This study is in patients with metastatic breast cancer; it’s based on real-world data from the imCORE network and the Flatiron database. The goal of this study is to evaluate surrogate endpoints in patients with metastatic breast cancer. We evaluated two surrogate endpoints, the first one being real world progression free survival, the second one being time to next line of therapy. We looked at these endpoints in relation to the gold standard which is overall survival.

We evaluated the correlation using dedicated copula models that are adapted for survival endpoints. We had a cohort of around 10,000 patients with metastatic breast cancer and for the current abstract we looked at the overall population but also at the stratification based on prognostic subgroups of metastatic disease. So patients were classified in a subgroup based on the location of their metastatic disease, so whether they had brain mets, whether they had liver mets, other visceral mets and maybe only bone mets. That would be the main stratification into four subgroups that are prognostically significant based on previous studies.

What we saw overall was in the overall population meaningful correlation for real world PFS with overall survival but also TTNT, or time to next line of therapy, with overall survival. Once certified across subgroups we also saw the same correlation being maintained across all subgroups for both surrogate endpoints.

So what is the main goal of the study? It’s to establish that these endpoints are being good surrogates for overall survival and eventually in the design of clinical trials, so this space so far in retrospective data. But eventually if these endpoints are fully validated this would help achieve a design of clinical trial that will incur shorter follow-up and also lower sample size, meaning potentially more rapid advances in the field of breast cancer therapy. 

Overall survival, if used as an endpoint in clinical trials, especially for a patient who has cancer, presents with a need for a very large sample size, that’s one, and also a very long follow-up because usually patients are able to benefit from therapies that prolong their survival by many years sometimes. So this means that the trial would require a very large period to be followed and also a very large sample size in order to achieve the statistical thresholds that are required. So in using other surrogate endpoints, if these are actually validated, instead of overall survival which is usually considered as the gold standard, if these surrogate endpoints are validated we can use them instead of overall survival. So meaning trials could go even faster and we could evaluate novel therapies using endpoints that are more easily acquired and more easily achieved. This would help more rapidly advance the field.

Is an agreed standard of validating surrogate endpoints required?

Yes. Actually the overall approach that we are working on and which has not been fully described in this abstract is the two-stage meta-analytical approach for the validation of surrogate endpoints. What we show here in this abstract is only related to the first condition and now there is also additional work being conducted to validate the second condition which is more related to patient-level data. In this case, if the two conditions are validated, so there is a correlation of surrogate endpoints but also there is also correlation across different clinical conditions and a relation to different clinical contexts and more looking at the patient-level data and the second condition is also validated this would technically mean an overall validation of the surrogate endpoint. This is one of the standards that are established for the thorough evaluation of surrogate endpoints.