Regulatory Issues: FDA
Applications for Oncologic Drugs: A Descriptive Analysis of the Oncologic Drugs Advisory Committee Reviews JOHN K. CHAN,a,d TUYEN K. KIET,a BRADLEY J. MONK,b NICHOLE YOUNG-LIN,a KEVIN BLANSIT,a,d DANIEL S. KAPP,c IDOROENYI AMANAMa a Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California, USA; bDivision of Gynecologic Oncology, Creighton University School of Medicine, St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, USA; cDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California, USA; dPalo Alto Medical Foundation Research Institute, Palo Alto, California, USA
Disclosures of potential conflicts of interest may be found at the end of this article.
Key Words. Oncologic Drugs Advisory Committee x U.S. Food and Drug Administration x Oncology drug applications x
ABSTRACT Background. Despite advances in cancer research, the majority of drug applications submitted to the U.S. Food and Drug Administration (FDA) are not approved. It is important to identify the concerns of the Oncologic Drugs Advisory Committee (ODAC) from rejected applications. Methods. All applications referred to the ODAC from 2001 to 2012 were reviewed. Results. Of 46 applications, 31 (67%) were for full and 15 (33%) were for supplemental approval, 34 (74%) were for solid and 12 (26%) were for hematologic tumors. In all, 22 (48%) were not approved. ODAC comments addressed missing or inadequate data (65%), excessive toxicity (55%), inappropriate study endpoints (45%), poor study design (40%), and insufficient sample size (30%). To define efficacy, 19 applications used response rates (RR) (median 5 38%), and 19 applications used
hazard ratios (HR) (median 5 0.67). For all organ systems combined,the median cumulative grade 3 or 4 toxicity was 64%. Drugs with higher RR, lower HR, and lower toxicity were more likely to be approved versus other drugs (89% vs. 45%; p 5 .02). Over time (2001–2004, 2005–2008, 2009–2012), there was an increase in the following: number of applications submitted for review (from 11 to 12 to 23, respectively), number of approvals (from 6 to 6 to 12, respectively), and proportion of trials using progression-free survival as a primary endpoint (from 0% to 50% to 70%, respectively; p 5 .01). Conclusion. Of all applications, common ODAC concerns included inadequate data, excessive toxicity, and inappropriate study endpoints. Over time, there was an approximate doubling of FDA application submissions and approved oncology drugs. The Oncologist 2014;19:299–304
Implications for Practice: Currently, there is limited information regarding how clinical trials are evaluated by the FDA and Oncologic Drugs Advisory Committee (ODAC). To guide clinical researchers toward improving the design of clinical trials and potentially improving the likelihood of FDA approval, we studied the concerns addressed by the ODAC on rejected drug applications and identified factors associated with FDA approval. Furthermore, we showed that there was an increase in the number of FDA applications and approved drugs over the last 10 years. These encouraging findings from our report may guide clinical researchers to more efficiently use resources for clinical trials.
INTRODUCTION Over the last decade, significant advances in cancer research have been made based on sequencing of the human genome, identification of driving growth factors and receptors, and signaling pathways [1]. From 2007 to 2010, research innovations led to an estimated 1,884 phase I, 3,436 phase II, and 1,025 phase III oncology clinical trials [2]. The number of therapeutic cancer agents in development has also doubled annually over the last 20 years [3]. Prospective phase III registration trials are costly, arduous, and lengthy [4]. The current costs of an industry-sponsored
phase III clinical trial range from 10 to 20 million dollars [5]. In addition,these clinical studies require hundreds tothousands of patients and necessitate an average of 6 years to complete [6]. It is estimated that pharmaceutical companies spend an average of $1.7 billion dollars per drug from development to market approval [7]. Despite these investments, only 40% of drug applications submitted for consideration are approved [1, 8, 9]. The U.S. Food and Drug Administration (FDA) is responsible for protecting and promoting public health in part through regulation of pharmaceutical drugs. The FDA often
Correspondence: John K. Chan, M.D., University of California, San Francisco School of Medicine, 1600 Divisadero Street, Room A747, Box 1702, San Francisco, California 94143-1702, USA; or Palo Alto Medical Foundation Research Institute, 795 El Camino Real, Ames Research Building, Palo Alto, California 94301, USA.Telephone: 415-751-1847; E-Mail: [email protected] Received July 29, 2013; accepted for publication December 23, 2013; first published online in The Oncologist Express on March 5, 2014. ©AlphaMed Press 1083-7159/2014/$20.00/0 http://dx.doi.org/ 10.1634/theoncologist.2013-0276
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MATERIALS AND METHODS We identified all drug license applications referred to ODAC from 2001 to 2012. Using the FDA’s website, we analyzed FDA and sponsor presentations, minutes, and transcripts. We then abstracted the characteristics of these drug applications (Table 1). We also supplemented this information by reviewing the drug application’s pivotal study published in a peer-reviewed journal (supplemental online appendix). More specifically, we analyzed the clinical trial data published in the peer-reviewed journal that was referenced as the pivotal study supporting the drug application. We identified the publication by searching ClinicalTrials.gov, Cancer.gov, PubMed, Google Scholar, and the drug manufacturer’s website. The clinical trial data was correlated with information from the transcripts, presentations, and peer-reviewed journals.We then compiled the hazard ratio (HR), response rate (RR), and cumulative toxicity profiles of each drug.The HRs were extracted from studies using either progression-free survival (PFS) or overall survival (OS) as the primary endpoint. The RRs were evaluated using Response Evaluation Criteria in Solid Tumors or other biomarker criteria. To better assess the level and extent of toxicity, we elected to use the median cumulative grade 3 or 4 toxicities, defined as the sum of all significant toxicity percentages, of each organ system. We then investigated these factors to estimate the likelihood of FDA approval. To identify concerns addressed by the ODAC members, we identified key words such as endpoint, toxicity, adverse, safety, inadequate, population, sample, size, small, missing, length, collection, study, design, analysis, imaging, and radiology. Next, we grouped the concerns into six major categories: adequacy of data, toxicity, endpoints, study design, sample size, and radiological imaging. We compared the ODAC decision with the FDA Approved Drug Products database (Drugs@FDA, http://www. accessdata.fda.gov/scripts/cder/drugsatfda/) to identify discrepancies between ODAC recommendations and final FDA approval. To determine the trend and progress over time, the applications were divided into three groups based on the year of ODAC submission: 2001–2004, 2005–2008, and 2009–2012.
