Immune-checkpoint inhibitors and candidate surrogate endpoints for overall survival across tumour types: A systematic literature review

Time to strategy failure and treatment beyond progression in pretreated metastatic renal cell carcinoma patients receiving nivolumab: post-hoc analysis of the Meet-URO 15 study

Background

Immunotherapies exhibit peculiar cancer response patterns in contrast to chemotherapy and targeted therapy. Some patients experience disease response after initial progression or durable responses after treatment interruption. In clinical practice, immune checkpoint inhibitors may be continued after radiological progression if clinical benefit is observed. As a result, estimating progression-free survival (PFS) based on the first disease progression may not accurately reflect the actual benefit of immunotherapy.

Methods

The Meet-URO 15 study was a multicenter retrospective analysis of 571 pretreated metastatic renal cell carcinoma (mRCC) patients receiving nivolumab. Time to strategy failure (TSF) was defined as the interval from the start of immunotherapy to definitive disease progression or death. This post-hoc analysis compared TSF to PFS and assess the response and survival outcomes between patients treatated beyond progression (TBP) and non-TBP. Moreover, we evaluated the prognostic accuracy of the Meet-URO score versus the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) score based on TSF and PFS.

Results

Overall, 571 mRCC patients were included in the analysis. Median TSF was 8.6 months (95% CI: 7.0 - 10.1), while mPFS was 7.0 months (95% CI: 5.7 - 8.5). TBP patients (N = 93) had significantly longer TSF (16.3 vs 5.5 months; p < 0.001) and overall survival (OS) (34.8 vs 17.9 months; p < 0.001) but similar PFS compared to non-TBP patients. In TBP patients, a median delay of 9.6 months (range: 6.7-16.3) from the first to the definitive disease progression was observed, whereas non-TBP patients had overlapped median TSF and PFS (5.5 months). Moreover, TBP patients had a trend toward a higher overall response rate (33.3% vs 24.3%; p = 0.075) and disease control rate (61.3% vs 55.5%; p = 0.31). Finally, in the whole population the Meet-URO score outperformed the IMDC score in predicting both TSF (c-index: 0.63 vs 0.59) and PFS (0.62 vs 0.59).

Conclusion

We found a 2-month difference between mTSF and mPFS in mRCC patients receiving nivolumab. However, TBP patients had better outcomes, including significantly longer TSF and OS than non-TBP patients. The Meet-URO score is a reliable predictor of TSF and PFS.

Toward Best Practices for Economic Evaluations of Tumor-Agnostic Therapies: A Review of Current Barriers and Solutions

OBJECTIVES

Cancer therapies targeting tumor-agnostic biomarkers are challenging traditional health technology assessment (HTA) frameworks. The high prevalence of nonrandomized single-arm trials, heterogeneity, and small benefiting populations are driving outcomes uncertainty, challenging healthcare decision making. We conducted a structured literature review to identify barriers and prioritize solutions to generating economic evidence for tumor-agnostic therapies.

METHODS

We searched MEDLINE and Embase for English-language studies conducting economic evaluations of tumor-agnostic treatments or exploring related challenges and solutions. We included studies published by December 2022 and supplemented our review with Canadian Agency for Drugs and Technologies in Health and National Institute for Health and Care Excellence technical reports for approved tumor-agnostic therapies. Three reviewers abstracted and summarized key methodological and empirical study characteristics. Challenges and solutions were identified through authors' statements and categorized using directed content analysis.

RESULTS

Twenty-six studies met our inclusion criteria. Studies spanned economic evaluations (n = 5), reimbursement reviews (n = 4), qualitative research (n = 1), methods validations (n = 3), and commentaries or literature reviews (n = 13). Challenges encountered related to (1) the treatment setting and clinical trial designs, (2) a lack of data or low-quality data on clinical and cost parameters, and (3) an inability to produce evidence that meets HTA guidelines. Although attempted solutions centered on analytic approaches for managing missing data, proposed solutions highlighted the need for real-world evidence combined with life-cycle HTA to reduce future evidentiary uncertainty.

