; CI: 0.47–0.72; P < .001 HR: 0.91; CI: 0.76–1.09

<65 years: Pembrolizumab every 2 weeks HR: 0.55; CI: 0.41–0.73 Pembrolizumab every 3 weeks HR: 0.59; CI: 0.45–0.79 <65 years: HR: 0.89; CI: 0.70–1.13

Brahmer 2015

Nivolumab

3

S-NSCLC

Nivolumab v Docetaxel

<65: 56% ≥65–<75: 33% ≥75: 11%

HR: 0.63; CI: 0.48–0.82

<65 years: HR: 0.62; CI: 0.44–0.89

Hodi 2016

Nivolumab & Ipilimumab Nivolumab & Ipilimumab

2

Melanoma

<65: 48% ≥65: 52%

3

Melanoma

Nivolumab + Ipilimumab v Ipilimumab Nivolumab + Ipilimumab v Nivolumab v Ipilimumab

HR: 0.36; CI: 0.22–0.56; P = .0 0 01 Nivolumab + Ipilimumab v Ipilimumab: HR: 0.43; CI: 0.35–0.52 Nivolumab v Ipilimumab: HR: 0.55; CI: 0.45–0.66 Nivolumab + Ipilimumab v Nivolumab: HR: 0.78; CI: 0.64–0.96

Ipilimumab

2

Melanoma

Ipilimumab + Sargramostin v Ipilimumab

<65: 56% ≥65: 44%

<65 years: HR: 0.29; CI: 0.14–0.60 <65 years: Nivolumab + Ipilimumab v Ipilimumab: HR: 0.42; CI: 0.32–0.54 Nivolumab v Ipilimumab: HR: 0.58; CI: 0.45–0.73 Nivolumab + Ipilimumab v Nivolumab: HR: 0.73; CI: 0.56–0.94 <65 years: HR: 0.88; CI: 0.60–1.28

≥65 years: Pembrolizumab every 2 weeks HR: 0.61; CI: 0.43–0.86 Pembrolizumab every 3 weeks HR: 0.57; CI: 0.41–0.81 ≥65–<75 years: HR: 0.94; CI: 0.69–1.27 ≥75 years: HR: 0.97 CI: 0.49–1.95 ≥65–<75 years: HR: 0.51; CI: 0.32–0.82 ≥75 years: HR: 1.76; CI: 0.77–4.05 ≥65 years: HR: 0.43; CI: 0.24–0.79 ≥65 years: Nivolumab + Ipilimumab v Ipilimumab: HR: 0.45; 0.33–0.60 Nivolumab v Ipilimumab: HR: 0.49; CI: 0.37–0.67 Nivolumab + Ipilimumab v Nivolumab: HR: 0.90; CI: 0.65–1.24 ≥65 years: HR: 0.87; CI: 0.55–1.39

Wolchok 2017

Hodi 2014

<65: 43.52% ≥65: 56.48%

<65: 60% ≥65: 40%

HR: 0.87; CI: 0.64–1.18; P = .37

HR PFS older adults

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Table 4 Response rates in patients treated with checkpoint inhibitors by age group: data from randomized trials. Trial phase

Malignancy

Study arms

Distribution by age (years)

General ORR

Balar 2016

Atezolizumab

2

Atezolizumab

<80: 79% ≥80: 21%

23.0% (16.0–31.0)

Rosenberg 2016

Atezolizumab

2

Atezolizumab

<65: 41% ≥65: 59%

14.8% (11.1–19.3)

<65 years: 13.4% (8.0–20.6)

Kaufman 2016

Avelumab

2

Avelumab

<65: 25% ≥65: 75%

31.8% (21.9–43.1)

Hui 2017

Pembrolizumab

1

Urothelial Cancer Urothelial Cancer Merkel Cell Cancer NSCLC

Ribas 2016

Pembrolizumab

1

Melanoma

Pembrolizumab

<65: 61% ≥65: 39%

Pembrolizumab 2 mg/kg every 3 weeks: 33% (4.0–78.0) v Pembrolizumab 10 mg/kg every 3 weeks: 26% (15.0–41.0) v Pembrolizumab 10 mg/kg every 2 weeks: 26% (14.0–41.0) Overall: 27& (18.0–37.0) 33.4% (29.6–37.4)

