Do Surrogate Endpoints Better Correlate with Overall Survival in Studies That Did Not Allow for Crossover or Reported Balanced Postprogression Treatments? An Application in Advanced Non-Small Cell Lung Cancer

UK Stakeholder Perspectives on Surrogate Endpoints in Cancer, and the Potential for UK Real-World Datasets to Validate Their Use in Decision-Making

Duration of overall survival in patients with cancer has lengthened due to earlier detection and improved treatments. However, these improvements have created challenges in assessing the impact of newer treatments, particularly those used early in the treatment pathway. As overall survival remains most decision-makers' preferred primary endpoint, therapeutic innovations may take a long time to be introduced into clinical practice. Moreover, it is difficult to extrapolate findings to heterogeneous populations and address the concerns of patients wishing to evaluate everyday quality and extension of life. There is growing interest in the use of surrogate or interim endpoints to demonstrate robust treatment effects sooner than is possible with measurement of overall survival. It is hoped that they could speed up patients' access to new drugs, combinations, and sequences, and inform treatment decision-making. However, while surrogate endpoints have been used by regulators for drug approvals, this has occurred on a case-by-case basis. Evidence standards are yet to be clearly defined for acceptability in health technology appraisals or to shape clinical practice. This article considers the relevance of the use of surrogate endpoints in cancer in the UK context, and explores whether collection and analysis of real-world UK data and evidence might contribute to validation.

Progression-free survival as a surrogate endpoint for overall survival in patients with relapsed or refractory multiple myeloma

OBJECTIVES

The goal of the research was to assess the quantitative relationship between median progression-free survival (PFS) and median overall survival (OS) specifically among patients with relapsed/refractory multiple myeloma (RRMM) based on published randomized controlled trials (RCTs).

METHODS

Two bibliographic databases (PubMed and Embase, 1970-2017) were systematically searched for RCTs in RRMM that reported OS and PFS, followed by an updated search of studies published between 2010 and 2022 in 3 databases (Embase, MEDLINE, and EBM Reviews, 2010-2022). The association between median PFS and median OS was assessed using the nonparametric Spearman rank and parametric Pearson correlation coefficients. Subsequently, the quantitative relationship between PFS and OS was assessed using weighted least-squares regression adjusted for covariates including age, sex, and publication year. Study arms were weighted by the number of patients in each arm.

RESULTS

A total of 31 RCTs (56 treatment arms, 10,450 patients with RRMM) were included in the analysis. The average median PFS and median OS were 7.1 months (SD 5.5) and 28.1 months (SD 11.8), respectively. The Spearman and Pearson correlation coefficients between median PFS and median OS were 0.80 (P < 0.0001) and 0.79 (P < 0.0001), respectively. In individual treatment arms of RRMM trials, each 1-month increase in median PFS was associated with a 1.72-month (95% CI 1.26-2.17) increase in median OS.

CONCLUSION

Analysis of the relationship between PFS and OS incorporating more recent studies in RRMM further substantiates the use of PFS to predict OS in RRMM.

Correlations of response rate and progression-free survival with overall survival in immunotherapy trials for metastatic non-small-cell lung cancer: an FDA pooled analysis

BACKGROUND

Radiographic changes might not fully capture the treatment effects of immune checkpoint inhibitors (ICIs). We aimed to assess correlations of overall response rate and progression-free survival with overall survival in trials of ICIs for metastatic non-small-cell lung cancer (NSCLC).

METHODS

To assess trial-level and patient-level correlations of overall response rate and progression-free survival with overall survival, we conducted a pooled analysis of first-line randomised trials (including patients aged ≥18 years with metastatic squamous and non-squamous NSCLC and an Eastern Cooperative Oncology Group performance status of 0-1) submitted to the US Food and Drug Administration from June 24, 2016, to March 16, 2021. Eligible trials evaluated at least one ICI in the experimental group versus chemotherapy in the control group. At the trial level, we used weighted linear regression to derive coefficients of determination (R2). At the patient level, we used Cox proportional hazards models to compare overall survival between responders versus non-responders per Response Evaluation Criteria in Solid Tumours (version 1.1).

