FDA Acceptance of Surrogate End Points for Cancer Drug Approval: 1992-2019 | Cancer Biomarkers | JAMA Internal Medicine | JAMA Network
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Figure.  First-Surrogate–Based Regular and Accelerated Cancer Drug Approvals and Subsequent Use, 1992-2019
First-Surrogate–Based Regular and Accelerated Cancer Drug Approvals and Subsequent Use, 1992-2019

PFS indicates progression-free survival; RR, response rate; the listed numbers represent the following: 1, acute lymphoblastic leukemia (RR); 2, metastatic breast cancer (PFS); 3, indolent b-cell lymphoma (RR); 4, melanoma (RR); 5, T-cell lymphoma (RR); 6, hairy cell leukemia (RR); 7, prostate cancer (RR); 8, acute myeloid leukemia (RR); 9, gastric cancer (RR); 10, pancreatic cancer (RR); 11, myelodysplastic syndrome (RR); 12, metastatic breast cancer (RR); 13, kidney cancer (PFS); 14, gastrointestinal stromal tumor (PFS); 15, multiple myeloma (PFS); 16, ovarian cancer (PFS); 17, dermatofibroma protuberans (RR); 18, systemic mastocytosis (RR); 19, chronic eosinophilic leukemia (RR); 20, localized breast cancer (PFS); 21, mantle cell lymphoma (RR); 22, chronic lymphocytic leukemia (PFS); 23, melanoma (PFS); 24, medullary thyroid cancer (PFS); 25, neuroendocrine tumor (PFS); 26, basal cell carcinoma (RR); 27, soft tissue sarcoma (PFS); 28, chronic myelogenous leukemia (RR); 29, non–small cell lung cancer (RR); 30, giant cell tumor of bone (RR); 31, non–small cell lung cancer (PFS); 32, differentiated thyroid cancer (PFS); 33, lymphoplasmacytic lymphoma (RR); 34, follicular lymphoma (PFS); 35, diffuse large B-cell lymphoma (RR); 36, Erdheim-Chester disease (RR); 37, prostate cancer (PFS); 38, anaplastic thyroid cancer (RR); 39, pheochromocytoma (RR); 40, T-cell lymphoma (PFS); 41, squamous cell carcinoma (RR); 42, neurotrophic tyrosine kinase receptor fusion solid tumor (RR); 43, localized breast cancer (RR); 44, metastatic breast cancer (RR); 45, colorectal cancer (RR); 46, T-cell lymphoma (RR); 47, ovarian cancer (RR); 48, brain cancer (RR); 49, acute myeloid leukemia (RR); 50, chronic myelogenous leukemia (RR); 51, chronic lymphocytic leukemia (RR); 52, gastrointestinal stromal tumor (RR); 53, indolent B-cell lymphoma (RR); 54, colorectal cancer (PFS); 55, localized breast cancer (PFS); 56, non–small cell lung cancer (RR); 57, multiple myeloma (RR); 58, pheochromocytoma (RR); 59, kidney cancer (RR); 60, metastatic breast cancer (PFS); 61, tuberous sclerosis: giant cell astrocytoma (RR); 62, Hodgkin lymphoma (RR); 63, anaplastic large cell lymphoma (RR); 64, tuberous sclerosis: renal angiomyolipoma (RR); 65, localized breast cancer (RR); 66, mantle cell lymphoma (RR); 67, melanoma (RR); 68, multiple myeloma (PFS); 69, urothelial cancer (RR); 70, head and neck squamous cell carcinoma (RR); 71, soft tissue sarcoma (PFS); 72, Merkel cell carcinoma (RR); 73, microsatellite instability-high solid tumor (RR); 74, follicular lymphoma (RR); 75, hepatocellular carcinoma (RR); 76, gastric cancer (RR); 77, cervical cancer (RR); 78, mediastinal B-cell lymphoma (RR); 79, small cell lung cancer (RR); 80, diffuse large B-cell lymphoma (RR).

