Designing a phase‐III time‐to‐event clinical trial using a modified sample size formula and Poisson‐Gamma model for subject accrual that accounts for the lag in site initiation using the PERT distribution
A priori estimation of sample size and subject accrual in multi‐site, time‐to‐event clinical trials is often challenging. Such trials are powered based on the number of events needed to detect a clinically significant difference. Sample size based on number of events relates to the expected duration...
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Published in | Statistics in medicine Vol. 42; no. 30; pp. 5694 - 5707 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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Hoboken, USA
John Wiley & Sons, Inc
30.12.2023
Wiley Subscription Services, Inc |
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Online Access | Get full text |
ISSN | 0277-6715 1097-0258 1097-0258 |
DOI | 10.1002/sim.9935 |
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Abstract | A priori estimation of sample size and subject accrual in multi‐site, time‐to‐event clinical trials is often challenging. Such trials are powered based on the number of events needed to detect a clinically significant difference. Sample size based on number of events relates to the expected duration of observation time for each subject. Temporal patterns in site initiation and subject enrollment ultimately affect when subjects can be accrued into the study. Lag times are common as the site start‐up process optimizes, resulting in delays that may curtail observational follow‐up and therefore undermine power. The proposed method introduces a Program Evaluation and Review Technique (PERT) model into the sample size estimation which accounts for the lag in site start‐up. Additionally, a PERT model is introduced into a Poisson‐Gamma subject accrual model to predict the quantity of study sites needed. The introduction of the PERT model provides greater flexibility in both a priori power assessment and planning the number of sites, as it specifically allows for the inclusion of anticipated delays in site start‐up time. This model results in minimal power loss even when PERT distribution inputs are misspecified compared to the traditional assumption of simultaneous start‐up for all sites. Together these updated formulations for sample size and subject accrual models offer an improved method for designing a multi‐site time‐to‐event clinical trial that accounts for a flexible site start‐up process. |
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AbstractList | A priori estimation of sample size and subject accrual in multi-site, time-to-event clinical trials is often challenging. Such trials are powered based on the number of events needed to detect a clinically significant difference. Sample size based on number of events relates to the expected duration of observation time for each subject. Temporal patterns in site initiation and subject enrollment ultimately affect when subjects can be accrued into the study. Lag times are common as the site start-up process optimizes, resulting in delays that may curtail observational follow-up and therefore undermine power. The proposed method introduces a Program Evaluation and Review Technique (PERT) model into the sample size estimation which accounts for the lag in site start-up. Additionally, a PERT model is introduced into a Poisson-Gamma subject accrual model to predict the quantity of study sites needed. The introduction of the PERT model provides greater flexibility in both a priori power assessment and planning the number of sites, as it specifically allows for the inclusion of anticipated delays in site start-up time. This model results in minimal power loss even when PERT distribution inputs are misspecified compared to the traditional assumption of simultaneous start-up for all sites. Together these updated formulations for sample size and subject accrual models offer an improved method for designing a multi-site time-to-event clinical trial that accounts for a flexible site start-up process.A priori estimation of sample size and subject accrual in multi-site, time-to-event clinical trials is often challenging. Such trials are powered based on the number of events needed to detect a clinically significant difference. Sample size based on number of events relates to the expected duration of observation time for each subject. Temporal patterns in site initiation and subject enrollment ultimately affect when subjects can be accrued into the study. Lag times are common as the site start-up process optimizes, resulting in delays that may curtail observational follow-up and therefore undermine power. The proposed method introduces a Program Evaluation and Review Technique (PERT) model into the sample size estimation which accounts for the lag in site start-up. Additionally, a PERT model is introduced into a Poisson-Gamma subject accrual model to predict the quantity of study sites needed. The introduction of the PERT model provides greater flexibility in both a priori power assessment and planning the number of sites, as it specifically allows for the inclusion of anticipated delays in site start-up time. This model results in minimal power loss even when PERT distribution inputs are misspecified compared to the traditional assumption of simultaneous start-up for all sites. Together these updated formulations for sample size and subject accrual models offer an improved method for designing a multi-site time-to-event clinical trial that accounts for a flexible site start-up process. A