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Mah J, Magari R, Lo KK, Winden N, Xu G. A benefit risk approach in cutoff determination for diagnostic tests. Clin Chim Acta 2024; 559:117887. [PMID: 38643818 DOI: 10.1016/j.cca.2024.117887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 03/08/2024] [Accepted: 03/22/2024] [Indexed: 04/23/2024]
Abstract
A crucial step in the design of a diagnostic test is determining the cutoff point, the threshold which separates a negative measurement from a positive one. The results of a diagnostic test have clinical consequences: only when disease is accurately detected, proper treatments be administered, and vice versa. Benefit-Risk (BR) analysis should be used to determine the optimal cutoff point that optimizes the consequence. Quantitative BR analysis requires measurable benefit and risk and a function, e.g., linear or ratio, to combine all the components. When BR corresponding to the four possible diagnostic test outcomes are all scaled in units of risk resulting from an untreated disease, we propose a net BR (linear BR) equation as a function of diagnostic parameters, disease prevalence, benefit of correct diagnosis and risk of false diagnostic results. Optimal cutoff of a diagnostic test can be obtained using this function. Comparison of diagnostic tests based on their benefit and risk of tests is also discussed. Use of this function is illustrated with a biosensor rapid antigen test for SARS-CoV-2.
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Affiliation(s)
- Jeng Mah
- Department of Biostatistics and Data Management, Beckman Coulter, Inc. Chaska, MN, USA.
| | - Robert Magari
- Department of Biostatistics and Data Management, Beckman Coulter, Inc. Miami, Florida, USA.
| | - Karen Kw Lo
- Department of Biostatistics and Data Management, Beckman Coulter, Inc. Miami, Florida, USA.
| | - Nicole Winden
- Department of Biostatistics and Data Management, Beckman Coulter, Inc. Chaska, MN, USA.
| | - Gang Xu
- Department of Biostatistics, Vertex Pharmaceuticals, Inc. Boston, MA, USA.
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2
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Vikkula J, Uusi-Rauva K, Ranki T, Toppila I, Aalto-Setälä M, Pousar K, Vassilev L, Porkka K, Silvennoinen R, Brück O. Real-world evidence of multiple myeloma treated from 2013 to 2019 in the Hospital District of Helsinki and Uusimaa, Finland. Future Oncol 2023; 19:2029-2043. [PMID: 37828901 DOI: 10.2217/fon-2023-0120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023] Open
Abstract
Background: The rapid development of multiple myeloma (MM) management underscores the value of real-world data. In our study we examined 509 adult MM patients treated with immunochemotherapy (ICT) with/without stem cell transplantation (SCT) from 2013 to 2019 in the Hospital District of Helsinki and Uusimaa, Finland. Materials & methods: Our study was based on computational analyses of data integrated into the hospital data lake. Results: After 2017, treatment pattern diversity increased with improved access to novel treatments. 5-year survivals were 74.4% (95% CI: 65.5-84.5) in SCT-eligible and 44.0% (95% CI: 37.6-51.4) in non-SCT subgroups. In the SCT-eligible subgroup, high first-year hospitalization costs were followed by stable resource requirements. Conclusion: Hospital data lakes can be adapted to carry out complex analysis of large MM cohorts.
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Affiliation(s)
| | | | | | | | | | | | | | - Kimmo Porkka
- Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, & University of Helsinki, Helsinki, Finland
| | - Raija Silvennoinen
- Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, & University of Helsinki, Helsinki, Finland
| | - Oscar Brück
- Hematoscope Lab, Comprehensive Cancer Center & Center of Diagnostics, Helsinki University Hospital & University of Helsinki, Haartmaninkatu 8, PO Box 700, Helsinki, 00290, Finland
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3
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The Role of T Cell Immunity in Monoclonal Gammopathy and Multiple Myeloma: From Immunopathogenesis to Novel Therapeutic Approaches. Int J Mol Sci 2022; 23:ijms23095242. [PMID: 35563634 PMCID: PMC9104275 DOI: 10.3390/ijms23095242] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/03/2022] [Accepted: 05/05/2022] [Indexed: 02/01/2023] Open
Abstract
Multiple Myeloma (MM) is a malignant growth of clonal plasma cells, typically arising from asymptomatic precursor conditions, namely monoclonal gammopathy of undetermined significance (MGUS) and smoldering MM (SMM). Profound immunological dysfunctions and cytokine deregulation are known to characterize the evolution of the disease, allowing immune escape and proliferation of neoplastic plasma cells. In the past decades, several studies have shown that the immune system can recognize MGUS and MM clonal cells, suggesting that anti-myeloma T cell immunity could be harnessed for therapeutic purposes. In line with this notion, chimeric antigen receptor T cell (CAR-T) therapy is emerging as a novel treatment in MM, especially in the relapsed/refractory disease setting. In this review, we focus on the pivotal contribution of T cell impairment in the immunopathogenesis of plasma cell dyscrasias and, in particular, in the disease progression from MGUS to SMM and MM, highlighting the potentials of T cell-based immunotherapeutic approaches in these settings.
