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VALIDATION OF SURROGATE ENDPOINTS IN ADVANCED SOLID TUMORS: SYSTEMATIC REVIEW OF STATISTICAL METHODS, RESULTS, AND IMPLICATIONS FOR POLICY MAKERS

Part of: Special Collection - Methods

Published online by Cambridge University Press:  02 September 2014

Oriana Ciani ,
Sarah Davis ,
Paul Tappenden ,
Ruth Garside ,
Ken Stein ,
Anna Cantrell ,
Everardo D. Saad ,
Marc Buyse  and
Rod S. Taylor
Oriana Ciani
Affiliation:
Peninsula Technology Assessment Group, University of Exeter Medical School, Veysey Building, Salmon Pool Lane, Exeter, EX2 4SG, UK CERGAS - Università Commerciale L. Bocconi, via Roentgen, 1 20136 Milan, [email protected]
Sarah Davis
Affiliation:
Decision Support Unit, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
Paul Tappenden
Affiliation:
Decision Support Unit, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
Ruth Garside
Affiliation:
European Centre for Environment and Human Health University of Exeter Medical School Knowledge Spa, Royal Cornwall Hospital, Truro, TR1 3HD, UK
Ken Stein
Affiliation:
Peninsula Technology Assessment Group, University of Exeter Medical School, Veysey Building, Salmon Pool Lane, Exeter, EX2 4SG, UK
Anna Cantrell
Affiliation:
Decision Support Unit, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK
Everardo D. Saad
Affiliation:
Dendrix Research, Rua Joaquim Floriano, 72/24, 04534-000, Sao Paulo, Brazil
Marc Buyse
Affiliation:
International Drug Development Institute, Avenue Provinciale, 30, 1340, Louvain-la-Neuve, Belgium
Rod S. Taylor
Affiliation:
Peninsula Technology Assessment Group, University of Exeter Medical School, Veysey Building, Salmon Pool Lane, Exeter, EX2 4SG, UK
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Abstract

Objectives: Licensing of, and coverage decisions on, new therapies should rely on evidence from patient-relevant endpoints such as overall survival (OS). Nevertheless, evidence from surrogate endpoints may also be useful, as it may not only expedite the regulatory approval of new therapies but also inform coverage decisions. It is, therefore, essential that candidate surrogate endpoints be properly validated. However, there is no consensus on statistical methods for such validation and on how the evidence thus derived should be applied by policy makers.

Methods: We review current statistical approaches to surrogate-endpoint validation based on meta-analysis in various advanced-tumor settings. We assessed the suitability of two surrogates (progression-free survival [PFS] and time-to-progression [TTP]) using three current validation frameworks: Elston and Taylor's framework, the German Institute of Quality and Efficiency in Health Care's (IQWiG) framework and the Biomarker-Surrogacy Evaluation Schema (BSES3).

Results: A wide variety of statistical methods have been used to assess surrogacy. The strength of the association between the two surrogates and OS was generally low. The level of evidence (observation-level versus treatment-level) available varied considerably by cancer type, by evaluation tools and was not always consistent even within one specific cancer type.

Conclusions: Not in all solid tumors the treatment-level association between PFS or TTP and OS has been investigated. According to IQWiG's framework, only PFS achieved acceptable evidence of surrogacy in metastatic colorectal and ovarian cancer treated with cytotoxic agents. Our study emphasizes the challenges of surrogate-endpoint validation and the importance of building consensus on the development of evaluation frameworks.