<65 years: 31.8% (13.9–54.9) <65 years: PD-L1 ≥50: 50% (19.0–81.0) 1% ≤ PD-L1 <50%: 15% (3.0–38.0) PD-L <1%: 0% (0.0–52.0)

Robert 2014

Pembrolizumab

1

Melanoma

Pembrolizumab 2 mg/kg v Pembrolizumab 10 mg/kg

<65: 64% ≥65: 36%

Gettinger 201 Hida 2017

Nivolumab Nivolumab

1 2

NSCLC S-NSCLC

Nivolumab Nivolumab

Rizvi 2015

Nivolumab

2

S-NSCLC

Weber 2015

Nivolumab

3

Postow 2015

Nivolumab & Ipilimumab

2

Pembrolizumab 2 mg/kg every 3 weeks v Pembrolizumab 10 mg/kg every 3 weeks v Pembrolizumab 10 mg/kg every 2 weeks

ORR younger adults

Nivolumab

<65: 49.57% ≥65: 50.42%

15.0% (8.7–22.2)

<65 years: 12% (5.0–23.3)

Melanoma

Nivolumab v Chemotherapy

<65: 64% ≥65: 36%

31.7% (23.5–40.8)

<65 years: 29.3% (19.7–40.4)

Melanoma

Nivolumab + Ipilimumab v Ipilimumab

<65: 40% ≥65: 60%

Nivolumab + Ipilimumab: 61.0% (48.9–72.4) Ipilimumab: 10.8% (3.0–25.4)

<65 years: Nivolumab + Ipilimumab: 71.0% (52.0–85.8) Ipilimumab: 0% (0.0–24.7)

≥80 years: 28.0% (12.0–49.0) ≥65 years: 15.8% (10.9–22.0) ≥65 years: 31.8% (20.9–44.4) ≥65 years: PD-L1 ≥50: 53% (28.0–77.0) 1% ≤ PD-L1 <50%: 19% (7.0–36.0) PD-L <1%: 14% (0.4–58.0)

≥65 years: 36.6% (30.3–43.2) ≥65 years: Pembrolizumab 2 mg/kg 17.0% (6.0–35.0) Pembrolizumab 10 mg/kg 25.0% (11.0–43.0) ≥70 years: 17.9% (7.5–33.5) ≥65 years: 35.0% (18.1–56.7) ≥65 years: 17.0% (8.4–29.0) ≥65–<75 years: 21.0% (10.0–36.0) ≥75 years: 6.0% (0.2–30.2) ≥65 years: 36.8% (21.8–54.0) ≥65–<75 years: 41.7% (22.1–63.4) ≥75 years: 28.6% (8.4–58.1) ≥65 years: Nivolumab + Ipilimumab: 53.7% (37.4–69.3) Ipilimumab: 16.7% (4.7–37.4)

9

[mUS5Gb;October 24, 2018;22:17]

<70: 69.76% ≥70: 30.23% <65: 43% ≥65: 57%

Pembrolizumab 2 mg/kg 23.6% (15.2–33.8) Pembrolizumab 10 mg/kg 23.8% (15.2–34.3) 17.0% (11.0–24.7) 25.7% (14.2–42.1)

<65 years: 31.4% (26.6–36.5) <65 years: Pembrolizumab 2 mg/kg 27.0% (16.0–40.0) Pembrolizumab 10 mg/kg 23.0% (13.0–39.0) <70 years: 16.7% (9.6–26.0) <65 years: 13.3% (3.7–37.9)

ORR older adults

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Toxicity of checkpoint inhibitors in older adults

