Skip to main content

Advertisement

SpringerLink
Log in

A Survey of Survival Outcomes for Targeted Cancer Drugs Approved by the US Food and Drug Administration

  • Original Research
  • Published:
Therapeutic Innovation & Regulatory Science Aims and scope Submit manuscript

Abstract

Background

The last two decades have witnessed the vigorous development of targeted cancer drugs and the potent therapeutic effects of these drugs have been validated by various true and surrogate end points. Overall survival (OS) and progression-free survival (PFS) outcomes were two important end points used in targeted cancer drugs clinical trials but investigation on which was rare as a consequence of inherent heterogeneity and complexity. Here, we present the review and analysis of OS and PFS outcomes of all targeted cancer drugs approved by the U.S. Food and Drug Administration (FDA) through December 31, 2019, in the setting of clinical studies.

Methods

The targeted cancer drug directory was accessed via NCI website. The survival outcomes of those drugs in the setting of clinical trials were collected from publicly available Package Inserts and ClinicalTrials.gov. Median overall (OS) and progression-free survival (PFS) outcomes were summarized for targeted cancer drugs that were evaluated as monotherapies in clinical trials, contributions of targeted drugs to combination therapies in terms of survival benefit were analyzed, survival outcomes of FDA-approved first-line targeted therapies in different cancers were investigated, and the correlation between the absolute OS gain (ΔOS) and PFS gain (ΔPFS) as well as the hazard ratios for PFS (HRPFS) and OS (HROS) between comparative arms of available randomized clinical trials was evaluated.

Results

A total of 223 indications for 126 targeted cancer drugs have been approved by the FDA through December 31, 2019, among which 28 indications of 23 drugs have been approved for first-line therapies. Eighty indications for leukemia, lymphoma, and rare cancer types without survival data were excluded in the investigation of survival outcomes. For the remaining 143 indications, 99 were approved as monotherapies and 72 were approved as combination therapies. Among monotherapy subset, 18 of 72 (25%) indications with available OS outcomes have maximum median OS less than 12 months, 55 of 72 (76%) drug indications have maximum median OS less than 24 months, and 67 of 72 (93%) have maximum median OS less than 36 months. Regarding PFS, 38 of 88 (43%) drug indications have maximum median PFS less than 6 months, 69 of 88 (78%) drug indications have maximum median PFS less than 12 months, and 84 of 88 (95%) drug indications have maximum median PFS less than 24 months. The addition of targeted drugs to combination regimens under FDA’s approval provided notable survival benefit, but the median value of OS gain rate of the available combination regimens was lower than that of PFS. The univariate Spearman Rank correlation coefficient suggested a significant positive correlation between ΔOS and ΔPFS (R = 0.62) but a weak correlation between HROS and HRPFS (R = 0.11) in 46 randomized clinical trials that investigated contributions of targeted cancer drugs to combination therapies with available data. A moderate correlation between ΔOS and ΔPFS (R = 0.43) and a rather weak correlation between HROS and HRPFS (R = 0.07) were also found in other randomized clinical trials that included in our study with available data.

Conclusions

The survival benefit provided by targeted cancer drugs varied a lot among cancer types. Though targeted cancer drugs showed improvements in both OS and PFS in approved combination regimens, the median value of OS gain rate was lower than that of PFS. As only weak correlation was found between HRPFS and HROS, the evidence supporting the use of PFS as a surrogate to OS in the setting of targeted cancer drugs might also be limited.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. National Cancer Institute (NCI). Targeted therapy to treat cancer. https://www.cancer.gov/about-cancer/treatment/types/targeted-therapies. Accessed 31 Dec 2019.

  2. Lee YT, Tan YJ, Oon CE. Molecular targeted therapy: treating cancer with specificity. Eur J Pharmacol. 2018;834:188–96.

    Article  CAS  Google Scholar 

  3. National Cancer Institute (NCI). What targeted therapies have been approved for specific types of cancer? https://www.cancer.gov/about-cancer/treatment/types/targeted-therapies. Accessed 31 Dec 2019.

  4. Johnson JR, Williams G, Pazdur R. End points and United States Food and Drug Administration approval of oncology drugs. J Clin Oncol. 2003;21(7):1404–11.

    Article  Google Scholar 

  5. Lesko LJ, Atkinson AJ. Use of biomarkers and surrogate endpoints in drug development and regulatory decision making: criteria, validation, strategies. Annu Rev Pharmacol. 2001;41:347–66.

    Article  CAS  Google Scholar 

  6. Clinical trial endpoints for the approval of cancer drugs and biologics, guidance for industry, December 2018. https://www.fda.gov/regulatory-information/search-fda-guidance-documents. Accessed 31 Dec 2019.

  7. Pazdur R. Endpoints for assessing drug activity in clinical trials. Oncologist. 2008;13:19–21.

    Article  Google Scholar 

  8. Naci H, Smalley KR, Kesselheim AS. Characteristics of preapproval and postapproval studies for drugs granted accelerated approval by the US Food and Drug Administration. JAMA. 2017;318(7):626–36.

    Article  Google Scholar 

  9. Smith BD, DeZern AE, Bastian AW, Durie BGM. Meaningful endpoints for therapies approved for hematologic malignancies. Cancer Am Cancer Soc. 2017;123(10):1689–94.