FINDINGS

A total of 13 trials including 9285 patients evaluated ICIs alone or in combination with chemotherapy versus chemotherapy alone. At the trial level, the R2 was 0·61 (95% CI 0·32-0·84) for correlation of overall response rate with overall survival and 0·70 (0·40-0·89) for correlation of progression-free survival with overall survival. Correlations ranged from weak to moderate when evaluating subgroups by PD-L1 expression and were consistent across trials evaluating ICIs alone or in combination with chemotherapy. At the patient level, responders had longer overall survival than non-responders (hazard ratio [HR] 0·28 [95% CI 0·26-0·30]). Among responders, overall survival was longer in patients enrolled in experimental groups than in control groups (HR 0·54 [95% CI 0·48-0·61]).

INTERPRETATION

Correlations of overall response rate and progression-free survival with overall survival were generally moderate in this pooled analysis. The findings support routine analysis of mature overall survival data, where feasible, in first-line randomised trials of ICIs for metastatic NSCLC.

FUNDING

US Food and Drug Administration.

Adapting Health Technology Assessment agency standards for surrogate outcomes in early stage cancer trials: what needs to happen?

INTRODUCTION

An avalanche of early stage cancer clinical trials is coming. The majority of these solely use surrogate outcomes that have not been validated against a target outcome of interest (e.g. overall survival). Current HTA guidance on surrogate outcome validation are not methodologically or practically conducive to this scenario.

AREAS COVERED

We provide a high-level overview of methods, approaches, and conceptual thinking for making better use of limited evidence within early stage cancer HTA submissions. We outline regulatory and HTA issues and emphasize how evidence transitions from one to another, what major gaps currently exist, and how these may be bridged. We summarize current methodologies and practices, their pros and cons. We outline how complementary measurements strengthen evaluations and address fallacies and biases of conventional statistical methods for surrogate outcomes validation. The value of real-world data to support some of the necessary validity components is discussed. Lastly, we address the importance of the patient voice for better understanding which surrogate outcomes may appropriately inform HTA.

EXPERT OPINION

Conventional surrogate outcome validation represents a fraught and sub-optimal framework for HTA purposes, particularly for early stage cancer. Tools for optimizing use of limited evidence exist. Education of stakeholders is highly needed.

Challenges, Complexities, and Considerations in the Design and Interpretation of Late-Phase Oncology Trials

Optimal management of cancer patients relies heavily on late-phase oncology randomized controlled trials. A comprehensive understanding of the key considerations in designing and interpreting late-phase trials is crucial for improving subsequent trial design, execution, and clinical decision-making. In this review, we explore important aspects of late-phase oncology trial design. We begin by examining the selection of primary endpoints, including the advantages and disadvantages of using surrogate endpoints. We address the challenges involved in assessing tumor progression and discuss strategies to mitigate bias. We define informative censoring bias and its impact on trial results, including illustrative examples of scenarios that may lead to informative censoring. We highlight the traditional roles of the log-rank test and hazard ratio in survival analyses, along with their limitations in the presence of nonproportional hazards as well as an introduction to alternative survival estimands, such as restricted mean survival time or MaxCombo. We emphasize the distinctions between the design and interpretation of superiority and noninferiority trials, and compare Bayesian and frequentist statistical approaches. Finally, we discuss appropriate utilization of phase II and phase III trial results in shaping clinical management recommendations and evaluate the inherent risks and benefits associated with relying on phase II data for treatment decisions.

What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort

Tumor mutation burden (TMB) is a widely recognized biomarker for predicting the efficacy of immunotherapy. However, its use still remains highly controversial. In this study, we examine the underlying causes of this controversy based on clinical needs. By tracing the source of the TMB errors and analyzing the design philosophy behind variant callers, we identify the conflict between the incompleteness of biostatistics rules and the variety of clinical samples as the critical issue that renders TMB an ambivalent biomarker. A series of experiments were conducted to illustrate the challenges of mutation detection in clinical practice. Additionally, we also discuss potential strategies for overcoming these conflict issues to enable the application of TMB in guiding decision-making in real clinical settings.