Table,  Characteristics of Cancer Drugs Approved on the Basis of Surrogate End Points, 1992-2019
Characteristics of Cancer Drugs Approved on the Basis of Surrogate End Points, 1992-2019
1.
Kim  C, Prasad  V.  Cancer drugs approved on the basis of a surrogate end point and subsequent overall survival: an analysis of 5 years of US Food and Drug Administration approvals.   JAMA Intern Med. 2015;175(12):1992-1994. doi:10.1001/jamainternmed.2015.5868PubMedGoogle ScholarCrossref
2.
Kim  C, Prasad  V.  Strength of validation for surrogate end points used in the US Food and Drug Administration’s approval of oncology drugs.   Mayo Clin Proc. 2016;91(6)713-725. doi:10.1016/j.mayocp.2016.02.012PubMedGoogle Scholar
3.
Gyawali  B, Hey  SP, Kesselheim  AS.  Assessment of the clinical benefit of cancer drugs receiving accelerated approval.   JAMA Intern Med. 2019;179(7):906-913. doi:10.1001/jamainternmed.2019.0462PubMedGoogle ScholarCrossref
4.
Chen  EY, Joshi  SK, Tran  A, Prasad  V.  Estimation of study time reduction using surrogate end points rather than overall survival in oncology clinical trials.   JAMA Intern Med. 2019;179(5):642-647. doi:10.1001/jamainternmed.2018.8351PubMedGoogle ScholarCrossref
5.
Sun  J, Wei  Q, Zhou  Y, Wang  J, Liu  Q, Xu  H.  A systematic analysis of FDA-approved anticancer drugs.   BMC Syst Biol. 2017;11(suppl 5):87. doi:10.1186/s12918-017-0464-7PubMedGoogle ScholarCrossref
6.
Haslam  A, Hey  SP, Gill  J, Prasad  V.  A systematic review of trial-level meta-analyses measuring the strength of association between surrogate end-points and overall survival in oncology.   Eur J Cancer. 2019;106:196-211. doi:10.1016/j.ejca.2018.11.012PubMedGoogle ScholarCrossref
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    1 Comment for this article
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    The treatment of breast cancer has always been a challenge, since the drugs used, mainly chemotherapeutic agents, have low effectiveness ass
    valfredo Menezes, médico | Universidade Ferderal de Mato Grosso
    Valfredo da Mota Menezes*

    M.D., PhD, Associate Professor at the Faculty of Medicine of the Federal University of Mato Grosso - Brazil.
    valdamotamenezes@gmail.com

    In most of these studies, inclusion criteria were also similar, particularly that the lesion should be "measurable". The need for the lesion to be measurable is due to the fact that the entire effectiveness assessment is based on the measurement of the size of the tumor lesion by the RECIST criteria, that is, it was based only on the “tumor response”.
    The large (and negative) impression gained after reading the studies was that
    the patients simply “lent” their lesions to be “photographed” and measured, with the use of computed tomography or magnetic resonance imaging and bone scintigraphy. While the patients were using the medication, the lesions were measured to know whether or not changes in volume and/or size occurred, because the main outcome of effectiveness was “progression-free survival”, evaluated by the researcher, without any need to know if the patients were improving clinically. Thus, the term "survival" used here, is merely a figure of speech, because most of the participants of these studies had a good prognosis (ECOG status of zero or one). Moreover, in most of studies, the high incidence of adverse effects may have alerted the researchers about the allocation of patients to different groups, with alterations in doses and/or discontinuation of the medication. One question remains: could this possible awareness by the investigator have caused any bias in the results?
    Overall survival" was more than just a secondary outcome to be evaluated. However, however we don't know if sample size had sufficient power for this type of evaluation. Although, in most of studies, “Quality of Life” was an outcome taken into account, the results were omitted in most of them. I believe, as the majority of clinicians, that the large benefit of a drug for the treatment of cancer, should be, in addition to similar or superior effectiveness to current treatments (chemotherapy or other), to overcome the traumatic and devastating adverse effects of therapy. When considering a surrogate endpoint (“progression-free survival”) as the main outcome and considering "Quality of Life" as a secondary outcome or simply as "other outcomes", studies have raised several doubts about the effectiveness of different treatment of cancer, leaving, however, some certainties about their disadvantages.
    CONFLICT OF INTEREST: None Reported
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    Research Letter
    April 27, 2020