Table 1. Characteristics of drug applications Characteristics
n (%)
Type of application New drug application Biologic license application Supplemental Type of approval Full Accelerated Type of cancer Solid Hematologic Type of therapy Single agent Combination Route of administration Intravenous Oral Other Phase of study IIa III Type of cancerb Leukemia Lymphoma Breast Prostate Brain Lung Pancreatic Skin Ovarian Renal Bone Sarcoma Thyroid
26 (56) 5 (11) 15 (33) 31 (67) 15 (33) 34 (74) 12 (26) 35 (76) 11 (24) 29 (63) 16 (35) 1 (2) 16 (35) 30 (65) 9 (20) 8 (17) 5 (11) 5 (11) 3 (7) 3 (7) 3 (7) 3 (7) 2 (4) 2 (4) 1 (2) 1 (2) 1 (2)
a
Two trials were randomized phase II studies. Percentages do not add up to 100% because 1 drug is reported for two indications.
b
x2 test was used to determine the association of FDA approval versus rejection based on efficacy (HR or RR) and toxicity (cumulative grades 3 and 4) of each agent. Moreover, other potential predictive factors such as type of agent, indication of use, stage of study, and study endpoint were also evaluated. A trends analysis was performed to determine the impact of study time periods and likelihood of approval. All data were analyzed using SPSS version 19 (IBM Corp., Armonk, NY, http://www-01.ibm.com/software/analytics/spss/).
RESULTS From 2001 to 2012, ODAC reviewed 46 new applications. The characteristics of drug applications and list of drugs are provided in Tables 1 and 2. Of all applications, 91% (42 of 46) of studies were published in peer-reviewed journals and the majority in the Journal of Clinical Oncology. Nearly half (48%,
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requests the Oncologic Drugs Advisory Committee (ODAC) to evaluate data concerning the safety and effectiveness of cancer drugs and provide approval recommendations. The Office of Hematology and Oncology Products made a statement on the need to “reduce inconsistencies and misunderstandings” between the FDA and sponsors that may result in failed products [10]. A prior report from our study group showed that FDA applications that contain one or more clinical trials from multiple institutions and those with industry sponsorship had a greater likelihood of obtaining FDA approval [11]. There is a lack of information on the factors that predict for the likelihood of FDA approval based on prior applications. Moreover, few studies have reported on ODAC concerns of rejected applications. In addition, there are no recent updates on the trends and progress on FDA approval of anticancer therapies. In this study, we reviewed the ODAC summary minutes, transcripts, sponsor and FDA presentations, and peer-reviewed journals over the last 10 years. The findings from this study may guide clinical researchers toward designing clinical trials more likely to obtain FDA approval based on ODAC recommendations.
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Table 2. List of drugs by indications Brand name
Drug name
Cancer type
Application
Endpoint
FDA approval
Arranona
Nelarabine
Leukemia & lymphoma
NDA/sNDA
RR
Yes
Year approved 2005/2011
Arzerra
Ofatumumab
Leukemia
BLA
RR
Yes
2009
Clolar
Clofarabine
Leukemia
sNDA
RR
No
Genasense
Oblimersen
Leukemia
NDA
RR
No
Omapro
Omacetaxine mepesuccinate
Leukemia
NDA
PFS
No
Onrigin
Laromustine
Leukemia
NDA
RR
No
Revlimidb
Lenalidomide
Leukemia
NDA
RR
Yes
2005
Sprycelc
Dasatinib
Leukemia
NDA
RR
Yes
2006
Tipifarnib
Leukemia
NDA
RR
No
Brentuximab vedotin
Lymphoma
BLA
RR
Yes
2011
Adcetrisd
Brentuximab vedotin
Lymphoma
BLA
RR
Yes
2011
Bexxar
Tositumomab
Lymphoma
BLA
RR
Yes
2003
Folotyn
Pralatrexate
Lymphoma
NDA
RR
Yes
2009
Istodaxe
Romidepsin
Lymphoma
NDA
RR
Yes
2009
Marqibo
Vincristine liposome
Lymphoma
NDA
RR
No
Pixuvri
Pixantrone dimaleate
Lymphoma
NDA
RR
No
Zevalinf
Ibritumomab tiuxetan
Lymphoma
BLA
RR
Yes
Avasting
Bevacizumab
Breast
sBLA
PFS
No
Avasting
Bevacizumab
Breast
sBLA
PFS
No
Avasting
Bevacizumab
Breast
sBLA
PFS
No
Doxil
Doxorubicin liposome
Breast
sNDA
TTP
No
Evista
Raloxifene
Breast
NDA
DFS
Yes
Avodart
Dutasteride
Prostate
sNDA
DFS
No
Casodex
Bicalutamide
Prostate
sNDA
TTP
No
Orplatna
Satraplatin
Prostate
NDA
PFS
No
Proscar
Finasteride
Prostate
sNDA
DFS
No
Xinlay
Atrasentan
Prostate
NDA
TTP
No
Avastinh
Bevacizumab
Brain
sBLA
RR
Yes
2009
Gliadel
Carmustine
Brain
NDA
OS
Yes
2003
RSR 13
Efaproxiral
Brain
NDA
OS
No
Iressai
Gefitinib
Lung
NDA
RR
Yes
2003
Alimtaj
Pemetrexed
Lung
NDA
OS
Yes
2004
Tarceva
Erlotinib
Lung
sNDA
PFS
Yes
2010
Afinitor
Everolimus
Pancreas
sNDA
PFS
Yes
2009
Sutent
Sunitinib
Pancreas
sNDA
PFS
Yes
Tarcevak
Erlotinib
Pancreas
NDA
OS
Yes
Genasense
Oblimersen
Skin
NDA
OS
No
2002
2007
2005
IntraDose
Cisplatin/Epinephrine
Skin
NDA
RR
No
Pegintronl
Peginterferon a-2b
Skin
sBLA
PFS
Yes
2011
Gemzarm
Gemcitabine
Ovary
NDA
PFS
Yes
2006
Yondelis
Trabectedin
Ovary
NDA
PFS
No
Inlyta
Axitinib
Kidney
NDA
PFS
No
Votrient
Pazopanib
Kidney
NDA
PFS
Yes
2009
Zometa
Zoledronic acid
Bone
sNDA
Skeletal event
Yes
2004
Junovan
Mifamurtide
Sarcoma
NDA
DFS
No
Caprelsa
Vandetanib
Thyroid
NDA
PFS
Yes
2011
a
Arranon: T-cell acute lymphoblastic leukemia and T-cell lymphoblastic lymphoma after two failed chemotherapy regimens. b Revlimid: transfusion-dependent anemia because of low- or intermediate-risk myelodysplastic syndromes with a deletion 5q cytogenetic abnormality. c Sprycel: chronic, accelerated, or blast-phase chronic myeloid leukemia with resistance/intolerance to imatinib; adults with Philadelphia chromosome-positive acute lymphoblastic leukemia and lymphoid blast chronic myeloid leukemia with resistance/intolerance to prior therapy. d Adcetris: Two different BLAs were filled for this drug; both were included for completeness. e Istodax: cutaneous T-cell lymphoma in patients who have received at least one prior systemic therapy. f Zevalin: relapsed or refractory low-grade, follicular, or CD201 transformed B-cell non-Hodgkins lymphoma (NHL) and rituximab refractory follicular NHL. g Avastin: Multiple indications referenced. h Avastin: previously treated glioblastoma multiforme. i Iressa: locally advanced or metastatic non-small cell lung cancer in patients who have previously received platinum-based chemotherapy. j Alimta: locally advanced or metastatic non-small cell lung cancer after prior chemotherapy. k Tarceva: in combination with gemcitabine for first-line, locally advanced, unresectable, or metastatic pancreatic cancer. l Pegintron: adjuvant treatment for melanoma. m Gemcitabine: combination with carboplatin for advanced ovarian cancer that had relapsed at least 6 months after first-line platinum-based therapy. Abbreviations: BLA, biologic license application; DFS, disease-free survival; NDA, new drug application; OS, overall survival; PFS, progression-free survival; RR, response rate; sBLA, supplemental BLA; sNDA, supplemental NDA; TTP, time to progression.