TMBserval: a statistical explainable learning model reveals weighted tumor mutation burden better categorizing therapeutic benefits

A high tumor mutation burden (TMB) is known to drive the response to immune checkpoint inhibitors (ICI) and is associated with favorable prognoses. However, because it is a one-dimensional numerical representation of non-synonymous genetic alterations, TMB suffers from clinical challenges due to its equal quantification. Since not all mutations elicit the same antitumor rejection, the effect on immunity of neoantigens encoded by different types or locations of somatic mutations may vary. In addition, other typical genomic features, including complex structural variants, are not captured by the conventional TMB metric. Given the diversity of cancer subtypes and the complexity of treatment regimens, this paper proposes that tumor mutations capable of causing various degrees of immunogenicity should be calculated separately. TMB should therefore, be segmented into more exact, higher dimensional feature vectors to exhaustively measure the foreignness of tumors. We systematically reviewed patients' multifaceted efficacy based on a refined TMB metric, investigated the association between multidimensional mutations and integrative immunotherapy outcomes, and developed a convergent categorical decision-making framework, TMBserval (Statistical Explainable machine learning with Regression-based VALidation). TMBserval integrates a multiple-instance learning concept with statistics to create a statistically interpretable model that addresses the broad interdependencies between multidimensional mutation burdens and decision endpoints. TMBserval is a pan-cancer-oriented many-to-many nonlinear regression model with discrimination and calibration power. Simulations and experimental analyses using data from 137 actual patients both demonstrated that our method could discriminate between patient groups in a high-dimensional feature space, thereby rationally expanding the beneficiary population of immunotherapy.

Overall and complete response rates as potential surrogates for overall survival in relapsed/refractory multiple myeloma

Aim: The correlation between response and survival has not been well-studied in relapsed or refractory multiple myeloma (RRMM). Materials & methods: A systematic literature review of Medline, Embase and Cochrane databases (2010-06/2020) and relevant congresses (2018-2020) was performed to identify randomized clinical trials in RRMM reporting median overall survival (mOS), progression-free survival and response endpoints. The relationship between mOS and response endpoints was analyzed using Pearson's product-moment correlation. Results: A total of 81 records for 65 original studies, representing 12,827 patients were included. The correlation was moderate for mOS with overall response rate (Pearson r = 0.79), very good partial response (r = 0.73) and duration of response (r = 0.78); all were statistically significant. In linear regression models, estimated mOS gain was 0.48, 0.47 and 1.94 months per percentage point of overall response rate, very good partial response and complete response, respectively (all p < 0.001). Significance was maintained after adjustment for age, relapsed versus refractory multiple myeloma and study year. The analysis was limited by small sample sizes and inconsistent reporting of study-level covariates. Conclusion: These findings support short-term response-based endpoints as surrogates to survival in RRMM.

Surrogate Endpoints as Predictors of Overall Survival in Metastatic Urothelial Cancer: A Trial-level Analysis

Background

Surrogate endpoints (SEs), such as progression-free survival (PFS) and objective response rate (ORR), are frequently used in clinical trials. The relationship between SEs and overall survival (OS) has not been well described in metastatic urothelial cancer (MUC).

Objective

We evaluated trial-level data to assess the relationship between SEs and OS. We hypothesize a moderate surrogacy relationship between both PFS and ORR with OS.

Design setting and participants

We systematically reviewed phase 2/3 trials in MUC with two or more treatment arms, and report PFS and/or ORR, and OS.

Outcome measurements and statistical analysis

Linear regression was performed, and the coefficient of determination (R²) and surrogate threshold effect (STE) estimate were determined between PFS/ORR and OS.

