Do immune checkpoint inhibitors need new studies methodology?

Navigating the landscape of liver cancer management: Study designs in clinical trials and clinical practice

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide and its prognosis is highly heterogeneous, being related not only to tumour burden but also to the severity of underlying chronic liver disease. Moreover, advances in systemic therapies for HCC have increased the complexity of patient management. Randomised-controlled trials represent the gold standard for evidence generation across all areas of medicine and especially in the oncology field, as they allow for unbiased estimates of treatment effect without confounders. Observational studies have many problems that could reduce their internal and external validity. However, large prospective (well-conducted) observational real-world studies can detect rare adverse events or monitor the occurrence of long-term adverse events. How best to harness real world data, which refers to data generated from the routine care of patients, and real-world 'evidence', which is the evidence generated from real-world data, represents an open challenge. In this review article, we aim to provide an overview of the benefits and limitations of different study designs, particularly focusing on randomised-controlled trials and observational studies, to address important and not fully resolved questions in HCC research.

Resistance to immune checkpoint inhibitors in colorectal cancer with deficient mismatch repair/microsatellite instability: misdiagnosis, pseudoprogression and/or tumor heterogeneity?

Colorectal carcinoma (CRC) with deficiency of the deficient mismatch repair (dMMR) pathway/microsatellite instability (MSI) is characterized by a high mutation load and infiltration of immune cells in the tumor microenvironment. In agreement with these findings, clinical trials have demonstrated a significant activity of immune checkpoint inhibitors (ICIs) in dMMR/MSI metastatic CRC (mCRC) patients and, more recently, in CRC patients with early disease undergoing neoadjuvant therapy. However, despite high response rates and durable clinical benefits, a fraction of mCRC patients, up to 30%, showed progressive disease when treated with single agent anti-programmed cell death 1 (PD-1) antibody. This article discusses the three main causes that have been associated with early progression of dMMR/MSI mCRC patients while on treatment with ICIs, i.e., misdiagnosis, pseudoprogression and tumor heterogeneity. While pseudoprogression probably does not play a relevant role, data from clinical studies demonstrate that some dMMR/MSI CRC cases with rapid progression on ICIs may be misdiagnosed, underlining the importance of correct diagnostics. More importantly, evidence suggests that dMMR/MSI mCRC is a heterogeneous group of tumors with different sensitivity to ICIs. Therefore, we propose novel diagnostic and therapeutic strategies to improve the outcome of dMMR/MSI CRC patients.

Circulating Tumor DNA Monitoring on Chemo-immunotherapy for Risk Stratification in Advanced Non-Small Cell Lung Cancer

PURPOSE

Chemoimmunotherapy (chemoIO) is a prevalent first-line treatment for advanced driver-negative non-small cell lung cancer (NSCLC), with maintenance therapy given after induction. However, there is significant clinical variability in the duration, dosing, and timing of maintenance therapy after induction chemoIO. We used circulating tumor DNA (ctDNA) monitoring to inform outcomes in patients with advanced NSCLC receiving chemoIO.

EXPERIMENTAL DESIGN

This retrospective study included 221 patients from a phase III trial of atezolizumab+carboplatin+nab-paclitaxel versus carboplatin+nab-paclitaxel in squamous NSCLC (IMpower131). ctDNA monitoring used the FoundationOne Tracker involving comprehensive genomic profiling of pretreatment tumor tissue, variant selection using an algorithm to exclude nontumor variants, and multiplex PCR of up to 16 variants to detect and quantify ctDNA.

RESULTS

ctDNA was detected (ctDNA+) in 96% of pretreatment samples (median, 93 mean tumor molecules/mL), and similar ctDNA dynamics were noted across treatment arms during chemoIO. ctDNA decrease from baseline to C4D1 was associated with improved outcomes across multiple cutoffs for patients treated with chemoIO. When including patients with missing plasma or ctDNA- at baseline, patients with ctDNA- at C4D1 (clearance), had more favorable progression-free survival (median 8.8 vs. 3.5 months; HR, 0.32;0.20-0.52) and OS (median not reached vs. 8.9 months; HR, 0.22; 0.12-0.39) from C4D1 than ctDNA+ patients.

CONCLUSIONS

ctDNA monitoring during induction chemoIO can inform treatment outcomes in patients with advanced NSCLC. Importantly, monitoring remains feasible and informative for patients missing baseline ctDNA. ctDNA testing during induction chemoIO identifies patients at higher risk for disease progression and may inform patient selection for novel personalized maintenance or second-line treatment strategies.

Safety monitoring of drug-induced muscle injury and rhabdomyolysis: a biomarker-guided approach for clinical practice and drug trials

Skeletal muscle tissue (SKM) may be damaged due to mechanical, metabolic, and exertional causes. However, drug-induced myopathy is among the most frequent causes of muscle disease. The clinical picture of drug-induced myopathies may be highly variable. It may present as asymptomatic or mild myalgias, with or without muscle weakness, which are likely underreported. However, it may also appear as chronic myopathy with severe weakness and, rarely, even as massive rhabdomyolysis with acute kidney injury (AKI). Unfortunately, the available biomarkers for SKM injury do not fully meet the needs for satisfactory detection of drug-induced damage, both in clinical and research settings, mainly due to their low sensitivity and specificity. Therefore, the present study proposes a strategy for drug safety monitoring using the available biomarkers of SKM injury. Moreover, we will discuss mechanisms of drug-induced SKM injury, traditional laboratory testing for SKM injury, and novel skeletal myocyte biomarkers under investigation. This can be incredibly useful in both clinical practice and for de-challenge/re-challenge investigational trials where the risk of drug-induced SKM injury is present.

The Application of Evidence-Based Medicine in Individualized Medicine

The fundamental aim of healthcare is to improve overall health of the population by providing state-of-the-art healthcare for individuals at an affordable cost. The foundation for this system is largely referred to as "evidence-based medicine". Too often, evidence-based medicine is based solely on so-called "best research evidence", collected through randomized controlled trials while disregarding clinical expertise and patient expectations. As healthcare gravitates towards personalized and individualized medicine, such external clinical (research) evidence can inform, but never replace, individual clinical expertise. This applies in particular to orphan diseases, for which clinical trials are methodologically particularly problematic, and evidence derived from them is often questionable. Evidence-based medicine constitutes a complex process to allow doctors and patients to select the best possible solutions for each individual based on rapidly developing new therapeutic directions. This requires a revisit of the foundations of evidence-based medicine. A proposition as to how to manage evidence-based data in individualized immune-oncology is presented here.

A longitudinal circulating tumor DNA-based model associated with survival in metastatic non-small-cell lung cancer

One of the great challenges in therapeutic oncology is determining who might achieve survival benefits from a particular therapy. Studies on longitudinal circulating tumor DNA (ctDNA) dynamics for the prediction of survival have generally been small or nonrandomized. We assessed ctDNA across 5 time points in 466 non-small-cell lung cancer (NSCLC) patients from the randomized phase 3 IMpower150 study comparing chemotherapy-immune checkpoint inhibitor (chemo-ICI) combinations and used machine learning to jointly model multiple ctDNA metrics to predict overall survival (OS). ctDNA assessments through cycle 3 day 1 of treatment enabled risk stratification of patients with stable disease (hazard ratio (HR) = 3.2 (2.0-5.3), P < 0.001; median 7.1 versus 22.3 months for high- versus low-intermediate risk) and with partial response (HR = 3.3 (1.7-6.4), P < 0.001; median 8.8 versus 28.6 months). The model also identified high-risk patients in an external validation cohort from the randomized phase 3 OAK study of ICI versus chemo in NSCLC (OS HR = 3.73 (1.83-7.60), P = 0.00012). Simulations of clinical trial scenarios employing our ctDNA model suggested that early ctDNA testing outperforms early radiographic imaging for predicting trial outcomes. Overall, measuring ctDNA dynamics during treatment can improve patient risk stratification and may allow early differentiation between competing therapies during clinical trials.

Development and validation of a decision model for the evaluation of novel lung cancer treatments in the Netherlands

Recent discoveries in molecular diagnostics and drug treatments have improved the treatment of patients with advanced (inoperable) non-squamous non-small cell lung cancer (NSCLC) from solely platinum-based chemotherapy to more personalized treatment, including targeted therapies and immunotherapies. However, these improvements come at considerable costs, highlighting the need to assess their cost-effectiveness in order to optimize lung cancer care. Traditionally, cost-effectiveness models for the evaluation of new lung cancer treatments were based on the findings of the randomized control trials (RCTs). However, the strict RCT inclusion criteria make RCT patients not representative of patients in the real-world. Patients in RCTs have a better prognosis than patients in a real-world setting. Therefore, in this study, we developed and validated a diagnosis-treatment decision model for patients with advanced (inoperable) non-squamous NSCLC based on real-world data in the Netherlands. The model is a patient-level microsimulation model implemented as discrete event simulation with five health events. Patients are simulated from diagnosis to death, including at most three treatment lines. The base-model (non-personalized strategy) was populated using real-world data of patients treated with platinum-based chemotherapy between 2008 and 2014 in one of six Dutch teaching hospitals. To simulate personalized care, molecular tumor characteristics were incorporated in the model based on the literature. The impact of novel targeted treatments and immunotherapies was included based on published RCTs. To validate the model, we compared survival under a personalized treatment strategy with observed real-world survival. This model can be used for health-care evaluation of personalized treatment for patients with advanced (inoperable) NSCLC in the Netherlands.

