One of the most interesting sessions I attended at this year’s American Society of Clinical Oncology (ASCO) annual meeting in Chicago was the Clinical Science Symposium (CSS) on the next generation of EGFR inhibitors.
We’ve previously written on the blog about the data for AZD9291 and CO-1686 presented at ASCO, but the CSS also featured an informative discussion by Larry Schwartz, MD, Professor of Radiology at Columbia University Medical Center which raised questions about how we should evaluate new lung cancer drugs.
In a presentation entitled, “Getting the Right Drug to the Right Patient Faster,” Schwartz who is a diagnostic radiologist, discussed and critiqued abstract 8012 by Gideon Michael Blumenthal and colleagues at the U.S. Food and Drug Administration (FDA).
A meta-analysis of fifteen trials involving 12,534 patients (median N = 698) from nine experimental agents (tyrosine kinase inhibitor = 5, chemotherapy = 2, monoclonal antibody = 2) submitted to the FDA for treatment of metastatic non-small cell lung cancer (NSCLC) cancer in initial or supplemental New Drug or Biologics License Applications since 2003 was performed by Blumenthal and colleagues.
Their analysis showed a strong correlation (R² of 0.89) between overall response rate (ORR) and progression-free-survival (PFS) but only a weak or no correlation between ORR and overall survival (OS) (R² of 0.07) or between PFS and OS (R² of 0.09).
Dr Blumenthal noted in his conclusion that further work is ongoing to corroborate these findings given the lack of correlation between OS and ORR could have been due to high cross-over, under-power and long post-progression survival.
He went on to note that what the findings do show is that “a drug with a large effect on ORR is likely to have a large effect on PFS, conversely a drug with a small ORR may have a small effect on PFS.”
The debate around objective response and outcomes is a very interesting one, as is the drive to find better biomarkers of response to improve chances of clinical trial success.
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Bevacizumab (Avastin®) should be withdrawn for metastatic breast cancer. That is the unequivocal recommendation of the Oncology Drugs Advisory Committee (ODAC) yesterday.
Despite the passionate patient advocacy in favor of continued approval, withdrawal is the right decision and it is hard to see the FDA overruling ODAC, given the safety issues such as bowel perforations and relative lack of efficacy. The patient advocacy at this week’s public hearing was fundamentally biased, those who died early and who received no treatment benefit are not alive to stand up and share their experiences.
The bottom line is that Genentech were unable to identify the sub-set of patients who might benefit from the drug. They simply did not have the data, and the reality is that treating all potential HER2- patients in the hope of finding the few who might respond is not a rational drug development or marketing strategy, especially when those that don’t respond may do worse on the drug.
Personalized medicine requires a thorough understanding of the science and molecular biology of a disease. Pfizer recently showed an excellent example of this with crizotinib that targets ALK mutations in non small cell lung cancer (NSCLC).
It is disappointing that a scientifically orientated company such as Genentech would continue to try and push Avastin in Breast Cancer when the data is clearly unconvincing to ODAC. But, if we look at how Genentech approached the Lucentis v Off-label Avastin issue in AMD, with a 40x higher cost for using Lucentis, then what we see is that commercial decisions, and maximization of profit has become more important than doing what’s right for patients.
This is a flawed long-term strategy in my opinion. Society cannot afford to pay for treatments that don’t work in many patients or pay for treatments that are excessively priced. We are already seeing “pay for results” being introduced in Europe, notably England and Italy where payors are reimbursing companies only for those patients that respond.
Personalized medicine is the future. This requires targeted therapies that are aimed at patients who we can predict will have a good chance of responding based on our understanding of mutations, molecular biology and biomarkers.
Avastin in metastatic breast cancer is not an example of personalized medicine and should be withdrawn from the market for this indication.