CONCLUSIONS

Therapeutic innovation outpaces HTA evidence generation and the methods that support it. Existing HTA frameworks must be adapted for tumor-agnostic treatments to support future economic evaluations enabling timely patient access.

Identification of novel immune-related molecular subtypes and a prognosis model to predict thyroid cancer prognosis and drug resistance

Background: Thyroid cancer is a common malignant tumor of the endocrine system that has shown increased incidence in recent decades. We explored the relationship between tumor-infiltrating immune cell classification and the prognosis of thyroid carcinoma. Methods: RNA-seq, SNV, copy number variance (CNV), and methylation data for thyroid cancer were downloaded from the TCGA dataset. ssGSEA was used to calculate pathway scores. Clustering was conducted using ConsensusClusterPlus. Immune infiltration was assessed using ESTIMATE and CIBERSORT. CNV and methylation were determined using GISTIC2 and the KNN algorithm. Immunotherapy was predicted based on TIDE analysis. Results: Three molecular subtypes (Immune-enrich(E), Stromal-enrich(E), and Immune-deprived(D)) were identified based on 15 pathways and the corresponding genes. Samples in Immune-E showed higher immune infiltration, while those in Immune-D showed increased tumor mutation burden (TMB) and mutations in tumor driver genes. Finally, Immune-E showed higher CDH1 methylation, higher progression-free survival (PFS), higher suitability for immunotherapy, and higher sensitivity to small-molecule chemotherapeutic drugs. Additionally, an immune score (IMScore) based on four genes was constructed, in which the low group showed better survival outcome, which was validated in 30 cancers. Compared to the TIDE score, the IMScore showed better predictive ability. Conclusion: This study constructed a prognostic evaluation model and molecular subtype system of immune-related genes to predict the thyroid cancer prognosis of patients. Moreover, the interaction network between immune genes may play a role by affecting the biological function of immune cells in the tumor microenvironment.

Tumor Response, Disease Control, and Progression-Free Survival as Surrogate Endpoints in Trials Evaluating Immune Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer: Study- and Patient-Level Analyses

Background: To assess the usefulness of tumor response and progression-free survival (PFS) as surrogates for overall survival (OS) in non-small cell lung cancer (NSCLC) trials with immune checkpoint inhibitors (ICI), which have not been confirmed. Methods: Patient- and trial-level analyses were performed. The Response Evaluation Criteria in Solid Tumors was preferred for image assessment. For trial-level analysis, surrogacy was assessed using the weighted rank correlation coefficient (r) following "reciprocal duplication." This method duplicates all plots as if the experimental and the reference arms were switched. Monte Carlo simulations were performed for evaluating this method. Results: A total of 3312 cases were included in the patient-level analysis. Patients without response (first line (1L): hazard ratio (HR) 1.95, 95% confidence interval (CI) 1.71-2.23; second or later line (2L-): HR 4.22, 95% CI 3.22-5.53), without disease control (1L: HR 4.34, 95% CI 3.82-4.94; 2L-: HR 3.36, 95% CI 2.96-3.81), or with progression during the first year (1L: HR 3.42, 95% CI 2.60-4.50; 2L-: HR 3.33, 95% CI 2.64-4.20), had a higher risk of death. Systematic searches identified 38 RCTs including 17,515 patients for the study-level analysis. Odds ratio in the objective response rate (N = 38 × 2, r = -0.87) and HR in PFS (N = 38 × 2, r = 0.85) showed an excellent association with HR in overall survival, while this effect was not observed in the disease control rate (N = 26 × 2, r = -0.03). Conclusions: Objective response rate and PFS are reasonable surrogates for OS in NSCLC trials with ICI.