Cost-effectiveness of anlotinib vs. pembrolizumab and nivolumab as third-line treatment in recurrent small cell lung cancer in China

BACKGROUND

The study aims to evaluate the cost-effectiveness of anlotinib versus pembrolizumab and nivolumab as the third-line treatment in recurrent small cell lung cancer (SCLC) patients from the Chinese healthcare system perspective.

RESEARCH DESIGN AND METHODS

A Markov model was built to simulate the costs and health outcomes in the 4-year horizon. Efficacy and safety data of anlotinib, pembrolizumab, and nivolumab in patients with recurrent SCLC were derived from three studies. Cost and utility values were derived from local charges, the published literature, and related databases. Three scenario analyses and sensitivity analyses were performed to explore the robustness of the results.

RESULTS

Compared with anlotinib, pembrolizumab and nivolumab were estimated to gain an additional 0.18 and 0.10 quality-adjusted life years (QALYs) at an incremental cost of $10,446 and $5,182, resulting in an increment cost-utility ratio (ICUR) of $58,221/QALY and $56,733/QALY. The sensitivity analyses showed that the likelihood of anlotinib being cost-effective was 87.5% to 99.9% at a willingness-to-pay (WTP) threshold of $11,144 to $33,431/QALY. The scenario analyses indicated that the results varied in different scenarios.

CONCLUSIONS

The findings suggest that anlotinib could be the most cost-effective option versus pembrolizumab and nivolumab in the third-line treatment of recurrent SCLC from the Chinese healthcare system perspective.

The Evolving Scenario in the Assessment of Radiological Response for Hepatocellular Carcinoma in the Era of Immunotherapy: Strengths and Weaknesses of Surrogate Endpoints

Hepatocellular carcinoma (HCC) is a challenging malignancy characterised by clinical and biological heterogeneity, independent of the stage. Despite the application of surveillance programs, a substantial proportion of patients are diagnosed at advanced stages when curative treatments are no longer available. The landscape of systemic therapies has been rapidly growing over the last decade, and the advent of immune-checkpoint inhibitors (ICIs) has changed the paradigm of systemic treatments. The coexistence of the tumour with underlying cirrhosis exposes patients with HCC to competing events related to tumour progression and/or hepatic decompensation. Therefore, it is relevant to adopt proper clinical endpoints to assess the extent of treatment benefit. While overall survival (OS) is the most accepted endpoint for phase III randomised controlled trials (RCTs) and drug approval, it is affected by many limitations. To overcome these limits, several clinical and radiological outcomes have been used. For instance, progression-free survival (PFS) is a useful endpoint to evaluate the benefit of sequential treatments, since it is not influenced by post-progression treatments, unlike OS. Moreover, radiological endpoints such as time to progression (TTP) and objective response rate (ORR) are frequently adopted. Nevertheless, the surrogacy between these endpoints and OS in the setting of unresectable HCC (uHCC) remains uncertain. Since most of the surrogate endpoints are radiology-based (e.g., PFS, TTP, ORR), the use of standardised tools is crucial for the evaluation of radiological response. The optimal way to assess the radiological response has been widely debated, and many criteria have been proposed over the years. Furthermore, none of the criteria have been validated for immunotherapy in advanced HCC. The coexistence of the underlying chronic liver disease and the access to several lines of treatments highlight the urgent need to capture early clinical benefit and the need for standardised radiological criteria to assess cancer response when using ICIs in mono- or combination therapies. Here, we review the most commonly used clinical and radiological endpoints for trial design, as well as their surrogacy with OS. We also review the criteria for radiological response to treatments for HCC, analysing the major issues and the potential future perspectives.

Facts and Hopes for Gut Microbiota Interventions in Cancer Immunotherapy

Immune checkpoint inhibitors (ICI) targeting cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed death 1 (PD-1) proteins transformed the management of advanced cancers. Many tumor-intrinsic factors modulate immunological and clinical responses to such therapies, but ample evidence also implicates the gut microbiome in responses. The gut microbiome, comprising the bacteria, archaea, fungi, and viruses that live in the human digestive tract, is an established determinant of host immunity, but its impact on response to ICI therapy in mice and humans with cancer has only recently been appreciated. Therapeutic interventions to optimize microbiota composition to improve immunotherapy outcomes show promise in mice and humans with cancer. In this review, we discuss the rationale for gut microbiome-based cancer therapies, the results from early-phase clinical trials, and possible future developments.

Tremelimumab and durvalumab in the treatment of unresectable, advanced hepatocellular carcinoma

Liver cancer is the third most common cause of cancer-related mortality worldwide, with over 780,000 deaths in 2018. About 90% of liver cancer cases are hepatocellular carcinoma (HCC), a prototype of inflammation-driven cancer, leading to a robust rationale for the exploration of immune therapy. Previously approved agents for first-line therapy, such as sorafenib, lenvatinib and bevacizumab combined with atezolizumab, have focused on angiogenesis. HIMALAYA was the first trial to demonstrate the benefit of dual immune checkpoint inhibitors, representing a new treatment option in this scenario.

Validating Restricted Mean Survival Time Estimates From Reconstructed Kaplan-Meier Data Against Original Trial Individual Patient Data From Trials Conducted by the Canadian Cancer Trials Group

OBJECTIVES

The development of novel cancer therapies, including immuno-oncology agents, has increased interest in reconstructed individual patient data (IPD) based restricted mean survival time (RMST) analyses. Additionally, reconstructed IPD-based RMST is recommended in cost-effectiveness analyses when original trial IPD are not available. Nevertheless, recently concerns regarding potential bias of reconstructed-IPD RMST have been presented, because reconstructed-IPD RMSTs have not been validated and previous validation endpoints may not capture the entire Kaplan-Meier (KM) curve, especially the "tail." Our study aims to validate the recommended method of IPD reconstruction by comparing reconstructed IPD- and original trial IPD-based RMST.

METHODS

Canadian Cancer Trials Group trials from 1990 to 2017 were included. Overall survival and progression-free survival IPD were reconstructed based on published KM curves using the Guyot method. Analysts were blinded to original trial IPD. RMST was calculated at 1 year and over the entire KM curve. Reconstructed-IPD and original trial-IPD (gold-standard) RMSTs were compared for accuracy and predictive error via mean deviation, mean absolute error (MAE), mean percentage bias, and Bland-Altman plots and across KM curve quality (vector traced or bitmapped).

RESULTS

We identified 39 trials. The mean deviation, MAE, and mean percentage bias of RMST between the reconstructed IPD and original trial IPD were small. In particular, the mean deviation was -0.01 months and -0.04 months, MAE was 0.19 months and 0.24 months, and mean percentage bias was 0.82% and 0.84% in overall survival KM curves in control and experimental arms, respectively. Accuracy was generally not associated with KM curve quality.

CONCLUSIONS

RMST derived from reconstructed IPD displayed excellent accuracy and predictive error compared with the gold standard. Reconstructed IPD could be used to calculate RMST in lieu of original trial IPD, to facilitate decision making for clinicians, researchers, and policy makers.

Analysis of patient reported outcomes included in the registrational clinical trials of nivolumab for advanced non-small cell lung cancer

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Patients’ perspectives are at the center of value-based oncology care.

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Patient reported outcomes (PROs) guide clinical and regulatory decisions.

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PRO instruments do not capture immune-related adverse events in clinical trials.

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Studies did not accurately report PROs after treatment discontinuation.

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Precise analyses of longitudinal effects of nivolumab on PROs were lacking.

In the era of value-based oncology care, stakeholders are increasingly using patient reported outcomes (PROs) to guide clinical and regulatory decisions. PROs are also included in health technology assessments to guide patient access, drug reimbursement and pricing. We reviewed PROs collected in the United States Food and Drug Administration approved indications of nivolumab in advanced NSCLC. We analyzed the PRO data reported in the CheckMate 9LA (NCT03215706), CheckMate 227 (NCT02477826), CheckMate 057 (NCT01673867), and CheckMate 017 (NCT01642004) registrational clinical trials, and concluded that nivolumab alleviated symptom burden and improved health status of patients in this setting. However, inability of the included PRO instruments to measure immune-related adverse events, differences in the timing of PRO evaluation between treatment groups, incomplete patient participation at all time points, limited patient participation in the later time points, and interpretation of the longitudinal data are key challenges that impede accurate analysis and validation of PROs.