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4
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Tsirpitzi RE, Miller F. Optimal dose-finding for efficacy-safety models. Biom J 2021; 63:1185-1201. [PMID: 33829555 DOI: 10.1002/bimj.202000181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 12/11/2020] [Accepted: 01/22/2021] [Indexed: 11/05/2022]
Abstract
Dose-finding is an important part of the clinical development of a new drug. The purpose of dose-finding studies is to determine a suitable dose for future development based on both efficacy and safety. Optimal experimental designs have already been used to determine the design of this kind of studies, however, often that design is focused on efficacy only. We consider an efficacy-safety model, which is a simplified version of the bivariate Emax model. We use here the clinical utility index concept, which provides the desirable balance between efficacy and safety. By maximizing the utility of the patients, we get the estimated dose. This desire leads us to locally c -optimal designs. An algebraic solution for c -optimal designs is determined for arbitrary c vectors using a multivariate version of Elfving's method. The solution shows that the expected therapeutic index of the drug is a key quantity determining both the number of doses, the doses itself, and their weights in the optimal design. A sequential design is proposed to solve the complication of parameter dependency, and it is illustrated in a simulation study.
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Affiliation(s)
| | - Frank Miller
- Department of Statistics, Stockholm University, Stockholm, Sweden
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5
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Raju GK, Khozin S, Gurumurthi K, Domike R, Woodcock J. Patient-Centered Approach to Benefit-Risk Characterization Using Number Needed to Benefit and Number Needed to Harm: Advanced Non-Small-Cell Lung Cancer. JCO Clin Cancer Inform 2020; 4:769-783. [PMID: 32853030 DOI: 10.1200/cci.19.00103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
This work summarizes the benefit and risk of the results of clinical trials submitted to the US Food and Drug Administration of therapies for the treatment of non-small cell lung cancer (NSCLC) using number needed to benefit (NNB) and number needed to harm (NNH) metrics. NNB and NNH metrics have been reported as potentially being more patient centric and more intuitive to medical practitioners than more common metrics, such as the hazard ratio, and valuable to medical practitioners in complementing other metrics, such as the median time to event. This approach involved the characterization of efficacy and safety results in terms of NNB and NNH of 30 clinical trials in advanced NSCLC supporting US Food and Drug Administration approval decisions from 2003 to 2017. We assessed trends of NNB over time of treatment (eg, for programmed death 1 inhibitors) and variation of NNB across subpopulations (eg, characterized by epidermal growth factor receptor mutation, programmed death ligand 1 expression, Eastern Cooperative Oncology Group performance status, age, and extent of disease progression). Furthermore, the evolution of NNB of treatments for advanced NSCLC was charted from 2003 to 2017. Across subpopulations, NNB, on average, was 4 patients for approved targeted therapies in molecularly enriched populations, 11 patients for approved therapies in nonmolecularly enriched populations, and 23 patients for withdrawn or unapproved therapies. Furthermore, the NNB analysis showed variation for attributes of epidermal growth factor receptor mutations, level of programmed death 1 expression, Eastern Cooperative Oncology Group performance status, etc. When considering the best-case subpopulations and available drugs, the NNB frontier reduced from an estimated value of 7.7 in 2003 to an estimated value of 2.5 in 2017 at the estimated median overall survival-equal to 6 months-of an untreated patient.