Results and limitations

Of 3791 search results, 59 trials and 62 comparisons met the inclusion criteria. Of the 53 trials that reported PFS, 31 (58%) reported proportional hazard regression for PFS and OS. Linear regression across trials demonstrated an R² of 0.60 between hazard ratio (HR) for PFS (HR^PFS) and HR for OS (HR^OS), and an STE of 0.41. Linear regression of ΔPFS (median PFS in months of the treatment arm - that of the control arm) and ΔOS demonstrated an R² of 0.12 and an STE of 14.1 mo. Thirty trials reported ORRs. Linear regression for ORR^ratio and HR^OS among all trials found an R² of 0.08; an STE of 95% was not reached at any value and ΔORR and HR^OS similarly demonstrated a poor correlation with an R² value of 0.03.

Conclusions

PFS provides only a moderate level of surrogacy for OS; An HR^PFS of ≤0.41 provides 95% confidence of OS improvement. ORR is weakly correlated with OS and should be de-emphasized in MUC clinical trials. When PFS is discussed, proportional hazard regression should be reported.

Patient summary

We examined the relationship between surrogate endpoints, common outcomes in clinical trials, with survival in urothelial cancer trials. Progression-free survival is moderately correlated, while objective response rate had a poor correlation with survival and should be de-emphasized as a primary endpoint.

Validating ORR and PFS as surrogate endpoints in phase II and III clinical trials for NSCLC patients: difference exists in the strength of surrogacy in various trial settings

OBJECTIVE

This study aims to systematically validate the performance of surrogate endpoints in phase II and III clinical trials for NSCLC patients under various trial settings.

METHODS

A literature search retrieved all registered phase II and III trials of NSCLC patients in which OS, with at least one of ORR and PFS, were reported. Associations between surrogate and true endpoints were assessed on two levels. On the arm level, three pairs of correlations, i.e., ORR vs. median OS, ORR vs. median PFS, and median PFS vs. median OS, were analysed using Spearman's rho. On the trial level, similarly, three pairs of correlations, i.e., ΔORR vs. HR of OS, ΔORR vs. HR of PFS, and HR of PFS vs. HR of OS, were analysed using Spearman's rho and weighted linear regression model respectively. Finally, sensitivity analyses were performed to explore surrogacy under various trial settings.

RESULTS

At arm level, three pairs of correlations are all high (Spearman's rho = 0.700, 0.831, 0.755, respectively). At trial level, there is a low correlation between ΔORR and HR of OS, a high correlation between ΔORR and HR of PFS and a moderate correlation between HR of PFS and HR of OS (Spearman's rho = 0.462, 0.764, 0.584, respectively). In the sensitivity analysis, we find correlations between surrogate and true endpoints vary by different trial settings. It is noteworthy that the strength of surrogacy of these intermediate endpoints in targeted therapy is greater than that in immunotherapy.

CONCLUSION

According to the arm-level and trial level-analysis, we suggest that in phase II and III trials of targeted therapy and immunotherapy for NSCLC patients: 1) ORR lacks validity for the surrogacy of OS, excluding in first-line therapy, and 2) ORR may be an appropriate surrogate endpoint for PFS, and 3) PFS may be considered a modest surrogacy for OS, with better performance in first-line therapy trials. Moreover, to provide more convincing evidence of surrogacy of the surrogate endpoints, patient-level analyses are in desperate need.

TMBcat: A multi-endpoint p-value criterion on different discrepancy metrics for superiorly inferring tumor mutation burden thresholds

Tumor mutation burden (TMB) is a widely recognized stratification biomarker for predicting the efficacy of immunotherapy; however, the number and universal definition of the categorizing thresholds remain debatable due to the multifaceted nature of efficacy and the imprecision of TMB measurements. We proposed a minimal joint p-value criterion from the perspective of differentiating the comprehensive therapeutic advantages, termed TMBcat, optimized TMB categorization across distinct cancer cohorts and surpassed known benchmarks. The statistical framework applies to multidimensional endpoints and is fault-tolerant to TMB measurement errors. To explore the association between TMB and various immunotherapy outcomes, we performed a retrospective analysis on 78 patients with non-small cell lung cancer and 64 patients with nasopharyngeal carcinomas who underwent anti-PD-(L)1 therapy. The stratification results of TMBcat confirmed that the relationship between TMB and immunotherapy is non-linear, i.e., treatment gains do not inherently increase with higher TMB, and the pattern varies across carcinomas. Thus, multiple TMB classification thresholds could distinguish patient prognosis flexibly. These findings were further validated in an assembled cohort of 943 patients obtained from 11 published studies. In conclusion, our work presents a general criterion and an accessible software package; together, they enable optimal TMB subgrouping. Our study has the potential to yield innovative insights into therapeutic selection and treatment strategies for patients.