Versatile tests for window mean survival time

Window mean survival time (WMST) evaluates the mean survival between a lower time horizon, τ 0 $$ {\tau}_0 $$ , and an upper time horizon, τ 1 $$ {\tau}_1 $$ . As a flexible extension of restricted mean survival time, specific clinically relevant windows of time can be assessed for survival difference accompanied by a communicable interpretation of estimates and tests. In its original application, WMST required the pre-specification of a window through the selection of appropriate window bounds, τ 0 $$ {\tau}_0 $$ and τ 1 $$ {\tau}_1 $$ . In the instance of severe window misspecification of τ 0 $$ {\tau}_0 $$ and τ 1 $$ {\tau}_1 $$ , the analysis may suffer from low power and a less meaningful interpretation. In this article, we introduce versatile tests whose procedures are based on the simultaneous use of multiple WMST test statistics that are asymptotically normal under the null hypothesis of no difference between two groups. Simulations are performed to examine the power of the tests in moderate sample sizes when the data are uncensored to heavily censored with a ramp-up enrollment period. The survival scenarios chosen for simulation are intended to imitate those which are commonly encountered in oncology, especially in trials involving immunotherapies. Implementation of the procedures is discussed in two real data examples for illustration. Functions for performing versatile WMST tests are provided in the survWMST package in R.

Assessment of hyperprogression versus the natural course of disease development with nivolumab with or without ipilimumab versus placebo in phase III, randomized, controlled trials

BACKGROUND

Retrospective studies have suggested a potential risk of hyperprogressive disease (HPD) in patients receiving immune checkpoint inhibitors (ICIs). We compared the incidence of HPD during treatment with nivolumab±ipilimumab versus natural tumor progression with placebo in post hoc analyses of two randomized, double-blind clinical trials.

METHODS

ATTRACTION-2 randomized patients with advanced gastric or gastroesophageal junction cancer (GC/GEJC) and progression on ≥2 prior regimens to nivolumab 3 mg/kg Q2W or placebo. CheckMate 451 randomized patients with extensive-disease small cell lung cancer (ED SCLC) and ongoing complete/partial response or stable disease after first-line chemotherapy to nivolumab 240 mg Q2W, nivolumab 1 mg/kg+ipilimumab 3 mg/kg Q3W for four doses then nivolumab 240 mg Q2W, or placebo. Patients receiving ≥1 dose of study drug and with tumor scans at baseline and the first on-treatment evaluation were included in the HPD analyses. HPD definitions were ≥20%, ≥50%, and ≥100% increase in target lesion sum of the longest diameters (SLD) at the first on-treatment assessment.

RESULTS

In the ATTRACTION-2 HPD-evaluable population, 243 patients received nivolumab and 115 placebo. Fewer patients receiving nivolumab versus placebo had increases in SLD ≥20% (33.7% vs 46.1%) and ≥50% (6.2% vs 11.3%); similar proportions had increases in SLD ≥100% (1.6% vs 1.7%). In the CheckMate 451 HPD-evaluable population, 177 patients received nivolumab, 179 nivolumab+ipilimumab, and 175 placebo. Fewer patients receiving nivolumab or nivolumab+ipilimumab versus placebo had increases in SLD ≥20% (27.1%, 27.4% vs 45.7%), ≥50% (10.2%, 11.2% vs 22.3%), and ≥100% (2.8%, 2.8% vs 6.3%).

CONCLUSIONS

Nivolumab±ipilimumab was not associated with an increased rate of progression versus placebo in patients with GC, GEJC, or ED SCLC, suggesting that previous reports of HPD may reflect the natural disease course in some patients rather than ICI-mediated progression.

TRIAL REGISTRATION NUMBER

NCT02538666; NCT02267343.

Parametric Survival Extrapolation of Early Survival Data in Economic Analyses: A Comparison of Projected Versus Observed Updated Survival

OBJECTIVES

To establish the value of cancer drugs by cost-effectiveness analysis, lifetime parametric survival extrapolations are often fitted to early data. Recent literature suggests that the benefit of cancer agents in primary publications is often different compared with updated data. This study aimed to examine the projected survival based on parametric extrapolations compared with observed survival based on updated data.

METHODS

US Food and Drug Administration oncology approvals from January 2006 to December 2015 were reviewed to identify randomized controlled trials, with updated overall survival (OS) or progression-free survival (PFS) data within 5 years. Individual patient data were reconstructed using established methods on initial and updated publications. Projected survival was calculated as the best-fit parametric restricted mean survival time (RMST) based on extrapolated initial Kaplan-Meier curves whereas observed survival was calculated as observed RMST based on updated Kaplan-Meier curves. Mean deviations, mean absolute error (MAE), mean absolute percentage error, and linear regressions were conducted to examine the relationship between projected and observed survival.

RESULTS

In total, 32 randomized controlled trials were included. The MAE between the projected RMST and observed RMST was 3.18 months (OS) and 2.84 months (PFS) and absolute percentage error of 100% (OS) and 23% (PFS), suggesting substantial imprecision of the projected RMST in predicting the updated RMST. The linear regression indicated MAE increased as time extrapolated and as the percentage of censored patients increased.

CONCLUSIONS

This study demonstrated substantial difference in projected survival between initial and updated publications. Health technology assessment committees need to be aware of the potential uncertainty of incremental effectiveness and resultant value-for-money assessment when making reimbursement decisions based on initial publications with immature survival data.

Pembrolizumab Alone or with Chemotherapy for Metastatic Non-Small-Cell Lung Cancer: A Systematic Review and Network Meta-Analysis

Pembrolizumab monotherapy has replaced chemotherapy as first-line treatment for patients with metastatic non-small-cell lung cancer with tumor programmed death-ligand 1 expression ≥50%. The benefit of chemotherapy combined with pembrolizumab, as compared to pembrolizumab monotherapy, remains uncertain. This systematic review and network meta-analysis aimed to compare these therapies through a network of randomized controlled trials. Endpoints evaluated were progression-free survival (PFS) and overall survival (OS) expressed as hazard ratio (HR) and restricted mean survival time (RMST) through reconstruction of individual patient data from Kaplan-Meier curves, and objective response rate and adverse events. Four trials were included. Through HR and RMST, combination therapy demonstrated longer PFS and similar OS as compared to pembrolizumab monotherapy. Combination therapy was associated with an increase in response rate and adverse events. Thus, combination therapy can be considered when rapid response or prevention of rapid progression is needed. Further evidence to directly compare these therapies is required.

[Dual Immunotherapy in Advanced Non-small Cell Lung Cancer: the Progress and Clinical Application]

Programmed cell death protein-1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and PD-1 inhibitors plus chemotherapy combination regimens have been widely used in the first-line treatment of advanced non-small cell lung cancer(NSCLC), but patients with low PD-L1 expression have limited objective response and survival benefits. Existing treatment regimens are still difficult to fully meet the clinical needs of patients in the real world. Therefore, researchers are still exploring novel superactive treatment options to further improve the efficacy and survival prognosis of different sub-groups in NSCLC. Dual immunotherapy [such as the combination of PD-1 and cytotoxic T lymphocyte associated antigen-4 (CTLA-4) inhibitors] has shown considerable long-term survival benefits in a variety of tumors and has also shown broad clinical prospects in NSCLC. In addition to exploring different emerging combination options, how to accurately identify the optimal-benefit groups through predictive biomarkers and how to effectively manage the safety of combination immunotherapy through multidisciplinary collaboration are also the focus of dual immunotherapy. This article reviews the mechanism of action, research progress, predictive biomarkers and future exploration directions of dual immunotherapy.
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Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects

Individual participant data (IPD) from oncology clinical trials is invaluable for identifying factors that influence trial success and failure, improving trial design and interpretation, and comparing pre-clinical studies to clinical outcomes. However, the IPD used to generate published survival curves are not generally publicly available. We impute survival IPD from ~500 arms of Phase 3 oncology trials (representing ~220,000 events) and find that they are well fit by a two-parameter Weibull distribution. Use of Weibull functions with overall survival significantly increases the precision of small arms typical of early phase trials: analysis of a 50-patient trial arm using parametric forms is as precise as traditional, non-parametric analysis of a 90-patient arm. We also show that frequent deviations from the Cox proportional hazards assumption, particularly in trials of immune checkpoint inhibitors, arise from time-dependent therapeutic effects. Trial duration therefore has an underappreciated impact on the likelihood of success.

Analysis of more than 150 Phase 3 oncology clinical trials supports parametric statistical analysis, significantly increasing the precision of small early-phase trials and relating deviations from the Cox proportional hazards model to trial duration.

