State of the Art
Using a Benefit–Risk Analysis Approach to Capture Regulatory Decision Making: Renal Cell Carcinoma
G. K. Raju,
Karthik Gurumurthi,
Reuben Domike,
Harpreet Singh,
Chana Weinstock,
Paul Kluetz,
Richard Pazdur,
Janet Woodcock,
Corresponding Author
G. K. Raju
Light Pharma, Inc., Cambridge, Massachusetts, USA
Correspondence: G. K. Raju ([email protected])Search for more papers by this authorKarthik Gurumurthi
Light Pharma, Inc., Cambridge, Massachusetts, USA
Search for more papers by this authorReuben Domike
Light Pharma, Inc., Cambridge, Massachusetts, USA
Manufacturing Engineering, Brigham Young University, Provo, Utah, USA
Search for more papers by this authorHarpreet Singh
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorChana Weinstock
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorPaul Kluetz
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorRichard Pazdur
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorJanet Woodcock
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorG. K. Raju,
Karthik Gurumurthi,
Reuben Domike,
Harpreet Singh,
Chana Weinstock,
Paul Kluetz,
Richard Pazdur,
Janet Woodcock,
Corresponding Author
G. K. Raju
Light Pharma, Inc., Cambridge, Massachusetts, USA
Correspondence: G. K. Raju ([email protected])Search for more papers by this authorKarthik Gurumurthi
Light Pharma, Inc., Cambridge, Massachusetts, USA
Search for more papers by this authorReuben Domike
Light Pharma, Inc., Cambridge, Massachusetts, USA
Manufacturing Engineering, Brigham Young University, Provo, Utah, USA
Search for more papers by this authorHarpreet Singh
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorChana Weinstock
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorPaul Kluetz
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorRichard Pazdur
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorJanet Woodcock
Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
Search for more papers by this authorAbstract
Drug regulators such as the US Food and Drug Administration (FDA) make decisions about drug approvals based on benefit–risk analysis. In this work, a quantitative benefit–risk analysis approach captures regulatory decision making about new drugs to treat renal cell carcinoma (RCC). Fifteen FDA decisions on RCC drugs based on clinical trials whose results were published from 2005 to 2018 were identified and analyzed. The benefits and risks of the new drug in each clinical trial were quantified relative to comparators (typically the control arm of the same clinical trial) to estimate whether the benefit–risk was positive or negative. A sensitivity analysis was demonstrated using pazopanib to explore the magnitude of uncertainty. FDA approval decision outcomes for the clinical trials assessed were consistent and logical using this benefit–risk framework.
Conflict of Interest
The authors declared no competing interests for this work.
Supporting Information
| Filename | Description |
|---|---|
| cpt1589-sup-0001-FigS1.tifimage/tif, 83.2 KB | Figure S1. Renal cell carcinoma (RCC) trials used in benefit–risk analyses. *Unless otherwise shown in the figure, all trials were randomized, and all randomized trials isolated the treatment effect of the experimental drug. |
| cpt1589-sup-0002-FigS2a.tifimage/tif, 170.3 KB | Figure S2a. Pivotal trials with progression-free survival (PFS) as primary endpoint. Points shown in yellow represent doses or combinations that are not used. |
| cpt1589-sup-0003-FigS2b.pdfPDF document, 78.4 KB | Figure S2b. Pivotal trials with overall response rate (ORR) as primary endpoint. |
| cpt1589-sup-0004-FigS3ai.tifimage/tif, 296.8 KB | Figure S3ai. ORR vs. PFS (i) only experimental drugs (weighted based on number of patients). |
| cpt1589-sup-0005-FigS3aii.tifimage/tif, 302.5 KB | Figure S3aii. ORR vs. PFS (ii) only experimental drugs (not weighted). |