CNPY4 is a potential promising prognostic-related biomarker and correlated with immune infiltrates in gliomas

Glioblastomas are classified into primary and secondary; primary glioblastomas develop rapidly and aggressively, whereas secondary glioblastomas are more common in grade II and III gliomas. Here, we aimed to demonstrate the role of the CNPY4 gene as a potential biomarker in immune infiltration in gliomas. Based on gene expression profile interaction analysis (GEPIA), we studied the survival model of CNPY4 and evaluated its effect on patients with glioma. The glioma dataset was downloaded from The Cancer Genome Atlas (TCGA) database. Logistic regression was used to analyze the relationship between clinical data and CNPY4 expression. Univariate and multivariate Cox proportional-hazards models were used to compare clinical features and patient survival. The relationship between CNPY4 and immune infiltration in glioma was studied using GEPIA and CIBERSORT online tools. TCGA data were analyzed using gene set enrichment analysis (GSEA). Finally, TIMER was used to analyze the expression and immune infiltration of CNPY4 in glioma to study the cumulative survival rate. Univariate logistic regression analysis showed that increased CNPY4 expression was associated with tumor age, grade, IDH status, and 1p/19q codeletion. Multivariate analysis showed that that downregulation of CNPY4 expression was an independent and satisfactory prognostic factor. CNPY4 expression was correlated with the infiltration level of dendritic cells in glioblastoma. In contrast, in low-grade gliomas, the infiltration level of B cells, dendritic cells, macrophages, neutrophils, and CD4+ T cells was significantly correlated with CNPY4 expression. The GSEA results showed that CNPY4 played an immunoregulatory role in immune-related phenotypic pathways between lymphoid and nonlymphoid cells. The intestinal immune networks for IgA production, rabbit thyroid disease, primary immunodeficiencies, and cancer immunotherapy were enriched by PD-1 blockade. High CNPY4 expression is a biomarker of glioma prognosis and is associated with the immune invasion of glioma.

Time to next treatment or death as a candidate surrogate endpoint for overall survival in advanced melanoma patients treated with immune checkpoint inhibitors: an insight from the phase III CheckMate 067 trial

Background

Time to next treatment or death (TNT-D) may be a patient-relevant endpoint in patients treated with immune checkpoint inhibitors. This study investigated TNT-D as a surrogate endpoint (SE) for overall survival (OS) in previously untreated advanced melanoma patients.

Methods

Patient-level data from the 60-month results of the CheckMate 067 randomised, controlled trial were used. Analyses were carried out for nivolumab monotherapy or nivolumab with ipilimumab versus ipilimumab monotherapy. The SE 1-step validation method based on a joint frailty-copula model was used where the country of enrolment was applied to define clusters. Kendall’s τ and the coefficient of determination (R²_trial) were estimated for respective measurements of association at the individual and cluster levels. The surrogate threshold effect, the maximum threshold hazard ratio for TNT-D that would translate into OS benefit, was estimated. A leave-one-out cross-validation analysis was carried out to evaluate model robustness.

Results

Fifteen clusters of data were generated from 945 patients. For both nivolumab-containing arms, the association between TNT-D and OS was deemed acceptable at the individual level (Kendall’s τ > 0.60) and strong at the cluster level, with R²_trial fairly close to 1, with narrow confidence intervals. The estimated surrogate threshold effects were 0.61 for nivolumab versus ipilimumab and 0.49 for nivolimub + ipilimumab versus ipilimumab. Cross-validation results showed minimum variation of the correlation measures and satisfactory predictive accuracy for the model.

Conclusion

Results suggest that TNT-D may be a valuable SE in previously untreated advanced melanoma patients treated with immune checkpoint inhibitors. Surrogacy analyses considering multiple randomised controlled trials are warranted for confirming these findings.

•

This is the first study to assess the surrogacy properties of TNT-D for OS in immune checkpoint inhibitor-treated patients.

•

TNT-D is a clinically relevant, pragmatic and often measurable endpoint that reflects the result of a therapeutic decision.

•

TNT-D appears to be a promising SE for OS in advanced melanoma patients treated with immune checkpoint inhibitors.