Altered expression of ACOX2 in non-small cell lung cancer

Peroxisomes are organelles that play essential roles in many metabolic processes, but also play roles in innate immunity, signal transduction, aging and cancer. One of the main functions of peroxisomes is the processing of very-long chain fatty acids into metabolites that can be directed to the mitochondria. One key family of enzymes in this process are the peroxisomal acyl-CoA oxidases (ACOX1, ACOX2 and ACOX3), the expression of which has been shown to be dysregulated in some cancers. Very little is however known about the expression of this family of oxidases in non-small cell lung cancer (NSCLC). ACOX2 has however been suggested to be elevated at the mRNA level in over 10% of NSCLC, and in the present study using both standard and bioinformatics approaches we show that expression of ACOX2 is significantly altered in NSCLC. ACOX2 mRNA expression is linked to a number of mutated genes, and associations between ACOX2 expression and tumour mutational burden and immune cell infiltration were explored. Links between ACOX2 expression and candidate therapies for oncogenic driver mutations such as KRAS were also identified. Furthermore, levels of acyl-CoA oxidases and other associated peroxisomal genes were explored to identify further links between the peroxisomal pathway and NSCLC. The results of this biomarker driven study suggest that ACOX2 may have potential clinical utility in the diagnosis, prognosis and stratification of patients into various therapeutically targetable options.

Correlation Between Early Time-to-Event Outcomes and Overall Survival in Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma Receiving Definitive Chemoradiation Therapy: Systematic Review and Meta-Analysis

Background

Overall survival (OS) is the most patient-relevant outcome in oncology; however, in early cancers, large sample sizes and extended follow-up durations are needed to detect statistically significant differences in OS between interventions. Use of early time-to-event outcomes as surrogates for OS can help facilitate faster approval of cancer therapies. In locally advanced head and neck squamous cell carcinoma (LA-HNSCC), event-free survival (EFS) was previously evaluated as a surrogate outcome (Michiels 2009) and demonstrated a strong correlation with OS. The current study aimed to further assess the correlation between EFS and OS in LA-HNSCC using an updated systematic literature review (SLR) focusing on patients receiving definitive chemoradiation therapy (CRT).

Methods

An SLR was conducted on May 27, 2021 to identify randomized controlled trials assessing radiotherapy alone or CRT in the target population. Studies assessing CRT and reporting hazard ratios (HRs) or Kaplan-Meier data for OS and EFS were eligible for the analysis. CRT included any systemic treatments administered concurrently or sequentially with radiation therapy. Trial-level EFS/OS correlations were assessed using regression models, and the relationship strength was measured with Pearson correlation coefficient (R). Correlations were assessed across all CRT trials and in trial subsets assessing concurrent CRT, sequential CRT, RT+cisplatin, targeted therapies and intensity-modulated RT. Subgroup analysis was conducted among trials with similar EFS definitions (i.e. EFS including disease progression and/or death as events) and longer length of follow-up (i.e.≥ 5 years).

Results

The SLR identified 149 trials of which 31 were included in the analysis. A strong correlation between EFS and OS was observed in the overall analysis of all CRT trials (R=0.85, 95% confidence interval: 0.72-0.93). Similar results were obtained in the sensitivity analyses of trials assessing concurrent CRT (R=0.88), sequential CRT (R=0.83), RT+cisplatin (R=0.82), targeted therapies (R=0.83) and intensity-modulated RT (R=0.86), as well as in trials with similar EFS definitions (R=0.87), with longer follow-up (R=0.81).

Conclusion

EFS was strongly correlated with OS in this trial-level analysis. Future research using individual patient-level data can further investigate if EFS could be considered a suitable early clinical endpoint for evaluation of CRT regimens in LA-HNSCC patients receiving definitive CRT.

