Group-by-Treatment Interaction Effects in Comparative Bioavailability Studies
Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be...
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| Published in | The AAPS journal Vol. 26; no. 3; p. 50 |
|---|---|
| Main Authors | , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Cham
Springer International Publishing
17.04.2024
Springer |
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| Online Access | Get full text |
| ISSN | 1550-7416 1550-7416 |
| DOI | 10.1208/s12248-024-00921-x |
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| Abstract | Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups.
Graphical Abstract |
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| AbstractList | Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups.Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups. Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups. Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups. Graphical Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups. Graphical Abstract |
| ArticleNumber | 50 |
| Audience | Academic |
| Author | Dubins, David D. Stus, Volodymyr Tomashevskiy, Michael Burger, Divan A. Schütz, Helmut Shitova, Anastasia Cobo, Erik Ocaña, Jordi Labes, Detlew Lang, Benjamin Farkás, Tibor Ring, Arne |
| Author_xml | – sequence: 1 givenname: Helmut orcidid: 0000-0002-1167-7880 surname: Schütz fullname: Schütz, Helmut email: helmut.schuetz@bebac.at organization: Center for Medical Data Science of the Medical University of Vienna, Faculty of Pharmacy, Universidade de Lisboa, BEBAC – sequence: 2 givenname: Divan A. orcidid: 0000-0001-8096-6371 surname: Burger fullname: Burger, Divan A. organization: University of Pretoria, Syneos Health – sequence: 3 givenname: Erik orcidid: 0000-0002-3534-5602 surname: Cobo fullname: Cobo, Erik organization: Department of Statistics and Operations Research, Universitat Politecnica de Catalunya – sequence: 4 givenname: David D. orcidid: 0000-0002-3039-3808 surname: Dubins fullname: Dubins, David D. organization: Leslie Dan Faculty of Pharmacy – sequence: 5 givenname: Tibor surname: Farkás fullname: Farkás, Tibor organization: Gedeon Richter Plc – sequence: 6 givenname: Detlew orcidid: 0000-0003-2169-426X surname: Labes fullname: Labes, Detlew – sequence: 7 givenname: Benjamin surname: Lang fullname: Lang, Benjamin organization: Boehringer Ingelheim Pharma GmbH & Co. KG – sequence: 8 givenname: Jordi surname: Ocaña fullname: Ocaña, Jordi organization: Department of Genetics, Microbiology and Statistics, Universitat de Barcelona – sequence: 9 givenname: Arne orcidid: 0000-0002-4324-5820 surname: Ring fullname: Ring, Arne organization: University of the Free State, Hexal – a Sandoz Brand – sequence: 10 givenname: Anastasia orcidid: 0000-0003-3546-7316 surname: Shitova fullname: Shitova, Anastasia organization: Quinta-Analytica Yaroslavl – sequence: 11 givenname: Volodymyr surname: Stus fullname: Stus, Volodymyr organization: Zakłady Farmaceutyczne Polpharma S.A – sequence: 12 givenname: Michael surname: Tomashevskiy fullname: Tomashevskiy, Michael organization: OnTarget Group |
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| Keywords | Monte-Carlo simulations group-by-treatment interaction regulatory guidelines average bioequivalence |
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| References | PressWHFlanneryBPTeukolskySAVetterlingWTNumerical recipes in Fortran 77: the art of scientific computing19922CambridgeCambridge University Press603 US Food and Drug Administration, CDER. Guidance for industry. Bioavailability studies submitted in NDAs or INDs — general considerations. Silver Spring, April 2022. https://www.fda.gov/media/121311/download. Accessed 22 October 2023. AloshMFritschKHuqueMMahjoobKPennelloGRothmannMRussek-CohenESmithFWilsonSYueLStatistical considerations on subgroup analysis in clinical trialsStat Biopharm Res20157428630410.1080/19466315.2015.1077726 SunWSchuirmannDGrosserSQualitative versus quantitative treatment-by-subgroup interaction