    Google Scholar 

  10. Svensson S, Menkes DB, Lexchin J. Surrogate outcomes in clinical trials a cautionary tale. JAMA Intern Med. 2013;173(8):611–2.

    Article  Google Scholar 

  11. Prasad V, Kim C, Burotto M, Vandross A. The strength of association between surrogate end points and survival in oncology: a systematic review of trial-level meta-analyses. JAMA Intern Med. 2015;175(8):1389–98.

    Article  Google Scholar 

  12. 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.

    Article  Google Scholar 

  13. Blumenthal GM, Karuri SW, Zhang H, Zhang LJ, Khozin S, Kazandjian D, et al. Overall response rate, progression-free survival, and overall survival with targeted and standard therapies in advanced non-small-cell lung cancer: US Food and Drug Administration trial-level and patient-level analyses. J Clin Oncol. 2015;33(9):1008+.

    Article  Google Scholar 

  14. Shi Q, Sargent DJ. Meta-analysis for the evaluation of surrogate endpoints in cancer clinical trials. Int J Clin Oncol. 2009;14(2):102–11.

    Article  Google Scholar 

  15. Downing NS, Aminawung JA, Shah ND, Krumholz HM, Ross JS. Clinical trial evidence supporting FDA approval of novel therapeutic agents, 2005–2012. JAMA. 2014;311(4):368–77.

    Article  CAS  Google Scholar 

  16. Redberg RF. Faster drug approvals are not always better and can be worse. JAMA Intern Med. 2015;175(8):1398–1398.

    Article  Google Scholar 

  17. Carpenter D, Kesselheim AS, Joffe S. Reputation and precedent in the bevacizumab decision. N Engl J Med. 2011;365(2):e3.

    Article  CAS  Google Scholar 

  18. Ocana A, Amir E, Vera F, Eisenhauer EA, Tannock IF. Addition of bevacizumab to chemotherapy for treatment of solid tumors: similar results but different conclusions. J Clin Oncol. 2011;29(3):254–6.

    Article  CAS  Google Scholar 

  19. RStudio Team. RStudio: Integrated Development for R. Boston: RStudio, PBC; 2020. http://www.rstudio.com/.

  20. Miller KD, Nogueira L, Mariotto AB, Rowland JH, Yabroff KR, Alfano CM, et al. Cancer treatment and survivorship statistics, 2019. CA Cancer J Clin. 2019;69(5):363–85.

    Article  Google Scholar 

  21. Lakdawalla DN, Chou JW, Linthicum MT, MacEwan JP, Zhang J, Goldman DP. Evaluating expected costs and benefits of granting access to new treatments on the basis of progression-free survival in non-small-cell lung cancer. JAMA Oncol. 2015;1(2):196–202.

    Article  Google Scholar 

  22. Ott PA, Hodi FS, Kaufman HL, Wigginton JM, Wolchok JD. Combination immunotherapy: a road map. J Immunother Cancer. 2017;5:16.

    Article  Google Scholar 

  23. Zahorowska B, Crowe PJ, Yang JL. Combined therapies for cancer: a review of EGFR-targeted monotherapy and combination treatment with other drugs. J Cancer Res Clin. 2009;135(9):1137–48.

    Article  CAS  Google Scholar 

  24. Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell. 2015;161(2):205–14.

    Article  CAS  Google Scholar 

  25. Mincu RI, Mahabadi AA, Michel L, Mrotzek SM, Schadendorf D, Rassaf T, et al. Cardiovascular adverse events associated with BRAF and MEK inhibitors: a systematic review and meta-analysis. JAMA Netw Open. 2019;2(8):e198890.

    Article  Google Scholar 

Download references

Funding

The authors received no financial support for the research, authorship, or publication of this article.

Author information

Authors and Affiliations

  1. School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai, 201203, China

    Qian He BS & Liming Shao PhD

  2. Shanghai Center for iDrug Discovery & Development, 826 Zhangheng Road, Shanghai, 201203, China

    Qiu Li MSc & Liming Shao PhD

  3. Huadong Hospital Affiliated to Fudan University, 221 West Yan’an Road, Jing’an, Shanghai, 200040, China

    Fanzhen Lv MD

  4. Tufts Center for the Study of Drug Development, Tufts University School of Medicine, Boston, MA, USA

    Kenneth I. Kaitin PhD

Authors
  1. Qian He BS
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qiu Li MSc
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fanzhen Lv MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kenneth I. Kaitin PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Liming Shao PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

LMS and QH conceived and designed the study. QH evaluated the data and wrote the manuscript. QL and FZL devised the study and contributed to the manuscript. KIK and LMS reviewed and edited the manuscript. The authors would like to acknowledge LX for the assistance with statistical analysis for this study. All authors read and approved the manuscript.

Corresponding author

Correspondence to Liming Shao PhD.

Ethics declarations

Conflict of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplementary information

Below is the link to the electronic supplementary material.

(DOCX 144 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, Q., Li, Q., Lv, F. et al. A Survey of Survival Outcomes for Targeted Cancer Drugs Approved by the US Food and Drug Administration. Ther Innov Regul Sci 55, 676–684 (2021). https://doi.org/10.1007/s43441-021-00264-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s43441-021-00264-1

Keywords

Search

Navigation