| cpt1589-sup-0006-FigS3aiii.tifimage/tif, 303.2 KB | Figure S3aiii. ORR vs. PFS (iii) experimental drugs and controls (not weighted). |
| cpt1589-sup-0007-FigS3bi.tifimage/tif, 295.9 KB | Figure S3bi. ORR vs. overall survival (OS) (i) only experimental drugs (weighted based on number of patients). |
| cpt1589-sup-0008-FigS3bii.tifimage/tif, 286.1 KB | Figure S3bii. ORR vs. OS (ii) only experimental drugs (not weighted). |
| cpt1589-sup-0009-FigS3bv.tifimage/tif, 191.9 KB | Figure S3biii. ORR vs. OS (iii) experimental drugs and controls (not weighted). |
| cpt1589-sup-0010-FigS3iii.tifimage/tif, 274.6 KB | Figure S3biv. ORR vs. OS (iv) regression of OS against ORR and proportion of patients in intermediate risk category at baseline (only experimental drugs). |
| cpt1589-sup-0011-FigS3iv.tifimage/tif, 183.3 KB | Figure S3bv. ORR vs. OS (v) regression of OS against ORR and proportion of patients in intermediate risk category at baseline (experimental drugs and controls). |
| cpt1589-sup-0012-FigS3ci.tifimage/tif, 271.4 KB | Figure S3ci. PFS vs. OS (i) only experimental drugs (weighted based on number of patients). |
| cpt1589-sup-0012-FigS3ciii.tifimage/tif, 278.2 KB | Figure S3cii. PFS vs. OS (ii) only experimental drugs (not weighted). |
| cpt1589-sup-0013-FigS3cii.tifimage/tif, 254.7 KB | Figure S3ciii PFS vs. OS (iii) experimental drugs and controls (not weighted). |
| cpt1589-sup-0013-FigS3civ.tifimage/tif, 195.3 KB | Figure S3civ. PFS vs. OS (iv) regression of OS against PFS and proportion of patients in intermediate risk category at baseline (only experimental drugs). |
| cpt1589-sup-0014-FigS3cv.tifimage/tif, 195.2 KB | Figure S3cv. PFS vs. OS (v) regression of OS against PFS and proportion of patients in intermediate risk category at baseline (experimental drugs and controls). |
| cpt1589-sup-0015-FigS4.tifimage/tif, 344.4 KB | Figure S4. Evolution of estimated OS benefit over time for RCC. The estimated median OS is for the corresponding drug product only and not relative to a control. |
| cpt1589-sup-0016-FigS5.tifimage/tif, 213.9 KB | Figure S5. Median vs. hazard ratio. |
| cpt1589-sup-0017-FigS6.tifimage/tif, 253.1 KB | Figure S6 (a) Points obtained from the Kaplan-Meier curve of OS of experimental drug arm (Nivolumab + Ipilimumab) of clinical trial CheckMate 214. (b) Fitting a Weibull distribution to the points obtained from the Kaplan-Meier curve of OS of Experimental Drug Arm (nivolumab + ipilimumab) of clinical trial CheckMate 214. (c) Estimates of scale (λ) and shape (k) factors from regression model fitting Weibull distribution to the Kaplan-Meier curve of OS of experimental drug arm (Nivolumab + Ipilimumab) of clinical trial CheckMate 214. |
| cpt1589-sup-0018-TableS1.docxWord document, 15 KB | Table S1. Benefit–risk quotes. |
| cpt1589-sup-0019-TableS2.docxWord document, 19.8 KB | Table S2. Summary of RCC trials. Confidence limits are 95% confidence limits. |
| cpt1589-sup-0020-TableS3.docxWord document, 22.2 KB | Table S3. Analysis of risks of RCC drugs. Confidence limits are 95% confidence limits. |
| cpt1589-sup-0021-TableS4.docxWord document, 17.6 KB | Table S4. Benefit–risk and decision analysis for pazopanib. |
| cpt1589-sup-0022-TableS5.docxWord document, 15.1 KB | Table S5. Pazopanib risk assessment computations. median duration of treatment on the pazopanib arm is 7.4 months. Median duration of treatment on the control arm is 3.8 months. |
| cpt1589-sup-0023-Supinfo.docxWord document, 16.1 KB | Supplementary Material S1. |
| cpt1589-sup-0024-2019-0222C-s01.xlsxMS Excel, 80 KB | Excel version of all tables. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
References
- 1 US Food and Drug Administration. Benefit–risk assessment in drug regulatory decision-making <https://www.fda.gov/downloads/ForIndustry/UserFees/PrescriptionDrugUserFee/UCM602885.pdf> (March 2018). Accessed March 13, 2019.
