Validation of Progression-Free Survival Rate at 6 Months and Objective Response for Estimating Overall Survival in Immune Checkpoint Inhibitor Trials

Kok, Peey‐Sei; Cho, Doah; Yoon, Won-Hee; Ritchie, Gill; Marschner, Ian C.; Lord, Sarah J.; Friedlander, Michael; Simes, John; Lee, Chee Khoon

doi:10.1001/jamanetworkopen.2020.11809

Cited by 38 publications

(30 citation statements)

References 25 publications

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“…This is a frequently reported statistic for many early phase oncology trials (Phase 1 and 2) that involve relatively small numbers of patients. It is also a landmark outcome in systematic reviews and metaanalysis of oncology clinical trials 39 , and used to guide the design of larger trials. A challenge in the analysis of such data is that, when too few events have occurred, nonparametric numeric confidence estimates return non-informative values (usually reported as a value "not reached" or "indeterminate" 27 as illustrated for two different scenarios in Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects

et al. 2022

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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.

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Section: Resultsmentioning

confidence: 99%

Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects

et al. 2022

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“…A recent meta-analysis of 60 published immunotherapy randomized clinical trials suggested that ORR could be a meager surrogate of response to evaluate the efficacy of IO, and the use of PFS as a surrogate of OS is still indeterminate [ 44 ]. Another meta-analysis of 12 randomized clinical trials did not find a significant positive correlation between the OS and PFS hazard estimates, suggesting that PFS assessment is not sufficient to capture the benefit of PD-1-inhibitors in patients with solid tumors [ 42 ].…”

Section: Challenges and Opportunities In Io Drugs Developmentmentioning

confidence: 99%

Lights and Shadows in Immuno-Oncology Drug Development

Sirvén

Pernas

Cheang

2021

Cancers

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The rapidly evolving landscape of immuno-oncology (IO) is redefining the treatment of a number of cancer types. IO treatments are becoming increasingly complex, with different types of drugs emerging beyond checkpoint inhibitors. However, many of the new drugs either do not progress from phase I-II clinical trials or even fail in late-phase trials. We have identified at least five areas in the development of promising IO treatments that should be redefined for more efficient designs and accelerated approvals. Here we review those critical aspects of IO drug development that could be optimized for more successful outcome rates in all cancer types. It is important to focus our efforts on the mechanisms of action, types of response and adverse events of these novel agents. The use of appropriate clinical trial designs with robust biomarkers of response and surrogate endpoints will undoubtedly facilitate the development and subsequent approval of these drugs. Further research is also needed to establish biomarker-driven strategies to select which patients may benefit from immunotherapy and identify potential mechanisms of resistance.

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“…The increasing efficacy of immunotherapy with immune checkpoint inhibitors (ICIs) has deeply changed life expectancy for different types of fatal cancer: melanoma, lung cancer, renal carcinoma, advanced squamous cell carcinoma of the head and neck or skin districts, some colorectal cancers, and refractory lymphomas (1)(2)(3)(4)(5). At the same time, it is widely recognized that the therapeutic indication of ICI cannot be extended to all subtypes of tumor histology since it has been observed that majority of patients are not responsive (6).…”

Section: Introductionmentioning

confidence: 99%

Are Molecular Alterations Linked to Genetic Instability Worth to Be Included as Biomarkers for Directing or Excluding Melanoma Patients to Immunotherapy?

et al. 2021

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The improvement of the immunotherapeutic potential in most human cancers, including melanoma, requires the identification of increasingly detailed molecular features underlying the tumor immune responsiveness and acting as disease-associated biomarkers. In recent past years, the complexity of the immune landscape in cancer tissues is being steadily unveiled with a progressive better understanding of the plethora of actors playing in such a scenario, resulting in histopathology diversification, distinct molecular subtypes, and biological heterogeneity. Actually, it is widely recognized that the intracellular patterns of alterations in driver genes and loci may also concur to interfere with the homeostasis of the tumor microenvironment components, deeply affecting the immune response against the tumor. Among others, the different events linked to genetic instability—aneuploidy/somatic copy number alteration (SCNA) or microsatellite instability (MSI)—may exhibit opposite behaviors in terms of immune exclusion or responsiveness. In this review, we focused on both prevalence and impact of such different types of genetic instability in melanoma in order to evaluate whether their use as biomarkers in an integrated analysis of the molecular profile of such a malignancy may allow defining any potential predictive value for response/resistance to immunotherapy.

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Validation of Progression-Free Survival Rate at 6 Months and Objective Response for Estimating Overall Survival in Immune Checkpoint Inhibitor Trials

Cited by 38 publications

References 25 publications

Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects

Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects

Lights and Shadows in Immuno-Oncology Drug Development

Are Molecular Alterations Linked to Genetic Instability Worth to Be Included as Biomarkers for Directing or Excluding Melanoma Patients to Immunotherapy?

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