Literature DB >> 24296321

Central site monitoring: results from a test of accuracy in identifying trials and sites failing Food and Drug Administration inspection.

Anne S Lindblad1, Zorayr Manukyan, Tejashri Purohit-Sheth, Gary Gensler, Paul Okwesili, Ann Meeker-O'Connell, Leslie Ball, John R Marler.   

Abstract

BACKGROUND: Site monitoring and source document verification account for 15%-30% of clinical trial costs. An alternative is to streamline site monitoring to focus on correcting trial-specific risks identified by central data monitoring. This risk-based approach could preserve or even improve the quality of clinical trial data and human subject protection compared to site monitoring focused primarily on source document verification.
PURPOSE: To determine whether a central review by statisticians using data submitted to the Food and Drug Administration (FDA) by clinical trial sponsors can identify problem sites and trials that failed FDA site inspections.
METHODS: An independent Analysis Center (AC) analyzed data from four anonymous new drug applications (NDAs) where FDA had performed site inspections overseen by FDA's Office of Scientific Investigations (OSI). FDA team members in the OSI chose the four NDAs from among all NDAs with data in Study Data Tabulation Model (SDTM) format. Two of the NDAs had data that OSI had deemed unreliable in support of the application after FDA site inspections identified serious data integrity problems. The other two NDAs had clinical data that OSI deemed reliable after site inspections. At the outset, the AC knew only that the experimental design specified two NDAs with significant problems. FDA gave the AC no information about which NDAs had problems, how many sites were inspected, or how many were found to have problems until after the AC analysis was complete. The AC evaluated randomization balance, enrollment patterns, study visit scheduling, variability of reported data, and last digit reference. The AC classified sites as 'High Concern', 'Moderate Concern', 'Mild Concern', or 'No Concern'.
RESULTS: The AC correctly identified the two NDAs with data deemed unreliable by OSI. In addition, central data analysis correctly identified 5 of 6 (83%) sites for which FDA recommended rejection of data and 13 of 15 sites (87%) for which any regulatory deviations were identified during inspection. Of the six sites for which OSI reviewed inspections and found no deviations, the central process flagged four at the lowest level of concern, one at a moderate level, and one was not flagged. LIMITATIONS: Central data monitoring during the conduct of a trial while data checking was in progress was not evaluated.
CONCLUSION: Systematic central monitoring of clinical trial data can identify problems at the same trials and sites identified during FDA site inspections. Central data monitoring in conjunction with an overall monitoring process that adapts to identify risks as a trial progresses has the potential to reduce the frequency of site visits while increasing data integrity and decreasing trial costs compared to processes that are dependent primarily on source documentation.

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Mesh:

Year:  2013        PMID: 24296321     DOI: 10.1177/1740774513508028

Source DB:  PubMed          Journal:  Clin Trials        ISSN: 1740-7745            Impact factor:   2.486


  14 in total

1.  Statistical monitoring of data quality and consistency in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial.

Authors:  Catherine Timmermans; Erik Doffagne; David Venet; Lieven Desmet; Catherine Legrand; Tomasz Burzykowski; Marc Buyse
Journal:  Gastric Cancer       Date:  2015-08-23       Impact factor: 7.370

Review 2.  Statistical challenges for central monitoring in clinical trials: a review.

Authors:  Koji Oba
Journal:  Int J Clin Oncol       Date:  2015-10-23       Impact factor: 3.402

Review 3.  The impact of clinical trial monitoring approaches on data integrity and cost--a review of current literature.

Authors:  Rasmus Olsen; Asger Reinstrup Bihlet; Faidra Kalakou; Jeppe Ragnar Andersen
Journal:  Eur J Clin Pharmacol       Date:  2016-01-04       Impact factor: 2.953

4.  Data fraud in clinical trials.

Authors:  Stephen L George; Marc Buyse
Journal:  Clin Investig (Lond)       Date:  2015

5.  INVESTIGATING THE EFFICACY OF CLINICAL TRIAL MONITORING STRATEGIES: Design and Implementation of the Cluster Randomized START Monitoring Substudy.

Authors:  Katherine Huppler Hullsiek; Jonathan M Kagan; Nicole Engen; Jesper Grarup; Fleur Hudson; Eileen T Denning; Catherine Carey; David Courtney-Rodgers; Elizabeth B Finley; Per O Jansson; Mary T Pearson; Dwight E Peavy; Waldo H Belloso
Journal:  Ther Innov Regul Sci       Date:  2015-03-01       Impact factor: 1.778

6.  Truths, lies, and statistics.

Authors:  Matthew S Thiese; Skyler Walker; Jenna Lindsey
Journal:  J Thorac Dis       Date:  2017-10       Impact factor: 2.895

7.  A randomized evaluation of on-site monitoring nested in a multinational randomized trial.

Authors:  Nicole Wyman Engen; Kathy Huppler Hullsiek; Waldo H Belloso; Elizabeth Finley; Fleur Hudson; Eileen Denning; Catherine Carey; Mary Pearson; Jonathan Kagan
Journal:  Clin Trials       Date:  2019-10-24       Impact factor: 2.486

8.  Closeout of the HALT-PKD trials.

Authors:  Charity G Moore; Susan Spillane; Gertrude Simon; Barbara Maxwell; Frederic F Rahbari-Oskoui; William E Braun; Arlene B Chapman; Robert W Schrier; Vicente E Torres; Ronald D Perrone; Theodore I Steinman; Godela Brosnahan; Peter G Czarnecki; Peter C Harris; Dana C Miskulin; Michael F Flessner; K Ty Bae; Kaleab Z Abebe; Marie C Hogan
Journal:  Contemp Clin Trials       Date:  2015-07-29       Impact factor: 2.226

9.  Risk-adapted monitoring is not inferior to extensive on-site monitoring: Results of the ADAMON cluster-randomised study.

Authors:  Oana Brosteanu; Gabriele Schwarz; Peggy Houben; Ursula Paulus; Anke Strenge-Hesse; Ulrike Zettelmeyer; Anja Schneider; Dirk Hasenclever
Journal:  Clin Trials       Date:  2017-08-08       Impact factor: 2.486

10.  Comparative costs and activity from a sample of UK clinical trials units.

Authors:  Daniel Hind; Barnaby C Reeves; Sarah Bathers; Christopher Bray; Andrea Corkhill; Christopher Hayward; Lynda Harper; Vicky Napp; John Norrie; Chris Speed; Liz Tremain; Nicola Keat; Mike Bradburn
Journal:  Trials       Date:  2017-05-02       Impact factor: 2.279

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