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42 of 46) of all applications submitted for ODAC review were rejected. The most common concerns are listed in Figure 1. More specifically, the category of “inadequate data” included “missing patient information, inadequate survival follow-up, limited or discrepant data, robustness of survival benefit, and lack of meaningful quality of life data.” The major concerns of “study design and endpoint” included issues with “control group, unspecified subgroup, sample size, blinding, off-trial subsequent therapy confounding survival analysis, and subset analysis of endpoint not prespecified, such as symptom-free time analysis.” Under the category “sample size” concerns, we included “lack or poor accrual of U.S. enrollees or population not prevalent in U.S., and unspecified subgroup and heterogeneous populations.” To evaluate the factors associated with the likelihood of approval based on FDA reports over the last 10 years, we focused on efficacy and toxicity. Forty-one percent (19 of 46) of applications used hazard ratios (HR) and 41% (19 of 46) used response rates (RR) as endpoints for efficacy. Of the 19 applications that reported on hazard ratios, 74% (14 of 19) used progression-free survival (PFS) and 26% (5 of 19) had overall survival (OS) as the primary endpoint. Of these 19 applications, the median HR was 0.67 (range: 0.35–0.99), and 47% (9 of 19) of applications were approved. In a subset analysis of these applications (n 5 19), 60% (3 of 5) of applications were approved for OS benefit versus 50% (7 of 14) approved for PFS benefit (p 5 .70). Of the 19 drugs that reported on RRs, the median RR was 38% (range: 17%–86%), and 63% (12 of 19) were approved. The remaining eight studies used other endpoints. To evaluate the toxicity associated with each drug, we elected to use the median grade 3 or 4 toxicity, defined as the sum of all grade 3 and grade 4 toxicity percentages of each organ system. As this is the sum of all toxicities, the median was 64% (range: 5%–323%). Based on the calculated medians of the efficacy and toxicity, we defined better agents as those with lower HR (#median) and lower toxicity (#median); these drugs had an approval rate of 80% (4 of 5) versus 21% (3 of 21) in those less efficacious and more toxic drugs (p 5 .02). Similarly, higher RR ($median) and lower toxicity had an indication approval rate of 100% (6 of 6) versus 53% (8 of 15) (p 5 .09); however, this was based on four of four approved drugs. We then analyzed the efficacy (as per FDA usage) endpoints (HR and RR) and cumulative toxicity of these drugs. Our analyses showed that more efficacious and less toxic drugs
Figure 2. Food and Drug Administration approval by efficacy and toxicity.
were more likely to attain FDA approval versus others (89% [8 of 9] vs. 45% [13 of 29]; p 5 .02). In Figure 2, we provide a diagrammatic representation of our analyses that incorporates efficacy and toxicity to estimate the likelihood of FDA approval. Based on their efficacy and toxicity, we plotted all the approved drugs with filled markers and left the rejected ones unfilled. The dotted line box incorporated drugs with lower hazard ratio and lower toxicity, whereas the dashed line box represents the higher RR and lower toxicity based on median value. Our data showed that drugs that have efficacy and toxicity found within the dotted line box have an estimated approval rate of 89% (8 of 9) compared with only 45% (13 of 29) for those outside of the box. To identify the trends and progress of oncology drug application development using ODAC reviews over the last decade, we divided the study into three time periods: 2001–2004, 2005–2008, and 2009–2012. Over these periods, 11, 12, and 23 applications were submitted for review with corresponding approval rates of 55% (6 of 11), 50% (6 of 12), and 53% (12 of 23) (Fig. 3). Although the rate of approval did not change, the number of approved drugs increased from 6 during the first and second time periods to 12 during the last time period. There was also a significant increase in the proportion of applications using progression-free survival as an endpoint (0% [0 of 11] to 50% [6 of 12] to 70% [16 of 23]; p 5 .01). Accordingly, there was a decrease in the use of overall survival (36% [4 of 11] to 8% [1 of 12] to 0% [0 of 23]) and RR (46% [5 of 11] to 25% [3 of 12] to 26% [6 of 23]) as primary endpoints.There was no significant change in the proportion of full versus accelerated approval, type of cancers, route of drug administration, and type of clinical trial (phase II vs. III) submitted for review over the study period.
DISCUSSION Despite the significant time and costs invested in drug development, the reported success rate is only 8% [7, 8]. To guide clinical researchers to better design clinical trials and potentially improve the likelihood of FDA approval, we studied the concerns addressed by the ODAC on rejected drug applications and identified factors associated with FDA approval.
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Figure 1. Concerns addressed by Oncologic Drugs Advisory Committee review. Abbreviation: ODAC, Oncologic Drugs Advisory Committee.
