Association of blood biomarkers and autoimmunity with immune related adverse events in patients with cancer treated with immune checkpoint inhibitors

Impact of Nutritional Status on Neutrophil-to-Lymphocyte Ratio as a Predictor of Efficacy and Adverse Events of Immune Check-Point Inhibitors

The neutrophil -to-lymphocyte ratio (NLR) is useful for predicting the effectiveness of treatment with immune checkpoint inhibitors (ICIs) and immune-related adverse events (irAEs). Because a growing body of evidence has recently shown that the number of lymphocytes that comprise NLR fluctuates according to nutritional status, this study examined whether the usefulness of NLR varies in ICI treatment due to changes in nutritional status. A retrospective analysis was performed on 1234 patients who received ICI treatment for malignant tumors at our hospital. Progression-free survival (PFS) was significantly prolonged in patients with NLR < 4. Multivariate analysis revealed that the factors associated with the occurrence of irAE were NLR < 4 and the use of ipilimumab. However, when limited to cases with serum albumin levels <3.8 g/dL, lymphocyte counts significantly decreased, and the associations between NLR and PFS and between NLR and irAE occurrence disappeared. In contrast, when limited to the cases with serum albumin levels ≥3.8 g/dL, the associations remained, with significantly prolonged PFS and significantly increased irAE occurrence at NLR < 4. NLR may be a good predictive tool for PFS and irAE occurrence during ICI treatment when a good nutritional status is maintained.

Predictive value of NLR and PLR for immune-related adverse events: a systematic review and meta-analysis

BACKGROUND

Currently, there is a lack of affordable and accessible indicators that can accurately predict immune-related adverse events (irAEs) resulting from the use of immune checkpoint inhibitors (ICIs). In order to address this knowledge gap, our study explore the potential predictive value of two ratios, namely the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR), for irAEs in cancer patients.

METHODS

A systematic search was performed in PubMed, Embase, and the Cochrane library. Studies involving NLR or PLR with irAEs were included. Quality and risk of bias of the selected studies were assessed. Forest plots were created based on Cox model analysis. Random effects meta-analyses were conducted to estimate odds ratio (OR) and its 95% confidence interval (CI).

RESULTS

After screening 594 studies, a total of 7 eligible studies with 1068 cancer patients were included. Analysis based on Cox regression showed that low neutrophil-lymphocyte ratio (L-NLR) (OR = 3.02, 95% CI 1.51 to 6.05, P = 0.002) and low platelet-lymphocyte ratio (L-PLR) (OR = 1.83, 95% CI 1.21 to 2.76, P = 0.004) were associated with irAEs. In the subgroup analysis of cut-off value, when the NLR cut-off value was 3, irAEs was significantly correlated with NLR (OR = 2.63, 95% CI 1.63 to 4.26, P < 0.001).

CONCLUSIONS

Both L-NLR and L-PLR have been found to be significantly associated with irAEs. Consequently, patients identified as being at a higher risk for irAEs should be subjected to more diligent monitoring and close observation.

Biomarkers for immune-related adverse events in cancer patients treated with immune checkpoint inhibitors

Although immune checkpoint inhibitors have greatly improved cancer therapy, they also cause immune-related adverse events, including a wide range of inflammatory side effects resulting from excessive immune activation. Types of immune-related adverse events are diverse and can occur in almost any organ, with different frequencies and severities. Furthermore, immune-related adverse events may occur within the first few weeks after treatment or even several months after treatment discontinuation. Predictive biomarkers include blood cell counts and cell surface markers, serum proteins, autoantibodies, cytokines/chemokines, germline genetic variations and gene expression profiles, human leukocyte antigen genotype, microRNAs and the gut microbiome. Given the inconsistencies in research results and limited practical utility, there is to date no established biomarker that can be used in routine clinical practice, and additional investigations are essential to demonstrate efficacy and subsequently facilitate integration into routine clinical use.

Established and emerging biomarkers of immunotherapy in renal cell carcinoma

Immunotherapies, such as immune checkpoint inhibitors, have heralded impressive progress for patient care in renal cell carcinoma (RCC). Despite this success, some patients' disease fails to respond, and other patients experience significant side effects. Thus, development of biomarkers is needed to ensure that patients can be selected to maximize benefit from immunotherapies. Improving clinicians' ability to predict which patients will respond to immunotherapy and which are most at risk of adverse events - namely through clinical biomarkers - is indispensable for patient safety and therapeutic efficacy. Accordingly, an evolving suite of therapeutic biomarkers continues to be investigated. This review discusses biomarkers for immunotherapy in RCC, highlighting current practices and emerging innovations, aiming to contribute to improved outcomes for patients with RCC.

Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio: Markers predicting immune-checkpoint inhibitor efficacy and immune-related adverse events

We conducted a comprehensive review of existing prediction models pertaining to the efficacy of immune-checkpoint inhibitor (ICI) and the occurrence of immune-related adverse events (irAEs). The predictive potential of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in determining ICI effectiveness has been extensively investigated, while limited research has been conducted on predicting irAEs. Furthermore, the combined model incorporating NLR and PLR, either with each other or in conjunction with additional markers such as carcinoembryonic antigen, exhibits superior predictive capabilities compared to individual markers alone. NLR and PLR are promising markers for clinical applications. Forthcoming models ought to incorporate established efficacious models and newly identified ones, thereby constituting a multifactor composite model. Furthermore, efforts should be made to explore effective clinical application approaches that enhance the predictive accuracy and efficiency.

The role of circulating biomarkers in predicting the 30-day mortality of immune checkpoint inhibitors-related myocarditis: a retrospective cohort study