- 2 US Food and Drug Administration. Structured approach to benefit-risk assessment in drug regulatory decision-making. Draft PDUFA V implementation plan—February 2013. Fiscal years 2013–2017. https://www.fda.gov/media/84831/download (2013). Accessed August 22, 2019.
- 3 National Center for Health Statistics. Health: Unites States, 2010: With Special Feature on Death and Dying. Hyattsville, MD <https://www.ncbi.nlm.nih.gov/pubmed/21634072> (2011). Accessed August 27, 2019.
- 4Morris, S.A., Rosenblatt, M., Orloff, J.J., Lewis-Hall, F. & Waldstreicher, J. The PCAST report: impact and implications for the pharmaceutical industry. Clin. Pharmacol. Ther. 94, 300–302 (2013).
- 5Woodcock, J. The PCAST report on pharmaceutical innovation: implications for the FDA. Clin. Pharmacol. Ther. 94, 297–300 (2013).
- 6Raju, G., Gurumurthi, K. & Domike, R. Benefit–risk analysis for decision-making: an approach. Clin. Pharmacol. Ther. 100, 654–671 (2016).
- 7Raju, G. et al. A benefit–risk analysis approach to capture regulatory decision-making: non-small cell lung cancer. Clin. Pharmacol. Ther. 100, 672–684 (2016).
- 8Raju, G.K. et al. A benefit–risk analysis approach to capture regulatory decision-making: multiple myeloma. Clin. Pharmacol. Ther. 103, 67–76 (2018).
- 9 National Cancer Institute. Surveillance epidemiology and end results. SEER Stat fact sheets: kidney and renal pelvis cancer <https://seer.cancer.gov/statfacts/html/kidrp.html> (2018). Accessed December 7, 2018.
- 10McDermott, D.F. et al. Randomized phase III trial of high-dose interleukin-2 versus subcutaneous interleukin-2 and interferon in patients with metastatic renal cell carcinoma. J. Clin. Oncol. 23, 133–141 (2005).
- 11Choueiri, T.K. et al. Cabozantinib versus sunitinib as initial targeted therapy for patients with metastatic renal cell carcinoma of poor or intermediate risk: the alliance A031203 CABOSUN trial. J. Clin. Oncol. 35, 591–597 (2017).
- 12 US Food and Drug Administration. Drug Approval Package; NEXAVAR (sorafenib) Tablets; Company; Bayer Pharmaceuticals Corporation; Application No.; 021923; Approval Date: 02/08/2006 <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2005/021923_s000_NexavarTOC.cfm> (2011). Accessed December 7, 2018.
- 13 US Food and Drug Administration. Drug Approval Package; Sutent (Sunitinib Malate) Capsules; Company; Pfizer, Inc.; Application No.; 021968; Approval Date: 01/26/2006 <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2006/021938s000_021968s000_Stutent.cfm> (2006). Accessed December 7. 2018.
- 14 US Food and Drug Administration. Drug Approval Package; Torisel (Temsirolimus) Intravenous Solution; Company; Wyeth Pharmaceuticals Inc.; Application No.; 022088; Approval Date: 05/30/2007 <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2007/022088s000TOC.cfm> (2012). Accessed December 7, 2018.
- 15 US Food and Drug Administration. Drug Approval Package; Afinitor (Everolimus) Tablets; Company; Novartis Pharmaceuticals Corporation; Application No.; 22-334; Approval Date: 3/30 <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2009/022334s000TOC.cfm> (2009). Accessed December 7, 2018.
- 16 US Food and Drug Administration. Drug Approval Package; Votrient (pazopanib hydrochloride) Tablets; Company; GlaxoSmithKline; Application No.; 022465; Approval Date: 10/19/2009 <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2009/022465s000TOC.cfm> (2010). Accessed December 7, 2018.
