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. 2020 Nov;123(11):1686-1696.
doi: 10.1038/s41416-020-01050-w. Epub 2020 Sep 11.

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

Katy Cooper  1 , Paul Tappenden  2 , Anna Cantrell  2 , Kate Ennis  2
Affiliations

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

Katy Cooper et al. Br J Cancer. 2020 Nov.

Abstract

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. PRISMA flow diagram for study inclusion.
Illustrates the number of references retrieved from the literature searches and included/excluded at each stage of screening.
Fig. 2
Fig. 2. Correlation (r or rs) between absolute (individual-level) values of ORR and PFS.
For each study, the plot illustrates the range of correlation coefficients across all subgroup analyses. N represents the number of studies included in each meta-regression. CUP cancer of unknown primary, NHL non-Hodgkin’s lymphoma, NSCLC non-small cell lung cancer, ORR overall response rate, PFS progression-free survival, SCLC small cell lung cancer.
Fig. 3
Fig. 3. Correlation (r or rs) between absolute (individual-level) values of ORR and OS.
For each study, the plot illustrates the range of correlation coefficients across all subgroup analyses. N represents the number of studies included in each meta-regression. AML, acute myeloid leukaemia, CUP cancer of unknown primary, NSCLC non-small cell lung cancer, ORR overall response rate, OS overall survival, SCLC small cell lung cancer.
Fig. 4
Fig. 4. Regression R2 between treatment effects (trial-level) for ORR and PFS.
For each study, the plot illustrates the range of correlation coefficients across all subgroup analyses. N represents the number of studies included in each meta-regression. NSCLC non-small cell lung cancer, ORR overall response rate, PFS progression-free survival.
Fig. 5
Fig. 5. Regression R2 between treatment effects (trial-level) for ORR and OS.
For each study, the plot illustrates the range of correlation coefficients across all subgroup analyses. N represents the number of studies included in each meta-regression. NSCLC non-small cell lung cancer, ORR overall response rate, OS overall survival, SCLC small cell lung cancer.
See this image and copyright information in PMC

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