Keywords

surrogate outcomesPFSTTPmetastatic cancervalidation
Type
Methods
Information
International Journal of Technology Assessment in Health Care , Volume 30 , Issue 3: Theme: Adaptive Approaches to Licensing , July 2014 , pp. 312 - 324
Copyright
Copyright © Cambridge University Press 2014 

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References

REFERENCES

1. De Gruttola, VG, Clax, P, DeMets, DL, et al. Considerations in the evaluation of surrogate endpoints in clinical trials. Summary of a National Institutes of Health workshop. Control Clin Trials. 2001;22:485–502.Google Scholar
2. Elston, J, Taylor, RS. Use of surrogate outcomes in cost-effectiveness models: A review of United Kingdom health technology assessment reports. Int J Technol Assess Health Care. 2009;25:6–13.Google Scholar
3. Yudkin, JS, Lipska, KJ, Montori, VM. The idolatry of the surrogate. BMJ. 2011;343:d7995.CrossRefGoogle ScholarPubMed
4. Messerli, FH, Bangalore, S. ALTITUDE Trial and Dual RAS Blockade: The alluring but soft science of the surrogate end point. Am J Med. 2013;126:e1–e3.CrossRefGoogle ScholarPubMed
5. Fleming, TR, DeMets, DL. Surrogate end points in clinical trials: Are we being misled? Ann Intern Med. 1996;125:605–613.Google Scholar
6. Ciani, O, Buyse, M, Garside, R, et al. Comparison of treatment effect sizes associated with surrogate and final patient relevant outcomes in randomised controlled trials: Meta-epidemiological study. BMJ. 2013;346:f457.CrossRefGoogle ScholarPubMed
7. Lassere, MN. The Biomarker-Surrogacy Evaluation Schema: A review of the biomarker-surrogate literature and a proposal for a criterion-based, quantitative, multidimensional hierarchical levels of evidence schema for evaluating the status of biomarkers as surrogate endpoints. Stat Methods Med Res. 2008;17:303–340.CrossRefGoogle Scholar
8. Weir, CJ, Walley, RJ. Statistical evaluation of biomarkers as surrogate endpoints: A literature review. Stat Med. 2006;25:183–203.Google Scholar
9. Buyse, M, Molenberghs, G, Burzykowski, T, Renard, D, Geys, H. The validation of surrogate endpoints in meta-analyses of randomized experiments. Biostatistics. 2000;1:49–67.CrossRefGoogle ScholarPubMed
10. Buyse, M, Sargent, DJ, Grothey, A, Matheson, A, de Gramont, A. Biomarkers and surrogate end points–the challenge of statistical validation. Nat Rev Clin Oncol. 2010;7:309–317.Google Scholar
11. Velasco Garrido, M, Mangiapane, S. Surrogate outcomes in health technology assessment: An international comparison. Int J Technol Assess Health Care. 2009;25:315–322.Google Scholar
12. IQWiG. Validity of surrogate endpoints in oncology. Executive Summary. Cologne, Germany: IQWiG; 2011. https://www.iqwig.de/download/A10-05_Executive_Summary_v1-1_Surrogate_endpoints_in_oncology.pdf (accessed January, 2013).Google Scholar
13. Ellenberg, S, Hamilton, JM. Surrogate endpoints in clinical trials: Cancer. Stat Med. 1989;8:405–413.CrossRefGoogle ScholarPubMed
14. Dunn, BK, Akpa, E. Biomarkers as surrogate endpoints in cancer trials. Semin Oncol Nurs. 2012;28:99–108.CrossRefGoogle ScholarPubMed
15. Berghmans, T, Pasleau, F, Paesmans, M, et al. Surrogate markers predicting overall survival for lung cancer: ELCWP recommendations. Eur Respir J. 2012;39:9–28.Google Scholar
16. Shi, Q, Sargent, DJ. Meta-analysis for the evaluation of surrogate endpoints in cancer clinical trials. Int J Clin Oncol. 2009;14:102–111.CrossRefGoogle ScholarPubMed
17. Saad, ED, Katz, A, Buyse, M. Overall survival and post-progression survival in advanced breast cancer: A review of recent randomized clinical trials. J Clin Oncol. 2010;28:1958–1962.Google Scholar