in equivalence studies with multiple subgroupsStat Biopharm Res202210.1080/19466315.2022.2123385 FuglsangASequential bioequivalence trial designs with increased power and controlled type I error ratesAAPS J20131565966110.1208/s12248-013-9475-5235436033691437 MatsumotoMNishimuraTMersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generatorACM Trans Model Comput Simul1998833010.1145/272991.272995 ZimmermanDWA note on preliminary tests of equality of variancesBr J Math Stat Psychol200457117318110.1348/00071100484922215171807 LeeJFengKXuMGongXSunWKimJZhangZWangMFangLZhaoLApplications of adaptive designs in generic drug developmentClin Pharm Ther20201101323510.1002/cpt.2050 MontagueTHPotvinDDiLibertiCEHauckWWParrAFSchuirmannDJAdditional results for ‘Sequential design approaches for bioequivalence studies with crossover designs’Pharm Stat.20111181310.1002/pst.48321308974 US Food and Drug Administration, CDER. Guidance for industry. Food-effect bioavailability and fed bioequivalence studies. Rockville, December 2002. https://www.fda.gov/files/drugs/published/Food-Effect-Bioavailability-and-Fed-Bioequivalence-Studies.pdf. Accessed 22 October 2023. SennSD’AngeloGPotvinDCarry-over in cross-over trials in bioequivalence: theoretical concerns and empirical evidencePharm Stat2004313314210.1002/pst.111 BoltonSBonCPharmaceutical statistics. Practical and clinical applications20105New YorkInforma Healthcare629 R Core Team. R: a language and environment for statistical computing. Vienna, Austria, 2023. https://www.r-project.org/. Accessed 22 Oct 2023. US Food and Drug Administration, CDER. Guidance for industry. Statistical approaches to establishing bioequivalence. Revision 1. Silver Spring, December 2022. https://www.fda.gov/media/163638/download. Accessed 22 October 2023. FreemanPRThe performance of the two-stage analysis of two-treatment, two-period crossover trialsStatist Med1989812142114321:STN:280:DyaK3c7jvF2rsg%3D%3D10.1002/sim.4780081202 US Food and Drug Administration, CDER. ANDA 077570. Bioequivalence reviews. 2008. Control document #98–392 regarding the Group-by-Treatment interaction discussion. Rockville, September 10, 1999. https://www.accessdata.fda.gov/drugsatfda_docs/anda/2008/077570Orig1s000BioeqR.pdf. Accessed 22 October 2023. D’AngeloGPotvinDTurgeonJCarry-over effects in bioequivalence studiesJ Biopharm Stat2001111&2354310.1081/bip-100104196 EndrényiLTabackNTóthfalusiProperties of the estimated variance component for subject-by-formulation interaction in studies of individual bioequivalenceStatist Med.2000192867287810.1002/1097-0258(20001030)19:20<2867::AID-SIM551>3.0.CO;2-J EMA, CHMP. Guideline on the investigation of bioequivalence. London; 2010. https://www.ema.europa.eu/documents/scientific-guideline/guideline-investigation-bioequivalence-rev1_en.pdf. Accessed 22 October 2023. PotvinDDiLibertiCEHauckWWParrAFSchuirmannDJSmithRASequential design approaches for bioequivalence studies with crossover designsPharm Stat2008724526210.1002/pst.29417710740 US Food and Drug Administration, CDER. Guidance for industry. Bioequivalence studies with pharmacokinetic endpoints for drugs submitted under an ANDA. Silver Spring, August 2021. https://www.fda.gov/media/87219/download. Accessed 22 October 2023. US Food and Drug Administration, CDER. Guidance for industry. SUPAC-IR: immediate-release solid oral dosage forms: scale-up and post-approval changes: chemistry, manufacturing and controls, in vitro dissolution testing, and in vivo bioequivalence documentation. Rockville, November 1995. https://www.fda.gov/media/70949/download. Accessed 22 October 2023. Sun W. Bioequivalence studies in multiple groups. Presentation at: SBIA. A deep dive: FDA draft guidance on statistical approaches to establishing bioequivalence. Silver Spring, March 14, 2023. https://www.fda.gov/media/167459/download. Accessed 22 October 2023. WestlakeWJBlanchardJSawchukRJBrodieBBDesign and evaluation of bioequivalence studies in manPrinciples and perspectives in drug bioavailability1979BaselKarger192210 KentDMPaulusJKvan