Immune checkpoint inhibitors-related myocarditis (ICIs-M) is a rare and highly lethal immune-related adverse events (irAEs) in common irAEs. This study aims to find circulating biomarkers that can reflect disease state and prognosis accurately. 48 patients with ICIs-M were enrolled according to the diagnostic criteria for ICIs-related myocarditis. For all enrolled patients, valuable information was extracted retrospectively from the medical system, mainly including demographic information, tumor information and laboratory examination. The follow-up period was defined as 30 days after the first diagnosis of ICIs-M. In this study, the 30-day mortality rate of ICIs-M was 24.4%. After adjusting for potential confounding factors using multivariate analysis tools, we demonstrated the excellent performance of biomarkers in predicting 30-day mortality in patients with ICIs-M, including PLT (hazard ratio (HR), 1.07; 95% confidence interval (95%CI), 1.01-1.14; p = 0.028), ALT (HR, 1.23; 95%CI, 1.06-1.41; p = 0.005), AST(HR, 1.06; 95%CI, 1.01-1.10; p = 0.015), LDH (HR, 1.15; 95%CI, 1.04-1.26; p = 0.004), troponin I(HR, 1.44; 95%CI, 1.09-1.89; p = 0.009), PLR (blood plate/lymphocyte) (HR, 1.04; 95% CI, 1.01-1.07; p = 0.024), LAR (lactate dehydrogenase/albumin) (HR, 1.05; 95%CI, 1.01-1.09; p = 0.012), and AAR (aspartate transaminase/albumin) (HR, 1.18; 95%CI, 1.00-1.39; p = 0.048). The analysis of the receiver operating characteristic showed that biomarkers with area under curve (AUC) greater than or equal to 0.80 were LDH (cutoff value, 724.5; AUC, 0.86; 95%CI, 0.75-0.97), LAR (cutoff value, 18.11; AUC, 0.87; 95%CI, 0.76-0.97), troponin I (cutoff value, 0.87; AUC, 0.80; 95%CI, 0.62-0.99), and AAR(cutoff value, 1.52; AUC, 0.80; 95%CI, 0.61-0.98). LDH, LAR, troponin I, and AAR are a group of promising biomarkers that demonstrate excellent predictive ability in predicting the 30-day mortality rate of immune-related myocarditis.

Neutrophil-to-Lymphocyte Ratio Predicts Immune-related Adverse Events in Patients With Hepatocellular Carcinoma Treated With Atezolizumab Plus Bevacizumab

Background/Aim

Atezolizumab in combination with bevacizumab is an approved systemic chemotherapy regimen for advanced hepatocellular carcinoma (HCC). However, immune checkpoint inhibitors (ICIs), such as atezolizumab, frequently lead to immune-related adverse events (irAEs). The identification of biomarkers that can predict the occurrence of irAEs is crucial for the optimal management of patients undergoing ICI treatment.

Patients and Methods

Between October 2020 and June 2023, we conducted a study involving 69 patients with advanced HCC who received treatment with atezolizumab plus bevacizumab. We conducted an analysis of blood-based biomarkers to identify independent risk factors associated with irAEs.

Results

In our study, 12 out of 69 patients (17.4%) experienced irAEs. Our investigation into blood-based biomarkers revealed that a neutrophil-to-lymphocyte ratio (NLR) <2.04 at three weeks after the initiation of treatment had high predictive power (area under the curve: 0.77) for irAEs. Furthermore, multivariate logistic analysis identified NLR at three weeks (hazard ratio=0.23; p=0.037) and non-viral infection (hazard ratio=4.47; p=0.037) as independent factors contributing to the occurrence of irAEs. Patients who developed irAEs demonstrated a more favorable overall response rate (75.0% vs. 28.1%, p=0.005), disease control rate (91.6% vs. 52.6%, p=0.016), and progression-free survival (12.1 months vs. 6.0 months, p=0.010) than those who did not experience irAEs.

Conclusion

An NLR <2.04 at three weeks after the initiation of treatment may serve as a valuable biomarker for predicting irAEs in patients with HCC undergoing atezolizumab plus bevacizumab therapy.

Baseline Circulating Blood Cell Counts and Ratios and Changes Therein for Predicting Immune-Related Adverse Events during Immune Checkpoint Inhibitor Therapy: A Multicenter, Prospective, Observational, Pan-Cancer Cohort Study with a Gender Perspective

Several factors have been associated with the occurrence of immune-related adverse events (irAEs) induced by immune checkpoint inhibitor (ICI) therapy. Despite their availability, the predictive value of circulating blood cell parameters remains underexplored. Our aim was to investigate whether baseline values of and early changes in absolute neutrophil count (ANC), absolute lymphocyte count (ALC), other blood cell counts, and lymphocyte-related ratios can predict irAEs and whether sex may differentially influence this potential predictive ability. Of the 145 patients included, 52 patients (35.8%) experienced at least one irAE, with a 1-year cumulative incidence of 41.6%. Using Fine and Gray competing risk models, we identified female sex (hazard ratio (HR) = 2.17, 95% confidence interval (CI) = 1.20-3.85), high ALC before ICI initiation (HR = 1.63, 95% CI = 1.09-2.45), and low ANC after ICI initiation (HR = 0.81, 95% CI = 0.69-0.96) as predictors of irAEs. However, ALC and ANC may only have an impact on the risk of irAEs in women (stratified for female sex, ALC-related HR = 2.61, 95% CI = 1.40-4.86 and ANC-related HR = 0.57, 95% CI = 0.41-0.81). Priority should be given to developing models to predict ICI-related toxicity and their validation in various settings, and such models should assess the impact of patient sex on the risk of toxicity.

The Heart of the Matter: Immune Checkpoint Inhibitors and Immune-Related Adverse Events on the Cardiovascular System

Cancer remains a prominent global cause of mortality, second only to cardiovascular disease. The past decades have witnessed substantial advancements in anti-cancer therapies, resulting in improved outcomes. Among these advancements, immunotherapy has emerged as a promising breakthrough, leveraging the immune system to target and eliminate cancer cells. Despite the remarkable potential of immunotherapy, concerns have arisen regarding associations with adverse cardiovascular events. This review examines the complex interplay between immunotherapy and cardiovascular toxicity and provides an overview of immunotherapy mechanisms, clinical perspectives, and potential biomarkers for adverse events, while delving into the intricate immune responses and evasion mechanisms displayed by cancer cells. The focus extends to the role of immune checkpoint inhibitors in cancer therapy, including CTLA-4, PD-1, and PD-L1 targeting antibodies. This review underscores the multifaceted challenges of managing immunotherapy-related cardiovascular toxicity. Risk factors for immune-related adverse events and major adverse cardiac events are explored, encompassing pharmacological, treatment-related, autoimmune, cardiovascular, tumor-related, social, genetic, and immune-related factors. The review also advocates for enhanced medical education and risk assessment tools to identify high-risk patients for preventive measures. Baseline cardiovascular evaluations, potential prophylactic strategies, and monitoring of emerging toxicity symptoms are discussed, along with the potential of adjunct anti-inflammatory therapies.

Key Determinants of Immune-Mediated Adverse Reactions to Oncology Drugs

To overcome the epidemiological severity of cancer, developing effective treatments is urgently required. In response, immune checkpoint inhibitors (ICIs) have been revealed as a promising resolution for treatment-resistant cancers across the world. Yet, they have both advantages and disadvantages, bringing therapeutic benefits while simultaneously inducing toxicity, and in particular, immune-mediated adverse drug reactions (imADRs), to the human body. These imADRs can be pathogenic and sometimes lethal, hampering health prediction and monitoring following the provision of ICI treatment. Therefore, it is necessary to collectively identify the determinant factors that contribute to these imADRs induced by ICIs. This article evaluated treatment-, tumor-, and patient-related determinants, and indicated a research gap for future investigations on the pathogenic mechanism of imADRs and translational conversion of determinants into clinical biomarkers to aid pharmacovigilance and cancer therapies.