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In our analysis of the concerns addressed by the FDA/ODAC that likely contributed to a drug’s disapproval, we highlighted the importance to our regulatory agency of providing a comprehensive analysis of clinical trial data. We also elucidated important information that was uncovered by the FDA/ODAC consultants and reviewers but that was not found in the peerreviewed publication, pointing to the limitations of our current peer-review process (Fig. 1). Although our peer-review system is limited, it is the primary modality for dissemination of important clinical trial data [12, 13]. Nevertheless, researchers need to be mindful of these FDA/ODAC concerns in the design of future clinical trials. To assure optimal chance for approval, attention should be directed toward adherence to the ODAC concerns, as summarized in Figure 1. Study design should consider issues of adequacy of sample size, appropriateness of control group, specific subgroup stratification, employment of correct analytic methods, and appropriateness of endpoints. It may be intuitive that effective and nontoxic drugs warrant FDA approval; however, there are limited studies that have attempted to quantify this complex decision process using descriptive analyses. Experts have advised on the importance of registration agencies to balance the improved efficacy of a new drug with its toxicity before approval [14, 15]. Unfortunately, there is a lack of information on the level of acceptable toxicity combined with the extent ofclinical benefit that is more likely to result in FDA approval. In this current report, we identified toxicity and efficacy endpoints correlated with FDA decision and demonstrated these analyses in a diagrammatic chart (Fig. 2). Clearly, further studies are warranted to validate these analyses on assessing FDA approval of drug applications by utilizing larger sample sizes or data from other agencies. By evaluating the drug license applications and subsequent approvals or rejections over the last 10 years, we were able to identify changes in oncology trial design and associated trends of FDA decisions. We found an increase in the number of drugs reviewed by ODAC and the number of drugs approved over time (Fig. 3).There was also an increase in the use of progression-free survival (PFS) as a primary endpoint, such as in colon cancer [16–18]. Moreover, in a review of randomized control trials from 2004 to 2009 on breast, colorectal, and non-small cell lung cancer, Booth and Eisenhauer found a 26% increase in the use of PFS as a primary endpoint [19]. In contrast, breast cancer researchers
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showed that the prediction of OS based on PFS is uncertain [20, 21]. Although we found an increased use of PFS as primary endpoint over time, this was not correlated with an increase in FDA approval rate. In our trends analysis, we showed thatthe rate of drug approvals did not increase over time, but the absolute number of drugs approved has increased significantly over the years. Our study was limited by the lack of information on drugs disapproved or approved as new agents or for additional indications without ODAC review.We were unable to evaluate new drugs or existing drugs with other indications that were not presented to ODAC. Some of these agents included sunitinib (Sutent) for gastrointestinal stromal tumor and renal cell carcinoma; vorinostat (Zolinza) for cutaneous T-cell lymphoma; bortezomib (Velcade) for multiple myeloma or mantle cell lymphoma; everolimus (Afinitor) for renal cell carcinoma, astrocytoma, and breast cancer; abiraterone (Zytiga) for prostate cancer; and bevacizumab (Avastin) for colorectal, lung, and renal cell cancer. Given the small sample size, more rigorous statistical analyses of factors associated with approval or disapproval of drugs were not undertaken. Although we elected to report the toxicity based on the median of all types inclusive of cardiovascular, pulmonary, hematologic, gastrointestinal, renal, and others, the generalization of these toxicities into one group may not lend itself to an accurate reflection of a drug’s true toxic effect. Moreover, in treating cancers with poorer prognoses, physicians and patients may have a higher tolerance for toxicities with more aggressive agents. The grouping of these heterogeneous agents may therefore confound the predictive factors associated with FDA approval. Furthermore, the accelerated approval data collected from ODAC may not reflect confirmatory results of mature data from clinical trials. Additionally, because trials with positive results that have satisfied prespecified endpoints may not go to ODAC, the results of this current report may be biased toward studies that qualify for ODAC review. Moreover, the FDA summaries reviewed in our study may not reflect a complete account of these reviewers’ opinions, because the final FDA decisions are made in closed sessions.These shortcomings may limit our analysis and ability to form definitive conclusions. Factors for advancing drugs for development and market are complex. Prior studies have shown that the novelty and unique target of the drug, favorable pharmacokinetic profile, biologic activity in phase I-II trials, clinical demand for new therapies, market demand, and financial return on investment are all important components for successful drug development [5]. With respect to the financial implications of drug development, it is estimated that more than 30% of the drugs entering clinical trials are abandoned because of economic considerations [22]. In addition, some have suggested the use of biomarkers to identify the most sensitive population while reducing the cost and duration of drug development; however, this is unlikely to reduce the market price of drugs [23]. Clearly, all these factors are important in advancing new drugs but were difficult to evaluate in our study. Furthermore, our analyses make the assumption that these oncologic drugs have similar clinical efficacy across all tumor types. It is clear that there are cancers with unmet need, for which the expectations are based not only on survival but also on acceptable levels of toxicity and improvements in quality of life. Additionally, we did ©AlphaMed Press 2014
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Figure 3. Applications and approvals by year of Oncologic Drugs Advisory Committee review. Abbreviation: ODAC, Oncologic Drugs Advisory Committee.
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CONCLUSION In this analysis of oncology drug applications, we were able to learn from the rejected applications by identifying the most common FDA concerns.We also highlighted the importance of our regulatory agency to provide a comprehensive analysis of clinical trial data not reported in peer-reviewed publications. Our study using drug efficacy and toxicity provides specific measurements to aid in forecasting the FDA approval process. Clinical researchers need to consider these FDA concerns in the design of future clinical trials, including inadequate data, excessive toxicity, and inappropriate study endpoints.With the advances in cancer research and drug development, there has
been a doubling of FDA applications and approved drugs over time. These encouraging findings from our report should provide some reassurance to cancer patients, oncologists, clinical trial investigators, and drug development researchers.
ACKNOWLEDGMENT This work was supported by the Dr. John A. Kerner Research Fund.
AUTHOR CONTRIBUTIONS Conception and design: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Provision of study material or patients: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Collection and/or assembly of data: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Data analysis and interpretation: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Manuscript writing: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Final approval of manuscript: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam
DISCLOSURES Bradley J. Monk: Qiagen, Roche/Genentech, GlaxoSmithKline, Merck, Arno (C/A); Roche/Genentech, Johnson & Johnson (H); Novartis, Amgen, Genentech, Lilly (compensation paid to institution) (RF). The other authors indicated no financial relationships. (C/A) Consulting/advisory relationship; (RF) Research funding; (E) Employment; (ET) Expert testimony; (H) Honoraria received; (OI) Ownership interests; (IP) Intellectual property rights/ inventor/patent holder; (SAB) Scientific advisory board
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17. Tang PA, Bentzen SM, Chen EX et al. 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. 18. 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. 19. Booth CM, Eisenhauer EA. Progression-free survival: Meaningful or simply measurable? J Clin Oncol 2012;30:1030–1033. 20. 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. 21. 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. 22. Dimasi JA. Risks in new drug development: Approval success rates for investigational drugs. Clin Pharmacol Ther 2001;69:297–307. 23. Amir E, Seruga B, Martinez-Lopez J et al. Oncogenic targets, magnitude of benefit, and market pricing of antineoplastic drugs. J Clin Oncol 2011;29: 2543–2549.
See http://www.TheOncologist.com for supplemental material available online.
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not thoroughly evaluate all efficacious drugs currently available on the market; nevertheless, many of these trials incorporated regimens that are the standard of care. Lastly, our descriptive analyses are limited, because they are based on historical actions of the FDA, and may not predict future trial success as this process is complex and dynamic. Our descriptive study may not be capable of predicting for FDA approval given that there are insufficient numbers of trials available to perform the indepth analysis required to develop a robust model. Nevertheless, this is one of the first studies that has attempted to analyze the FDA approval process using objective measurements of efficacy and toxicity. More complex discriminatory studies can be developed once larger data sets with objective information on approved and disapproved drugs are available.
