Some statistical considerations in the clinical development of cancer immunotherapies

Huang, Bo

doi:10.1002/pst.1835

Cited by 25 publications

(19 citation statements)

References 57 publications

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“…One area is cancer immunotherapies targeting immune cells instead of targeting the cancer cell, as did traditional chemotherapies and targeted therapies (eg, Menis et al). Many clinical trials have shown that immunotherapy as a monotherapy generally has (a) a delayed treatment effect (ie, the survival curves overlap at the start of the study and then separate) and (b) a durable anticancer effect, resulting in a long, flat tail of the survival curve (eg, Huang). Consequently, analyses that assume proportional hazards may no longer be valid, and the popular log‐rank test may not be optimal.…”

Section: Use Of the Win Ratio With Nonproportional Hazardsmentioning

confidence: 99%

The win ratio: Impact of censoring and follow‐up time and use with nonproportional hazards

Dong¹,

Huang

Chang³

et al. 2019

Pharmaceutical Statistics

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The win ratio has been studied methodologically and applied in data analysis and in designing clinical trials. Researchers have pointed out that the results depend on follow-up time and censoring time, which are sometimes used interchangeably. In this article, we distinguish between follow-up time and censoring time, show theoretically the impact of censoring on the win ratio, and illustrate the impact of follow-up time. We then point out that, if the treatment has long-term benefit from a more important but less frequent endpoint (eg, death), the win ratio can show that benefit by following patients longer, avoiding masking by more frequent but less important outcomes, which occurs in conventional time-to-first-event analyses. For the situation of nonproportional hazards, we demonstrate that the win ratio can be a good alternative to methods such as landmark survival rate, restricted mean survival time, and weighted log-rank tests. KEYWORDS hazard ratio, landmark survival rate, log-rank test, prioritized pairwise comparisons, restricted mean survival time 1 | INTRODUCTIONMuch interest has focused on composite time-to-event endpoints when the component outcomes can be prioritized according to their clinical importance. The win ratio 1 takes into account the clinical importance order among the components, and its simple and intuitive derivation make it attractive, compared with other methods for prioritized multiple outcomes such as weighted composites and rank tests. The net benefit 2-4 (proportion in favor of treatment) is the difference in win proportion between the two groups, so the two methods are closely related.The win ratio method has received much attention in methodological research. 5-14 One possible drawback is that it depends on follow-up time and censoring. [5][6][7][8]15 To reduce the impact of censoring (or follow-up) time, Oakes 7 proposed to calculate the win ratio from the time-to-event information as of a common time, c. Further, Rauch et al 16 argued that the win ratio should not be used in the presence of censoring, and they gave an illustrative example under proportional hazards (see Section 5.2 of Rauch et al 16 ). Also, some discussions of the win ratio have used censoring time and followup time interchangeably in a broad sense.In practice, the win ratio method has been used for many retrospective analyses of clinical trials and applied in study designs. In particular, together with the Finkelstein-Schoenfeld test, 17 the win ratio was used in the primary analysis for the tafamidis Phase III transthyretin amyloid cardiomyopathy (ATTR-ACT) study. 18,19 On the composite primary endpoint of all-cause mortality and frequency of cardiovascular(CV)-related hospitalization, the (stratified) win ratio

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Section: Use Of the Win Ratio With Nonproportional Hazardsmentioning

confidence: 99%

The win ratio: Impact of censoring and follow‐up time and use with nonproportional hazards

Dong¹,

Huang

Chang³

et al. 2019

Pharmaceutical Statistics

Self Cite

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show abstract

“…However, as it was necessary to introduce the ir-RECIST criteria in order to meet the novel requirements of CIT, it will likewise be necessary to adapt our statistical analysis. Possible methods to better incorporate pseudoprogression and additional new phenomena into statistics might include time-specific endpoints, immune-related endpoints, restricted mean survival time or generalized pairwise comparison[26].…”

Section: Discussionmentioning

confidence: 99%

Pseudo- or real progression? An ovarian cancer patient under nivolumab: A case report

Passler¹,

Taube²,

Sehouli³

et al. 2019

WJCO

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BACKGROUND Checkpoint-Inhibition has revolutionized the treatment for several entities such as melanoma and renal cell carcinoma. The first encouraging experience in ovarian cancer was reported for nivolumab, a fully humanized anti-programmed death-1 antibody. Pseudoprogression is a new phenomenon associated with these novel immuno-oncologic agents. It can be explained by infiltrating leucocytes and edema that result in a temporary increase in tumor size and delayed subsequent shrinkage due to tumor cell destruction. CASE SUMMARY We report on a 47-year old patient with platinum-resistant ovarian cancer that was treated off-label with nivolumab 3mg/kg iv d1q14d. She first experienced classic pseudoprogression with inguinal lymph node swelling after cycle two and subsequent shrinkage. After 6 cycles she presented with rectal bleeding and progressive disease was diagnosed due to new tumor infiltration into the rectum. CONCLUSION Clinicians should be aware of pseudoprogression, its underlying mechanisms and strategies to discriminate pseudo- from real progression in ovarian cancer.

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“…These two aspects of the survival curves could potentially lead to underestimation of trial duration and loss of power to detect treatment effects [ 20 ]. Any statistical test used to compare survival curves between treatment arms should be described in detail; the unique characteristics of IO Kaplan-Meier curves have led to varied recommendations concerning tests that differently weight survival differences early versus late in the time course [ 21 , 22 ].…”

Section: Efficacy Reporting Standards For Io Trialsmentioning

confidence: 99%

Trial Reporting in Immuno-Oncology (TRIO): An American Society of Clinical Oncology-Society for Immunotherapy of Cancer Statement

Tsimberidou¹,

Levit²,

Schilsky³

et al. 2018

j. immunotherapy cancer

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PurposeTo develop recommendations for clinical trial reporting that address the unique efficacy, toxicity, and combination and sequencing aspects of immuno-oncology (IO) treatments.MethodsASCO and the Society for Immunotherapy of Cancer (SITC) convened a working group that consisted of practicing medical oncologists, immunologists, clinical researchers, biostatisticians, and representatives from industry and government to develop Trial Reporting in Immuno-Oncology (TRIO) recommendations. These recommendations are based on expert consensus, given that existing data to support evidence-based recommendations are limited.ConclusionThe TRIO recommendations are intended to improve the reporting of IO clinical trials and thus provide more complete evidence on the relative benefits and risks of an IO therapeutic approach. Given the rapid expansion of the number of IO clinical trials and ongoing improvements to the evidence base supporting the use of IO treatments in clinical care, these recommendations will likely need regular revision as the IO field develops.

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Some statistical considerations in the clinical development of cancer immunotherapies

Cited by 25 publications

References 57 publications

The win ratio: Impact of censoring and follow‐up time and use with nonproportional hazards

The win ratio: Impact of censoring and follow‐up time and use with nonproportional hazards

Pseudo- or real progression? An ovarian cancer patient under nivolumab: A case report

Trial Reporting in Immuno-Oncology (TRIO): An American Society of Clinical Oncology-Society for Immunotherapy of Cancer Statement

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