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Affiliation(s)
- Gokaraju K Raju
- Light Pharma, Cambridge, MA.,Massachusetts Institute of Technology, Cambridge, MA
| | - Sean Khozin
- US Food and Drug Administration, Silver Spring, MD
| | | | - Reuben Domike
- Light Pharma, Cambridge, MA.,Brigham Young University, Provo, UT
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6
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Selen A, Müllertz A, Kesisoglou F, Ho RJY, Cook JA, Dickinson PA, Flanagan T. Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products. AAPS JOURNAL 2020; 22:97. [PMID: 32719954 DOI: 10.1208/s12248-020-00470-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 06/04/2020] [Indexed: 12/20/2022]
Abstract
Decision-making in drug development benefits from an integrated systems approach, where the stakeholders identify and address the critical questions for the system through carefully designed and performed studies. Biopharmaceutics Risk Assessment Roadmap (BioRAM) is such a systems approach for application of systems thinking to patient focused and timely decision-making, suitable for all stages of drug discovery and development. We described the BioRAM therapy-driven drug delivery framework, strategic roadmap, and integrated risk assessment instrument (BioRAM Scoring Grid) in previous publications (J Pharm Sci 103:3377-97, 2014; J Pharm Sci 105:3243-55, 2016). Integration of systems thinking with pharmaceutical development, manufacturing, and clinical sciences and health care is unique to BioRAM where the developed strategy identifies the system and enables risk characterization and balancing for the entire system. Successful decision-making process in BioRAM starts with the Blueprint (BP) meetings. Through shared understanding of the system, the program strategy is developed and captured in the program BP. Here, we provide three semi-hypothetical examples for illustrating risk-based decision-making in high and moderate risk settings. In the high-risk setting, which is a rare disease area, two completely alternate development approaches are considered (gene therapy and small molecule). The two moderate-risk examples represent varied knowledge levels and drivers for the programs. In one moderate-risk example, knowledge leveraging opportunities are drawn from the manufacturing knowledge and clinical performance of a similar drug substance. In the other example, knowledge on acute tolerance patterns for a similar mechanistic pathway is utilized for identifying markers to inform the drug release profile from the dosage form with the necessary "flexibility" for dosing. All examples illustrate implementation of the BioRAM strategy for leveraging knowledge and decision-making to optimize the clinical performance of drug products for patient benefit.
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Affiliation(s)
- Arzu Selen
- US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Pharmaceutical Quality, Office of Testing and Research, 10903 New Hampshire Ave., Silver Spring, Maryland, 20993, USA.
| | - Anette Müllertz
- Bioneer: FARMA, Department of Pharmacy, University of Copenhagen, 2100, Copenhagen, Denmark
| | - Filippos Kesisoglou
- Biopharmaceutics, Pharmaceutical Sciences and Clinical Supply, Merck & Co, Inc., West Point, Pennsylvania, 19486, USA
| | - Rodney J Y Ho
- University of Washington, Seattle, Washington, 98195, USA
| | - Jack A Cook
- Clinical Pharmacology Department, Global Product Development, Pfizer, Inc., Groton, Connecticut, 06340, USA
| | - Paul A Dickinson
- Seda Pharmaceutical Development Services, Alderley Park, Alderley Edge, Cheshire, SK10 4TG, UK
| | - Talia Flanagan
- UCB Pharma S.A., Avenue de l'Industrie, 1420, Braine - l'Alleud, Belgium
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7
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Sun S, Heske S, Mercadel M, Wimmer J. Predicting Regulatory Product Approvals Using a Proposed Quantitative Version of FDA's Benefit-Risk Framework to Calculate Net-Benefit Score and Benefit-Risk Ratio. Ther Innov Regul Sci 2020; 55:129-137. [PMID: 32643080 PMCID: PMC7785542 DOI: 10.1007/s43441-020-00197-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 06/23/2020] [Indexed: 12/17/2022]
Abstract
Background Approval of regulated medical products in the USA is based upon a rigorous review of the benefits and risks as performed by the US Food and Drug Administration (FDA) staff of scientists and is summarized in a descriptive and qualitative format called the FDA’s Benefit–Risk Framework (BRF). This present method highlights the key factors in regulatory decision-making, but does not clearly define the reason for its final approval. Method This study proposes a quantitative version of FDA’s BRF to calculate a Net-Benefit Score and a Benefit–Risk Ratio as a method to define a single-value summary of the tradeoffs between benefits and risks and allow comparisons among other products. In this retrospective review of five years of new molecular entities and new biologic (N = 185 products) regulatory decision-making, this proposed scoring system codifies and quantitates the information about a product’s benefits, risks, and risk management information in a format that may predict why regulated medical products are approved in the USA. Results Simple calculation of codified benefits, risks, and risk mitigations with numerical limits is proposed to provide a repeatable process and transparency for documenting the net-benefit of regulatory product approval. Conclusion Use of a strict process of collecting, codifying, and analyzing public information to determine a Net-Benefit score and a Benefit–Risk Ratio is possible to anticipate regulatory product approval.