Evaluating Survival After Hospitalization Due to Immune-Related Adverse Events From Checkpoint Inhibitors

BACKGROUND

As immune checkpoint inhibitors (CPI) are increasingly approved for cancer treatment, hospitalizations related to severe immune-related adverse events (irAE) will increase. Here, we identify patients hospitalized due to irAEs and describe survival outcomes across irAE, CPI, and cancer type.

METHODS

We identified patients hospitalized at our institution from January 2012 to December 2020 due to irAEs. Survival was analyzed using Kaplan-Meier survival curves with log-rank tests.

RESULTS

Of 3137 patients treated with CPIs, 114 (3.6%) were hospitalized for irAEs, resulting in 124 hospitalizations. Gastrointestinal (GI)/hepatic, endocrine, and pulmonary irAEs were the most common causes of irAE-related hospitalization. After CPI initiation, the average time to hospitalization was 141 days. Median survival from hospital admission was 980 days. Patients hospitalized due to GI/hepatic and endocrine irAEs had longer median survival than patients with pulmonary irAEs (795 and 949 days vs. 83 days [P < .001]). Patients with melanoma and renal cell carcinoma had longer median survival than patients with lung cancer (2792 days and not reached vs. 159 days [P < .001]). There was longer median survival in the combination group compared to the PD-(L)1 group (1471 vs. 529 days [P = .04]).

CONCLUSIONS

As CPI use increases, irAE-related hospitalizations will as well. These findings suggest that among patients hospitalized for irAEs, survival differs by irAE and cancer type, with worse survival for patients with irAE pneumonitis or lung cancer. This real-world data contributes to research pertaining to hospitalization due to severe irAEs, which may inform patient counseling and treatment decision-making.

Immune-related adverse events after immune check point inhibitors: Understanding the intersection with autoimmunity

Immune checkpoint inhibitor therapies act through blockade of inhibitory molecules involved in the regulation of T cells, thus releasing tumor specific T cells to destroy their tumor targets. However, immune checkpoint inhibitors (ICI) can also lead to a breach in self-tolerance resulting in immune-related adverse events (irAEs) that include tissue-specific autoimmunity. This review addresses the question of whether the mechanisms that drive ICI-induced irAEs are shared or distinct with those driving spontaneous autoimmunity, focusing on ICI-induced diabetes, ICI-induced arthritis, and ICI-induced thyroiditis due to the wealth of knowledge about the development of autoimmunity in type 1 diabetes, rheumatoid arthritis, and Hashimoto's thyroiditis. It reviews current knowledge about role of genetics and autoantibodies in the development of ICI-induced irAEs and presents new studies utilizing single-cell omics approaches to identify T-cell signatures associated with ICI-induced irAEs. Collectively, these studies indicate that there are similarities and differences between ICI-induced irAEs and autoimmune disease and that studying them in parallel will provide important insight into the mechanisms critical for maintaining immune tolerance.

Immune checkpoint inhibitor-associated myocarditis and fulminant type I diabetes in a patient with metastatic non-small cell lung cancer

A woman in her mid-60s presented to the hospital due to a history of nausea, vomiting, shortness of breath, dyspnoea on exertion and polyuria. She was receiving medical therapy for advanced non-small cell lung cancer and recently initiated immune checkpoint inhibitor (ICI) immunotherapy. Investigations revealed lab results consistent with diabetic ketoacidosis (DKA), elevated cardiac biomarkers, multiple cardiac arrhythmias and reduced ejection fraction on transthoracic echocardiogram. Cardiac catheterisation showed non-obstructive coronary arteries.The patient was diagnosed with an ICI-associated myocarditis and type I diabetes due to recent initiation of the ICI durvalumab. She was treated with the institutional DKA protocol and received corticosteroid therapy for drug toxicity according to guidelines. She was discharged with marked improvement in symptoms. The patient had good recovery after discharge with further investigations showing improvement in her cardiac ejection fraction on cardiac MRI. She remains on medical therapy with an insulin regimen for diabetes management.

Melanoma patients with immune-related adverse events after immune checkpoint inhibitors are characterized by a distinct immunological phenotype of circulating T cells and M-MDSCs

Treatment with immune checkpoint inhibitors (ICIs) has improved the prognosis of melanoma patients. However, ICIs can cause an overactivation of the immune system followed by diverse immunological side effects known as immune-related adverse events (irAE). Currently, the toxicity of irAE is limiting the usage of ICIs. Here, we studied circulating monocytic myeloid-derived suppressor cells (M-MDSCs) and T cells in course of irAE after the ICI therapy. Our longitudinal study involved 31 melanoma patients with and without adverse events during anti-PD-1 monotherapy or anti-CTLA-4/PD-1 combination therapy. Peripheral blood samples were analyzed before ICI start, during ICI treatment, at the time point of irAE and during immunosuppressive treatment to cure irAE. We observed an enhanced progression-free survival among patients with irAE. In patients with irAE, we found an upregulation of CD69 on CD8+ T cells and a decreased frequency of regulatory T cells (Tregs). Moreover, lower frequencies of Tregs correlated with more severe side effects. Patients treated with immunomodulatory drugs after irAE manifestation tend to show an elevated number of M-MDSCs during an immunosuppressive therapy. We suggest that an activation of CD8+ T cells and the reduction of Treg frequencies could be responsible for the development of irAE.

Neutrophil to Lymphocyte ratio as a predictor for immune-related adverse events in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background

The use of immune checkpoint inhibitors (ICIs) in cancer treatment has led to an increase in immune-related adverse events (irAEs), which can cause treatment discontinuation and even fatal reactions. The purpose of this study was to evaluate the usefulness of the peripheral biomarker neutrophil to lymphocyte ratio (NLR) in predicting irAEs.

Methods

A systematic search of databases was conducted to identify studies on the predictive value of NLR for irAEs. The standardized mean difference (SMD) was used to compare continuous NLR, while crude odds ratios (ORs) were calculated for categorized NLR if adjusted ORs and 95% confidence intervals (CIs) were not provided in the original study.

