A retrospective analysis of clinical research misconduct using FDA-Issued Warning Letters and Clinical Investigator Inspection List from 2010 to 2014

Christopher A. Romano, Singh R. Nair, Ellise S. Delphin

Research output: Contribution to journalReview article

Abstract

BACKGROUND: The US Food and Drug Administration (FDA) conducts inspections of clinical investigation sites as a component of clinical trial regulation. The FDA describes the results of these inspections in the Clinical Investigator Inspection List (CLIIL). More serious violations are followed up in FDA warning letters issued to investigators. The primary objective of the current study is to qualitatively and quantitatively describe the CLIIL data and contents of FDA-issued warning letters from 2010 to 2014. METHODS: We retrospectively analyzed the CLIIL and FDA warning letters. For the CLIIL, we quantified the frequency of each violation among other data points. We compared recent data (2010-2014) to the previous 5 years (2005-2009). To analyze FDA warning letters, we developed a coding system to quantify the frequency of violations found. RESULTS: We analyzed 3637 inspections in the CLIIL database and 60 warning letters. Overall, there was a decrease or no change in all violations in the CLIIL database. The largest violation code reported was "failure to follow investigational plan" in both the 2005-2009 and 2010-2014 timeframes. Coding of FDA warning letters shows that the most common violations reported were failing to maintain accurate case histories (10.82%), enrolling ineligible subjects (8.85%), and failing to perform required tests (8.52%). CONCLUSIONS: The overall decrease in violations is encouraging. But, the high proportion of violations related to failure to follow the investigational plan is concerning as the complexity of trials increases. We conclude that more detailed information is necessary to accurately evaluate these violations. The current study provides a model for creating more granular data of violations to better inform clinical investigators and improve clinical trials. (Anesth Analg 2018;126:976-82).

Original languageEnglish (US)
Pages (from-to)976-982
Number of pages7
JournalAnesthesia and Analgesia
Volume126
Issue number3
DOIs
StatePublished - Jan 1 2018

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Scientific Misconduct
United States Food and Drug Administration
Research Personnel
Clinical Trials
Databases

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine

Cite this

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title = "A retrospective analysis of clinical research misconduct using FDA-Issued Warning Letters and Clinical Investigator Inspection List from 2010 to 2014",
abstract = "BACKGROUND: The US Food and Drug Administration (FDA) conducts inspections of clinical investigation sites as a component of clinical trial regulation. The FDA describes the results of these inspections in the Clinical Investigator Inspection List (CLIIL). More serious violations are followed up in FDA warning letters issued to investigators. The primary objective of the current study is to qualitatively and quantitatively describe the CLIIL data and contents of FDA-issued warning letters from 2010 to 2014. METHODS: We retrospectively analyzed the CLIIL and FDA warning letters. For the CLIIL, we quantified the frequency of each violation among other data points. We compared recent data (2010-2014) to the previous 5 years (2005-2009). To analyze FDA warning letters, we developed a coding system to quantify the frequency of violations found. RESULTS: We analyzed 3637 inspections in the CLIIL database and 60 warning letters. Overall, there was a decrease or no change in all violations in the CLIIL database. The largest violation code reported was {"}failure to follow investigational plan{"} in both the 2005-2009 and 2010-2014 timeframes. Coding of FDA warning letters shows that the most common violations reported were failing to maintain accurate case histories (10.82{\%}), enrolling ineligible subjects (8.85{\%}), and failing to perform required tests (8.52{\%}). CONCLUSIONS: The overall decrease in violations is encouraging. But, the high proportion of violations related to failure to follow the investigational plan is concerning as the complexity of trials increases. We conclude that more detailed information is necessary to accurately evaluate these violations. The current study provides a model for creating more granular data of violations to better inform clinical investigators and improve clinical trials. (Anesth Analg 2018;126:976-82).",
author = "Romano, {Christopher A.} and Nair, {Singh R.} and Delphin, {Ellise S.}",
year = "2018",
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T1 - A retrospective analysis of clinical research misconduct using FDA-Issued Warning Letters and Clinical Investigator Inspection List from 2010 to 2014

AU - Romano, Christopher A.

AU - Nair, Singh R.

AU - Delphin, Ellise S.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - BACKGROUND: The US Food and Drug Administration (FDA) conducts inspections of clinical investigation sites as a component of clinical trial regulation. The FDA describes the results of these inspections in the Clinical Investigator Inspection List (CLIIL). More serious violations are followed up in FDA warning letters issued to investigators. The primary objective of the current study is to qualitatively and quantitatively describe the CLIIL data and contents of FDA-issued warning letters from 2010 to 2014. METHODS: We retrospectively analyzed the CLIIL and FDA warning letters. For the CLIIL, we quantified the frequency of each violation among other data points. We compared recent data (2010-2014) to the previous 5 years (2005-2009). To analyze FDA warning letters, we developed a coding system to quantify the frequency of violations found. RESULTS: We analyzed 3637 inspections in the CLIIL database and 60 warning letters. Overall, there was a decrease or no change in all violations in the CLIIL database. The largest violation code reported was "failure to follow investigational plan" in both the 2005-2009 and 2010-2014 timeframes. Coding of FDA warning letters shows that the most common violations reported were failing to maintain accurate case histories (10.82%), enrolling ineligible subjects (8.85%), and failing to perform required tests (8.52%). CONCLUSIONS: The overall decrease in violations is encouraging. But, the high proportion of violations related to failure to follow the investigational plan is concerning as the complexity of trials increases. We conclude that more detailed information is necessary to accurately evaluate these violations. The current study provides a model for creating more granular data of violations to better inform clinical investigators and improve clinical trials. (Anesth Analg 2018;126:976-82).

AB - BACKGROUND: The US Food and Drug Administration (FDA) conducts inspections of clinical investigation sites as a component of clinical trial regulation. The FDA describes the results of these inspections in the Clinical Investigator Inspection List (CLIIL). More serious violations are followed up in FDA warning letters issued to investigators. The primary objective of the current study is to qualitatively and quantitatively describe the CLIIL data and contents of FDA-issued warning letters from 2010 to 2014. METHODS: We retrospectively analyzed the CLIIL and FDA warning letters. For the CLIIL, we quantified the frequency of each violation among other data points. We compared recent data (2010-2014) to the previous 5 years (2005-2009). To analyze FDA warning letters, we developed a coding system to quantify the frequency of violations found. RESULTS: We analyzed 3637 inspections in the CLIIL database and 60 warning letters. Overall, there was a decrease or no change in all violations in the CLIIL database. The largest violation code reported was "failure to follow investigational plan" in both the 2005-2009 and 2010-2014 timeframes. Coding of FDA warning letters shows that the most common violations reported were failing to maintain accurate case histories (10.82%), enrolling ineligible subjects (8.85%), and failing to perform required tests (8.52%). CONCLUSIONS: The overall decrease in violations is encouraging. But, the high proportion of violations related to failure to follow the investigational plan is concerning as the complexity of trials increases. We conclude that more detailed information is necessary to accurately evaluate these violations. The current study provides a model for creating more granular data of violations to better inform clinical investigators and improve clinical trials. (Anesth Analg 2018;126:976-82).

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