    FDA Acceptance of Surrogate End Points for Cancer Drug Approval: 1992-2019

    Author Affiliations
    • 1Knight Cancer Institute, Division of Hematology and Medical Oncology, Oregon Health & Science University, Portland
    • 2Department of Public Health and Preventive Medicine, Oregon Health & Science University, Portland
    JAMA Intern Med. 2020;180(6):912-914. doi:10.1001/jamainternmed.2020.1097

    The US Food and Drug Administration (FDA) approves cancer drugs based on direct measures of patient benefit—such as overall survival (OS) or quality of life—or surrogate measures, such as change in biomarker level or tumor size on imaging studies. Surrogate end points often have weak or unknown correlations with OS,1,2 and postmarketing studies are limited.3 A surrogate end point can be used repeatedly in a particular cancer setting, such as response rate (tumor shrinkage) in mantle cell lymphoma in 2013 (with ibrutinib and lenalidomide) and 2017 (with acalabrutinib) after it was accepted for the first time in 2006 (with bortezomib).4

    One open question is how often does the FDA approve a drug based on a surrogate end point that has never been used before in treating that type of cancer? In this study, we assess the frequency of surrogate measures used for the first time vs subsequent times in a cancer setting and the surrogate’s strength of correlation with patient-centered outcomes.

    Methods

    A retrospective review of cancer drugs approved from January 1992 through July 2019 on the basis of surrogate end points, either response rate or progression-free survival, was conducted using the FDA website and a previous systematic review.5 Data related to the drug, cancer type, approval basis, dates of approval, and postmarketing follow-up were extracted from FDA review documents, package inserts, or publications from PubMed (search terms were the drug name and cancer type).

    The primary outcome measure was the determination of whether the surrogate end point was used for the first time or subsequent times in treatment of that cancer type. If drug A (eg, bortezomib in 2006) is the first drug approved for the treatment of a particular cancer type (eg, mantle cell lymphoma), based on response rate, followed by drugs B and C (eg, ibrutinib and lenalidomide in 2013),4 also based on response rate, then A is considered to be first and B and C are subsequent. We did not count molecular subtypes as separate cancer types, and breast cancer was the only form that was separated into localized and metastatic types. The strength of correlation between the surrogate end point and OS in that cancer type was based on the results of previous studies.6 Approval dates were plotted to describe the timing of accelerated and regular approvals based on first or subsequent surrogate end points.

    Results

    We identified 194 unique drug authorizations for 132 drugs that were based on surrogate end points from 1992 through 2019. There were 89 accelerated approvals and 105 regular approvals (Table). A surrogate end point was used for the first time for a specific cancer type in 64 of 194 approvals (32.9%), and the remaining 130 of 194 (67.0%) were subsequent uses of the surrogate. The number of unique surrogate measure–cancer combinations accepted for drug approval has increased over time between 1992 and 2019 (Figure), to as many as 70 (36.1%) from 2016 through 2019 (Table). Most of these combinations had unknown postmarketing OS data (Table).

    When examining the strength of correlation between the surrogate end point and OS among the 64 first-surrogate–based approvals, we found that 39 (61%) had no documented correlation, 10 (16%) had a poor correlation (r ≤ 0.7), 1 (2%) had a medium correlation (0.70 < r <0.85), and only 3 (5%) had a high correlation (r ≥ 0.85). Eleven approvals (17%) had varied levels of correlation across multiple validation studies. Among the 49 approvals with low or unknown correlation, 23 (47%) were accelerated approvals, and 26 (53%) were regular approvals.