Classical mathematical models for prediction of response to chemotherapy and immunotherapy

Classical mathematical models of tumor growth have shaped our understanding of cancer and have broad practical implications for treatment scheduling and dosage. However, even the simplest textbook models have been barely validated in real world-data of human patients. In this study, we fitted a range of differential equation models to tumor volume measurements of patients undergoing chemotherapy or cancer immunotherapy for solid tumors. We used a large dataset of 1472 patients with three or more measurements per target lesion, of which 652 patients had six or more data points. We show that the early treatment response shows only moderate correlation with the final treatment response, demonstrating the need for nuanced models. We then perform a head-to-head comparison of six classical models which are widely used in the field: the Exponential, Logistic, Classic Bertalanffy, General Bertalanffy, Classic Gompertz and General Gompertz model. Several models provide a good fit to tumor volume measurements, with the Gompertz model providing the best balance between goodness of fit and number of parameters. Similarly, when fitting to early treatment data, the general Bertalanffy and Gompertz models yield the lowest mean absolute error to forecasted data, indicating that these models could potentially be effective at predicting treatment outcome. In summary, we provide a quantitative benchmark for classical textbook models and state-of-the art models of human tumor growth. We publicly release an anonymized version of our original data, providing the first benchmark set of human tumor growth data for evaluation of mathematical models.

Mathematical oncology uses quantitative models for prediction of tumor growth and treatment response. The theoretical foundation of mathematical oncology is provided by six classical mathematical models: the Exponential, Logistic, Classic Bertalanffy, General Bertalanffy, Classic Gompertz and General Gompertz model. These models have been introduced decades ago, have been used in thousands of scientific articles and are part of textbooks and curricula in mathematical oncology. However, these models have not been systematically tested in clinical data from actual patients. In this study, we have collected quantitative tumor volume measurements from thousands of patients in five large clinical trials of cancer immunotherapy. We use this dataset to systematically investigate how accurately mathematical models can describe tumor growth, showing that there are pronounced differences between models. In addition, we show that two of these models can predict tumor response to immunotherapy and chemotherapy at later time points when trained on early tumor growth dynamics. Thus, our article closes a conceptual gap in the literature and at the same time provides a simple tool to predict response to chemotherapy and immunotherapy on the level of individual patients.

The efficacy of immune checkpoint inhibitors in thoracic malignancies

The advent of immune checkpoint inhibitors (ICIs) has rapidly transformed the treatment paradigm for multiple cancer types, including thoracic malignancies. In advanced non-small cell lung cancer (NSCLC), ICIs have shifted treatment paradigm and improved overall survival reaching almost one-third of patients alive at 5 years. ICIs therapies have also modified the therapeutic strategy in first-line setting in metastatic small-cell lung cancer (SCLC) patients as well as in malignant pleural mesothelioma (MPM) improving the overall survival compared with standard treatment. This phenomenon is of huge relevance as both SCLC and MPM were considered orphan diseases without any significant improvement in the therapeutic strategy in the first-line setting during the last 15 years. In this review, we aim to review the efficacy of ICI in thoracic malignancies either in monotherapy or in combination, according to predictive biomarkers, and to the US Food and Drug Administration and the European Medicines Agency approvals of treatment strategies. We address the efficacy of these agents, especially in NSCLC according to PD-L1 expression and histologic subtype.

Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study

Background

Non-proportional hazards are common with time-to-event data but the majority of randomised clinical trials (RCTs) are designed and analysed using approaches which assume the treatment effect follows proportional hazards (PH). Recent advances in oncology treatments have identified two forms of non-PH of particular importance - a time lag until treatment becomes effective, and an early effect of treatment that ceases after a period of time. In sample size calculations for treatment effects on time-to-event outcomes where information is based on the number of events rather than the number of participants, there is crucial importance in correct specification of the baseline hazard rate amongst other considerations. Under PH, the shape of the baseline hazard has no effect on the resultant power and magnitude of treatment effects using standard analytical approaches. However, in a non-PH context the appropriateness of analytical approaches can depend on the shape of the underlying hazard.

Methods

A simulation study was undertaken to assess the impact of clinically plausible non-constant baseline hazard rates on the power, magnitude and coverage of commonly utilized regression-based measures of treatment effect and tests of survival curve difference for these two forms of non-PH used in RCTs with time-to-event outcomes.

Results

In the presence of even mild departures from PH, the power, average treatment effect size and coverage were adversely affected. Depending on the nature of the non-proportionality, non-constant event rates could further exacerbate or somewhat ameliorate the losses in power, treatment effect magnitude and coverage observed. No single summary measure of treatment effect was able to adequately describe the full extent of a potentially time-limited treatment benefit whilst maintaining power at nominal levels.

Conclusions

Our results show the increased importance of considering plausible potentially non-constant event rates when non-proportionality of treatment effects could be anticipated. In planning clinical trials with the potential for non-PH, even modest departures from an assumed constant baseline hazard could appreciably impact the power to detect treatment effects depending on the nature of the non-PH. Comprehensive analysis plans may be required to accommodate the description of time-dependent treatment effects.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01372-0.

Real-world treatment patterns and outcomes in PD-L1-positive non-small cell lung cancer

Aim: We report real-world treatment patterns and outcomes in patients with PD-L1+ non-small cell lung cancer (NSCLC). Methods: This retrospective, observational study using the ConcertAI Oncology Dataset (Symphony AI, CA, USA), included patients with PD-L1+ (≥1% expression) metastatic NSCLC who began first-line (1L) treatment between 2016 and 2019. Treatment outcomes were assessed by treatment class (immune checkpoint inhibitor [ICI] monotherapy, ICI combinations or chemotherapy). Results: In total, 128 (25.5%), 237 (47.3%) and 136 patients (27.1%) received 1L chemotherapy, 1L ICI monotherapy and 1L ICI combinations, respectively. ICI combinations and monotherapy had improved clinical outcomes versus chemotherapy. Adjusted analyses showed no significant difference in outcome between ICI monotherapy and ICI combinations. Conclusion: ICI-based treatments are being increasingly adopted into clinical practice and were associated with better outcomes versus chemotherapy.

Safety, Efficacy, and Pharmacodynamics of Tremelimumab Plus Durvalumab for Patients With Unresectable Hepatocellular Carcinoma: Randomized Expansion of a Phase I/II Study

This phase I/II study evaluated tremelimumab (anticytotoxic T-lymphocyte–associated antigen-4 monoclonal antibody) and durvalumab (antiprogrammed death ligand-1 monoclonal antibody) as monotherapies and in combination for patients with unresectable hepatocellular carcinoma (HCC), including a novel regimen featuring a single, priming dose of tremelimumab (ClinicalTrials.gov identifier: NCT02519348).

Window mean survival time

We propose a class of alternative estimates and tests to restricted mean survival time (RMST) which improves power in numerous survival scenarios while maintaining a level of interpretability. The industry standards for interpretable hypothesis tests in survival analysis, RMST and logrank tests (LRTs), can suffer from low power in cases where the proportional hazards assumption fails. In particular, when late differences occur between survival curves, our proposed estimate and class of tests, window mean survival time (WMST), outperforms both RMST and LRT without sacrificing interpretability, unlike weighted rank tests (WRTs). WMST has the added advantage of maintaining high power when the proportional hazards assumption is met, while WRTs do not. With testing methods often being chosen in advance of data collection, WMST can ensure adequate power without distributional assumptions and is robust to the choice of its restriction parameters. Functions for performing WMST analysis are provided in the survWM2 package in R.

Immune checkpoint inhibitors in oncogene-addicted non-small cell lung cancer: a systematic review and meta-analysis

BACKGROUND

Treatment of oncogene-addicted non-small cell lung cancer (NSCLC) has been changed by the advent of tyrosine kinase inhibitors (TKIs). Albeit great benefits are achieved with target therapies, resistance invariably occurs and recourse to alternative treatments is unavoidable. Immune checkpoint inhibitors (ICIs) role and the best setting of immunotherapy administration in oncogene-driven NSCLC are matter of debate.

METHODS

We performed a systematic literature review through PubMed, in order to gather all the available information regarding ICI activity and efficacy in oncogene-addicted NSCLC, from both prospective trials and retrospective series. A meta-analysis of objective response rate in different molecular subgroups was provided. Combinatorial strategies including ICIs and related toxicities were also recorded.

RESULTS

Eighty-seven studies were included in the qualitative analysis. EGFR mutation may be a biomarker of poor response to single-agent ICIs (7% of EGFR-mutant NSCLC patients achieved disease response in prospective trials), while encouraging results have been shown with combination strategies. KRAS-mutated disease (response rate, RR, 22%) has different clinical and pathological characteristics, and the co-existence of additional mutations (e.g., STK11 or TP53) influence tumor microenvironment and response to immunotherapy. Other molecular alterations have been marginally considered prospectively, and data from clinical practice are variegated, given poor effectiveness of ICIs in ALK-rearranged disease (RR 9.5%, pooling the data of retrospective studies) or some encouraging results in BRAF-(RR 25%, retrospective data) or MET-driven one (with estimations conditioned by the presence of both exon 14 skipping mutations and gene amplification in reported series).