priori estimation of sample size and subject accrual in multi-site, time-to-event clinical trials is often challenging. Such trials are powered based on the number of events needed to detect a clinically significant difference. Sample size based on number of events relates to the expected duration of observation time for each subject. Temporal patterns in site initiation and subject enrollment ultimately affect when subjects can be accrued into the study. Lag times are common as the site start-up process optimizes, resulting in delays that may curtail observational follow-up and therefore undermine power. The proposed method introduces a Program Evaluation and Review Technique (PERT) model into the sample size estimation which accounts for the lag in site start-up. Additionally, a PERT model is introduced into a Poisson-Gamma subject accrual model to predict the quantity of study sites needed. The introduction of the PERT model provides greater flexibility in both a priori power assessment and planning the number of sites, as it specifically allows for the inclusion of anticipated delays in site start-up time. This model results in minimal power loss even when PERT distribution inputs are misspecified compared to the traditional assumption of simultaneous start-up for all sites. Together these updated formulations for sample size and subject accrual models offer an improved method for designing a multi-site time-to-event clinical trial that accounts for a flexible site start-up process. A priori estimation of sample size and subject accrual in multi-site, time-to-event clinical trials is often challenging. Such trials are powered based on the number of events needed to detect a clinically significant difference. Sample size based on number of events relates to the expected duration of observation time for each subject. Temporal patterns in site initiation and subject enrollment ultimately affect when subjects can be accrued into the study. Lag times are common as the site start-up process optimizes, resulting in delays that may curtail observational follow-up and therefore undermine power. The proposed method introduces a Program Evaluation and Review Technique (PERT) model into the sample size estimation which accounts for the lag in site start-up. Additionally, a PERT model is introduced into a Poisson-Gamma subject accrual model to predict the quantity of study sites needed. The introduction of the PERT model provides greater flexibility in both a priori power assessment and planning the number of sites, as it specifically allows for the inclusion of anticipated delays in site start-up time. This model results in minimal power loss even when PERT distribution inputs are misspecified compared to the traditional assumption of simultaneous start-up for all sites. Together these updated formulations for sample size and subject accrual models offer an improved method for designing a multi-site time-to-event clinical trial that accounts for a flexible site start-up process. |
Author | Shipes, Virginia B. Meinzer, Caitlyn Wolf, Bethany J. Li, Hong Kamel, Hooman Martin, Renee H. Carpenter, Mathew J. |
AuthorAffiliation | 1 Division of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States 3 Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States 2 The Emmes Company, Rockville, Maryland, United States 5 Department of Neurology, Weill Cornell Medicine, New York, NY, United States 4 Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, United States |
AuthorAffiliation_xml | – name: 2 The Emmes Company, Rockville, Maryland, United States – name: 4 Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, United States – name: 1 Division of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States – name: 3 Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States – name: 5 Department of Neurology, Weill Cornell Medicine, New York, NY, United States |
Author_xml | – sequence: 1 givenname: Virginia B. orcidid: 0000-0003-2104-6094 surname: Shipes fullname: Shipes, Virginia B. organization: The Emmes Company – sequence: 2 givenname: Caitlyn orcidid: 0000-0002-9905-4329 surname: Meinzer fullname: Meinzer, Caitlyn organization: Medical University of South Carolina – sequence: 3 givenname: Bethany J. orcidid: 0000-0002-7124-5158 surname: Wolf fullname: Wolf, Bethany J. organization: Medical University of South Carolina – sequence: 4 givenname: Hong surname: Li fullname: Li, Hong organization: Medical University of South Carolina – sequence: 5 givenname: Mathew J. surname: Carpenter fullname: Carpenter, Mathew J. organization: Medical University of South Carolina – sequence: 6 givenname: Hooman surname: Kamel fullname: Kamel, Hooman organization: Weill Cornell Medicine – sequence: 7 givenname: Renee H. surname: Martin fullname: Martin, Renee H. email: hebertrl@musc.edu organization: Medical University of South Carolina |
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Cites_doi | 10.2307/2531201 10.2307/2531021 10.1287/opre.7.5.646 10.2307/2531910 10.1016/j.jclinepi.2019.07.002 10.1002/(SICI)1097-0258(19980815/30)17:15/16<1753::AID-SIM977>3.0.CO;2-X 10.1177/1740774512447996 10.1002/sim.4780050112 10.1007/978‐3‐7908‐1952‐6_1 10.1002/pst.525 10.1002/sim.3847 10.1177/1747493018799981 10.1002/sim.3128 10.1080/10543406.2014.1000546 10.1002/pst.1506 10.1016/0021-9681(74)90004-6 10.1002/sim.8036 10.1016/j.cct.2015.07.010 10.1080/03610926.2011.581189 |