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Affiliation(s)
- Stephen Sun
- Syneos Health, 1030 Sync Street, Morrisville, NC, 27560, USA.
| | - Suzanne Heske
- Syneos Health, 1030 Sync Street, Morrisville, NC, 27560, USA
| | | | - Jean Wimmer
- Syneos Health, 1030 Sync Street, Morrisville, NC, 27560, USA
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8
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Cowan AJ, Allen C, Barac A, Basaleem H, Bensenor I, Curado MP, Foreman K, Gupta R, Harvey J, Hosgood HD, Jakovljevic M, Khader Y, Linn S, Lad D, Mantovani L, Nong VM, Mokdad A, Naghavi M, Postma M, Roshandel G, Shackelford K, Sisay M, Nguyen CT, Tran TT, Xuan BT, Ukwaja KN, Vollset SE, Weiderpass E, Libby EN, Fitzmaurice C. Global Burden of Multiple Myeloma: A Systematic Analysis for the Global Burden of Disease Study 2016. JAMA Oncol 2019; 4:1221-1227. [PMID: 29800065 PMCID: PMC6143021 DOI: 10.1001/jamaoncol.2018.2128] [Citation(s) in RCA: 388] [Impact Index Per Article: 77.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Question What is the burden of multiple myeloma globally and by country, how has it changed over time, and how widely available are treatments for this disease? Findings Myeloma incident cases and deaths increased from 1990 to 2016, with middle-income countries contributing the most to this increase. Treatment availability is very limited in countries with low socioeconomic development. Meaning Marked variation in myeloma incidence and mortality across countries highlights the need to improve access to diagnosis and effective therapy and to expand research on etiological determinants of myeloma. Introduction Multiple myeloma (MM) is a plasma cell neoplasm with substantial morbidity and mortality. A comprehensive description of the global burden of MM is needed to help direct health policy, resource allocation, research, and patient care. Objective To describe the burden of MM and the availability of effective therapies for 21 world regions and 195 countries and territories from 1990 to 2016. Design and Setting We report incidence, mortality, and disability-adjusted life-year (DALY) estimates from the Global Burden of Disease 2016 study. Data sources include vital registration system, cancer registry, drug availability, and survey data for stem cell transplant rates. We analyzed the contribution of aging, population growth, and changes in incidence rates to the overall change in incident cases from 1990 to 2016 globally, by sociodemographic index (SDI) and by region. We collected data on approval of lenalidomide and bortezomib worldwide. Main Outcomes and Measures Multiple myeloma mortality; incidence; years lived with disabilities; years of life lost; and DALYs by age, sex, country, and year. Results Worldwide in 2016 there were 138 509 (95% uncertainty interval [UI], 121 000-155 480) incident cases of MM with an age-standardized incidence rate (ASIR) of 2.1 per 100 000 persons (95% UI, 1.8-2.3). Incident cases from 1990 to 2016 increased by 126% globally and by 106% to 192% for all SDI quintiles. The 3 world regions with the highest ASIR of MM were Australasia, North America, and Western Europe. Multiple myeloma caused 2.1 million (95% UI, 1.9-2.3 million) DALYs globally in 2016. Stem cell transplantation is routinely available in higher-income countries but is lacking in sub-Saharan Africa and parts of the Middle East. In 2016, lenalidomide and bortezomib had been approved in 73 and 103 countries, respectively. Conclusions and Relevance Incidence of MM is highly variable among countries but has increased uniformly since 1990, with the largest increase in middle and low-middle SDI countries. Access to effective care is very limited in many countries of low socioeconomic development, particularly in sub-Saharan Africa. Global health policy priorities for MM are to improve diagnostic and treatment capacity in low and middle income countries and to ensure affordability of effective medications for every patient. Research priorities are to elucidate underlying etiological factors explaining the heterogeneity in myeloma incidence.