CONCLUSIONS

In oncogene-addicted NSCLC (with the exception of KRAS-mutated), ICIs are usually administered at the failure of other treatment options, but administering single-agent immunotherapy in later disease phases may limit its efficacy. With the progressive administration of TKIs and ICIs in early-stage disease, molecular characterization will become fundamental in this setting.

First-line immunotherapy in non-small cell lung cancer patients with poor performance status: a systematic review and meta-analysis

BACKGROUND

Immune checkpoint inhibitors (ICIs) have become the standard of care for the first-line treatment of advanced non-small cell lung cancer patients (NSCLC), either as single agents or combined with chemotherapy. The evidence sustaining their role for poor performance status (ECOG PS ≥2) patients is limited.

METHODS

We search PubMed and the proceedings of international oncology meetings to perform a systematic review to assess the outcomes poor PS NSCLC patients who received ICIs as first-line treatment. A meta-analysis included retrospective studies focusing on pembrolizumab monotherapy in PD-L1 ≥50% NSCLC. We reported the global objective response rate (ORR), disease control rate (DCR) and landmark progression-free and overall survival (PFS and OS, respectively) in ECOG PS ≥2 and 0-1 patients, respectively.

RESULTS

Forty-one studies were included in the systematic review. Thirty-two retrospective studies focused on pembrolizumab monotherapy in PD-L1 ≥50% cases. In total, 1,030 out of 5,357 (19%) of patients across 30 studies presented with a PS ≥2 at pembrolizumab initiation. In 18 studies with detailed clinical information, worse outcomes in poor PS compared to good PS patients were documented. The meta-analysis revealed that ORR and DCR within the PS ≥2 patient population were 30.9% and 41.5% respectively (55.2% and 71.5% in PS 0-1 patients). The rates of PFS (at 3, 6, 12 and 18 months) and OS (at 6, 12, 18 and 24 months) were approximately double in the good PS compared to the poor PS group of patients. In the three prospective trials where of ICIs in PS 2 populations, the diverse strictness in PS definition likely contributed to the differential outcomes observed. Six retrospective studies dealt with chemo-immunotherapy combinations.

CONCLUSIONS

Still with limited prospective evidence sustaining the role of immunotherapy in previously untreated NSCLC with poor PS, 19% of patients in retrospective series dealing with pembrolizumab in PD-L1 ≥50% tumors had an ECOG PS ≥2. Clinical effort encompassing the definition of poor PS, of the factors conditioning it, and the development of dedicated treatment strategies is required to improve the outcomes in this patient population.

Novel patterns of progression upon immunotherapy in other thoracic malignancies and uncommon populations

In the immunotherapy era, considering the prolonged survival benefit and responses observed with immunecheckpoint inhibitors (ICI) in many cancer types, the identification of patients with rapid progression (PD) and deaths upon ICI has found some skepticism and resistance among the scientific community. Nevertheless, an acceleration of tumour during ICI, defined as hyperprogressive disease (HPD), has been recognized across different cancer types and evidence regarding rapid PDs and deaths are emerging in patients with malignant pleural mesothelioma (MPM), small cell lung cancer (SCLC) and thymic malignancies and in uncommon non-small cell lung cancer (NSCLC) populations. Of note, PD and early deaths (ED) rates upon single agent ICI were up to 60% and 30% in MPM and 70% and 38% in SCLC patients, respectively. Similarly, rapid PDs and deaths were observed in clinical trials and retrospective studies including patients with poor performance status (PS), HIV infection and rare NSCLC histologies. Atypical patterns of response, such as pseudoprogression (PsPD) may also occur in other thoracic malignancies (MPM) and in some uncommon populations (i.e., HIV patients), however probably at lower rate compared to HPD. The characterizations of HPD and PsPD mechanisms and the identification of common definition criteria are the next future challenges in this area of cancer research.

What Did Time Tell Us? A Comparison and Retrospective Validation of Different Survival Extrapolation Methods for Immuno-Oncologic Therapy in Advanced or Metastatic Renal Cell Carcinoma

BACKGROUND

The immuno-oncologic (IO) mechanism of action may lead to an overall survival (OS) hazard that changes over time, producing shapes that standard parametric extrapolation methods may struggle to reflect. Furthermore, selection of the most appropriate extrapolation method for health technology assessment is often based on trial data with limited follow-up.

OBJECTIVE

To examine this problem, we fitted a range of extrapolation methods to patient-level survival data from CheckMate 025 (NCT01668784, CM-025), a phase III trial comparing nivolumab with everolimus for previously treated advanced renal cell carcinoma (aRCC), to assess their predictive accuracy over time.

METHODS

Six extrapolation methods were examined: standard parametric models, natural cubic splines, piecewise models combining Kaplan-Meier data with an exponential or non-exponential distribution, response-based landmark models, and parametric mixture models. We produced three database locks (DBLs) at minimum follow-ups of 15, 27, and 39 months to align with previously published CM-025 data. A three-step evaluation process was adopted: (1) selection of the distribution family for each method in each of the three DBLs, (2) internal validation comparing extrapolation-based landmark and mean survival with the latest CM-025 dataset (minimum follow-up, 64 months), and (3) external validation of survival projections using clinical expert opinion and long-term follow-up data from other nivolumab studies in aRCC (CheckMate 003 and CheckMate 010).

RESULTS

All extrapolation methods, with the exception of mixture models, underestimated landmark and mean OS for nivolumab compared with CM-025 long-term follow-up data. OS estimates for everolimus tended to be more accurate, with four of the six methods providing landmark OS estimates within the 95% confidence interval of observed OS as per the latest dataset. The predictive accuracy of survival extrapolation methods fitted to nivolumab also showed greater variation than for everolimus. The proportional hazards assumption held for all DBLs, and a dependent log-logistic model provided reliable estimates of longer-term survival for both nivolumab and everolimus across the DBLs. Although mixture models and response-based landmark models provided reasonable estimates of OS based on the 39-month DBL, this was not the case for the two earlier DBLs. The piecewise exponential models consistently underestimated OS for both nivolumab and everolimus at clinically meaningful pre-specified landmark time points.

CONCLUSIONS

This aRCC case study identified marked differences in the predictive accuracy of survival extrapolation methods for nivolumab but less so for everolimus. The dependent log-logistic model did not suffer from overfitting to early DBLs to the same extent as more complex methods. Methods that provide more degrees of freedom may accurately represent survival for IO therapy, particularly if data are more mature or external data are available to inform the long-term extrapolations.

Diagnosis, grading and management of toxicities from immunotherapies in children, adolescents and young adults with cancer

Cancer immunotherapies are associated with remarkable therapeutic response rates but also with unique and severe toxicities, which potentially result in rapid deterioration in health. The number of clinical applications for novel immune effector-cell therapies, including chimeric antigen receptor (CAR)-expressing cells, and other immunotherapies, such as immune-checkpoint inhibitors, is increasing. In this Consensus Statement, members of the Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network Hematopoietic Cell Transplantation-Cancer Immunotherapy (HCT-CI) Subgroup, Paediatric Diseases Working Party (PDWP) of the European Society of Blood and Marrow Transplantation (EBMT), Supportive Care Committee of the Pediatric Transplantation and Cellular Therapy Consortium (PTCTC) and MD Anderson Cancer Center CAR T Cell Therapy-Associated Toxicity (CARTOX) Program collaborated to provide updated comprehensive recommendations for the care of children, adolescents and young adults receiving cancer immunotherapies. With these recommendations, we address emerging toxicity mitigation strategies, we advocate for the characterization of baseline organ function according to age and discipline-specific criteria, we recommend early critical care assessment when indicated, with consideration of reversibility of underlying pathology (instead of organ failure scores) to guide critical care interventions, and we call for researchers, regulatory agencies and sponsors to support and facilitate early inclusion of young patients with cancer in well-designed clinical trials.

Characterizing tumor shrinkage as a measure of clinical benefit for immune checkpoint inhibitors

BACKGROUND

We explored whether the effectiveness of immune checkpoint inhibitors (ICIs) can be characterized by incorporating a composite of duration of response (DOR) to complement traditional Response Evaluation Criteria in Solid Tumors (RECIST) criteria for objective response rate (ORR) in an intent-to-treat (ITT) population. Furthermore, the correlation of this novel endpoint, characterized by the restricted mean time in response (RMTR), with overall survival (OS) will be examined.