Conclusions

An increasing number of patients are being treated with ICIs and therefore at risk of developing treatment-related toxicity. The toxicity profile of ICIs is distinct from that of systemic chemotherapy and results from autoimmune reactions affecting almost any organ-system [166]. These immune-related adverse events (IRAEs) vary based on the mechanism of action of the ICI. Any-grade IRAEs, including ≥grade 3, are seen at a higher incidence with CTLA-4 inhibitors compared to anti-PD1 or anti-PDL1 [167]. Safety of ICIs has not yet been directly evaluated in an older-adult population. Available data is conflicting, with some reports suggesting a higher rate of adverse events (AEs) in older adults and others showing comparable safety across age groups. An FDA analysis reviewed data from 4 phase-3 registration trials with nivolumab [168]. The rates of grade 1–2 AEs was similar among all age groups; however, older patients had a higher incidences of grade 3–5 AEs (71.7% in patients ≥70 years v 58.4% in patients <65 years), serious AEs (50.8% for <65 v 58% for ≥70), and AEs requiring treatment with immune modulating medication (41.5% for <65 v 51.9% for ≥70). In a singlecenter analysis of patients enrolled on immunotherapy phase I clinical trials, older patients were more likely to develop immunerelated toxicities (53% v 39%, P = 0.007) including a higher rate of grade 3of 4 AEs (19% v 11%, P = .047) [169]. In the CheckMate037 phase 3 trial exploring nivolumab versus chemotherapy in advanced melanoma, the rate of all grade AEs was similar across age groups, however, the incidence of grade 3–4 AEs was 37.1% in patients <65 years versus 45% in patients ≥65 years [152]. In the phase 1 Keynote-001 trial evaluating pembrolizumab in advanced melanoma the incidence of grade 3–4 AEs was higher in patients ≥65 years compared to younger patients (45.2% v 37.8%) although the rate of all grade AEs was similar [161]. In a paper that analyzed the impact of age on immunotherapy outcomes in metastatic melanoma the incidence of arthritis, thyroiditis, and endocrinerelated toxicity was higher in adults ≥75 years versus younger patients [146]. A pooled analysis evaluated safety data for nivolumab in 248 patients from the CheckMate-017 and CheckMate-063 trials; 35% of subjects were aged ≥65 and <75 years, and 11% were aged ≥75 years [170]. The rate of any-grade treatment-related AEs was 67.9% in patients aged <65 years, 66.7% in patients aged between ≥65 and <75 years, and 52.0% in those ≥75 years. Grade 3–4 AEs were observed in 11.2% of patients <65 years, 13.8% in those ≥65 and <75 years, and 7.4% in those ≥75 years. For patients aged ≥65 years on the CheckMate-069 trial, treatmentrelated grade 3–4 AEs were reported in 52% of those treated with combination nivolumab plus ipilimumab and 15% of those treated with ipilimumab monotherapy [171]. Patients aged <65 years had an incidence of grade 3–4 AEs, with rates of 54% in the combination arm and 26% of patients in the monotherapy arm. On the IMvigor-Cohort 2 phase 2 trial evaluating atezolizumab in urothelial cancer, similar rates of all grade AEs, including a 50% incidence of grade 3–4 AEs, were seen in patients younger versus ≥65 years [159]. Similarly, rates of toxicity were comparable for all age groups for patients treated with ipilimumab in the Italian EAP study [147]. However, data from a prospective cohort study focused on the safety of ipilimumab at a dose of 3 mg/kg that included 2,017 patients with metastatic melanoma (38% were ≥65 years) showed a higher incidence of IRAEs in patients ≥65 years compared to those <65 years (11% v 7%) [172]. Data from Memorial-Sloan Kettering Cancer Center presented at the American Society of Clinical Oncology 2016 meeting reported comparable rates of AEs to published phase III data in patients older than 80 years treated with ICIs for melanoma, although the rate of high-grade AEs among this subject group was higher in the case of combination therapy (ipilimumab + nivolumab) [173].

We are at the dawn of a new era in cancer therapy that may be of particular value in the treatment of older adults with cancer. Our understanding of immune changes with aging has advanced significantly, although how these changes relate to the incidence of cancer and the impact of immunotherapy in older adults is largely unknown. It is clear, however, that the currently available ICIs are highly effective in older adults with benefits that overall appear to be similar to those in younger individuals. However, the toxicity of these treatments may be more significant for older adults based on currently available data. There is a definite need for more studies specifically addressing the risks and benefits of ICIs in a prospective manner in older adults, who comprise the majority of patients with cancer. These studies should be combined with comprehensive immune profiling before and during therapy to guide future immunotherapeutic interventions and to develop novel tools to predict responses and toxicity. Conflict of interest No conflict of interest.

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