KlaverenDD’AgostinoRGoodmanSHaywardRIoannidisJPAPatrick-LakeBMortonSPencinaMRamanGRossJSSelkerHSVaradhanRVickersAWongJBSteyerbergEWThe predictive approaches to treatment effect heterogeneity (PATH) statementAnn Intern Med20201721354510.7326/M18-366731711134 WestlakeWJPeaceKEBioavailability and bioequivalence of pharmaceutical formulationsBiopharmaceutical statistics for drug development1988New YorkMarcel Dekker336337 US Food and Drug Administration, CDER. Guidance for industry. Clinical drug interaction studies — cytochrome P450 enzyme- and transporter-mediated drug interactions. Silver Spring, January 2020. https://www.fda.gov/media/134581/download. Accessed 22 October 2023. Cortés J, Casals M, Langohr K, González JA. Importance of statistical power and hypothesis in P value. Med Clin (Barc). 2016. https://doi.org/10.1016/j.medcli.2015.10.011. Medicines for Europe. Second bioequivalence workshop. Session 2 – ICH M13 – bioequivalence for IR solid oral dosage forms. Brussels; 2023. Health Canada, Guidance Document. Conduct and analysis of comparative bioavailability studies. Ottawa. Revised Date: 2023/01/30. https://www.canada.ca/content/dam/hc-sc/documents/services/drugs-health-products/drug-products/applications-submissions/guidance-documents/bioavailability-bioequivalence/conduct-analysis-comparative.pdf. Accessed 22 October 2023. Council of the Eurasian Economic Community. On the approval of the rules for conducting research of bioequivalence of drugs within the framework of the Eurasian Economic Union. November 3, 2016; amended September 4, 2020. ICH. Bioequivalence for immediate release solid oral dosage forms. M13A. Draft version. 20 December 2022. https://database.ich.org/sites/default/files/ICH_M13A_Step2_draft_Guideline_2022_1125.pdf. Accessed 22 October 2023. ZhengCWangJZhaoLTesting bioequivalence for multiple formulations with power and sample size calculationsPharm Stat20121133434110.1002/pst.152222692852 WassersteinRLLazarNAThe ASA’s statement on p-values: context, process, and purposeAm Stat201670212913310.1080/00031305.2016.1154108 FuglsangASequential bioequivalence approaches for parallel designsAAPS J20141637337810.1208/s12248-014-9571-1245266104012040 MolinsELabesDSchützHCoboEOcañaJAn iterative method to protect the type I error rate in bioequivalence studies under two-stage adaptive 2×2 crossover designsBiom J202163112213310.1002/bimj.20190038833000873 HubbardRBayarriMJConfusion over measures of evidence (p’s) versus errors (α’s) in classical statistical testingAm Stat200357317118210.1198/0003130031856 European Medicines Agency, CHMP. Guideline on the investigation of drug interactions. Revision 1. London, 21 June 2012. https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-investigation-drug-interactions-revision-1_en.pdf. Accessed 22 October 2023. DavitBBraddyACConnerDPYuLXInternational guidelines for bioequivalence of systemically available orally administered generic drug products: a survey of similarities and differencesAAPS J201315497429010.1208/s12248-013-9499-x238213523787230 MaurerWJonesBChenYControlling the type 1 error rate in two-stage sequential designs when testing for average bioequivalenceStatist Med2018371012110.1002/sim.7614 921_CR40 G D’Angelo (921_CR23) 2001; 11 R Hubbard (921_CR39) 2003; 57 921_CR21 S Senn (921_CR26) 2004; 3 A Fuglsang (921_CR30) 2013; 15 J Lee (921_CR33) 2020; 110 DW Zimmerman (921_CR24) 2004; 57 M Matsumoto (921_CR20) 1998; 8 921_CR6 L Endrényi (921_CR27) 2000; 19 921_CR7 921_CR8 A Fuglsang (921_CR31) 2014; 16 E Molins (921_CR34) 2021; 63 921_CR9 C Zheng (921_CR19) 2012; 11 B Davit (921_CR3) 2013; 15 PR Freeman (921_CR25) 1989; 8 921_CR11 921_CR12 921_CR10 921_CR2 921_CR15 WJ Westlake (921_CR17) 1979 921_CR16 921_CR4 WH Press (921_CR37) 1992 921_CR5 921_CR14 921_CR1 WJ Westlake (921_CR18) 1988 TH Montague (921_CR29) 2011; 11 RL Wasserstein (921_CR38) 2016; 70 S Bolton (921_CR13) 2010 W Sun (921_CR22) 2022 D Potvin (921_CR28) 2008; 7 M Alosh (921_CR36) 2015; 7 DM Kent (921_CR35) 2020; 172 W Maurer (921_CR32) 2018; 37 38710975 - AAPS J. 2024 May 6;26(3):58. doi: 10.1208/s12248-024-00927-5. 39251474 - AAPS J. 2024 Sep 9;26(5):101. doi: 10.1208/s12248-024-00972-0. |