METHODS

We analyzed ORR alone or in combination with DOR (RMTR) in available phase I, II, and III trials evaluating nivolumab monotherapy or in combination with ipilimumab across solid tumor types. ORR was evaluated per RECIST V.1.1. DOR was estimated using individual patient data in ITT populations regardless of RECIST response, with non-responders imputed as zero. Associations between ORR alone or RMTR and OS were evaluated in the ITT population. DOR curves were generated using the Kaplan-Meier product limit method, and 6-month RMTR, a measure of response durability, was derived from the area under the curves. For ORR and RMTR in the ITT population, the strength of association with OS was analyzed using Pearson correlation coefficients (r).

RESULTS

Nivolumab treatment was associated with longer response durations than active control in responder and ITT populations. Similarly, ORR and RMTR were both significantly correlated with OS (ORR vs OS: r=0.684, p=0.02; RMTR vs OS: r=0.695, p=0.018).

CONCLUSIONS

Combining ORR and DOR (RMTR) to objectively characterize tumor shrinkage in an ITT patient population is a novel approach that appears to correlate well with OS in patients treated with nivolumab monotherapy or in combination with ipilimumab. This endpoint may provide a more complete characterization of tumor shrinkage to incorporate into the design of future ICI clinical trials. However, confirmation of this approach will require further research.

Addressing resistance to immune checkpoint inhibitor therapy: an urgent unmet need

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of various cancers by reversing the immunosuppressive mechanisms employed by tumors to restore anticancer immunity. Although ICIs have demonstrated substantial clinical efficacy, patient response can vary in depth and duration, and many do not respond at all or eventually develop resistance. ICI resistance mechanisms can be tumor-intrinsic, related to the tumor microenvironment or patient-specific factors. Multiple resistance mechanisms may be present within one tumor subtype, or heterogeneity exists among patients with the same tumor type. Consequently, designing effective combination treatment strategies is challenging. This review will discuss ICI resistance mechanisms, and summarize findings from key preclinical and clinical trials of ICIs, to identify potential treatment strategies or pathways to overcome ICI resistance.

Progression-Free Survival Early Assessment Is a Robust Surrogate Endpoint of Overall Survival in Immunotherapy Trials of Hepatocellular Carcinoma

BACKGROUND

Radiology-based outcomes, such as progression-free survival (PFS) and objective response rate (ORR), are used as surrogate endpoints in oncology trials. We aimed to assess the surrogacy relationship of PFS with overall survival (OS) in clinical trials of systemic therapies targeting advanced hepatocellular carcinoma (HCC) by novel meta-regression methods.

METHODS

A search of databases (PubMed, American Society of Clinical Oncology (ASCO), and European Society for Medical Oncology (ESMO) Meeting Libraries, Clinicaltrials.gov) for trials of systemic therapies for advanced HCC reporting both OS and PFS was performed. Individual patient data were extracted from PFS and OS Kaplan-Meier curves. Summary median PFS and OS data were obtained from random-effect model. The surrogate relationships of median PFS, first quartile (Q1), third quartile (Q3), and restricted mean survival time (RMST) for OS were evaluated by the coefficient of determination R². Heterogeneity was explored by meta-regression.

RESULTS

We identified 49 trials, 11 assessing immune-checkpoint inhibitors (ICIs) and 38 multikinase inhibitors (MKIs). Overall, the correlation between median PFS and median OS was weak (R² = 0.20. 95% Confidence Intervals [CI]-0.02;0.42). Surrogacy robustness varied between treatment classes and PFS endpoints. In ICI trials only, the correlations between Q1-PFS and Q1-OS and between 12-month PFS-RMST and 12-month OS-RMST were high (R² = 0.89, 95%CI 0.78-0.98, and 0.80, 95% CI 0.63-0.96, respectively). Interaction p-values obtained by meta-regression confirmed the robustness of results.

CONCLUSIONS

In trials of systemic therapies for advanced HCC, the surrogate relationship of PFS with OS is highly variable depending on treatment class (ICI or MKI) and evaluation time-point. In ICI trials, Q1-PFS and 12-month PFS-RMST are robust surrogate endpoints for OS.

Salvage systemic therapy for advanced gastric and oesophago-gastric junction adenocarcinoma

BACKGROUND

Salvage systemic therapy has become the new standard of care in patients with advanced gastric and oesophago-gastric junction (OGJ) adenocarcinoma, following disease progression on first-line fluoropyrimidine and platinum-containing chemotherapy. Pharmacological agents proven to be effective in this setting include both chemotherapy and biological therapy, however, the consensus on the best salvage systemic therapy has not been reached.

OBJECTIVES

To assess the effects of systemic chemotherapy and biological therapy, either alone or in combination, on overall survival (OS) and progression-free survival (PFS) in patients with advanced gastric and OGJ adenocarcinoma, whose disease has progressed on, or relapsed after first-line fluoropyrimidine and platinum-containing chemotherapy. Adverse events (AEs), tumour response rate (TRR) and quality of life (QoL) associated with systemic chemotherapy and/or biological therapy were additionally assessed.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, trial registries and proceedings of the major oncology conferences up to October 2020. We additionally handsearched the reference lists of studies. No language restriction was applied.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) comparing salvage systemic therapy (chemotherapy and/or biological therapy) and either another type of salvage systemic therapy, placebo, best supportive care (BSC) or no treatment in patients with gastric and OGJ adenocarcinoma refractory to first-line fluoropyrimidine and platinum-containing chemotherapy.

DATA COLLECTION AND ANALYSIS

Two review authors independently performed selection of eligible studies and the primary author extracted study characteristics and outcome data from included studies. We assessed the quality and risk of bias of eligible studies according to the Cochrane Handbook for Systematic Reviews of Interventions. We expressed pooled estimates of effect using hazard ratio (HR) calculated using an inverse variance random-effects model for time-to-event data, and risk ratio (RR) calculated using Mantel-Haenszel random-effects model for binary data. The certainty of evidence was graded using GRADEpro.

MAIN RESULTS

We identified 17 RCTs with 5110 participants for inclusion in this review. Tweenty-nine studies are ongoing and twenty studies are awaiting classification. No studies examined the following comparisons: chemotherapy combined with biological therapy versus placebo, BSC or no treatment, chemotherapy combined with biological therapy versus biological therapy, biological therapy versus biological therapy and chemotherapy combined with biological therapy versus chemotherapy combined with biological therapy. Chemotherapy versus placebo, best supportive care or no treatment Chemotherapy probably improves OS (HR = 0.66, 95% CI 0.52 to 0.83, moderate-certainty evidence) based on two studies involving 547 participants and improves PFS (HR = 0.57, 95% CI 0.47 to 0.69, high-certainty evidence) based on one study involving 507 participants over placebo and BSC. Chemotherapy probably increases serious AEs (SAEs) (RR = 1.38, 95% CI 1.20 to 1.59, moderate-certainty evidence) based on one study involving 503 participants. Biological therapy versus placebo, best supportive care or no treatment Biological therapy improves OS (HR = 0.55, 95% CI 0.41 to 0.73, high-certainty evidence) and probably improves PFS (HR = 0.33, 95% CI 0.19 to 0.57, moderate-certainty evidence) over placebo based on three studies involving 781 participants. There is currently insufficient evidence for increased SAEs from biological therapy (RR = 1.14, 95% CI 0.95 to 1.37, low-certainty evidence) based on two studies involving 638 participants. Chemotherapy versus biological therapy This comparison only considered immunotherapy. There is probably no evidence of a difference for OS (HR = 0.82, 95% CI 0.66 to 1.02, moderate-certainty evidence) between chemotherapy and immunotherapy, and immunotherapy probably reduces PFS (HR = 1.27, 95% CI 1.03 to 1.57, moderate-certainty evidence) based on one study involving 395 participants. SAEs may be less frequent with immunotherapy compared to chemotherapy (RR = 0.41, 95% CI 0.30 to 0.57, low-certainty evidence). Chemotherapy combined with biological therapy versus chemotherapy Addition of biological therapy to chemotherapy probably does not improve OS (HR = 0.93, 95% CI 0.83 to 1.04, moderate-certainty evidence) and we are uncertain whether it improves PFS (HR = 0.87, 95% CI 0.74 to 1.02, very low-certainty evidence) based on seven studies involving 2743 participants. We are similarly uncertain whether combined chemotherapy and biological therapy increases SAEs (RR = 1.17, 95% CI 0.95 to 1.44, very low-certainty evidence) based on four studies involving 1618 participants. Chemotherapy versus chemotherapy There is no evidence of a difference for OS and PFS between irinotecan and paclitaxel (HR = 1.13, 95% CI 0.86 to 1.48, low-certainty evidence for OS; HR = 1.14, 95% CI 0.88 to 1.48, low-certainty evidence for PFS) based on one study involving 219 participants. Similarly, there is no evidence to indicate improved OS and PFS from addition of another chemotherapy to docetaxel (HR = 1.05, 95% CI 0.72 to 1.54, low-certainty evidence for OS; HR = 0.75, 95% CI 0.52 to 1.09, low-certainty evidence for PFS) based on two studies involving 121 participants. Grade ≥ 3 neutropenia occurred commonly with both mono- and poly-chemotherapy except for docetaxel-S1 and EOX chemotherapy.