Modelling approaches for histology-independent cancer drugs to inform NICE appraisals: a systematic review and decision-framework

BACKGROUND

The first histology-independent marketing authorisation in Europe was granted in 2019. This was the first time that a cancer treatment was approved based on a common biomarker rather than the location in the body at which the tumour originated. This research aims to explore the implications for National Institute for Health and Care Excellence appraisals.

METHODS

Targeted reviews were undertaken to determine the type of evidence that is likely to be available at the point of marketing authorisation and the analyses required to support National Institute for Health and Care Excellence appraisals. Several challenges were identified concerning the design and conduct of trials for histology-independent products, the greater levels of heterogeneity within the licensed population and the use of surrogate end points. We identified approaches to address these challenges by reviewing key statistical literature that focuses on the design and analysis of histology-independent trials and by undertaking a systematic review to evaluate the use of response end points as surrogate outcomes for survival end points. We developed a decision framework to help to inform approval and research policies for histology-independent products. The framework explored the uncertainties and risks associated with different approval policies, including the role of further data collection, pricing schemes and stratified decision-making.

RESULTS

We found that the potential for heterogeneity in treatment effects, across tumour types or other characteristics, is likely to be a central issue for National Institute for Health and Care Excellence appraisals. Bayesian hierarchical methods may serve as a useful vehicle to assess the level of heterogeneity across tumours and to estimate the pooled treatment effects for each tumour, which can inform whether or not the assumption of homogeneity is reasonable. Our review suggests that response end points may not be reliable surrogates for survival end points. However, a surrogate-based modelling approach, which captures all relevant uncertainty, may be preferable to the use of immature survival data. Several additional sources of heterogeneity were identified as presenting potential challenges to National Institute for Health and Care Excellence appraisal, including the cost of testing, baseline risk, quality of life and routine management costs. We concluded that a range of alternative approaches will be required to address different sources of heterogeneity to support National Institute for Health and Care Excellence appraisals. An exemplar case study was developed to illustrate the nature of the assessments that may be required.

CONCLUSIONS

Adequately designed and analysed basket studies that assess the homogeneity of outcomes and allow borrowing of information across baskets, where appropriate, are recommended. Where there is evidence of heterogeneity in treatment effects and estimates of cost-effectiveness, consideration should be given to optimised recommendations. Routine presentation of the scale of the consequences of heterogeneity and decision uncertainty may provide an important additional approach to the assessments specified in the current National Institute for Health and Care Excellence methods guide.

FURTHER RESEARCH

Further exploration of Bayesian hierarchical methods could help to inform decision-makers on whether or not there is sufficient evidence of homogeneity to support pooled analyses. Further research is also required to determine the appropriate basis for apportioning genomic testing costs where there are multiple targets and to address the challenges of uncontrolled Phase II studies, including the role and use of surrogate end points.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Evidence Synthesis programme and will be published in full in Health Technology Assessment; Vol. 25, No. 76. See the NIHR Journals Library website for further project information.

Proportion of Patients in Phase I Oncology Trials Receiving Treatments That Are Ultimately Approved

BACKGROUND

Phase I oncology trials are often regarded as a therapeutic option for patients. However, such claims have relied on surrogate measures of benefit, such as objective response.

METHODS

Using a systematic search of publications, we assessed the therapeutic value of phase I cancer trial participation by determining the probability that patients will receive active doses of treatments that eventually receive FDA approval or a National Comprehensive Cancer Network (NCCN) guideline recommendation for their indication. ClinicalTrials.gov, PubMed, American Society of Clinical Oncology reports, NCCN guidelines, and Drugs@FDA were searched between May 1, 2018, and July 31, 2018. All statistical tests were 2-sided.