18. Jaffe, CC. Measures of response: RECIST, WHO, and new alternatives. J Clin Oncol. 2006;24:3245–3251.Google Scholar
19. Appendix 1 to the guideline on the evaluation of anticancer medicinal products in man. Methodological consideration for using progression-free survival (PFS) or disease-free survival (DFS) in confirmatory trials. 2013. http://www.ema.europa.eu/ema/index.jsp?curl=pages/regulation/general/general_content_000406.jsp&mid=WC0b01ac0580034cf3 (accessed January, 2013).Google Scholar
20. Eisenhauer, EA, Therasse, P, Bogaerts, J, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228–247.CrossRefGoogle ScholarPubMed
21. Dancey, JE, Dodd, LE, Ford, R, et al. Recommendations for the assessment of progression in randomised cancer treatment trials. Eur J Cancer. 2009;45:281–289.Google Scholar
22. Tappenden, P, Chilcott, J, Ward, S, Eggington, S, Hind, D, Hummel, S. Methodological issues in the economic analysis of cancer treatments. Eur J Cancer. 2006;42:2867–2875.Google Scholar
23. Sridhara, R, Johnson, JR, Justice, R, et al. Review of oncology and hematology drug product approvals at the US Food and Drug Administration between July 2005 and December 2007. J Natl Cancer Inst. 2010;102:230–243.Google Scholar
24. Hartley, R, Keen, EM, Large, J, Tedd, LA. Online searching: Principles and practice. Epping, UK: BowkerSaur; 1990.Google Scholar
25. Bowater, RJ, Bridge, LJ, Lilford, RJ. The relationship between progression-free and post-progression survival in treating four types of metastatic cancer. Cancer Lett. 2008;262:48–53.Google Scholar
26. Burzykowski, T, Buyse, M. Surrogate threshold effect: An alternative measure for meta-analytic surrogate endpoint validation. Pharm Stat. 2006;5:173–186.Google Scholar
27. Chirila, C, Odom, D, Devercelli, G, et al. Meta-analysis of the association between progression-free survival and overall survival in metastatic colorectal cancer. Int J Colorectal Dis. 2012;27:623–634.Google Scholar
28. Green, E, Yothers, G, Sargent, DJ. Surrogate endpoint validation: Statistical elegance versus clinical relevance. Stat Methods Med Res. 2008;17:477–486.CrossRefGoogle ScholarPubMed
29. Johnson, KR, Ringland, C, Stokes, BJ, et al. Response rate or time to progression as predictors of survival in trials of metastatic colorectal cancer or non-small-cell lung cancer: A meta-analysis. Lancet Oncol. 2006;7:741–746.Google Scholar
30. Sherrill, B, Amonkar, M, Wu, Y, et al. Relationship between effects on time-to-disease progression and overall survival in studies of metastatic breast cancer. Br J Cancer. 2008;99:1572–1578.CrossRefGoogle ScholarPubMed
31. Buyse, M. Use of meta-analysis for the validation of surrogate endpoints and biomarkers in cancer trials. Cancer J. 2009;15:421–425.Google Scholar
32. Sherrill, B, Kaye, JA, Sandin, R, Cappelleri, JC, Chen, C. Review of meta-analyses evaluating surrogate endpoints for overall survival in oncology. Onco Targets Ther. 2012;5:287–296.Google Scholar
33. Lee, L, Wang, L, Crump, M. Identification of potential surrogate end points in randomized clinical trials of aggressive and indolent non-Hodgkin's lymphoma: Correlation of complete response, time-to-event and overall survival end points. Ann Oncol. 2011;22:1392–1403.Google Scholar
34. Tibaldi, F, Barbosa, FT, Molenberghs, G. Modelling associations between time-to-event responses in pilot cancer clinical trials using a Plackett-Dale model. Stat Med. 2004;23:2173–2186.Google Scholar
35. EUnetHTA. Endpoints used in REA of pharmaceuticals - Surrogate Endpoints. 2013. http://www.eunethta.eu/sites/5026.fedimbo.belgium.be/files/Surrogate%20Endpoints.pdf (accessed March, 2013).Google Scholar
