In the development process of cancer treatment drugs, the U.S. FDA has increasingly stringent requirements for overall survival (OS) data, especially for emerging cancer treatment drugs. For many years, the FDA has accepted progression-free survival (PFS) as a key endpoint and surrogate measure for accelerated approval of new cancer drugs. However, with the increase in drug types and innovation in treatments, the FDA is now more inclined to require pharmaceutical companies to provide sufficient evidence to prove that their therapies can substantially extend patients' survival. In this regard, Dr. Vas Narasimhan, CEO of Novartis, raised the importance of pursuing more OS data in addition to PFS data during the company's quarterly earnings call. This article examines the reasons behind this shift in strategy, the impact it may have on the development and approval process of cancer drugs, and what this change may mean for patients and healthcare providers.
Overall survival data is critical for assessing the clinical effectiveness of cancer treatments because it directly reflects how long patients survive after treatment. Unlike PFS, which only measures the time from the start of treatment to disease progression or death, OS data reflects the most fundamental goal of cancer treatment - extending a patient's life. This is particularly critical in patients with advanced or metastatic cancer, for whom disease progression is often unavoidable and treatment is focused on maximizing survival and maintaining or improving quality of life. The FDA's emphasis on more reliable OS data demonstrates its commitment to ensuring that new anticancer drugs not only have the effect of slowing disease progression, but also make a difference in improving patients' overall survival and quality of life.
Why is the FDA increasing scrutiny of OS data?
For many years, PFS has been widely used as a surrogate endpoint for cancer drug approval and is often used as a surrogate for OS in clinical trials. Using PFS as a surrogate endpoint has several advantages. It allows clinical trials to be conducted in a shorter time frame with smaller sample sizes, and it also allows for the clinical benefit of treatment to be confirmed more quickly than waiting for OS data to be revealed. . In addition, PFS is also considered a clinically meaningful endpoint because it reflects the delay in disease progression in patients after receiving treatment.
Although progression-free survival is often used as a surrogate endpoint for evaluating cancer therapeutics, it has limitations in predicting overall survival, especially when patients progress and receive subsequent treatments, and the correlation between PFS and OS may become unclear. Secondly, PFS may not fully reflect all clinical benefits brought by treatment, especially when treatment cannot significantly improve the patient's overall survival or quality of life. For example, a treatment that slows disease progression but has severe side effects or fails to significantly improve overall survival may not be considered a clinically meaningful advance. In addition, over-reliance on PFS as the basis for approval may lead to the approval of some treatments that fail to significantly improve patient prognosis, especially when OS data are not collected and analyzed in a timely manner. Therefore, the FDA is increasingly requiring more reliable OS data in cancer drug research and development, especially for new drug categories where the relationship between PFS and OS may not be clear, to ensure that new treatments can not only delay disease progression, but more importantly Can substantially improve patients' survival and quality of life.
The FDA's understanding of the relationship between response rate, disease progression and survival is evolving, Richard Pazdur, MD, director of the FDA's Oncology Center of Excellence, explained at a joint FDA-AACR industry symposium in July that the long-term use of PFS endpoints is This arose when cytotoxic chemotherapy became routine therapy, where there was a strong correlation between response rate, disease progression, and survival. However, this may not always be true when newer drugs are used for treatment.
For example, in a clinical trial for metastatic castration-resistant prostate cancer, the radioactive drug Pluvicto developed by Novartis showed efficacy in delaying disease progression, with a median radiographic progression-free survival compared with hormone therapy. (rPFS) was extended by about six months. However, its impact on the OS remains unclear. This is partly because a significant number of patients in the clinical trial's control group switched to Pluvicto after experiencing a worsening of their disease, which affects the clarity of the overall survival data. Therefore, despite the positive results in halting disease progression, there is uncertainty about whether Pluvicto will be approved quickly. This situation highlights the limitations of using PFS as a surrogate endpoint and the importance of more conclusive overall survival data when evaluating whether anticancer drugs actually improve patient outcomes.