Applications for Oncologic Drugs: A Descriptive Analysis of the Oncologic Drugs Advisory Committee Reviews JOHN K. CHAN,a,d TUYEN K. KIET,a BRADLEY J. MONK,b NICHOLE YOUNG-LIN,a KEVIN BLANSIT,a,d DANIEL S. KAPP,c IDOROENYI AMANAMa a Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California, USA; bDivision of Gynecologic Oncology, Creighton University School of Medicine, St. Joseph’s Hospital and Medical Center, Phoenix, Arizona, USA; cDepartment of Radiation Oncology, Stanford University School of Medicine, Stanford, California, USA; dPalo Alto Medical Foundation Research Institute, Palo Alto, California, USA
Disclosures of potential conflicts of interest may be found at the end of this article.
Key Words. Oncologic Drugs Advisory Committee x U.S. Food and Drug Administration x Oncology drug applications x
ABSTRACT Background. Despite advances in cancer research, the majority of drug applications submitted to the U.S. Food and Drug Administration (FDA) are not approved. It is important to identify the concerns of the Oncologic Drugs Advisory Committee (ODAC) from rejected applications. Methods. All applications referred to the ODAC from 2001 to 2012 were reviewed. Results. Of 46 applications, 31 (67%) were for full and 15 (33%) were for supplemental approval, 34 (74%) were for solid and 12 (26%) were for hematologic tumors. In all, 22 (48%) were not approved. ODAC comments addressed missing or inadequate data (65%), excessive toxicity (55%), inappropriate study endpoints (45%), poor study design (40%), and insufficient sample size (30%). To define efficacy, 19 applications used response rates (RR) (median 5 38%), and 19 applications used
hazard ratios (HR) (median 5 0.67). For all organ systems combined,the median cumulative grade 3 or 4 toxicity was 64%. Drugs with higher RR, lower HR, and lower toxicity were more likely to be approved versus other drugs (89% vs. 45%; p 5 .02). Over time (2001–2004, 2005–2008, 2009–2012), there was an increase in the following: number of applications submitted for review (from 11 to 12 to 23, respectively), number of approvals (from 6 to 6 to 12, respectively), and proportion of trials using progression-free survival as a primary endpoint (from 0% to 50% to 70%, respectively; p 5 .01). Conclusion. Of all applications, common ODAC concerns included inadequate data, excessive toxicity, and inappropriate study endpoints. Over time, there was an approximate doubling of FDA application submissions and approved oncology drugs. The Oncologist 2014;19:299–304
Implications for Practice: Currently, there is limited information regarding how clinical trials are evaluated by the FDA and Oncologic Drugs Advisory Committee (ODAC). To guide clinical researchers toward improving the design of clinical trials and potentially improving the likelihood of FDA approval, we studied the concerns addressed by the ODAC on rejected drug applications and identified factors associated with FDA approval. Furthermore, we showed that there was an increase in the number of FDA applications and approved drugs over the last 10 years. These encouraging findings from our report may guide clinical researchers to more efficiently use resources for clinical trials.
INTRODUCTION Over the last decade, significant advances in cancer research have been made based on sequencing of the human genome, identification of driving growth factors and receptors, and signaling pathways [1]. From 2007 to 2010, research innovations led to an estimated 1,884 phase I, 3,436 phase II, and 1,025 phase III oncology clinical trials [2]. The number of therapeutic cancer agents in development has also doubled annually over the last 20 years [3]. Prospective phase III registration trials are costly, arduous, and lengthy [4]. The current costs of an industry-sponsored
phase III clinical trial range from 10 to 20 million dollars [5]. In addition,these clinical studies require hundreds tothousands of patients and necessitate an average of 6 years to complete [6]. It is estimated that pharmaceutical companies spend an average of $1.7 billion dollars per drug from development to market approval [7]. Despite these investments, only 40% of drug applications submitted for consideration are approved [1, 8, 9]. The U.S. Food and Drug Administration (FDA) is responsible for protecting and promoting public health in part through regulation of pharmaceutical drugs. The FDA often
Correspondence: John K. Chan, M.D., University of California, San Francisco School of Medicine, 1600 Divisadero Street, Room A747, Box 1702, San Francisco, California 94143-1702, USA; or Palo Alto Medical Foundation Research Institute, 795 El Camino Real, Ames Research Building, Palo Alto, California 94301, USA.Telephone: 415-751-1847; E-Mail: [email protected] Received July 29, 2013; accepted for publication December 23, 2013; first published online in The Oncologist Express on March 5, 2014. ©AlphaMed Press 1083-7159/2014/$20.00/0 http://dx.doi.org/ 10.1634/theoncologist.2013-0276
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MATERIALS AND METHODS We identified all drug license applications referred to ODAC from 2001 to 2012. Using the FDA’s website, we analyzed FDA and sponsor presentations, minutes, and transcripts. We then abstracted the characteristics of these drug applications (Table 1). We also supplemented this information by reviewing the drug application’s pivotal study published in a peer-reviewed journal (supplemental online appendix). More specifically, we analyzed the clinical trial data published in the peer-reviewed journal that was referenced as the pivotal study supporting the drug application. We identified the publication by searching ClinicalTrials.gov, Cancer.gov, PubMed, Google Scholar, and the drug manufacturer’s website. The clinical trial data was correlated with information from the transcripts, presentations, and peer-reviewed journals.We then compiled the hazard ratio (HR), response rate (RR), and cumulative toxicity profiles of each drug.The HRs were extracted from studies using either progression-free survival (PFS) or overall survival (OS) as the primary endpoint. The RRs were evaluated using Response Evaluation Criteria in Solid Tumors or other biomarker criteria. To better assess the level and extent of toxicity, we elected to use the median cumulative grade 3 or 4 toxicities, defined as the sum of all significant toxicity percentages, of each organ system. We then investigated these factors to estimate the likelihood of FDA approval. To identify concerns addressed by the ODAC members, we identified key words such as endpoint, toxicity, adverse, safety, inadequate, population, sample, size, small, missing, length, collection, study, design, analysis, imaging, and radiology. Next, we grouped the concerns into six major categories: adequacy of data, toxicity, endpoints, study design, sample size, and radiological imaging. We compared the ODAC decision with the FDA Approved Drug Products database (Drugs@FDA, http://www. accessdata.fda.gov/scripts/cder/drugsatfda/) to identify discrepancies between ODAC recommendations and final FDA approval. To determine the trend and progress over time, the applications were divided into three groups based on the year of ODAC submission: 2001–2004, 2005–2008, and 2009–2012.