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Affiliation(s)
- Andrew J Cowan
- Division of Medical Oncology, University of Washington, Seattle
| | - Christine Allen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | | | | | - Maria Paula Curado
- Accamargo Cancer Center, São Paolo, Brazil.,International Prevention Research Institute, Ecully, France
| | - Kyle Foreman
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Rahul Gupta
- West Virginia Bureau for Public Health, Charleston
| | - James Harvey
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | - Mihajlo Jakovljevic
- University of Kragujevac, Kragujevac, Serbia.,Center for Health Trends and Forecasts, University of Washington, Seattle
| | - Yousef Khader
- Department of Community Medicine, Public Health and Family Medicine, Jordan University of Science and Technology, Irbid, Jordan
| | | | - Deepesh Lad
- Postgraduate Institute of Medical Education and Research, Candigarh, India
| | | | - Vuong Minh Nong
- Institute for Global Health Innovations, Duy Tan University, Danang, Vietnam
| | - Ali Mokdad
- International Prevention Research Institute, Ecully, France
| | - Mohsen Naghavi
- International Prevention Research Institute, Ecully, France
| | | | - Gholamreza Roshandel
- Golestan Research Center of Gastroenterology and Hepatology, Golestan University of Medical Sciences, Gorgan, Iran.,Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Katya Shackelford
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | - Cuong Tat Nguyen
- Institute for Global Health Innovations, Duy Tan University, Danang, Vietnam
| | - Tung Thanh Tran
- Institute for Global Health Innovations, Duy Tan University, Danang, Vietnam
| | - Bach Tran Xuan
- Haramaya University, Haramaya, Ethiopia.,Johns Hopkins University, Baltimore, Maryland.,Hanoi Medical University, Hanoi, Vietnam
| | | | | | - Elisabete Weiderpass
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.,Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo
| | - Edward N Libby
- Division of Medical Oncology, University of Washington, Seattle
| | - Christina Fitzmaurice
- Institute for Health Metrics and Evaluation, University of Washington, Seattle.,Division of Hematology, University of Washington, Seattle
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9
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Raju GK, Gurumurthi K, Domike R, Singh H, Weinstock C, Kluetz P, Pazdur R, Woodcock J. Using a Benefit–Risk Analysis Approach to Capture Regulatory Decision Making: Renal Cell Carcinoma. Clin Pharmacol Ther 2019; 107:495-506. [DOI: 10.1002/cpt.1589] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 06/19/2019] [Indexed: 01/05/2023]
Affiliation(s)
- G. K. Raju
- Light Pharma, Inc. Cambridge Massachusetts USA
| | | | - Reuben Domike
- Light Pharma, Inc. Cambridge Massachusetts USA
- Manufacturing Engineering Brigham Young University Provo Utah USA
| | - Harpreet Singh
- Center for Drug Evaluation and Research US Food and Drug Administration Silver Spring Maryland USA
| | - Chana Weinstock
- Center for Drug Evaluation and Research US Food and Drug Administration Silver Spring Maryland USA
| | - Paul Kluetz
- Center for Drug Evaluation and Research US Food and Drug Administration Silver Spring Maryland USA
| | - Richard Pazdur
- Center for Drug Evaluation and Research US Food and Drug Administration Silver Spring Maryland USA
| | - Janet Woodcock
- Center for Drug Evaluation and Research US Food and Drug Administration Silver Spring Maryland USA
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10
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Raju GK, Gurumurthi K, Domike R, Theoret MR, Pazdur R, Woodcock J. Using a Benefit-Risk Analysis Approach to Capture Regulatory Decision Making: Melanoma. Clin Pharmacol Ther 2019; 106:123-135. [PMID: 30993685 DOI: 10.1002/cpt.1461] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 03/17/2019] [Indexed: 01/05/2023]
Abstract
Drug regulators seek to make decisions regarding drug approvals based on analysis of the relevant benefits and risks. In this work, 25 US Food and Drug Administration (FDA) decisions on melanoma drugs were identified and analyzed based on clinical trial results published between 1999 and 2017. In each case, the benefits and risks of the new drug in each clinical trial relative to a comparator (typically the control arm of the same clinical trial) were quantified. The benefits and risks were analyzed using a common scale to allow for direct comparison. A sensitivity analysis was conducted using vemurafenib to explore the magnitude of uncertainty in the quantitative assessments. The associated FDA decision outcomes of the new drugs were consistent with the benefits and risks quantified in this work.
