Clinical Benefit and Regulatory Outcomes of Cancer Drugs Receiving Accelerated Approval.

Importance: The US Food and Drug Administration's (FDA) accelerated approval pathway allows approval of investigational drugs treating unmet medical needs based on changes to surrogate measures considered "reasonably likely" to predict clinical benefit. Postapproval clinical trials are then required to confirm whether these drugs offer clinical benefit. Objective: To determine whether cancer drugs granted accelerated approval ultimately demonstrate clinical benefit and to evaluate the basis of conversion to regular approval. Design, Setting, and Participants: In this cohort study, publicly available FDA data were used to identify cancer drugs granted accelerated approval from 2013 to 2023. Main Outcomes and Measures: Demonstrated improvement in quality of life or overall survival in accelerated approvals with more than 5 years of follow-up, as well as confirmatory trial end points and time to conversion for drug-indication pairs converted to regular approval. Results: A total of 129 cancer drug-indication pairs were granted accelerated approval from 2013 to 2023. Among 46 indications with more than 5 years of follow-up (approved 2013-2017), approximately two-thirds (29, 63%) were converted to regular approval, 10 (22%) were withdrawn, and 7 (15%) remained ongoing after a median of 6.3 years. Fewer than half (20/46, 43%) demonstrated a clinical benefit in confirmatory trials. Time to withdrawal decreased from 9.9 years to 3.6 years, and time to regular approval increased from 1.6 years to 3.6 years. Among 48 drug-indication pairs converted to regular approval, 19 (40%) were converted based on overall survival, 21 (44%) on progression-free survival, 5 (10%) on response rate plus duration of response, 2 (4%) on response rate, and 1 (2%) despite a negative confirmatory trial. Comparing accelerated and regular approval indications, 18 of 48 (38%) were unchanged, while 30 of 48 (63%) had different indications (eg, earlier line of therapy). Conclusions and Relevance: Most cancer drugs granted accelerated approval did not demonstrate benefit in overall survival or quality of life within 5 years of accelerated approval. Patients should be clearly informed about the cancer drugs that use the accelerated approval pathway and do not end up showing benefits in patient-centered clinical outcomes.

Administrative action on drug pricing: Lessons and opportunities for the Center for Medicare and Medicaid Innovation.

BACKGROUND: In October 2022, the Biden administration issued an executive order to the Center for Medicare and Medicaid Innovation (CMMI) to develop new health care payment and delivery models to lower prescription drug costs and promote access to innovative therapies. In response, the agency proposed 3 novel drug payment models for testing. OBJECTIVE: To understand the impact that CMMI demonstration projects can have on the prescription drug market. METHODS: We examined each of the models listed on the CMMI website and searched the Federal Register and news articles for additional models that contained interventions related to patient out-of-pocket drug costs, Medicare drug spending, or Medicaid drug spending. We excluded models with indirect effects on drug costs (for example, bundled payments). We comprehensively reviewed all previous cases in which CMMI has attempted models addressing prescription drug costs and spending and evaluated the circumstances, impact, and lessons learned that may aid policymakers in the design and implementation of new models. RESULTS: We identified 9 CMMI models containing direct interventions related to drug costs. Among prior models addressing drug prices, nearly half (44%, 4/9) were not implemented because of their scope, voluntary nature, and procedural challenges. No implemented models met the CMMI standard for expansion, although key elements of the Senior Savings model limiting monthly insulin costs to $35 were later incorporated into the Inflation Reduction Act. CONCLUSIONS: In future CMMI implementation efforts, we suggest maximizing voluntary collaboration when selection bias concerns are minimal, using mandatory models when not, ensuring that the geographic scope is not overly ambitious, and adhering closely to statutory authority and established administrative procedure to minimize legal challenges and maximize model demonstration utility.