Using an interim analysis based exclusively on an early outcome in a randomized clinical trial with a long-term clinical endpoint

In RCTs with an interest in a long-term efficacy endpoint, the follow-up time necessary to observe the endpoint may be substantial. In order to reduce the expected duration of such trials, early-outcome data may be collected to enrich an interim analysis aimed at stopping the trial early for efficacy. We propose to extend such a design with an additional interim analysis using solely early-outcome data in order to expedite the evaluation of treatment's efficacy. We evaluate the potential gain in operating characteristics (power, expected trial duration, and expected sample size) when introducing such an early interim analysis, in function of the properties of the early outcome as a surrogate for the long-term endpoint. In the context of a longitudinal age-related macular degeneration (ARMD) ophthalmology trial, results show potentially substantial gains in both the expected trial duration and the expected sample size. A prerequisite, though, is that the treatment effect on the early outcome has to be strongly correlated with the treatment effect on the long-term endpoint, that is, that the early outcome is a validated surrogate for the long-term endpoint.

Immune checkpoint inhibitors in ovarian cancer: where do we stand?

Numerous retrospective studies have demonstrated that the density of intra-tumoral immune cell infiltration is prognostic in epithelial ovarian cancer (OC). These observations together with reports of programmed death ligand-1 (PD-L1) expression in advanced OC provided the rationale for investigating the benefit of programmed death-1 (PD1) or PD-L1 inhibition in OC. Unfortunately clinical trials to date evaluating PD1/PD-L1 inhibition in patients with relapsed OC have been disappointing. In this review we will discuss early results from single agent PD1/PD-L1 inhibitors and the strategies to enhance benefit from immune-oncology agents in OC, including proposing anti-PD-L1 in combination with other agents (cytotoxics, anti-angiogenics, poly(ADP-ribose) polymerase. (PARP) inhibitors, targeted therapies or other immunotherapies), as well as evaluating these agents earlier in the disease course, or in biomarker selected patients.

Surrogate Endpoints in Oncology: Overview of Systematic Reviews and Their Use for Health Decision Making in Mexico

OBJECTIVES

The use of surrogate endpoints (SEs) for cancer drug approval in health systems is common. The objectives of this study were to identify systematic reviews (SRs) that evaluated the correlation of SEs with overall survival (OS) in cancer drugs to analyze the applications of approved cancer drugs with SEs in Mexico and to apply the validation framework proposed by the Institute for Quality and Efficiency in Health Care (IQWiG).

METHODS

An overview of SRs was conducted according to Cochrane Collaboration methodology. Applications for approved cancer drugs with SEs in Mexico were analyzed. The IQWiG validation framework was applied to evaluate the SEs identified in the overview and in the applications in Mexico.

RESULTS

A total of 85 SRs that assessed 192 SEs for different types of cancer were selected. According to the IQWiG model, only 2.5% of the SEs analyzed in the overview and only one of the applications in Mexico could be used as surrogates for OS because the reliability (methodological quality) of the SRs and the strength of the correlation of SEs with OS was mostly low (92%) and low (correlation coefficient r ≤ 0.7; 50.5%), respectively. Of the total number of cancer drugs approved in Mexico, 19.4% used SEs.

CONCLUSIONS

Most SEs for different types of cancer could not be used as surrogates for OS according to the IQWiG model, and their use for the approval of cancer drugs in Mexico is generally not justified.

Improving patient selection for immuno-oncology phase 1 trials: External validation of six prognostic scores in a French Cancer Center

We compared the performance of six prognostic scores (Royal Marsden Hospital, MDACC: MD Anderson Clinical Center and MDACC + NLR: neutrophil-to-lymphocyte ratio, MD Anderson - immune checkpoint inhibitors (MDA-ICI), GRIm: Gustave Roussy Immune Score and LIPI: Lung Immune Prognostic Index) in predicting overall survival (OS) in phase I trial patients treated with immune checkpoint inhibitors (ICI). Medical records of patients with advanced solid tumors enrolled in ICI phase I trials between 2015 and 2018 at Institut Universitaire du Cancer de Toulouse-Oncopole were reviewed. The performance of prognostic scores on OS was compared using different criteria. A total of 259 patients were included. Median age was 63 years (range: 18-83). Main primary cancers were melanoma (19%), head and neck (16%), lung (13%) and bladder (10%). With a median follow-up of 15 months (95% confidence interval [CI] = [11.6;17.5]), median OS was 12.5 months (95% CI = [10.3;16.0]). All scores were associated with OS. The MDACC, LIPI and GRIm scores performed better than the others. Concordance of risk group assignment between the scoring systems was poor. According to our results, the MDACC, GRIm and LIPI scores better suited to ICI phase I settings. Adequate scoring would allow better patient selection in early ICI trials, especially during the critical period of dose escalation, and in proof-of-concept expansion cohorts.