36. Bucher, HC, Guyatt, GH, Cook, DJ, Holbrook, A, McAlister, FA. Users’ guides to the medical literature: XIX. Applying clinical trial results. A. How to use an article measuring the effect of an intervention on surrogate end points. Evidence-Based Medicine Working Group. JAMA. 1999;282:771–778.Google Scholar
37. Lassere, MN, Johnson, KR, Schiff, M, Rees, D. Is blood pressure reduction a valid surrogate endpoint for stroke prevention? An analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the surrogate threshold effect (STE) and the Biomarker-Surrogacy (BioSurrogate) Evaluation Schema (BSES). BMC Med Res Methodol. 2012;12:27.CrossRefGoogle ScholarPubMed
38. Lassere, MN, Johnson, KR, Boers, M, et al. Definitions and validation criteria for biomarkers and surrogate endpoints: Development and testing of a quantitative hierarchical levels of evidence schema. J Rheumatol. 2007;34:607–615.Google Scholar
39. Bowater, RJ, Lilford, PE, Lilford, RJ. Estimating changes in overall survival using progression-free survival in metastatic breast and colorectal cancer. Int J Technol Assess Health Care. 2011;27:207–214.Google Scholar
40. Burzykowski, T, Molenberghs, G, Buyse, M, Geys, H, Renard, D. Validation of surrogate end points in multiple randomized clinical trials with failure time end points. J R Stat Soc Ser C Appl Stat. 2001;50:405–422.Google Scholar
41. Amir, E, Seruga, B, Kwong, R, Tannock, IF, Ocana, A. Poor correlation between progression-free and overall survival in modern clinical trials: Are composite endpoints the answer? Eur J Cancer. 2012;48:385–388.Google Scholar
42. Wilkerson, J, Fojo, T. Progression-free survival is simply a measure of a drug's effect while administered and is not a surrogate for overall survival. Cancer J. 2009;15:379–385.Google Scholar
43. Polley, MY, Lamborn, KR, Chang, SM, et al. Six-month progression-free survival as an alternative primary efficacy endpoint to overall survival in newly diagnosed glioblastoma patients receiving temozolomide. Neuro Oncol. 2010;12:274–282.Google Scholar
44. Ballman, KV, Buckner, JC, Brown, PD, et al. The relationship between six-month progression-free survival and 12-month overall survival end points for phase II trials in patients with glioblastoma multiforme. Neuro Oncol. 2007;9:29–38.Google Scholar
45. Louvet, C, de Gramont, A, Tournigand, C, Artru, P, Maindrault-Goebel, F, Krulik, M. Correlation between progression free survival and response rate in patients with metastatic colorectal carcinoma. Cancer. 2001;91:2033–2038.Google Scholar
46. Tang, PA, Bentzen, SM, Chen, EX, Siu, LL. Surrogate end points for median overall survival in metastatic colorectal cancer: Literature-based analysis from 39 randomized controlled trials of first-line chemotherapy. J Clin Oncol. 2007;25:4562–4568.CrossRefGoogle ScholarPubMed
47. Buyse, M, Burzykowski, T, Carroll, K, et al. Progression-free survival is a surrogate for survival in advanced colorectal cancer. J Clin Oncol. 2007;25:5218–5224.Google Scholar
48. Hotta, K, Fujiwara, Y, Matsuo, K, et al. Time to progression as a surrogate marker for overall survival in patients with advanced non-small cell lung cancer. J Thorac Oncol. 2009;4:311–317.CrossRefGoogle ScholarPubMed
49. Li, X, Liu, S, Gu, H, Wang, D. Surrogate end points for survival in the target treatment of advanced non-small-cell lung cancer with gefitinib or erlotinib. J Cancer Res Clin Oncol. 2012;138:1963–1969.Google Scholar
50. Mandrekar, SJ, Qi, Y, Hillman, SL, et al. Endpoints in phase II trials for advanced non-small cell lung cancer. J Thorac Oncol. 2010;5:3–9.Google Scholar