AUTHORS' CONCLUSIONS

Survival outcome of patients with advanced gastric and OGJ adenocarcinoma whose disease progressed on first-line fluoropyrimidine and platinum-containing chemotherapy can be improved by chemotherapy and biological therapy. Biological therapy, in particular, achieves this without clear increase in SAEs or QoL impairment. Whether biological therapy is preferred over chemotherapy is still unclear and there is no evidence of a difference for OS outcome, although immunotherapy may be associated with less SAEs. Addition of biological therapy to chemotherapy and poly-chemotherapy are associated with frequent treatment-related toxicity without clear survival benefit.

Real-World, Long-Term Outcomes of Nivolumab Therapy for Recurrent or Metastatic Squamous Cell Carcinoma of the Head and Neck and Impact of the Magnitude of Best Overall Response: A Retrospective Multicenter Study of 88 Patients

Simple Summary

No real-world, long-term outcomes of immunotherapy with nivolumab for recurrent or metastatic squamous cell carcinoma of the head and neck (R/M SCCHN) have yet been reported. Furthermore, the prognostic impact of the best overall response (BOR) of this therapy remains unclear. We conducted a multi-institutional cohort study of the long-term efficacy and safety of this therapy. We also evaluated the relationship between BOR and survival. Median follow-up time was 25.9 months. Median overall survival (OS) was 9.6 months, and two-year survival rate was 25.0%. Overall response rate was 18%, and disease control rate was 48%. For immune-related adverse events (irAEs), 38 irAEs were detected in 29 patients. The development of irAEs and better BOR were significantly associated with longer survival. These findings demonstrate the long-term efficacy and safety of nivolumab therapy for R/M SCCHN in a real-world setting. The magnitude of BOR and the development of irAEs might be useful surrogate markers of survival.

Abstract

No real-world, long-term outcomes of immunotherapy with nivolumab for recurrent or metastatic squamous cell carcinoma of the head and neck (R/M SCCHN) have yet been reported. Furthermore, the prognostic impact of the best overall response (BOR) of this therapy remains unclear. We conducted a multi-institutional cohort study of the long-term efficacy and safety of this therapy and investigated prognostic factors associated with survival. Further, we evaluated the relationship between BOR and survival. Median follow-up time was 25.9 months. Median overall survival (OS) was 9.6 months, and two-year survival rate was 25.0%. Median progression-free survival (PFS) was 3.7 months, and two-year PFS rate was 19.6%. BOR was assessed as complete response (CR) in 6%, partial response (PR) in 13%, stable disease (SD) in 30%, and progressive disease (PD) in 52% of the patients. Overall response rate was 18%, and disease control rate was 48%. For immune-related adverse events (irAEs), 38 irAEs were detected in 29 patients. On multivariate analysis, the development of irAEs was significantly associated with better OS and PFS. Better BOR was significantly associated with longer OS and PFS. These findings demonstrate the long-term efficacy and safety of nivolumab therapy for R/M SCCHN in a real-world setting. The magnitude of BOR and the development of irAEs might be useful surrogate markers of survival.

Meta-Analysis of PD-L1 Expression As a Predictor of Survival After Checkpoint Blockade

PURPOSE

Programmed cell death receptor ligand 1 (PD-L1) expression is the most studied biomarker to predict the efficacy of immune checkpoint inhibitors (ICIs), but its clinical significance is controversial. We estimated the distribution of PD-L1 expression scores (ie, tumor proportion score or combined proportion score) and the relationship between PD-L1 levels and ICIs’ impact on overall survival (OS).

METHODS

We reconstructed, pooled, and analyzed individual-level data on 7,617 patients with cancer from 14 randomized clinical trials. The effects of ICIs were quantified using differences in 24-month restricted mean survival times (ΔRMSTs; ie, the increase in life expectancy truncated at 2 years associated with ICI therapy). In a simulation study, we compared standard randomized clinical trial designs with a trial design that leverages meta-analytic results like ours.

RESULTS

Approximately 93% of patients had a PD-L1 expression ≤ 5% (66% of patients) or > 50% (27% of patients). OS improves with ICIs regardless of PD-L1 expression level, which predicts the benefits’ magnitude. For patients with non–small-cell lung cancer (NSCLC), ΔRMSTs ranged from 1.4 months (95% probability interval [PI], 0.7 to 2.2 months) for PD-L1 expression ≤ 1% to 4.1 months (95% PI, 3.2 to 5.2 months) for PD-L1 expression > 80%. For patients with non-NSCLC tumors, ΔRMSTs ranged from 0.8 months (95% PI, −0.1 to 1.7 months) to 2.3 months (95% PI, 1.3 to 4.4 months), again for PD-L1 expression levels of ≤ 1% and > 80%, respectively. Simulations suggested that designs tailored to meta-analytic results can detect the effects of ICIs in PD-L1 subgroups with higher probability (> 15%) than standard designs.

CONCLUSION

The practice of dichotomizing the range of PD-L1 expression scores is inadequate for patient stratification. Meta-analytic estimates of the distribution of PD-L1 scores and subgroup-specific treatment effects can improve the designs of future trials of ICIs.

Evolving use of real-world evidence in the regulatory process: a focus on immuno-oncology treatment and outcomes

In recent years, regulatory bodies have increasingly recognized the utility of real-world evidence (RWE) for supplementing and supporting clinical trial data in new drug applications. Nevertheless, the integration of RWE into established regulatory processes is complex and the generation of 'regulatory-grade' real-world data faces operational, methodological, data-related and policy-related challenges. In parallel with this evolving role for RWE, immuno-oncology therapies have emerged as leading cancer treatments and are expected to continue to play a central role in the future. In this article, we review the current literature on the use of RWE for regulatory submissions, with a focus on novel anticancer immunotherapies, and discuss the utility and current limitations of RWE in the context of drug development and regulatory approvals.

Adding PD-1/PD-L1 Inhibitors to Chemotherapy for the First-Line Treatment of Extensive Stage Small Cell Lung Cancer (SCLC): A Meta-Analysis of Randomized Trials

Simple Summary

Treatment strategies in advanced, metastatic small cell lung cancer have been recently implemented by the combination of chemotherapy and immunotherapy. Nevertheless, the magnitude of survival benefit observed in clinical trials does not reproduce the major improvements observed in non-small cell lung cancer and other malignant diseases. By performing a systematic review and gathering the available data in a meta-analysis, we aim to compare the outcomes of patients treated with standard chemotherapy alone or with PD-1/PD-L1 inhibitors immunotherapy across clinical trials, in order to sustain treatment decisions. The addition of PD-1/PD-L1 inhibitors to standard chemotherapy improves all activity and efficacy outcomes, with a manageable safety profile. The benefit in overall survival is more evident if considering long-term analysis, compared to median estimations.

Abstract

Survival outcomes in extensive-stage small cell lung cancer (ES SCLC) are dismal, with median overall survival (OS) less than 12 months. The combination of PD-1/PD-L1 immune checkpoint inhibitors (ICIs) with first-line platinum-etoposide chemotherapy has been recently evaluated in randomized clinical trials. We performed a systematic literature review through PubMed and conference proceedings. Randomized trials evaluating chemotherapy +/− PD-1/PD-L1 ICIs were included in the meta-analysis. Efficacy (OS), activity [progression-free survival (PFS) and objective response rate (ORR)] outcomes and toxicities were analyzed. For selected endpoints, we focused on patients’ subgroups (OS) and on landmark analyses (OS, PFS). Four randomized trials were identified; globally, 1553 patients were randomized to receive chemotherapy +/− PD-1/PD-L1 ICIs. Adding a PD-1/PD-L1 ICI to chemotherapy led to a significant benefit in OS [hazard ratio (HR) 0.76, 95% confidence interval (CI) 0.68–0.85, p < 0.00001), PFS [HR 0.75, 95% CI 0.68–0.84, p < 0.00001] and ORR [odds ratio 1.28, 95% CI 1.04–1.57, p = 0.02]. No unexpected toxicity emerged. At 12, 18, 24 months for OS, and at 12, 18 months for PFS, experimental arms retained significant improvement in event-free rates, with absolute gain of approximately 10% compared with standard treatment. Albeit the magnitude of the benefit is less impacting compared to other settings of immunotherapy, the addition of PD-1/PD-L1 ICIs to chemotherapy in ES SCLC provided significant improvements in survival outcomes with the known toxicity profile. Biomarkers predicting which patients are suitable to derive long-term benefits are eagerly awaited.