| References_xml | – reference: LeeJFengKXuMGongXSunWKimJZhangZWangMFangLZhaoLApplications of adaptive designs in generic drug developmentClin Pharm Ther20201101323510.1002/cpt.2050 – reference: US Food and Drug Administration, CDER. Guidance for industry. Bioavailability studies submitted in NDAs or INDs — general considerations. Silver Spring, April 2022. https://www.fda.gov/media/121311/download. Accessed 22 October 2023. – reference: US Food and Drug Administration, CDER. Guidance for industry. Statistical approaches to establishing bioequivalence. Revision 1. Silver Spring, December 2022. https://www.fda.gov/media/163638/download. Accessed 22 October 2023. – reference: SunWSchuirmannDGrosserSQualitative versus quantitative treatment-by-subgroup interaction in equivalence studies with multiple subgroupsStat Biopharm Res202210.1080/19466315.2022.2123385 – reference: US Food and Drug Administration, CDER. Guidance for industry. SUPAC-IR: immediate-release solid oral dosage forms: scale-up and post-approval changes: chemistry, manufacturing and controls, in vitro dissolution testing, and in vivo bioequivalence documentation. Rockville, November 1995. https://www.fda.gov/media/70949/download. Accessed 22 October 2023. – reference: Council of the Eurasian Economic Community. On the approval of the rules for conducting research of bioequivalence of drugs within the framework of the Eurasian Economic Union. November 3, 2016; amended September 4, 2020. – reference: D’AngeloGPotvinDTurgeonJCarry-over effects in bioequivalence studiesJ Biopharm Stat2001111&2354310.1081/bip-100104196 – reference: HubbardRBayarriMJConfusion over measures of evidence (p’s) versus errors (α’s) in classical statistical testingAm Stat200357317118210.1198/0003130031856 – reference: Health Canada, Guidance Document. Conduct and analysis of comparative bioavailability studies. Ottawa. Revised Date: 2023/01/30. https://www.canada.ca/content/dam/hc-sc/documents/services/drugs-health-products/drug-products/applications-submissions/guidance-documents/bioavailability-bioequivalence/conduct-analysis-comparative.pdf. Accessed 22 October 2023. – reference: BoltonSBonCPharmaceutical statistics. Practical and clinical applications20105New YorkInforma Healthcare629 – reference: PotvinDDiLibertiCEHauckWWParrAFSchuirmannDJSmithRASequential design approaches for bioequivalence studies with crossover designsPharm Stat2008724526210.1002/pst.29417710740 – reference: DavitBBraddyACConnerDPYuLXInternational guidelines for bioequivalence of systemically available orally administered generic drug products: a survey of similarities and differencesAAPS J201315497429010.1208/s12248-013-9499-x238213523787230 – reference: ZhengCWangJZhaoLTesting bioequivalence for multiple formulations with power and sample size calculationsPharm Stat20121133434110.1002/pst.152222692852 – reference: US Food and Drug Administration, CDER. Guidance for industry. Bioequivalence studies with pharmacokinetic endpoints for drugs submitted under an ANDA. Silver Spring, August 2021. https://www.fda.gov/media/87219/download. Accessed 22 October 2023. – reference: PressWHFlanneryBPTeukolskySAVetterlingWTNumerical recipes in Fortran 77: the art of scientific computing19922CambridgeCambridge University Press603 – reference: FuglsangASequential bioequivalence approaches for parallel designsAAPS J20141637337810.1208/s12248-014-9571-1245266104012040 – reference: ICH. Bioequivalence for immediate release solid oral dosage forms. M13A. Draft version. 