Results

The meta-analysis included 47 studies with a total of 11,491 cancer patients treated with ICIs. The baseline continuous NLR was significantly lower in patients with irAEs compared to those without (SMD=-1.55, 95%CI=-2.64 to -0.46, P=0.006). Similarly, categorized NLR showed that lower baseline NLR was associated with increased irAEs (OR=0.55, 95%CI=0.41-0.73, P<0.001). Subgroup analysis revealed that the OR for predicting irAEs with NLR cut-off values of 3 and 5 was 0.4 and 0.59, respectively. Interestingly, increased baseline NLR was associated with a higher incidence of immune-related liver injury (OR=2.44, 95%CI=1.23-4.84, I2 = 0%, P=0.010).

Conclusion

Our study suggests that lower baseline NLR is associated with a higher risk of overall irAEs. However, further studies are needed to determine the best cut-off value and explore the efficacy of NLR in predicting specific types of irAEs.

Korean Real-World Data on Patients With Unresectable Stage III NSCLC Treated With Durvalumab After Chemoradiotherapy: PACIFIC-KR

INTRODUCTION

This study aimed to investigate real-world evidence for efficacy and safety of durvalumab consolidation (DC) after chemoradiotherapy (CRT) in patients with unresectable stage III NSCLC.

METHODS

Patients with stage III NSCLC who started DC after CRT between September 2018 and December 2020 and were treated at five tertiary hospitals in the Republic of Korea were included. The primary end point was real-world progression-free survival (rwPFS). Secondary end points were overall survival, objective response rate, and adverse events including radiation pneumonitis (RP) and immune-related adverse events (irAEs).

RESULTS

A total of 157 patients were enrolled. At the median follow-up of 19.1 months, median rwPFS of DC was 25.9 months (95% confidence interval: 16.5-35.4) and the 1-, 2-, and 3-year rwPFS rates were 59.4%, 51.8%, and 43.5%, respectively. The median overall survival was not mature, and objective response rate of DC was 51.0%. High programmed death-ligand 1 expression (≥50%) and development of RP requiring steroid treatment were significantly associated with longer (p = 0.043) and shorter rwPFS (p = 0.036), respectively. RP, RP requiring steroid treatment, and irAEs developed in 57 (36.3%), 42 (26.8%), and 53 (33.8%) patients, respectively. Among peripheral blood cell counts at the initiation of DC, a high derived monocyte-to-lymphocyte ratio was the most significant risk factor for the development of RP requiring steroid treatment (OR 44.76, 95% CI: 8.89-225.43, p < 0.001) and irAEs (OR 2.85, 95% CI: 1.27-6.41, p = 0.011).

CONCLUSIONS

Compared with the outcome of the PACIFIC trial, these real-world data revealed favorable survival benefits of DC after CRT in patients with unresectable stage III NSCLC. Blood-based biomarkers could predict higher-grade RP and irAEs before the initiation of DC.

Immune-related adverse events after immune checkpoint inhibitor exposure in adult cancer patients with pre-existing autoimmune diseases

PURPOSE

Immune checkpoint inhibitor (ICI) therapy can predispose patients to immune-related adverse events (irAEs) and autoimmune disease (AD) flare-ups, but the characteristics of irAEs among patients with pre-existing ADs are largely unknown. We conducted this study to determine the clinical courses, irAEs, AD flares, treatment, and outcomes of patients with AD on ICIs.

METHODS

This was a retrospective study of adult cancer patients at a large cancer center who were diagnosed with ADs before undergoing ICI therapy. Patients' clinical courses, complications, treatments, and outcomes related to both ADs flares and irAEs were collected and analyzed.

RESULTS

The study included 197 patients. Most (55.4%) were women. Melanoma comprised the highest proportion (28.4%) of malignancies, and most (83.8%) patients received PD-1/PD-L1 inhibitors. Fifty (25.3%) patients developed a new irAE after starting ICI therapy, while 29 (14.7%) patients had an AD flare-up. Patients with inflammatory bowel disease had the highest incidence of AD flare-ups (31.7%), while patients with Hashimoto hypothyroidism had the highest incidence of new irAEs (39.2%). Patients with inflammatory bowel disease had more severe adverse events. In our cohort, patients with a new diagnosis of irAE were treated with immunosuppressive therapy. AD flares were managed similarly. With regard to irAE manifestations, the most common presentations were colitis (24 [12.1%] patients), hepatic transaminase elevations (8 [4%] patients), and pneumonitis (7 [3.5%] patients).

CONCLUSION

Our findings suggest that patients with gastrointestinal and rheumatologic ADs had a higher incidence of AD flare-ups, while patients with Hashimoto hypothyroidism and neurologic ADs had a higher incidence of new irAEs. Patients with prior ADs experiencing flare-ups or new irAEs after ICI therapy tend to require aggressive immunosuppressive treatment. Thorough evaluation of baseline disease status, appropriate medical management before ICI therapy, and early recognition of inflammatory exacerbation may help ensure long-term success in treating and improving outcomes in these patients.

Therapeutic drug monitoring of immune checkpoint inhibitors: based on their pharmacokinetic properties and biomarkers

As a new means of oncology treatment, immune checkpoint inhibitors (ICIs) can improve survival rates in patients with resistant or refractory tumors. However, there are obvious inter-individual differences in the unsatisfactory response rate, drug resistance rate and the occurrence of immune-related adverse events (irAE). These questions have sparked interest in researchers looking for a way to screen sensitive populations and predict efficacy and safety. Therapeutic drug monitoring (TDM) is a way to ensure the safety and effectiveness of medication by measuring the concentration of drugs in body fluids and adjusting the medication regimen. It has the potential to be an adjunctive means of predicting the safety and efficacy of ICIs treatment. In this review, the author outlined the pharmacokinetic (PK) characteristics of ICIs in patients. The feasibility and limitations of TDM of ICIs were discussed by summarizing the relationships between the pharmacokinetic parameters and the efficacy, toxicity and biomarkers.

Role of Underlying Liver Pathology in the Development of Immune-Related Hepatitis: A Case-Control Study

BACKGROUND

Immune-related hepatitis (irH) is a serious immune-related adverse event (IRAE) that may result in morbidity, immune checkpoint inhibitor (ICI) therapy interruption and, rarely, mortality. The impact of underlying liver pathology, including liver metastasis, on the incidence of irH remains poorly understood.

OBJECTIVES

We hypothesized that the presence of underlying liver pathology increased the risk of irH in patients with cancer treated with ICI.

PATIENTS AND METHODS

We conducted a retrospective case-control study of irH in patients with cancer receiving first ICI treatment from 2016-2020. Provider documented cases of ≥ grade 2 irH were identified and control matched in a 2:1 ratio based on age, sex, time of ICI initiation, and follow-up time. Conditional logistic regression was used to estimate the relationship between irH and liver metastasis at ICI initiation.