- 17 US Food and Drug Administration. Drug Approval Package; Inlyta (axitinib) Tablets; Company; Pfizer Inc.; Application No.; 202324s000; Approval Date: 1/27/2012 <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2012/202324Orig1s000TOC.cfm> (2012). Accessed December 7, 2018.
- 18 US Food and Drug Administration. Drug Approval Package; CABOMETYX (cabozantinib) Tablets; Company; Exelixis, Inc.; Application No.; 208692; Approval Date: 04/25/2016 <https://www.accessdata.fda.gov/drugsatfda_docs/nda/2016/208692Orig1s000TOC.cfm> (2018). Accessed December 7, 2018.
- 19 US Food and Drug Administration. FDA Briefing Document. Oncologic Drugs Advisory Committee Meeting. May 2, 2013. NDA 204408/S000. tivozanib. Applicant: Aveo Pharmaceuticals, Inc <https://wayback.archive-it.org/7993/20170405223301/>; <https://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/OncologicDrugsAdvisoryCommittee/UCM350075.pdf> (2013). Accessed August 22, 2019.
- 20 US Food and Drug Administration. Center for Drug Evaluation and Research. Summary Minutes of the Oncologic Drugs Advisory Committee Meeting. December 7, 2011. (2011). Accessed August 22, 2019.
- 21 US Food and Drug Administration. Center for Drug Evaluation and Research. Summary Minutes of the Oncologic Drugs Advisory Committee Meeting. May 2, 2013. <https://wayback.archiveit.org/7993/20170404153302/>; <http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/OncologicDrugsAdvisoryCommittee/UCM359160.pdf> (2013). August 22, 2019.
- 22 European Medicines Agency. Avastin-H-C-582-II-0015: EPAR-Assessment Report-Variation <https://www.ema.europa.eu/en/documents/variation-report/avastin-h-c-582-ii-0015-epar-assessment-report-variation_en.pdf> (2008). Accessed December 7, 2018.
- 23Motzer, R.J. et al. Overall survival and updated results for sunitinib compared with interferon alfa in patients with metastatic renal cell carcinoma. J. Clin. Oncol. 27, 3584–3590 (2009).
- 24Motzer, R.J. et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N. Engl. J. Med. 373, 1803–1813 (2015).
- 25Motzer, R.J. et al. Lenvatinib, everolimus, and the combination in patients with metastatic renal cell carcinoma: a randomised, phase 2, open-label, multicentre trial. Lancet Oncol. 16, 1473–1482 (2015).
- 26Motzer, R.J. et al. Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma. N. Engl. J. Med. 378, 1277–1290 (2018).
- 27Motzer, R.J., Mazumdar, M., Bacik, J., Berg, W., Amsterdam, A. & Ferrara, J. Survival and prognostic stratification of 670 patients with advanced renal cell carcinoma. J. Clin. Oncol. 17, 2530–2540 (1999).
- 28Motzer, R.J. et al. Prognostic factors for survival in previously treated patients with metastatic renal cell carcinoma. J. Clin. Oncol. 22, 454–463 (2004).
- 29Heng, D.Y. et al. Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: results from a large, multicenter study. J. Clin. Oncol. 27, 5794–5799 (2009).
- 30Heng, D.Y. et al. External validation and comparison with other models of the International Metastatic Renal-Cell Carcinoma Database Consortium prognostic model: a population-based study. Lancet Oncol. 14, 141–148 (2013).
- 31Basch, E. The missing voice of patients in drug-safety reporting. N. Engl. J. Med. 362, 865–869 (2010).
- 32Thanarajasingam, G., Hubbard, J.M., Sloan, J.A. & Grothey, A. The imperative for a new approach to toxicity analysis in oncology clinical trials. J. Natl Cancer Inst. 107, djv216 (2015).
- 33Sivendran, S. et al. Adverse event reporting in cancer clinical trial publications. J. Clin. Oncol. 32, 83–89 (2014).
- 34 US Department of Health and Human Services, US Food and Drug Administration. Expedited Programs for Serious Conditions—Drugs and Biologics. <https://www.fda.gov/files/drugs/published/Expedited-Programs-for-Serious-Conditions-Drugs-and-Biologics.pdf> (2014). Accessed August 22, 2019.