20 December 2022. https://database.ich.org/sites/default/files/ICH_M13A_Step2_draft_Guideline_2022_1125.pdf. Accessed 22 October 2023. – reference: EMA, CHMP. Guideline on the investigation of bioequivalence. London; 2010. https://www.ema.europa.eu/documents/scientific-guideline/guideline-investigation-bioequivalence-rev1_en.pdf. Accessed 22 October 2023. – reference: AloshMFritschKHuqueMMahjoobKPennelloGRothmannMRussek-CohenESmithFWilsonSYueLStatistical considerations on subgroup analysis in clinical trialsStat Biopharm Res20157428630410.1080/19466315.2015.1077726 – reference: Medicines for Europe. Second bioequivalence workshop. Session 2 – ICH M13 – bioequivalence for IR solid oral dosage forms. Brussels; 2023. – reference: SennSD’AngeloGPotvinDCarry-over in cross-over trials in bioequivalence: theoretical concerns and empirical evidencePharm Stat2004313314210.1002/pst.111 – reference: WestlakeWJPeaceKEBioavailability and bioequivalence of pharmaceutical formulationsBiopharmaceutical statistics for drug development1988New YorkMarcel Dekker336337 – reference: European Medicines Agency, CHMP. Guideline on the investigation of drug interactions. Revision 1. London, 21 June 2012. https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-investigation-drug-interactions-revision-1_en.pdf. Accessed 22 October 2023. – reference: US Food and Drug Administration, CDER. ANDA 077570. Bioequivalence reviews. 2008. Control document #98–392 regarding the Group-by-Treatment interaction discussion. Rockville, September 10, 1999. https://www.accessdata.fda.gov/drugsatfda_docs/anda/2008/077570Orig1s000BioeqR.pdf. Accessed 22 October 2023. – reference: US Food and Drug Administration, CDER. Guidance for industry. Food-effect bioavailability and fed bioequivalence studies. Rockville, December 2002. https://www.fda.gov/files/drugs/published/Food-Effect-Bioavailability-and-Fed-Bioequivalence-Studies.pdf. Accessed 22 October 2023. – reference: ZimmermanDWA note on preliminary tests of equality of variancesBr J Math Stat Psychol200457117318110.1348/00071100484922215171807 – reference: MatsumotoMNishimuraTMersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generatorACM Trans Model Comput Simul1998833010.1145/272991.272995 – reference: MontagueTHPotvinDDiLibertiCEHauckWWParrAFSchuirmannDJAdditional results for ‘Sequential design approaches for bioequivalence studies with crossover designs’Pharm Stat.20111181310.1002/pst.48321308974 – reference: MolinsELabesDSchützHCoboEOcañaJAn iterative method to protect the type I error rate in bioequivalence studies under two-stage adaptive 2×2 crossover designsBiom J202163112213310.1002/bimj.20190038833000873 – reference: FreemanPRThe performance of the two-stage analysis of two-treatment, two-period crossover trialsStatist Med1989812142114321:STN:280:DyaK3c7jvF2rsg%3D%3D10.1002/sim.4780081202 – reference: MaurerWJonesBChenYControlling the type 1 error rate in two-stage sequential designs when testing for average bioequivalenceStatist Med2018371012110.1002/sim.7614 – reference: WestlakeWJBlanchardJSawchukRJBrodieBBDesign and evaluation of bioequivalence studies in manPrinciples and perspectives in drug bioavailability1979BaselKarger192210 – reference: EndrényiLTabackNTóthfalusiProperties of the estimated variance component for subject-by-formulation interaction in studies of individual bioequivalenceStatist Med.2000192867287810.1002/1097-0258(20001030)19:20<2867::AID-SIM551>3.0.CO;2-J – reference: US Food and Drug Administration, CDER. Guidance for industry. Clinical drug interaction studies — cytochrome P450 enzyme- and transporter-mediated drug interactions. Silver Spring, January 2020. https://www.fda.gov/media/134581/download. Accessed 22 October 2023. – reference: WassersteinRLLazarNAThe ASA’s statement on p-values: context, process, and purposeAm Stat201670212913310.1080/00031305.2016.1154108 – reference: Sun W. Bioequivalence studies in multiple groups. Presentation at: SBIA. A deep dive: FDA draft guidance on statistical approaches to establishing bioequivalence. Silver Spring, March 14, 2023. https://www.fda.gov/media/167459/download. Accessed 22 October 2023. – reference: Cortés J, Casals M, Langohr K, González JA. Importance of statistical power and hypothesis in P value. Med Clin (Barc). 