RESULTS

Ninety-seven cases of irH were identified, 29% of which had liver metastases at time of ICI initiation. Thirty-eight percent of patients developed grade 2, 47% grade 3, and 14% grade 4 irH. When adjusted for covariates/confounders, the presence of liver metastasis was associated with increased odds of irH (aOR 2.79 95% CI 1.37-5.66, p = 0.005). The presence of liver metastases did not correlate with irH grade or rate of irH recurrence after ICI rechallenge.

CONCLUSIONS

Presence of liver metastases increased the odds of irH in patients with first-time ICI therapy. Limitations include the retrospective nature, moderate sample size, possible selection bias and confounding. Our findings are hypothesis-generating and warrant external validation as well as tissue and circulating biomarker exploration.

Immune-related adverse effects of checkpoint immunotherapy and implications for the treatment of patients with cancer and autoimmune diseases

During the past decade, there has been a revolution in cancer therapeutics by the emergence of antibody-based immunotherapies that modulate immune responses against tumors. These therapies have offered treatment options to patients who are no longer responding to classic anti-cancer therapies. By blocking inhibitory signals mediated by surface receptors that are naturally upregulated during activation of antigen-presenting cells (APC) and T cells, predominantly PD-1 and its ligand PD-L1, as well as CTLA-4, such blocking agents have revolutionized cancer treatment. However, breaking these inhibitory signals cannot be selectively targeted to the tumor microenvironment (TME). Since the physiologic role of these inhibitory receptors, known as immune checkpoints (IC) is to maintain peripheral tolerance by preventing the activation of autoreactive immune cells, IC inhibitors (ICI) induce multiple types of immune-related adverse effects (irAEs). These irAEs, together with the natural properties of ICs as gatekeepers of self-tolerance, have precluded the use of ICI in patients with pre-existing autoimmune diseases (ADs). However, currently accumulating data indicates that ICI might be safely administered to such patients. In this review, we discuss mechanisms of well established and newly recognized irAEs and evolving knowledge from the application of ICI therapies in patients with cancer and pre-existing ADs.

Physician Views on the Provision of Information on Immune Checkpoint Inhibitor Therapy to Patients with Cancer and Pre-Existing Autoimmune Disease: A Qualitative Study

Immune checkpoint inhibitors (ICIs) have improved cancer outcomes but can cause severe immune-related adverse events (irAEs) and flares of autoimmune conditions in cancer patients with pre-existing autoimmune disease. The objective of this study was to identify the information physicians perceived as most useful for these patients when discussing treatment initiation with ICIs. Twenty physicians at a cancer institution with experience in the treatment of irAEs were interviewed. Qualitative thematic analysis was performed to organize and interpret data. The physicians were 11 medical oncologists and 9 non-oncology specialists. The following themes were identified: (1) current methods used by physicians to provide information to patients and delivery options; (2) factors to make decisions about whether or not to start ICIs in patients who have cancer and pre-existing autoimmune conditions; (3) learning points for patients to understand; (4) preferences for the delivery of ICI information; and (5) barriers to the implementation of ICI information in clinics. Regarding points to discuss with patients, physicians agreed that the benefits of ICIs, the probability of irAEs, and risks of underlying autoimmune condition flares with the use of ICIs were most important. Non-oncologists were additionally concerned about how ICIs affect the autoimmune disease (e.g., impact on disease activity, need for changes in medications for the autoimmune disease, and monitoring of autoimmune conditions).

Predictive Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Events

Immune-checkpoint inhibitors (ICIs) are antagonists of inhibitory receptors in the immune system, such as the cytotoxic T-lymphocyte-associated antigen-4, the programmed cell death protein-1 and its ligand PD-L1, and they are increasingly used in cancer treatment. By blocking certain suppressive pathways, ICIs promote T-cell activation and antitumor activity but may induce so-called immune-related adverse events (irAEs), which mimic traditional autoimmune disorders. With the approval of more ICIs, irAE prediction has become a key factor in improving patient survival and quality of life. Several biomarkers have been described as potential irAE predictors, some of them are already available for clinical use and others are under development; examples include circulating blood cell counts and ratios, T-cell expansion and diversification, cytokines, autoantibodies and autoantigens, serum and other biological fluid proteins, human leucocyte antigen genotypes, genetic variations and gene profiles, microRNAs, and the gastrointestinal microbiome. Nevertheless, it is difficult to generalize the application of irAE biomarkers based on the current evidence because most studies have been retrospective, time-limited and restricted to a specific type of cancer, irAE or ICI. Long-term prospective cohorts and real-life studies are needed to assess the predictive capacity of different potential irAE biomarkers, regardless of the ICI type, organ involved or cancer site.

Machine Learning Models Using Routinely Collected Clinical Data Offer Robust and Interpretable Predictions of 90-Day Unplanned Acute Care Use for Cancer Immunotherapy Patients

PURPOSE

Clinical management of patients receiving immune checkpoint inhibitors (ICIs) could be informed using accurate predictive tools to identify patients at risk of short-term acute care utilization (ACU). We used routinely collected data to develop and assess machine learning (ML) algorithms to predict unplanned ACU within 90 days of ICI treatment initiation.

METHODS

We used aggregated electronic health record data from 7,960 patients receiving ICI treatments to train and assess eight ML algorithms. We developed the models using pre-SARS-COV-19 COVID-19 data generated between January 2016 and February 2020. We validated our algorithms using data collected between March 2020 and June 2022 (peri-COVID-19 sample). We assessed performance using area under the receiver operating characteristic curves (AUROC), sensitivity, specificity, and calibration plots. We derived intuitive explanations of predictions using variable importance and Shapley additive explanation analyses. We assessed the marginal performance of ML models compared with that of univariate and multivariate logistic regression (LR) models.

RESULTS

Most algorithms significantly outperformed the univariate and multivariate LR models. The extreme gradient boosting trees (XGBT) algorithm demonstrated the best overall performance (AUROC, 0.70; sensitivity, 0.53; specificity, 0.74) on the peri-COVID-19 sample. The algorithm performance was stable across both pre- and peri-COVID-19 samples, as well as ICI regimen and cancer groups. Type of ICI agents, oxygen saturation, diastolic blood pressure, albumin level, platelet count, immature granulocytes, absolute monocyte, chloride level, red cell distribution width, and alcohol intake were the top 10 key predictors used by the XGBT algorithm.