Table 1. Characteristics of drug applications Characteristics
n (%)
Type of application New drug application Biologic license application Supplemental Type of approval Full Accelerated Type of cancer Solid Hematologic Type of therapy Single agent Combination Route of administration Intravenous Oral Other Phase of study IIa III Type of cancerb Leukemia Lymphoma Breast Prostate Brain Lung Pancreatic Skin Ovarian Renal Bone Sarcoma Thyroid
26 (56) 5 (11) 15 (33) 31 (67) 15 (33) 34 (74) 12 (26) 35 (76) 11 (24) 29 (63) 16 (35) 1 (2) 16 (35) 30 (65) 9 (20) 8 (17) 5 (11) 5 (11) 3 (7) 3 (7) 3 (7) 3 (7) 2 (4) 2 (4) 1 (2) 1 (2) 1 (2)
a
Two trials were randomized phase II studies. Percentages do not add up to 100% because 1 drug is reported for two indications.
b
x2 test was used to determine the association of FDA approval versus rejection based on efficacy (HR or RR) and toxicity (cumulative grades 3 and 4) of each agent. Moreover, other potential predictive factors such as type of agent, indication of use, stage of study, and study endpoint were also evaluated. A trends analysis was performed to determine the impact of study time periods and likelihood of approval. All data were analyzed using SPSS version 19 (IBM Corp., Armonk, NY, http://www-01.ibm.com/software/analytics/spss/).
RESULTS From 2001 to 2012, ODAC reviewed 46 new applications. The characteristics of drug applications and list of drugs are provided in Tables 1 and 2. Of all applications, 91% (42 of 46) of studies were published in peer-reviewed journals and the majority in the Journal of Clinical Oncology. Nearly half (48%,
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requests the Oncologic Drugs Advisory Committee (ODAC) to evaluate data concerning the safety and effectiveness of cancer drugs and provide approval recommendations. The Office of Hematology and Oncology Products made a statement on the need to “reduce inconsistencies and misunderstandings” between the FDA and sponsors that may result in failed products [10]. A prior report from our study group showed that FDA applications that contain one or more clinical trials from multiple institutions and those with industry sponsorship had a greater likelihood of obtaining FDA approval [11]. There is a lack of information on the factors that predict for the likelihood of FDA approval based on prior applications. Moreover, few studies have reported on ODAC concerns of rejected applications. In addition, there are no recent updates on the trends and progress on FDA approval of anticancer therapies. In this study, we reviewed the ODAC summary minutes, transcripts, sponsor and FDA presentations, and peer-reviewed journals over the last 10 years. The findings from this study may guide clinical researchers toward designing clinical trials more likely to obtain FDA approval based on ODAC recommendations.
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Table 2. List of drugs by indications Brand name
Drug name
Cancer type
Application
Endpoint
FDA approval
Arranona
Nelarabine
Leukemia & lymphoma
NDA/sNDA
RR
Yes
Year approved 2005/2011
Arzerra
Ofatumumab
Leukemia
BLA
RR
Yes
2009
Clolar
Clofarabine
Leukemia
sNDA
RR
No
Genasense
Oblimersen
Leukemia
NDA
RR
No
Omapro
Omacetaxine mepesuccinate
Leukemia
NDA
PFS
No
Onrigin
Laromustine
Leukemia
NDA
RR
No
Revlimidb
Lenalidomide
Leukemia
NDA
RR
Yes
2005
Sprycelc
Dasatinib
Leukemia
NDA
RR
Yes
2006
Tipifarnib
Leukemia
NDA
RR
No
Brentuximab vedotin
Lymphoma
BLA
RR
Yes
2011
Adcetrisd
Brentuximab vedotin
Lymphoma
BLA
RR
Yes
2011
Bexxar
Tositumomab
Lymphoma
BLA
RR
Yes
2003
Folotyn
Pralatrexate
Lymphoma
NDA
RR
Yes
2009
Istodaxe
Romidepsin
Lymphoma
NDA
RR
Yes
2009
Marqibo
Vincristine liposome
Lymphoma
NDA
RR
No
Pixuvri
Pixantrone dimaleate
Lymphoma
NDA
RR
No
Zevalinf
Ibritumomab tiuxetan
Lymphoma
BLA
RR
Yes
Avasting
Bevacizumab
Breast
sBLA
PFS
No
Avasting
Bevacizumab
Breast
sBLA
PFS
No
Avasting
Bevacizumab
Breast
sBLA
PFS
No
Doxil
Doxorubicin liposome
Breast
sNDA
TTP
No
Evista
Raloxifene
Breast
NDA
DFS
Yes
Avodart
Dutasteride
Prostate
sNDA
DFS
No
Casodex
Bicalutamide
Prostate
sNDA
TTP
No
Orplatna
Satraplatin
Prostate
NDA
PFS
No
Proscar
Finasteride
Prostate
sNDA
DFS
No
Xinlay
Atrasentan
Prostate
NDA
TTP
No
Avastinh
Bevacizumab
Brain
sBLA
RR
Yes
2009
Gliadel
Carmustine
Brain
NDA
OS
Yes
2003
RSR 13
Efaproxiral
Brain
NDA
OS
No
Iressai
Gefitinib
Lung
NDA
RR
Yes
2003
Alimtaj
Pemetrexed
Lung
NDA
OS
Yes
2004
Tarceva
Erlotinib
Lung
sNDA
PFS
Yes
2010
Afinitor
Everolimus
Pancreas
sNDA
PFS
Yes
2009
Sutent
Sunitinib
Pancreas
sNDA
PFS
Yes
Tarcevak
Erlotinib
Pancreas
NDA
OS
Yes
Genasense
Oblimersen
Skin
NDA
OS
No
2002
2007
2005
IntraDose
Cisplatin/Epinephrine
Skin
NDA
RR
No
Pegintronl
Peginterferon a-2b
Skin
sBLA
PFS
Yes
2011
Gemzarm
Gemcitabine
Ovary
NDA
PFS
Yes
2006
Yondelis
Trabectedin
Ovary
NDA
PFS
No
Inlyta
Axitinib
Kidney
NDA
PFS
No
Votrient
Pazopanib
Kidney
NDA
PFS
Yes
2009
Zometa
Zoledronic acid
Bone
sNDA
Skeletal event
Yes
2004
Junovan
Mifamurtide
Sarcoma
NDA
DFS
No
Caprelsa
Vandetanib
Thyroid
NDA
PFS
Yes
2011
a
Arranon: T-cell acute lymphoblastic leukemia and T-cell lymphoblastic lymphoma after two failed chemotherapy regimens. b Revlimid: transfusion-dependent anemia because of low- or intermediate-risk myelodysplastic syndromes with a deletion 5q cytogenetic abnormality. c Sprycel: chronic, accelerated, or blast-phase chronic myeloid leukemia with resistance/intolerance to imatinib; adults with Philadelphia chromosome-positive acute lymphoblastic leukemia and lymphoid blast chronic myeloid leukemia with resistance/intolerance to prior therapy. d Adcetris: Two different BLAs were filled for this drug; both were included for completeness. e Istodax: cutaneous T-cell lymphoma in patients who have received at least one prior systemic therapy. f Zevalin: relapsed or refractory low-grade, follicular, or CD201 transformed B-cell non-Hodgkins lymphoma (NHL) and rituximab refractory follicular NHL. g Avastin: Multiple indications referenced. h Avastin: previously treated glioblastoma multiforme. i Iressa: locally advanced or metastatic non-small cell lung cancer in patients who have previously received platinum-based chemotherapy. j Alimta: locally advanced or metastatic non-small cell lung cancer after prior chemotherapy. k Tarceva: in combination with gemcitabine for first-line, locally advanced, unresectable, or metastatic pancreatic cancer. l Pegintron: adjuvant treatment for melanoma. m Gemcitabine: combination with carboplatin for advanced ovarian cancer that had relapsed at least 6 months after first-line platinum-based therapy. Abbreviations: BLA, biologic license application; DFS, disease-free survival; NDA, new drug application; OS, overall survival; PFS, progression-free survival; RR, response rate; sBLA, supplemental BLA; sNDA, supplemental NDA; TTP, time to progression.