2016. https://doi.org/10.1016/j.medcli.2015.10.011. – reference: R Core Team. R: a language and environment for statistical computing. Vienna, Austria, 2023. https://www.r-project.org/. Accessed 22 Oct 2023. – reference: FuglsangASequential bioequivalence trial designs with increased power and controlled type I error ratesAAPS J20131565966110.1208/s12248-013-9475-5235436033691437 – reference: KentDMPaulusJKvan KlaverenDD’AgostinoRGoodmanSHaywardRIoannidisJPAPatrick-LakeBMortonSPencinaMRamanGRossJSSelkerHSVaradhanRVickersAWongJBSteyerbergEWThe predictive approaches to treatment effect heterogeneity (PATH) statementAnn Intern Med20201721354510.7326/M18-366731711134 – ident: 921_CR4 – ident: 921_CR40 doi: 10.1016/j.medcli.2015.10.011 – ident: 921_CR15 – ident: 921_CR21 – volume: 172 start-page: 35 issue: 1 year: 2020 ident: 921_CR35 publication-title: Ann Intern Med doi: 10.7326/M18-3667 – ident: 921_CR8 – ident: 921_CR6 – ident: 921_CR2 – volume: 15 start-page: 974 issue: 4 year: 2013 ident: 921_CR3 publication-title: AAPS J doi: 10.1208/s12248-013-9499-x – volume: 70 start-page: 129 issue: 2 year: 2016 ident: 921_CR38 publication-title: Am Stat doi: 10.1080/00031305.2016.1154108 – ident: 921_CR11 – volume: 37 start-page: 1 issue: 10 year: 2018 ident: 921_CR32 publication-title: Statist Med doi: 10.1002/sim.7614 – start-page: 336 volume-title: Biopharmaceutical statistics for drug development year: 1988 ident: 921_CR18 – start-page: 603 volume-title: Numerical recipes in Fortran 77: the art of scientific computing year: 1992 ident: 921_CR37 – volume: 3 start-page: 133 year: 2004 ident: 921_CR26 publication-title: Pharm Stat doi: 10.1002/pst.111 – ident: 921_CR5 – year: 2022 ident: 921_CR22 publication-title: Stat Biopharm Res doi: 10.1080/19466315.2022.2123385 – volume: 8 start-page: 3 year: 1998 ident: 921_CR20 publication-title: ACM Trans Model Comput Simul doi: 10.1145/272991.272995 – ident: 921_CR16 – ident: 921_CR14 – volume: 15 start-page: 659 year: 2013 ident: 921_CR30 publication-title: AAPS J doi: 10.1208/s12248-013-9475-5 – start-page: 192 volume-title: Principles and perspectives in drug bioavailability year: 1979 ident: 921_CR17 – volume: 16 start-page: 373 year: 2014 ident: 921_CR31 publication-title: AAPS J doi: 10.1208/s12248-014-9571-1 – volume: 8 start-page: 1421 issue: 12 year: 1989 ident: 921_CR25 publication-title: Statist Med doi: 10.1002/sim.4780081202 – volume: 19 start-page: 2867 year: 2000 ident: 921_CR27 publication-title: Statist Med. doi: 10.1002/1097-0258(20001030)19:20<2867::AID-SIM551>3.0.CO;2-J – volume: 11 start-page: 334 year: 2012 ident: 921_CR19 publication-title: Pharm Stat doi: 10.1002/pst.1522 – ident: 921_CR9 – volume: 7 start-page: 245 year: 2008 ident: 921_CR28 publication-title: Pharm Stat doi: 10.1002/pst.294 – ident: 921_CR7 – volume: 63 start-page: 122 issue: 1 year: 2021 ident: 921_CR34 publication-title: Biom J doi: 10.1002/bimj.201900388 – ident: 921_CR1 – start-page: 629 volume-title: Pharmaceutical statistics. Practical and clinical applications year: 2010 ident: 921_CR13 – volume: 57 start-page: 171 issue: 3 year: 2003 ident: 921_CR39 publication-title: Am Stat doi: 10.1198/0003130031856 – volume: 57 start-page: 173 issue: 1 year: 2004 ident: 921_CR24 publication-title: Br J Math Stat Psychol doi: 10.1348/000711004849222 – volume: 7 start-page: 286 issue: 4 year: 2015 ident: 921_CR36 publication-title: Stat Biopharm Res doi: 10.1080/19466315.2015.1077726 – ident: 921_CR10 – ident: 921_CR12 – volume: 110 start-page: 32 issue: 1 year: 2020 ident: 921_CR33 publication-title: Clin Pharm Ther doi: 10.1002/cpt.2050 – volume: 11 start-page: 35 issue: 1&2 year: 2001 ident: 921_CR23 publication-title: J Biopharm Stat doi: 10.1081/bip-100104196 – volume: 11 start-page: 8 year: 2011 ident: 921_CR29 publication-title: Pharm Stat. doi: 10.1002/pst.483 – reference: 38710975 - AAPS J. 2024 May 6;26(3):58. doi: 10.1208/s12248-024-00927-5. – reference: 39251474 - AAPS J. 2024 Sep 9;26(5):101. doi: 10.1208/s12248-024-00972-0. |
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| Title | Group-by-Treatment Interaction Effects in Comparative Bioavailability Studies |
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