CONCLUSION

Machine learning algorithms trained using routinely collected data outperformed traditional statistical models when predicting 90-day ACU. The XGBT algorithm has the potential to identify high-ACU risk patients and enable preventive interventions to avoid ACU.

Clustering using unsupervised machine learning to stratify the risk of immune-related liver injury

BACKGROUND AND AIM

Immune-related liver injury (liver-irAE) is a clinical problem with a potentially poor prognosis.

METHODS

We retrospectively collected clinical data from patients treated with immune checkpoint inhibitors between September 2014 and December 2021 at the Nagoya University Hospital. Using an unsupervised machine learning method, the Gaussian mixture model, to divide the cohort into clusters based on inflammatory markers, we investigated the cumulative incidence of liver-irAEs in these clusters.

RESULTS

This study included a total of 702 patients. Among them, 492 (70.1%) patients were male, and the mean age was 66.6 years. During the mean follow-up period of 423 days, severe liver-irAEs (Common Terminology Criteria for Adverse Events grade ≥ 3) occurred in 43 patients. Patients were divided into five clusters (a, b, c, d, and e). The cumulative incidence of liver-irAE was higher in cluster c than in cluster a (hazard ratio [HR]: 13.59, 95% confidence interval [CI]: 1.70-108.76, P = 0.014), and overall survival was worse in clusters c and d than in cluster a (HR: 2.83, 95% CI: 1.77-4.50, P < 0.001; HR: 2.87, 95% CI: 1.47-5.60, P = 0.002, respectively). Clusters c and d were characterized by high temperature, C-reactive protein, platelets, and low albumin. However, there were differences in the prevalence of neutrophil count, neutrophil-to-lymphocyte ratio, and liver metastases between both clusters.

CONCLUSIONS

The combined assessment of multiple markers and body temperature may help stratify high-risk groups for developing liver-irAE.

Correlation of preclinical and clinical biomarkers with efficacy and toxicity of cancer immunotherapy

Immune checkpoint inhibitors (ICIs) have revealed significant clinical values in different solid tumors and hematological malignancy, changing the landscape for the treatment of multiple types of cancer. However, only a subpopulation of patients has obvious tumor response and long-term survival after ICIs treatment, and many patients may experience other undesirable clinical features. Therefore, biomarkers are critical for patients to choose exact optimum therapy. Here, we reviewed existing preclinical and clinical biomarkers of immunotherapeutic efficacy and immune-related adverse events (irAEs). Based on efficacy prediction, pseudoprogression, hyperprogressive disease, or irAEs, these biomarkers were divided into cancer cell-derived biomarkers, tumor microenvironment-derived biomarkers, host-derived biomarkers, peripheral blood biomarkers, and multi-modal model and artificial intelligence assessment-based biomarkers. Furthermore, we describe the relation between ICIs efficacy and irAEs. This review provides the overall perspective of biomarkers of immunotherapeutic outcome and irAEs prediction during ICIs treatment.

Current landscape and tailored management of immune-related adverse events

Unprecedented advances have been made in immune checkpoint inhibitors (ICIs) in the treatment of cancer. However, the overall benefits from ICIs are impaired by the increasing incidence of immune-related adverse events (irAEs). Although several factors and mechanisms have been proposed in the development of irAEs, there is still incomprehensive understanding of irAEs. Therefore, it is urgent to identify certain risk factors and biomarkers that predict the development of irAEs, as well as to understand the underlying mechanisms of these adverse events. Herein, we comprehensively summarize the state-of-the-art knowledge about clinical features and the related risk factors of irAEs. Particularly, we also discuss relevant mechanisms of irAEs and address the mechanism-based strategies, aiming to develop a tailored management approach for irAEs.

Prognostic Value of Lymphocyte-to-Monocyte Ratio (LMR) in Cancer Patients Undergoing Immune Checkpoint Inhibitors

Background

There is accumulating evidence that the lymphocyte-to-monocyte ratio (LMR) is related to the outcomes of cancer patients treated with immune checkpoint inhibitors (ICIs). However, the results remain controversial.

Method

Electronic databases were searched to retrieve the studies that explore the relationship between LMR and the efficacy of ICIs. The primary endpoints were overall survival (OS) and progression-free survival (PFS), evaluated by the hazard ratios (HRs) with 95% confidence intervals (CI), and the secondary endpoints included disease control rate (DCR) and immune-related adverse events (irAEs), assessed by the odd ratios (ORs) with 95% CI.

Results

A total of 27 studies involving 4,322 patients were eligible for analysis. The results indicated that increased LMR at baseline was associated with a superior OS (HR: 0.46, 95% CI: 0.39-0.56, p < 0.001), PFS (HR: 0.60, 95% CI: 0.49-0.74, p < 0.001), and DCR (OR: 3.16, 95% CI: 1.70-5.87, p < 0.001). Posttreatment LMR was linked to a better PFS (HR: 0.46, 95% CI: 0.29-0.71, p = 0.001), but failed to show this correlation in the analysis of OS and DCR. No correlation existed between LMR and irAEs regardless of the testing time (baseline or posttreatment). Subgroup analyses focusing on baseline LMR revealed that higher baseline LMR possessed a better OS in renal cell cancer (RCC) arm, nonsmall cell lung cancer (NSCLC) arm, multiple cancer arm, monotherapy arm, LMR <2 arm, LMR ≥2 arm, western countries arm, eastern countries arm, and anti-PD-1 arm. Higher baseline LMR correlated with better PFS in RCC arm, NSCLC arm, gastric cancer (GC) arm, multiple cancer arm, LMR <2 arm, LMR ≥2 arm, western countries arm, and eastern countries arm.

Conclusions

Higher LMR at baseline was positively correlated with a superior OS, PFS, and DCR for ICIs, but not with irAEs.

Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios as Prognostic Biomarkers in Unresectable Hepatocellular Carcinoma Treated with Atezolizumab plus Bevacizumab

Systemic inflammation is a key risk factor for hepatocellular carcinoma (HCC) progression and poor outcomes. Inflammatory markers such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) may have prognostic value in HCC treated with standard of care atezolizumab plus bevacizumab (Atezo-Bev). We conducted a multicenter, international retrospective cohort study of patients with unresectable HCC treated with Atezo-Bev to assess the association of NLR and PLR with overall survival (OS), progression-free survival (PFS), and objective response rates. Patients with NLR ≥ 5 had a significantly shorter OS (9.38 vs. 16.79 months, p < 0.001) and PFS (4.90 vs. 7.58 months, p = 0.03) compared to patients with NLR < 5. NLR ≥ 5 was an independent prognosticator of worse OS (HR 2.01, 95% CI 1.22−3.56, p = 0.007) but not PFS. PLR ≥ 300 was also significantly associated with decreased OS (9.38 vs. 15.72 months, p = 0.007) and PFS (3.45 vs. 7.11 months, p = 0.04) compared to PLR < 300, but it was not an independent prognosticator of OS or PFS. NLR and PLR were not associated with objective response or disease control rates. NLR ≥ 5 independently prognosticated worse survival outcomes and is worthy of further study and validation.