▲Pluvicto treatment significantly extends radiographic progression-free survival in metastatic castration-resistant prostate cancer
Dr. Pazdur further pointed out that although some of the newly approved drugs showed minimal improvement in PFS or response rate, these drugs showed a positive impact when analyzing the OS data. This suggests that when evaluating the benefit of new cancer treatments, in addition to considering the impact on PFS, overall survival data are also crucial. By requiring more evidence of clinical benefit, the FDA hopes to ensure that cancer drugs actually improve patient outcomes and don't just slow disease progression.
A 2018 paper published in JAMA Network Open, a sub-journal of the Journal of the American Medical Association (JAMA), concluded that “PFS cannot fully reflect the benefits of PD-1 inhibitors,” meaning that overall survival should still be It is the gold standard endpoint in PD-1 inhibitor trials.
This study conducted a correlation and meta-analysis of randomized controlled trials of PD-1 inhibitors (mainly nivolumab and pembrolizumab) in adult patients with solid tumors and evaluated PFS and OS based on clinical outcome correlations and treatment effect size differences. The analysis results found that OS and PFS were not significantly related in terms of median and median gain, but their hazard ratios were significantly related. PD-1 inhibitor treatment improves overall survival more than progression-free survival.
Additionally, drugs for advanced solid epithelial cancers approved by regulators between 2005 and 2010 with PFS as the primary endpoint did not necessarily show an increase in OS, according to a book published by the Agency for Healthcare Research and Quality, part of HHS.
▲Treatments for advanced solid epithelial cancer with PFS as the primary endpoint approved by regulatory agencies between 2005 and 2010
The U.S. FDA's requirements for OS data continue to increase during the development and approval process of cancer drugs. The impact of this policy is far-reaching. This potential regulatory change is expected to have a significant impact on the cancer drug development process, as it will force drug development companies to collect and analyze more comprehensive patient outcome data, including not only overall survival, but also quality-of-life related measures. . This requirement could extend drug development timelines, increase costs, and increase the complexity of clinical trials. However, such a shift could also have more profound clinical benefits for patients, as treatments would be evaluated based on their ability to improve overall survival and quality of life rather than simply slowing disease progression.
As drug development organizations face new challenges in adapting to OS data requirements, there are several factors that need to be considered. First, compared with the collection of PFS data, collecting and analyzing OS data is often more complex and time-consuming, requiring longer follow-up times and larger sample sizes. Secondly, when one treatment regimen is significantly better than another regimen in terms of OS, using OS as the endpoint may involve ethical considerations. In some cases, it can also be challenging to justify continuing an experiment that is significantly inferior on the OS. In addition, difficulties may arise in defining and measuring OS, especially when patients may receive multiple lines of treatment or have other confounding factors that may affect survival outcomes, such as comorbidities or other health problems. Finally, there may also be some challenges in interpreting OS data, especially if there are differences in patient populations or treatment regimens across trials. Despite these challenges, drug developers are increasingly recognizing the increasing importance of collecting reliable OS data in order to demonstrate the clinical benefit of their treatment regimens and meet the evolving standards of regulatory agencies.
Conclusion:
Taken together, the FDA's emphasis on more reliable OS data marks a critical shift in the cancer drug development landscape. This move is not only a pursuit of more stringent standards of evidence of clinical benefit, but also reflects a growing commitment to patient-centered care, specifically prioritizing real impact on patient survival time and quality of life. While the increased demand for OS data presents a range of challenges for drug developers, including longer trial durations and potential increased costs, this is all aimed at ensuring that drugs brought to market can provide substantial life extension for patients. benefit. The FDA's role in this process not only reflects its innovation in the standards for evaluating new treatments, but also drives oncology research and development toward more meaningful patient outcomes. As the industry adapts to these rigorous standards, it promises not just more effective cancer treatments, but a new paradigm in which the value of a treatment will be demonstrated through its benefit to patients as they face their disease. Measured by actual improvements in quality of life during challenges.