    Discussion

    The FDA has used surrogate end points approximately 194 times to approve cancer drugs since 1992, and about 1 in 3 times, a surrogate was used for the first time in a particular type of cancer. When this is the case, the strength of association between the surrogate end point and OS is often absent or weak. This means that the FDA’s use of these surrogate measures is justified neither by strength of association (ie, ability to predict gains in OS) nor previous first use, since 1 in 3 approvals constitute the use of a surrogate end point for the first time in the treament of a specific cancer type. Our study is limited by some missing FDA label updates before 2006 that are not publicly accessible.

    Surrogate end points can expedite trial completion compared with OS,4 but they add substantial uncertainty regarding whether the drugs involved improve quantity or quality of life.6 Moreover, the FDA rarely demands stringent confirmation of clinical benefit following market approval.3 We find that the FDA is steadily accepting more surrogate measures over time, which are not justified by scientific validity or adherence to regulatory precedent. This reflects a greater tolerance of risk, and if postmarketing studies are slow, incomplete, or demonstrate negative results, then patients experience harm and cost without the intended benefit.

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    Article Information

    Accepted for Publication: March 9, 2020.

    Published Online: April 27, 2020. doi:10.1001/jamainternmed.2020.1097

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Chen EY et al. JAMA Internal Medicine.

    Corresponding Author: Emerson Y. Chen, MD, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, OC14HO, Portland, OR 97239 (cheem@ohsu.edu).

    Author Contributions: Dr Chen had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Chen, Prasad.

    Acquisition, analysis, or interpretation of data: Chen, Haslam.

    Drafting of the manuscript: Chen.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Chen, Haslam.

    Supervision: Prasad.

    Conflict of Interest Disclosures: Dr Chen has received a lecture honorarium from Horizon CME. Dr Prasad reports research funding from Arnold Ventures; royalties from Johns Hopkins Press, Medscape; honoraria from grand rounds/lectures from universities, medical centers, nonprofit organizations, and professional societies; consulting fees from UnitedHealthcare; speaking fees from Evicore; and other support from Plenary Session podcast, which has Patreon backers. No other conflict of interest disclosures were reported.

    Funding/Support: This study was supported by Arnold Ventures (Haslam and Prasad).

    Role of the Funder/Sponsor: Arnold Ventures had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    References
    1.
    Kim  C, Prasad  V.  Cancer drugs approved on the basis of a surrogate end point and subsequent overall survival: an analysis of 5 years of US Food and Drug Administration approvals.   JAMA Intern Med. 2015;175(12):1992-1994. doi:10.1001/jamainternmed.2015.5868PubMedGoogle ScholarCrossref
    2.
    Kim  C, Prasad  V.  Strength of validation for surrogate end points used in the US Food and Drug Administration’s approval of oncology drugs.   Mayo Clin Proc. 2016;91(6)713-725. doi:10.1016/j.mayocp.2016.02.012PubMedGoogle Scholar
    3.
    Gyawali  B, Hey  SP, Kesselheim  AS.  Assessment of the clinical benefit of cancer drugs receiving accelerated approval.   JAMA Intern Med. 2019;179(7):906-913. doi:10.1001/jamainternmed.2019.0462PubMedGoogle ScholarCrossref
    4.
    Chen  EY, Joshi  SK, Tran  A, Prasad  V.  Estimation of study time reduction using surrogate end points rather than overall survival in oncology clinical trials.   JAMA Intern Med. 2019;179(5):642-647. doi:10.1001/jamainternmed.2018.8351PubMedGoogle ScholarCrossref
    5.
    Sun  J, Wei  Q, Zhou  Y, Wang  J, Liu  Q, Xu  H.  A systematic analysis of FDA-approved anticancer drugs.   BMC Syst Biol. 2017;11(suppl 5):87. doi:10.1186/s12918-017-0464-7PubMedGoogle ScholarCrossref
    6.
    Haslam  A, Hey  SP, Gill  J, Prasad  V.  A systematic review of trial-level meta-analyses measuring the strength of association between surrogate end-points and overall survival in oncology.   Eur J Cancer. 2019;106:196-211. doi:10.1016/j.ejca.2018.11.012PubMedGoogle ScholarCrossref
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