Sex-Related Differences in Metastatic Melanoma Patients Treated with Immune Checkpoint Inhibition

Objectives: We aimed to investigate sex-related differences in patients with advanced melanoma treated with ICI by linking the assessment of inflammatory response in peripheral blood, onset of immune-related adverse events IRAEs during therapy and treatment response in short- and long-term. Methods: For the purpose of this single-center retrospective study metastatic melanoma patients treated with ICI were included. Baseline patient characteristics, blood sample tests and the onset of immune-related adverse events IRAEs were documented based on clinical records. The short-term treatment response was assessed with 18F-2-Fluor-2-desoxy-D-glucose Positron Emission Tomography/Computed Tomography FDG-PET/CT scans performed six months after initiation of ICI. The overall survival OS and progression-free survival PFS were used as endpoints to assess the long-term response to immunotherapy. Results: In total, 103 patients with advanced melanoma (mean age 68 ± 13.83 years) were included, 29 women (mean age 60.41 ± 14.57 years) and 74 men (mean age 65.66 ± 13.34 years). The primary tumor was located on a lower extremity in one out of three women and on the head/neck in one out of three men (p < 0.001). While the superficial spreading (41%) and nodular (36%) melanoma subtypes represented together 77% of the cases in male population, women showed a more heterogenous distribution of melanoma subtypes with the superficial spreading (35%), nodular (23%), acral lentiginous (19%) and mucosal (12%) melanoma subtypes being most frequent in female population (p < 0.001). Most differences between women and men with regards to inflammatory parameters were observed six months after initiation of ICI with a higher median NLR (p = 0.038), lower counts of lymphocytes (p = 0.004) and thrombocytes (p = 0.089) in addition to lower counts of erythrocytes (p < 0.001) and monocytes (p < 0.001) in women towards men. IRAEs were more frequent in women towards men (p = 0.013). Women were more likely to display endocrinological IRAEs, such as thyroiditis being the most frequent adverse event in women. Interestingly IRAEs of the gastrointestinal tract were the most frequent ones in men. Finally, men with advanced melanoma showed a significantly better response to immunotherapy in short- (p = 0.015) and long-term (OS p = 0.015 and PFS p < 0.001) than women. In fact, every fourth man died during the course of the disease, while every second woman did not survive. (p = 0.001). Conclusion: Men with advanced melanoma showed a significantly better response to immunotherapy in short- and long-term than women. Higher immune activation in peripheral blood before and after initiation ICI might be linked to favorable treatment response during and after ICI in favor of men and decoupled from the onset of IRAEs. Given the significantly higher immunotoxicity and worse outcome experienced by women compared to men the use of ICI should be chosen carefully in women with advanced melanoma.

External validation of biomarkers for immune-related adverse events after immune checkpoint inhibition

Immune checkpoint inhibitors have revolutionized treatment of advanced melanoma, but commonly cause serious immune-mediated complications. The clinical ambition of reserving more aggressive therapies for patients least likely to experience immune-related adverse events (irAE) has driven an extensive search for predictive biomarkers. Here, we externally validate the performance of 59 previously reported markers of irAE risk in a new cohort of 110 patients receiving Nivolumab (anti-PD1) and Ipilimumab (anti-CTLA-4) therapy. Alone or combined, the discriminatory value of these routine clinical parameters and flow cytometry biomarkers was poor. Unsupervised clustering of flow cytometry data returned four T cell subsets with higher discriminatory capacity for colitis than previously reported populations, but they cannot be considered as reliable classifiers. Although mechanisms predisposing some patients to particular irAEs have been described, we are presently unable to capture adequate information from pre-therapy flow cytometry and clinical data to reliably predict risk of irAE in most cases.

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

Introduction: Immune checkpoint inhibitors (ICIs) are a major breakthrough in cancer treatment. Their increasingly frequent use leads to an uprising incidence of immune-related adverse events (irAEs). Among those, myocarditis is the most reported fatal cardiovascular irAE, frequently associated with ICI-related myositis. Case series: Here, we report three cases of ICI-induced myocarditis/myositis with an extremely severe myasthenia gravis-like (MG-like) presentation, highlighting the main challenges in irAEs management. These patients were over 60 years old and presented an ongoing melanoma, either locally advanced or metastatic, treated with ICI combinations. Shortly after the first or second ICI infusion, they were admitted in an intensive care unit (ICU) for grade 3 ICI-induced MG-like symptoms leading to acute respiratory failure (ARF) requiring invasive mechanical ventilation (IMV). The initial misdiagnosis was later corrected to severe ICI-induced seronegative myocarditis/myositis upon biological results and histopathology from muscular/endomyocardial biopsies. All of them received urgent high-dose corticosteroids pulses. The oldest patient died prematurely, but the two others received targeted therapies leading to complete recovery for one of them. Discussion: These cases highlight the four main challenges of irAEs, encompassing the lack of knowledge among physicians, the risk of misdiagnosis due to numerous and non-specific symptoms, the frequent overlapping forms of irAEs, and the extremely rare MG-like misleading presentation of myocarditis/myositis. The exact pathophysiology of irAEs remains unclear, although a major involvement of the lymphoid compartment (specifically T lymphocytes) was evidenced. Therapeutic management is based on urgent high-dose corticosteroids. For the severest forms of irAEs, case-by-case targeted immunosuppressive therapies should be urgently administered upon multidisciplinary meetings. Conclusion: These cases highlight the lack of knowledge of irAEs among physicians, aggravated by misleading overlapping forms, requiring specific management in trained units and multidisciplinary care. Severe MG-like presentation of irAEs constitutes an absolute therapeutic emergency with high-dose corticosteroids and targeted immunosuppressive therapy.