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Affiliation(s)
- G K Raju
- Light Pharma, Inc., Cambridge, Massachusetts, USA.,Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | | | - Reuben Domike
- Light Pharma, Inc., Cambridge, Massachusetts, USA.,Brigham Young University, Provo, Utah, USA
| | - Marc R Theoret
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Richard Pazdur
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Janet Woodcock
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
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11
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Zhu R, Poland B, Wada R, Liu Q, Musib L, Maslyar D, Cho E, Yu W, Ma H, Jin JY, Budha N. Exposure-Response-Based Product Profile-Driven Clinical Utility Index for Ipatasertib Dose Selection in Prostate Cancer. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 8:240-248. [PMID: 30762302 PMCID: PMC6482275 DOI: 10.1002/psp4.12394] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 01/14/2019] [Indexed: 12/21/2022]
Abstract
The aims of this work were to characterize ipatasertib exposure–response (E‐R) relationships in a phase II study and to quantitatively assess benefit‐risk using a clinical utility index approach to support ipatasertib phase III dose selection in patients with metastatic castration‐resistant prostate cancer. Logistic regression and Cox proportional‐hazards models characterized E‐R relationships for safety and efficacy endpoints, respectively. Exposure metrics with and without considering dose interruptions/reductions (modifications) were tested in the E‐R models. Despite a steeper E‐R relationship when accounting for dose modifications, similar dose‐response projections were generated. The clinical utility index analysis assessed important attributes, weights, and clinically meaningful cutoff/tradeoff values based on predefined minimal, target, and optimistic product profiles. Ipatasertib 400 mg daily, showing the highest probability of achieving the minimal product profiles and better benefit‐risk balance than other doses (200–500 mg daily), was selected for further development in metastatic castration‐resistant prostate cancer.
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Affiliation(s)
- Rui Zhu
- Genentech, Inc., South San Francisco, California, USA
| | | | - Russ Wada
- Certara, Menlo Park, California, USA
| | - Qi Liu
- Genentech, Inc., South San Francisco, California, USA
| | - Luna Musib
- Genentech, Inc., South San Francisco, California, USA
| | | | - Eunpi Cho
- Genentech, Inc., South San Francisco, California, USA
| | - Wei Yu
- Genentech, Inc., South San Francisco, California, USA
| | - Han Ma
- Genentech, Inc., South San Francisco, California, USA
| | - Jin Yan Jin
- Genentech, Inc., South San Francisco, California, USA
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12
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Waldman SA, Terzic A. Process Improvement for Maximized Therapeutic Innovation Outcome. Clin Pharmacol Ther 2018; 103:8-12. [PMID: 29265398 PMCID: PMC5745039 DOI: 10.1002/cpt.929] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Accepted: 11/02/2017] [Indexed: 12/18/2022]
Abstract
Deconvoluting key biological mechanisms forms the framework for therapeutic discovery. Strategies that enable effective translation of those insights along the development and regulatory path ultimately drive validated clinical application in patients and populations. Accordingly, parity in What vs. How we transform novel mechanistic insights into therapeutic paradigms is essential in achieving success. Aligning molecular discovery with innovations in structures and processes along the discovery-development-regulation-utilization continuum maximizes the return on public and private investments for next-generation solutions in managing health and disease.
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Affiliation(s)
- Scott A Waldman
- Department of Pharmacology and Experimental Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Andre Terzic
- Center for Regenerative Medicine, Mayo Clinic, Rochester, Minnesota, USA
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