RESULTS

A total of 1000 phase I oncology trials initiated between 2005 and 2010 and enrolling 32 582 patients were randomly sampled from 3229 eligible trials on ClinicalTrials.gov. A total of 386 (1.2%) patients received a treatment that was approved by the US Food and Drug Administration for their malignancy at a dose delivered in the trial; including NCCN guideline recommendations, the number and proportion are 1168 (3.6%). Meta-regression showed a statistically significantly greater proportion of patients receiving a drug that was ultimately FDA approved in biomarker trials (rate ratio = 4.49, 95% confidence interval [CI] = 1.53 to 13.23; P = .006) and single-indication trials (rate ratio = 3.32, 95% CI = 1.21 to 9.15; P  = .02); proportions were statistically significantly lower for combination vs monotherapy trials (rate ratio = 0.09, 95% CI = 0.01 to 0.68; P  = .02).

CONCLUSIONS

One in 83 patients in phase I cancer trials received a treatment that was approved for their indication at the doses received. Given published estimates of serious adverse event rates of 10%-19%, this represents low therapeutic value for phase I trial participation.

Concordance index: Surrogacy of progression-free survival for overall survival

In oncology clinical trials, the primary endpoint is often time to an event of clinical interest, e.g., time to disease progression or time to death. As a result, progression-free survival (PFS: the time from initiation of treatment till disease progression or death whichever occurs first) and overall survival (OS: the time from initiation of treatment till death) are the focus of statistical analysis in comparison of two treatment arms. It is often argued that PFS may serve as a surrogate endpoint for OS, while the validity of such surrogacy is still under debates in different types of cancer. In practice, one may observe a significant difference in PFS but no significant difference in OS; or vice versa. We provide a concordance index (C-index) to measure the degree of concordance between PFS and OS, and elaborate on the PFS vs OS discrepancies using the C-index using simulation studies and real trial analysis.

A systematic review of meta-analyses assessing the validity of tumour response endpoints as surrogates for progression-free or overall survival in cancer

BACKGROUND

Tumour response endpoints, such as overall response rate (ORR) and complete response (CR), are increasingly used in cancer trials. However, the validity of response-based surrogates is unclear. This systematic review summarises meta-analyses assessing the association between response-based outcomes and overall survival (OS), progression-free survival (PFS) or time-to-progression (TTP).

METHODS

Five databases were searched to March 2019. Meta-analyses reporting correlation or regression between response-based outcomes and OS, PFS or TTP were summarised.

RESULTS

The systematic review included 63 studies across 20 cancer types, most commonly non-small cell lung cancer (NSCLC), colorectal cancer (CRC) and breast cancer. The strength of association between ORR or CR and either PFS or OS varied widely between and within studies, with no clear pattern by cancer type. The association between ORR and OS appeared weaker and more variable than that between ORR and PFS, both for associations between absolute endpoints and associations between treatment effects.

CONCLUSIONS

This systematic review suggests that response-based endpoints, such as ORR and CR, may not be reliable surrogates for PFS or OS. Where it is necessary to use tumour response to predict treatment effects on survival outcomes, it is important to fully reflect all statistical uncertainty in the surrogate relationship.

Evaluation of Pathologic Complete Response as a Surrogate for Long-Term Survival Outcomes in Triple-Negative Breast Cancer

Background: Pathologic complete response (pCR) is a common efficacy endpoint in neoadjuvant therapy trials for triple-negative breast cancer (TNBC). Previous studies have shown that pCR is strongly associated with improved long-term survival outcomes, including event-free survival (EFS) and overall survival (OS). However, the trial-level associations between treatment effect on pCR and long-term survival outcomes are not well established. This study sought to evaluate these associations by incorporating more recent clinical trials in TNBC. Methods: A literature review identified published randomized controlled trials (RCTs) of neoadjuvant therapy for TNBC that reported results for both pCR and EFS/OS. Meta-regression models were performed to evaluate the association of treatment effect on pCR and EFS/OS. Sensitivity analyses were conducted to assess the impact of divergent study designs. Results: Ten comparisons from 8 RCTs (N=2,478 patients) were identified from the literature review. The log (odds ratio) of pCR was a significant predictor of the log (hazard ratio) of EFS (P=.003), with a coefficient of determination of 0.68 (95% CI, 0.41–0.95). There was a weaker association between pCR and OS (P=.18), with a coefficient of determination of 0.24 (95% CI, 0.01–0.77). Consistent results were found in the exploratory analysis and sensitivity analyses. Conclusions: This is the first study that has shown a trial-level association between pCR and survival outcomes in TNBC. By incorporating the most up-to-date RCTs, this study showed a significant trial-level association between pCR and EFS. A positive association between pCR and OS was also recorded.