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

Immune-related adverse events (irAEs) are a range of complications associated with the use of immune-checkpoint inhibitors (ICIs). Two major classes of ICIs widely used are Cytotoxic T-Lymphocyte Antigen 4 (CTLA4) and Programmed Cell death-1 (PD-1)/Programmed death-ligand 1 (PD-L1) inhibitors. High-grade irAEs are life-threatening and often cause a severe decline in performance status in such that patients do not qualify for any further anticancer treatments. It is difficult to generalize the evidence in the current literature on risk factors or biomarkers for the entire class of ICIs as the studies so far are either disease-specific (e.g., lung cancer or melanoma) or ICI agent-specific (e.g., pembrolizumab, ipilimumab) or irAE-specific (e.g., pneumonitis or gastritis). In this review, risk factors and biomarkers to consider before initiating or monitoring ICI are listed with a practical purpose in day-to-day practice. Risk factors are grouped into demographics and social history, medical history, and medication history, tumor-specific and agent-specific risk factors. A higher risk of irAE is associated with age <60 years, high body mass index, women on CTLA4 and men on PD-1/PD-L1 agents, and chronic smokers. Patients with significant kidney (Stage IV-V), cardiac (heart failure, coronary artery disease, myocardial infarction, hypertension), and lung (asthma, pulmonary fibrosis, and chronic obstructive pulmonary disease) are at a higher risk of respective organ-specific irAEs. Pre-existing autoimmune disease and chronic use of certain drugs (proton pump inhibitors, diuretics, anti-inflammatory drugs) also increase the irAE-risk. Biomarkers are categorized into circulating blood counts, cytokines, autoantibodies, HLA genotypes, microRNA, gene expression profiling, and serum proteins. The blood counts and certain protein markers (albumin and thyroid-stimulating hormone) are readily accessible in current practice. High neutrophil-lymphocyte ratio, eosinophil/monocyte/lymphocyte counts; TSH and troponins at diagnosis and drop in the white count and lymphocyte count can predict irAE. Other biomarkers with limited evidence are cytokines, autoantibodies, HLA genotypes, microRNA, and gene expression profiling. With fast-expanding approvals for ICIs in various cancer types, knowledge on risk factors and biomarkers can help providers assess the irAE-risk of their patients. Prospective disease and agent-specific studies are needed to provide further insight on this essential aspect of ICI therapy.

Association of Blood Biochemical Indexes and Antibiotic Exposure With Severe Immune-related Adverse Events in Patients With Advanced Cancers Receiving PD-1 Inhibitors

Some patients with cancer treated with programmed death 1 (PD-1) inhibitors experience immune-related severe adverse events (ir-SAEs), however, predictors are limited. The objective was to identify clinicopathologic features that may be associated with a higher ir-SAE risk. This was a nested case-control study. After screening a total of 832 PD-1 inhibitor-treated patients, we identified 42 ir-SAE cases. According to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0, ir-SAEs were defined as grade ≥3 toxic effects associated with immunotherapy. A total of 126 controls were matched. The crude and adjusted risks of ir-SAEs were estimated by odds ratio (ORs) and 95% CIs using multivariate logistic regression models. Baseline neutrophil-to-lymphocyte ratio (NLR) [per SD increment-adjusted (aOR): 1.16], lactate dehydrogenase (LDH) ≥245 U/L (aOR: 2.39), and antibiotic exposure (aOR: 4.39) were associated with a higher risk of ir-SAEs. When NLR was categorized in 3 groups, significantly higher risks of ir-SAEs (aOR: 4.95) were found in participants in group 3 (>6) than in those in group 1 (<3). Furthermore, NLR (per SD increment-adjusted hazard ratio:1.08) were also significantly associated with shorter overall survival (OS). Baseline LDH ≥245 U/L and antibiotic exposure were no significant association with OS. In conclusion, ir-SAEs were associated between baseline NLR, LDH ≥245 U/L and antibiotic exposure. Lower NLR was correlated with longer OS for cancer.

Comprehensive Statistical Exploration of Prognostic (Bio-)Markers for Responses to Immune Checkpoint Inhibitor in Patients with Non-Small Cell Lung Cancer

Simple Summary

Metastatic non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs) may suffer from heavy side effects, and not all patients benefit from the treatment. Therefore, it is crucial to gain knowledge about possible (bio-)markers for response to ICIs. We used retrospective data acquired from NSCLC patients treated with ICIs in first- or further-line therapy settings, including 16 possible markers. We conducted a comprehensive statistical analysis study to find markers for response to treatment, assessed the robustness of our results, and discussed often encountered statistical pitfalls. Our study yielded hypotheses for various predictive and prognostic (bio-)markers for response to ICIs in NSCLC patients. In particular, we found that high basophil counts may be predictive for treatment response in patients in further-line therapy settings.

Abstract

Metastatic non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs) may suffer from heavy side effects and not all patients benefit from the treatment. We conducted a comprehensive statistical analysis to identify promising (bio-)markers for treatment response. We analyzed retrospective data from NSCLC patients treated with ICIs in first- or further-line therapy settings at the University Hospital Zurich. We investigated 16 possible prognostic markers with respect to overall survival, tumor size reduction, and the development of an immune-related adverse event (irAE) and assessed the robustness of our results. For the further-line patient group, the most significant result was that increased basophil counts were associated with increased odds of tumor size reduction within three months and with the development of an irAE. For the first-line patient group, the most significant results were that increased lymphocyte counts, the histology of adenocarcinoma, and the intake of non-steroidal anti-rheumatic drugs (NSAR) were associated with decreased hazards of dying. Our study yielded new hypotheses for predictive (bio-)markers for response to ICIs in NSCLC patients. The possibly beneficial role of high basophil counts is a particularly interesting finding. Our results should be tested on independent data in a prospective fashion.

Facts and Hopes in Prediction, Diagnosis, and Treatment of Immune-Related Adverse Events

Over the past decade, the use of immune checkpoint inhibitors (ICI) has expanded across a wide spectrum of oncology indications. Immune-related adverse events (irAE) from ICIs represent a significant source of morbidity, and in rare instances, can lead to treatment-related mortality. There are significant opportunities to better identify patients at increased risk for immune-related toxicity, diagnose irAEs more accurately and earlier in their course, and develop more individualized therapeutic strategies once complications arise. Clinical characteristics, germline and somatic genetic features, microbiome composition, and circulating biomarkers have all been associated with higher risk of developing irAEs in retrospective series. Many of these data suggest that both antitumor and anti-host ICI-associated immune reactions may be driven by common features of either the tumor or the patient's preexisting immune milieu. While irAE diagnosis is currently based on clinical history, exclusion of alternative etiologies, and sometimes pathologic confirmation, novel blood-based and radiographic assays are in development to identify these complications more precisely. Anecdotal reports and small case series have highlighted the potential role of targeted immunomodulatory agents to treat irAEs, though further prospective investigation is needed to evaluate more rigorously their use in these settings. In this review, we highlight the current state of knowledge about predicting, diagnosing, and treating irAEs with a translational focus and discuss emerging strategies which aim to improve each of these domains.