51. Hayashi, H, Okamoto, I, Taguri, M, Morita, S, Nakagawa, K. Postprogression survival in patients with advanced non-small-cell lung cancer who receive second-line or third-line chemotherapy. Clin Lung Cancer. 2013;14:261–266.CrossRefGoogle ScholarPubMed
52. Hotta, K, Kiura, K, Fujiwara, Y, et al. Role of survival post-progression in phase III trials of systemic chemotherapy in advanced non-small-cell lung cancer: A systematic review. PloS One. 2011;6:e26646.Google Scholar
53. Burzykowski, T, Buyse, M, Piccart-Gebhart, MJ, et al. Evaluation of tumor response, disease control, progression-free survival, and time to progression as potential surrogate end points in metastatic breast cancer. J Clin Oncol. 2008;26:1987–1992.CrossRefGoogle ScholarPubMed
54. Hackshaw, A, Knight, A, Barrett-Lee, P, Leonard, R. Surrogate markers and survival in women receiving first-line combination anthracycline chemotherapy for advanced breast cancer. Br J Cancer. 2005;93:1215–1221.Google Scholar
55. Miksad, RA, Zietemann, V, Gothe, R, et al. Progression-free survival as a surrogate endpoint in advanced breast cancer. Int J Technol Assess Health Care. 2008;24:371–383.CrossRefGoogle ScholarPubMed
56. Rose, PG, Tian, C, Bookman, MA. Assessment of tumor response as a surrogate endpoint of survival in recurrent/platinum-resistant ovarian carcinoma: A Gynecologic Oncology Group study. Gynecol Oncol. 2010;117:324–329.CrossRefGoogle ScholarPubMed
57. Sundar, S, Wu, J, Hillaby, K, Yap, J, Lilford, R. A systematic review evaluating the relationship between progression free survival and post progression survival in advanced ovarian cancer. Gynecol Oncol. 2012;125:493–499.Google Scholar
58. Shitara, K, Ikeda, J, Yokota, T, et al. Progression-free survival and time to progression as surrogate markers of overall survival in patients with advanced gastric cancer: Analysis of 36 randomized trials. Invest New Drugs. 2012;30:1224–1231.Google Scholar
59. Foster, NR, Qi, Y, Shi, Q, et al. Tumor response and progression-free survival as potential surrogate endpoints for overall survival in extensive stage small-cell lung cancer: Findings on the basis of North Central Cancer Treatment Group trials. Cancer. 2011;117:1262–1271.Google Scholar
60. Halabi, S, Vogelzang, NJ, Ou, SS, Owzar, K, Archer, L, Small, EJ. Progression-free survival as a predictor of overall survival in men with castrate-resistant prostate cancer. J Clin Oncol. 2009;27:2766–2771.Google Scholar
61. Heng, DY, Xie, W, Bjarnason, GA, et al. Progression-free survival as a predictor of overall survival in metastatic renal cell carcinoma treated with contemporary targeted therapy. Cancer. 2011;117:2637–2642.Google Scholar
62. Delea, TE, Khuu, A, Heng, DYC, Haas, T, Soulieres, D. Association between treatment effects on disease progression end points and overall survival in clinical studies of patients with metastatic renal cell carcinoma. Br J Cancer. 2012;107:1059–1068.Google Scholar
63. Parmar, MK, Torri, V, Stewart, L. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Statist Med. 1998;17:2815–2834.Google Scholar
64. Buyse, M, Sargent, DJ, Saad, ED. Survival is not a good outcome for randomized trials with effective subsequent therapies. J Clin Oncol. 2011;29:4719–4720; author reply 4720–4721.Google Scholar
65. Saad, ED, Katz, A, Hoff, PM, Buyse, M. Progression-free survival as surrogate and as true end point: Insights from the breast and colorectal cancer literature. Ann Oncol. 2010;21:7–12.Google Scholar
66. Ciani, O, Taylor, RS. A more evidence based approach to the use of surrogate end points in policy making. BMJ. 2011;343:d6498.Google Scholar
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