Progression-free survival is a suboptimal predictor for overall survival among metastatic solid tumour clinical trials

BACKGROUND

The use of overall survival (OS) as the gold standard primary end-point (PEP) in metastatic oncologic randomised controlled trials (RCTs) has declined in favour of progression-free survival (PFS) without a complete understanding of the degree to which PFS reliably predicts for OS.

METHODS

Using ClinicalTrials.gov, we identified 1239 phase III oncologic RCTs, 260 of which were metastatic solid tumour trials with a superiority-design investigating a therapeutic intervention by using either a PFS or OS PEP. Each individual trial was reviewed to quantify RCT design factors and disease-related outcomes.

RESULTS

A total of 172,133 patients were enrolled from the year 1999 to 2015 in RCTs that used PFS (56.2%, 146/260) or OS (43.8%, 114/260) as the PEP. PFS trials were more likely to restrict patient eligibility by using molecular criteria (15.1% versus 4.4%, p = 0.005) use targeted therapy (80.1% versus 67.5%, p = 0.048), accrue fewer patients (median 495 versus 619, p = 0.03), and successfully meet the trial PEP (66.9% versus 33.3%, p < 0.0001). On multiple binary logistic regression analysis, factors that predicted for PFS or OS PEP trial success included choice of PFS PEP (p < 0.0001), molecular profile restriction (p = 0.02) and single agent therapy (p = 0.02). Notably, there was only a 38% (31/82) conversion rate of positive PFS-to-OS benefit; lack of industry sponsorship predicted for PFS-to-OS signal conversion (80.0% without industry sponsorship versus 35.1% with industry sponsorship, p = 0.045).

CONCLUSIONS

A PFS PEP has suboptimal positive predictive value for OS among phase III metastatic solid tumour RCTs. Regulatory agency decisions should be judicious in using PFS results as the primary basis for approval.

Benefit, burden, and impact for a cohort of post-approval cancer combination trials

BACKGROUND

After approval, drug developers often pursue trials aimed at extending the uses of a new drug by combining it with other drugs. Little is known about the risk and benefits associated with such research.

METHODS

To establish a historic benchmark of risk and benefit, we searched Medline and Embase for clinical trials testing anti-cancer drugs in combination within 5 years of approval by the Food and Drug Administration of 12 anti-cancer "index" drugs first licensed 2005-2007 inclusive. Risk was assessed based on grade 3 or above drug-related adverse events; benefit was assessed based on efficacy outcomes and advancement of combinations into clinical practice guidelines or approval by the Food and Drug Administration.

RESULTS

We captured 323 published post-approval trials exploring combinations, including 266 unique combination-indication pairings and enrolling 29,835 patients. The pooled risk ratios for treatment-related grade 3-4 severe adverse events and deaths attributed to the study drugs for trials randomized between a combination arm and a comparator were 1.54 (1.33-1.79) and 1.51 (1.16-1.97), respectively. The pooled hazard ratios for overall survival and progression-free survival were 0.99 (0.92-1.05) and 0.85 (0.79-0.93), respectively. None of the combination-indication pairings launched after initial drug approval received approval by the Food and Drug Administration, and 13 pairings (4.9%) were recommended by the National Comprehensive Cancer Network within 5 years of the first trial within that pairing. The proportion of patients in our sample who participated in trials leading to an approval by the Food and Drug Administration or a National Comprehensive Cancer Network guideline recommendation was 12.7% with 5 years of follow-up, and 22.3% among pairings for which there were 8 years of follow-up.

CONCLUSION

Patients were just as likely to benefit in the treatment arm as the control arm in terms of overall survival, but they were more likely to experience a treatment-related severe adverse event in post-approval trials of combination therapy.