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42 of 46) of all applications submitted for ODAC review were rejected. The most common concerns are listed in Figure 1. More specifically, the category of “inadequate data” included “missing patient information, inadequate survival follow-up, limited or discrepant data, robustness of survival benefit, and lack of meaningful quality of life data.” The major concerns of “study design and endpoint” included issues with “control group, unspecified subgroup, sample size, blinding, off-trial subsequent therapy confounding survival analysis, and subset analysis of endpoint not prespecified, such as symptom-free time analysis.” Under the category “sample size” concerns, we included “lack or poor accrual of U.S. enrollees or population not prevalent in U.S., and unspecified subgroup and heterogeneous populations.” To evaluate the factors associated with the likelihood of approval based on FDA reports over the last 10 years, we focused on efficacy and toxicity. Forty-one percent (19 of 46) of applications used hazard ratios (HR) and 41% (19 of 46) used response rates (RR) as endpoints for efficacy. Of the 19 applications that reported on hazard ratios, 74% (14 of 19) used progression-free survival (PFS) and 26% (5 of 19) had overall survival (OS) as the primary endpoint. Of these 19 applications, the median HR was 0.67 (range: 0.35–0.99), and 47% (9 of 19) of applications were approved. In a subset analysis of these applications (n 5 19), 60% (3 of 5) of applications were approved for OS benefit versus 50% (7 of 14) approved for PFS benefit (p 5 .70). Of the 19 drugs that reported on RRs, the median RR was 38% (range: 17%–86%), and 63% (12 of 19) were approved. The remaining eight studies used other endpoints. To evaluate the toxicity associated with each drug, we elected to use the median grade 3 or 4 toxicity, defined as the sum of all grade 3 and grade 4 toxicity percentages of each organ system. As this is the sum of all toxicities, the median was 64% (range: 5%–323%). Based on the calculated medians of the efficacy and toxicity, we defined better agents as those with lower HR (#median) and lower toxicity (#median); these drugs had an approval rate of 80% (4 of 5) versus 21% (3 of 21) in those less efficacious and more toxic drugs (p 5 .02). Similarly, higher RR ($median) and lower toxicity had an indication approval rate of 100% (6 of 6) versus 53% (8 of 15) (p 5 .09); however, this was based on four of four approved drugs. We then analyzed the efficacy (as per FDA usage) endpoints (HR and RR) and cumulative toxicity of these drugs. Our analyses showed that more efficacious and less toxic drugs
Figure 2. Food and Drug Administration approval by efficacy and toxicity.
were more likely to attain FDA approval versus others (89% [8 of 9] vs. 45% [13 of 29]; p 5 .02). In Figure 2, we provide a diagrammatic representation of our analyses that incorporates efficacy and toxicity to estimate the likelihood of FDA approval. Based on their efficacy and toxicity, we plotted all the approved drugs with filled markers and left the rejected ones unfilled. The dotted line box incorporated drugs with lower hazard ratio and lower toxicity, whereas the dashed line box represents the higher RR and lower toxicity based on median value. Our data showed that drugs that have efficacy and toxicity found within the dotted line box have an estimated approval rate of 89% (8 of 9) compared with only 45% (13 of 29) for those outside of the box. To identify the trends and progress of oncology drug application development using ODAC reviews over the last decade, we divided the study into three time periods: 2001–2004, 2005–2008, and 2009–2012. Over these periods, 11, 12, and 23 applications were submitted for review with corresponding approval rates of 55% (6 of 11), 50% (6 of 12), and 53% (12 of 23) (Fig. 3). Although the rate of approval did not change, the number of approved drugs increased from 6 during the first and second time periods to 12 during the last time period. There was also a significant increase in the proportion of applications using progression-free survival as an endpoint (0% [0 of 11] to 50% [6 of 12] to 70% [16 of 23]; p 5 .01). Accordingly, there was a decrease in the use of overall survival (36% [4 of 11] to 8% [1 of 12] to 0% [0 of 23]) and RR (46% [5 of 11] to 25% [3 of 12] to 26% [6 of 23]) as primary endpoints.There was no significant change in the proportion of full versus accelerated approval, type of cancers, route of drug administration, and type of clinical trial (phase II vs. III) submitted for review over the study period.
DISCUSSION Despite the significant time and costs invested in drug development, the reported success rate is only 8% [7, 8]. To guide clinical researchers to better design clinical trials and potentially improve the likelihood of FDA approval, we studied the concerns addressed by the ODAC on rejected drug applications and identified factors associated with FDA approval.
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Figure 1. Concerns addressed by Oncologic Drugs Advisory Committee review. Abbreviation: ODAC, Oncologic Drugs Advisory Committee.