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References_xml | – volume: 42 start-page: 507 year: 1986 end-page: 519 article-title: Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow‐up, noncompliance, and stratification publication-title: Biometrics – volume: 10 start-page: 517 year: 2011 end-page: 522 article-title: Predictive event modelling in multicenter clinical trials with waiting time to response publication-title: Pharm Stat – volume: 5 start-page: 97 year: 1986 end-page: 98 article-title: Tables of the number of patients required in clinical trials using the logrank test publication-title: Stat Med – volume: 44 start-page: 229 year: 1988 article-title: Sample sizes based on the log‐rank statistic in complex clinical trials publication-title: Biometrics – volume: 38 start-page: 945 year: 2019 end-page: 955 article-title: Statistical modeling and prediction of clinical trial recruitment publication-title: Stat Med – volume: 7 start-page: 646 year: 1959 end-page: 669 article-title: Application of a technique for research and development program evaluation publication-title: Oper Res – volume: 115 start-page: 141 year: 2019 end-page: 149 article-title: A systematic review describes models for recruitment prediction at the design stage of a clinical trial publication-title: J Clin Epidemiol – start-page: 1 year: 2007 end-page: 8 – start-page: 1248 year: 2009 end-page: 1259 article-title: Predictive modelling of recruitment and drug supply in multicenter clinical trials publication-title: Proc Jt Stat Meet – volume: 14 start-page: 207 year: 2018 end-page: 214 article-title: The AtRial cardiopathy and antithrombotic drugs in prevention after cryptogenic stroke randomized trial: rationale and methods publication-title: Int J Stroke – volume: 9 start-page: 681 year: 2012 end-page: 688 article-title: Modeling and prediction of subject accrual and event times in clinical trials: a systematic review publication-title: Clin Trials – volume: 40 start-page: 3684 year: 2011 end-page: 3699 article-title: Statistical modeling of clinical trials (recruitment and randomization) publication-title: Commun Stat Theory Methods – volume: 39 start-page: 499 year: 1983 end-page: 503 article-title: Sample‐size formula for the proportional‐hazards regression model publication-title: Biometrics – volume: 11 start-page: 351 year: 2012 end-page: 356 article-title: Prediction of accrual closure date in multi‐center clinical trials with discrete‐time Poisson process models publication-title: Pharm Stat – volume: 45 start-page: 26 year: 2015 end-page: 33 article-title: Real‐time prediction of clinical trial enrollment and event counts: a review publication-title: Contemp Clin Trials – volume: 29 start-page: 649 year: 2010 end-page: 658 article-title: Stochastic modeling and prediction for accrual in clinical trials publication-title: Stat Med – volume: 25 start-page: 1285 year: 2015 end-page: 1311 article-title: Some issues of sample size calculation for time‐to‐event endpoints using the Freedman and Schoenfeld formulas publication-title: J Biopharm Stat – volume: 27 start-page: 15 year: 1974 end-page: 24 article-title: Planning the size and duration of a clinical trial studying the time to some critical event publication-title: J Chronic Dis – volume: 27 start-page: 2328 year: 2008 end-page: 2340 article-title: Predicting accrual in clinical trials with Bayesian posterior predictive distributions publication-title: Stat Med – year: 2019 – volume: 17 start-page: 1753 year: 1998 end-page: 1765 article-title: Some controversies in planning and analysing multi‐center trials publication-title: Stat Med – ident: e_1_2_9_4_1 doi: 10.2307/2531201 – ident: e_1_2_9_3_1 doi: 10.2307/2531021 – ident: e_1_2_9_19_1 doi: 10.1287/opre.7.5.646 – ident: e_1_2_9_5_1 doi: 10.2307/2531910 – ident: e_1_2_9_9_1 doi: 10.1016/j.jclinepi.2019.07.002 – ident: e_1_2_9_10_1 doi: 10.1002/(SICI)1097-0258(19980815/30)17:15/16<1753::AID-SIM977>3.0.CO;2-X – ident: e_1_2_9_7_1 doi: 10.1177/1740774512447996 – start-page: 1248 year: 2009 ident: e_1_2_9_20_1 article-title: Predictive modelling of recruitment and drug supply in multicenter clinical trials publication-title: Proc Jt Stat Meet – ident: e_1_2_9_2_1 doi: 10.1002/sim.4780050112 – ident: e_1_2_9_14_1 doi: 10.1007/978‐3‐7908‐1952‐6_1 – ident: e_1_2_9_16_1 doi: 10.1002/pst.525 – ident: e_1_2_9_12_1 doi: 10.1002/sim.3847 – ident: e_1_2_9_21_1 doi: 10.1177/1747493018799981 – ident: e_1_2_9_11_1 doi: 10.1002/sim.3128 – ident: e_1_2_9_6_1 doi: 10.1080/10543406.2014.1000546 – ident: e_1_2_9_13_1 doi: 10.1002/pst.1506 – ident: e_1_2_9_18_1 – ident: e_1_2_9_22_1 doi: 10.1016/0021-9681(74)90004-6 – ident: e_1_2_9_17_1 doi: 10.1002/sim.8036 – ident: e_1_2_9_8_1 doi: 10.1016/j.cct.2015.07.010 – ident: e_1_2_9_15_1 doi: 10.1080/03610926.2011.581189 |
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Snippet | A priori estimation of sample size and subject accrual in multi‐site, time‐to‐event clinical trials is often challenging. Such trials are powered based on the... A priori estimation of sample size and subject accrual in multi-site, time-to-event clinical trials is often challenging. Such trials are powered based on the... A priori estimation of sample size and subject accrual in multi-site, time-to-event clinical trials is often challenging. Such trials are powered based on the... |
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SubjectTerms | Clinical trials Humans PERT Program Evaluation Sample Size subject accrual models Time Factors time‐to‐event |
Title | Designing a phase‐III time‐to‐event clinical trial using a modified sample size formula and Poisson‐Gamma model for subject accrual that accounts for the lag in site initiation using the PERT distribution |
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