A joint frailty-copula model for meta-analytic validation of failure time surrogate endpoints in clinical trials

In a meta-analysis framework, the classical approach for the validation of time-to-event surrogate endpoint is based on a two-step analysis. This approach often raises estimation issues. Recently, we proposed a one-step validation approach based on a joint frailty model. This approach was quite time consuming, despite parallel computing, due to individual-level frailties used to take into account heterogeneity in the data at the individual level. We now propose an alternative one-step approach for evaluating surrogacy, using a joint frailty-copula model. The model includes two correlated random effects treatment-by-trial interaction and a shared random effect associated with the baseline risks. At the individual level, the joint survivor functions of time-to-event endpoints are linked using copula functions. We used splines for the baseline hazard functions. We estimated parameters and hazard function using a semiparametric penalized marginal likelihood method, considering various numerical integration methods. Both individual-level and trial-level surrogacy were evaluated using Kendall's tau and coefficient of determination. The performance of the estimators was evaluated using simulation studies. The model was applied to individual patient data meta-analyses in advanced ovarian cancer to assess progression-free survival as a surrogate for overall survival, as part of the evaluation of new therapy. The model showed good performance and was quite robust regarding the integration methods and data variation, regardless of the surrogacy evaluation criteria. Kendall's Tau was better estimated using the Clayton copula model compared to the joint frailty model. The proposed model reduces the convergence and model estimation issues encountered in the two-step approach.

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.

Prognostic value of immune cell infiltration in bladder cancer: A gene expression-based study

The present study aimed to analyse the relationship between tumour-infiltrating immune cells (TIICs) and the prognosis of bladder cancer (BC). In the present study, an established computational method (CIBERSORT) was used to analyse the gene expression profile of BC from 409 patients to infer the number of infiltrating immune cells among 22 immune cell subsets. The relationship between each cell type and overall survival (OS) was further analysed. Single-sample GSEA and ESTIMATE algorithms were performed to evaluate the composition of immune microenvironment in each immune cluster. A significant difference in immune cell infiltration between BC and bladder tissue was observed. Increased natural killer and CD8⁺ T cell infiltration was associated with longer OS, whereas a higher percentage of M0 macrophages among the total immune cells was associated with shorter OS. The number of M0 macrophages increased with increasing BC stage, whereas the percentage of activated memory CD4⁺ and CD8⁺ T cells decreased. Patients with BC were divided into three subgroups by hierarchical cluster analysis of immune cells, and each cluster was associated with distinct survival and immune characteristics. The data indicated differences in the cellular composition of TIICs in patients with BC. Moreover, these TIICs were shown to be potential drug targets and reliable prognostic indicators.

Progression-free survival as a surrogate for overall survival in oncology trials: a methodological systematic review

Background

Progression-free survival (PFS) is a surrogate endpoint widely used for overall survival (OS) in oncology. Validation of PFS as a surrogate must be done for each indication and each intervention. We aimed to identify all studies evaluating the validity of PFS as a surrogate for OS in oncology, and to describe their methodological characteristics.

Methods

We conducted a systematic review by searching MEDLINE via PubMed and the Cochrane Library with no limitation on time, selected relevant studies and extracted data in duplicate on how surrogacy was evaluated (meta-analytic approach, assessment of correlation and level of evaluation).

Results

We identified 91 studies evaluating the validity of PFS as a surrogate for OS in 24 cancer localisations. Although a meta-analytic approach was used in 83 (91%) studies, the methods used to validate PFS as a surrogate of OS were heterogeneous across studies. Of the 47 studies concluding that PFS is a good surrogate for OS, for 15 (32%), there was no quantitative argument for surrogacy.

Conclusions

Although most studies used a meta-analytic approach as recommended, our methodological review highlights heterogeneity in methods and reporting, which stresses the importance of developing and applying clear recommendations in this area.