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In our analysis of the concerns addressed by the FDA/ODAC that likely contributed to a drug’s disapproval, we highlighted the importance to our regulatory agency of providing a comprehensive analysis of clinical trial data. We also elucidated important information that was uncovered by the FDA/ODAC consultants and reviewers but that was not found in the peerreviewed publication, pointing to the limitations of our current peer-review process (Fig. 1). Although our peer-review system is limited, it is the primary modality for dissemination of important clinical trial data [12, 13]. Nevertheless, researchers need to be mindful of these FDA/ODAC concerns in the design of future clinical trials. To assure optimal chance for approval, attention should be directed toward adherence to the ODAC concerns, as summarized in Figure 1. Study design should consider issues of adequacy of sample size, appropriateness of control group, specific subgroup stratification, employment of correct analytic methods, and appropriateness of endpoints. It may be intuitive that effective and nontoxic drugs warrant FDA approval; however, there are limited studies that have attempted to quantify this complex decision process using descriptive analyses. Experts have advised on the importance of registration agencies to balance the improved efficacy of a new drug with its toxicity before approval [14, 15]. Unfortunately, there is a lack of information on the level of acceptable toxicity combined with the extent ofclinical benefit that is more likely to result in FDA approval. In this current report, we identified toxicity and efficacy endpoints correlated with FDA decision and demonstrated these analyses in a diagrammatic chart (Fig. 2). Clearly, further studies are warranted to validate these analyses on assessing FDA approval of drug applications by utilizing larger sample sizes or data from other agencies. By evaluating the drug license applications and subsequent approvals or rejections over the last 10 years, we were able to identify changes in oncology trial design and associated trends of FDA decisions. We found an increase in the number of drugs reviewed by ODAC and the number of drugs approved over time (Fig. 3).There was also an increase in the use of progression-free survival (PFS) as a primary endpoint, such as in colon cancer [16–18]. Moreover, in a review of randomized control trials from 2004 to 2009 on breast, colorectal, and non-small cell lung cancer, Booth and Eisenhauer found a 26% increase in the use of PFS as a primary endpoint [19]. In contrast, breast cancer researchers
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showed that the prediction of OS based on PFS is uncertain [20, 21]. Although we found an increased use of PFS as primary endpoint over time, this was not correlated with an increase in FDA approval rate. In our trends analysis, we showed thatthe rate of drug approvals did not increase over time, but the absolute number of drugs approved has increased significantly over the years. Our study was limited by the lack of information on drugs disapproved or approved as new agents or for additional indications without ODAC review.We were unable to evaluate new drugs or existing drugs with other indications that were not presented to ODAC. Some of these agents included sunitinib (Sutent) for gastrointestinal stromal tumor and renal cell carcinoma; vorinostat (Zolinza) for cutaneous T-cell lymphoma; bortezomib (Velcade) for multiple myeloma or mantle cell lymphoma; everolimus (Afinitor) for renal cell carcinoma, astrocytoma, and breast cancer; abiraterone (Zytiga) for prostate cancer; and bevacizumab (Avastin) for colorectal, lung, and renal cell cancer. Given the small sample size, more rigorous statistical analyses of factors associated with approval or disapproval of drugs were not undertaken. Although we elected to report the toxicity based on the median of all types inclusive of cardiovascular, pulmonary, hematologic, gastrointestinal, renal, and others, the generalization of these toxicities into one group may not lend itself to an accurate reflection of a drug’s true toxic effect. Moreover, in treating cancers with poorer prognoses, physicians and patients may have a higher tolerance for toxicities with more aggressive agents. The grouping of these heterogeneous agents may therefore confound the predictive factors associated with FDA approval. Furthermore, the accelerated approval data collected from ODAC may not reflect confirmatory results of mature data from clinical trials. Additionally, because trials with positive results that have satisfied prespecified endpoints may not go to ODAC, the results of this current report may be biased toward studies that qualify for ODAC review. Moreover, the FDA summaries reviewed in our study may not reflect a complete account of these reviewers’ opinions, because the final FDA decisions are made in closed sessions.These shortcomings may limit our analysis and ability to form definitive conclusions. Factors for advancing drugs for development and market are complex. Prior studies have shown that the novelty and unique target of the drug, favorable pharmacokinetic profile, biologic activity in phase I-II trials, clinical demand for new therapies, market demand, and financial return on investment are all important components for successful drug development [5]. With respect to the financial implications of drug development, it is estimated that more than 30% of the drugs entering clinical trials are abandoned because of economic considerations [22]. In addition, some have suggested the use of biomarkers to identify the most sensitive population while reducing the cost and duration of drug development; however, this is unlikely to reduce the market price of drugs [23]. Clearly, all these factors are important in advancing new drugs but were difficult to evaluate in our study. Furthermore, our analyses make the assumption that these oncologic drugs have similar clinical efficacy across all tumor types. It is clear that there are cancers with unmet need, for which the expectations are based not only on survival but also on acceptable levels of toxicity and improvements in quality of life. Additionally, we did ©AlphaMed Press 2014
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Figure 3. Applications and approvals by year of Oncologic Drugs Advisory Committee review. Abbreviation: ODAC, Oncologic Drugs Advisory Committee.
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CONCLUSION In this analysis of oncology drug applications, we were able to learn from the rejected applications by identifying the most common FDA concerns.We also highlighted the importance of our regulatory agency to provide a comprehensive analysis of clinical trial data not reported in peer-reviewed publications. Our study using drug efficacy and toxicity provides specific measurements to aid in forecasting the FDA approval process. Clinical researchers need to consider these FDA concerns in the design of future clinical trials, including inadequate data, excessive toxicity, and inappropriate study endpoints.With the advances in cancer research and drug development, there has
been a doubling of FDA applications and approved drugs over time. These encouraging findings from our report should provide some reassurance to cancer patients, oncologists, clinical trial investigators, and drug development researchers.
ACKNOWLEDGMENT This work was supported by the Dr. John A. Kerner Research Fund.
AUTHOR CONTRIBUTIONS Conception and design: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Provision of study material or patients: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Collection and/or assembly of data: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Data analysis and interpretation: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Manuscript writing: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam Final approval of manuscript: John K. Chan, Tuyen K. Kiet, Bradley J. Monk, Nichole Young-Lin, Kevin Blansit, Daniel S. Kapp, Idoroenyi Amanam
DISCLOSURES Bradley J. Monk: Qiagen, Roche/Genentech, GlaxoSmithKline, Merck, Arno (C/A); Roche/Genentech, Johnson & Johnson (H); Novartis, Amgen, Genentech, Lilly (compensation paid to institution) (RF). The other authors indicated no financial relationships. (C/A) Consulting/advisory relationship; (RF) Research funding; (E) Employment; (ET) Expert testimony; (H) Honoraria received; (OI) Ownership interests; (IP) Intellectual property rights/ inventor/patent holder; (SAB) Scientific advisory board
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not thoroughly evaluate all efficacious drugs currently available on the market; nevertheless, many of these trials incorporated regimens that are the standard of care. Lastly, our descriptive analyses are limited, because they are based on historical actions of the FDA, and may not predict future trial success as this process is complex and dynamic. Our descriptive study may not be capable of predicting for FDA approval given that there are insufficient numbers of trials available to perform the indepth analysis required to develop a robust model. Nevertheless, this is one of the first studies that has attempted to analyze the FDA approval process using objective measurements of efficacy and toxicity. More complex discriminatory studies can be developed once larger data sets with objective information on approved and disapproved drugs are available.