A Review of the Mechanisms and Clinical Implications of Precision Cancer Therapy-Related Toxicity: A Primer for the Radiologist

OBJECTIVE. The purpose of this review is to elucidate the mechanisms, types, and clinical significance of molecular targeted therapy (MTT) and immune checkpoint inhibitors (ICIs) and their related toxicity, emphasizing the radiologic manifestations. CONCLUSION. The related toxicities of MTT and ICIs can have acute, recurrent, chronic, and delayed presentations. These toxicities may serve as markers of response and survival. By understanding the clinical significance of drug toxicities, radiologists can play an important role in personalized cancer therapy.

Immunotherapy for Early Stage Colorectal Cancer: A Glance into the Future

Immune checkpoint inhibitors (ICI) have reshaped therapeutic strategies for cancer patients. The development of ICI for early stage colorectal cancer is accompanied by specific challenges: (i) the selection of patients who are likely to benefit from these treatments, i.e., patients with tumors harboring predictive factors of efficacy of ICI, such as microsatellite instability and/or mismatch repair deficiency (MSI/dMMR), or other potential parameters (increased T cell infiltration using Immunoscore® or others, high tumor mutational burden, POLE mutation), (ii) the selection of patients at risk of disease recurrence (poor prognostic features), and (iii) the choice of an accurate clinical trial methodological framework. In this review, we will discuss the ins and outs of clinical research of ICI for early stage MSI/dMMR CC patients in adjuvant and neoadjuvant settings. We will then summarize data that might support the development of ICI in localized colorectal cancer beyond MSI/dMMR.

Current challenges for assessing the long-term clinical benefit of cancer immunotherapy: a multi-stakeholder perspective

Immuno-oncologics (IOs) differ from chemotherapies as they prime the patient's immune system to attack the tumor, rather than directly destroying cancer cells. The IO mechanism of action leads to durable responses and prolonged survival in some patients. However, providing robust evidence of the long-term benefits of IOs at health technology assessment (HTA) submission presents several challenges for manufacturers. The aim of this article was to identify, analyze, categorize, and further explore the key challenges that regulators, HTA agencies, and payers commonly encounter when assessing the long-term benefits of IO therapies. Insights were obtained from an international, multi-stakeholder steering committee (SC) and expert panels comprising of payers, economists, and clinicians. The selected individuals were tasked with developing a summary of challenges specific to IOs in demonstrating their long-term benefits at HTA submission. The SC and expert panels agreed that standard methods used to assess the long-term benefit of anticancer drugs may have limitations for IO therapies. Three key areas of challenges were identified: (1) lack of a disease model that fully captures the mechanism of action and subsequent patient responses; (2) estimation of longer-term outcomes, including a lack of agreement on ideal methods of survival analyses and extrapolation of survival curves; and (3) data limitations at the time of HTA submission, for which surrogate survival end points and real-world evidence could prove useful. A summary of the key challenges facing manufacturers when submitting evidence at HTA submission was developed, along with further recommendations for manufacturers in what evidence to produce. Despite almost a decade of use, there remain significant challenges around how best to demonstrate the long-term benefit of checkpoint inhibitor-based IOs to HTA agencies, clinicians, and payers. Manufacturers can potentially meet or mitigate these challenges with a focus on strengthening survival analysis methodology. Approaches to doing this include identifying reliable biomarkers, intermediate and surrogate end points, and the use of real-world data to inform and validate long-term survival projections. Wider education across all stakeholders-manufacturers, payers, and clinicians-in considering the long-term survival benefit with IOs is also important.

Hyperprogression Under Immune Checkpoint-Based Immunotherapy-Current Understanding, The Role of PD-1/PD-L1 Tumour-Intrinsic Signalling, Future Directions and a Potential Large Animal Model

Immune evasion is a major challenge for the development of successful cancer treatments. One of the known mechanisms is the expression of immune checkpoints (ICs)-proteins regulating the immune cells activation. The advent of immunotherapy using monoclonal antibodies (mAbs) to block the immune checkpoint receptor-ligand interaction brought about a landslide improvement in the treatment responses, leading to a prompt approval of such therapeutics. In recent years, it was discovered that a subset of patients receiving IC blockade treatment experienced a previously unknown pattern of treatment response called hyperprogression (HP), characterised by rapid deterioration on initialisation of the therapy. HP represents an urgent issue for clinicians and drug developers, while posing questions about the adequacy of the current clinical trial process. Here, we briefly summarise the state of knowledge and propose new directions for research into HP mechanisms, focusing on tumour-intrinsic signalling of IC proteins malignantly expressed by cancer. We also discuss the potential role of spontaneously occurring canine cancer in the assessment of immunotherapeutics, which can provide the missing link between murine and human studies.

Dramatic Response of Leptomeningeal Carcinomatosis to Nivolumab in PD-L1 Highly Expressive Non-small Cell Lung Cancer: A Case Report

In a patient who had been diagnosed of located squamous cell lung carcinoma, pneumonectomy, and adjuvant chemotherapy were performed. Brain recurrence and subsequent lung metastatic disease were uncontrolled by neurosurgery, holocranial radiotherapy, and first-line chemotherapy. In August 2015, appearance of leptomeningeal carcinomatosis triggered severe clinical deterioration and threatened the patient's life. Anti-PD1 immune checkpoint inhibitor Nivolumab was initiated in an attempt to stop tumor growth, achieving a spectacular brain and pulmonary complete response and clinical improvement, without serious adverse effects. High expression PD-L1 level (100%) was found in the pathological tissue sample. Nivolumab was maintained for more than 2 years and stopped in December 2017 after 28 months of treatment, with no disease evidence. More than 3 years after its onset, the patient maintains an outstanding PS with complete tumor response and no evidence of disease in last surveillance CT scan and brain MRI.

Comparison of Long-term Survival Benefits in Trials of Immune Checkpoint Inhibitor vs Non-Immune Checkpoint Inhibitor Anticancer Agents Using ASCO Value Framework and ESMO Magnitude of Clinical Benefit Scale

IMPORTANCE

Recently, anticancer agents have generated excitement owing to their capacity to preserve long-term durable survival in some patients who are represented by a tail of the survival curve. However, because traditional measures of clinical benefit may not accurately capture durable survival, amendments to various valuation frameworks have been proposed to capture this benefit.

OBJECTIVES

To determine how frequently immune checkpoint inhibitor (ICI) anticancer agents vs non-ICI anticancer agents displayed trends of long-term durable survival, as defined by the American Society of Clinical Oncology Value Framework version 2 (ASCO-VF v2) and European Society of Medical Oncology Magnitude of Clinical Benefit Scale version 1.1 (ESMO-MCBS v1.1), as well as to further analyze the degree of agreement between ASCO and ESMO frameworks.

DESIGN, SETTING, AND PARTICIPANTS

In this cohort study, anticancer agents from phase 2 or 3 randomized clinical trials (RCTs) cited for clinical efficacy evidence in drug approval by the US Food and Drug Administration between January 2011 and March 2018 were identified. Data required for the ASCO-VF v2 tail-of-the-curve bonus and the ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments were extracted from relevant RCTs. Frequency and difference in proportions were calculated to determine how often survival benefits were awarded to anticancer agents overall and to ICI and non-ICI anticancer agents individually.

MAIN OUTCOMES AND MEASURES

American Society of Clinical Oncology Value Framework v2 tail-of-the-curve bonuses and ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments.

RESULTS

In total, 247 RCTs were identified, and 100 RCTs involving 57 164 patients were included, with 14 examining ICI agents (1 ipilimumab, 5 pembrolizumab, 5 nivolumab, 2 atezolizumab, and 1 durvalumab) and 86 examining non-ICI agents (74 targeted therapy, 8 chemotherapy, 3 hormone therapy, and 1 radiopharmaceutical). Randomized clinical trials were awarded ASCO-VF v2 tail-of-the-curve bonuses more often than ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments (ASCO-VF v2, 45.0% [8 of 14 ICI RCTs and 37 of 86 non-ICI RCTs] vs ESMO-MCBS v1.1, 2.6% [1 of 12 ICI RCTs and 1 of 66 non-ICI RCTs). Randomized clinical trials for ICIs were not more likely to receive an ASCO-VF v2 bonus or ESMO-MCBS v1.1 adjustment than non-ICI RCTs (ASCO-VF: risk difference, 0.14; 95% CI, -0.14 to 0.42; P = .32; ESMO-MCBS: risk difference, 0.07; 95% CI, -0.09 to 0.23; P = .40). Poor agreement was found between the framework algorithms in identifying long-term survival benefits from RCTs (κ = 0.01; 95% CI, -0.23 to 0.22; P = .50).

CONCLUSIONS AND RELEVANCE

The ASCO-VF v2 and ESMO-MCBS v1.1 may require additional refinement to accurately capture the benefit of durable long-term survival, or ICI agents may not preserve long-term survival as conventionally thought.