The representativeness of eligible patients in type 2 diabetes trials: A case study using GIST 2.0

Anando Sen, Andrew Goldstein, Shreya Chakrabarti, Ning Shang, Tian Kang, Anil Yaman, Patrick B. Ryan, Chunhua Weng

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)

Abstract

Objective: The population representativeness of a clinical study is influenced by how real-world patients qualify for the study. We analyze the representativeness of eligible patients for multiple type 2 diabetes trials and the relationship between representativeness and other trial characteristics. Methods: Sixty-nine study traits available in the electronic health record data for 2034 patients with type 2 diabetes were used to profile the target patients for type 2 diabetes trials. A set of 1691 type 2 diabetes trials was identified from ClinicalTrials.gov, and their population representativeness was calculated using the published Generalizability Index of Study Traits 2.0 metric. The relationships between population representativeness and number of traits and between trial duration and trial metadata were statistically analyzed. A focused analysis with only phase 2 and 3 interventional trials was also conducted. Results: A total of 869 of 1691 trials (51.4%) and 412 of 776 phase 2 and 3 interventional trials (53.1%) had a population representativeness of <5%. The overall representativeness was significantly correlated with the representativeness of the Hba1c criterion. The greater the number of criteria or the shorter the trial, the less the representativeness. Among the trial metadata, phase, recruitment status, and start year were found to have a statistically significant effect on population representativeness. For phase 2 and 3 interventional trials, only start year was significantly associated with representativeness. Conclusions: Our study quantified the representativeness of multiple type 2 diabetes trials. The common low representativeness of type 2 diabetes trials could be attributed to specific study design requirements of trials or safety concerns. Rather than criticizing the low representativeness, we contribute a method for increasing the transparency of the representativeness of clinical trials.

Original languageEnglish
Pages (from-to)239-247
Number of pages9
JournalJournal of the American Medical Informatics Association
Volume25
Issue number3
Early online date13 Sep 2017
DOIs
Publication statusPublished - 1 Mar 2018

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Type 2 Diabetes Mellitus
Population
Electronic Health Records
Clinical Trials
Safety
Metadata

Keywords

  • Clinical trials
  • Eligibility criteria
  • Metadata analysis
  • Population representativeness

Cite this

Sen, Anando ; Goldstein, Andrew ; Chakrabarti, Shreya ; Shang, Ning ; Kang, Tian ; Yaman, Anil ; Ryan, Patrick B. ; Weng, Chunhua. / The representativeness of eligible patients in type 2 diabetes trials : A case study using GIST 2.0. In: Journal of the American Medical Informatics Association. 2018 ; Vol. 25, No. 3. pp. 239-247.
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abstract = "Objective: The population representativeness of a clinical study is influenced by how real-world patients qualify for the study. We analyze the representativeness of eligible patients for multiple type 2 diabetes trials and the relationship between representativeness and other trial characteristics. Methods: Sixty-nine study traits available in the electronic health record data for 2034 patients with type 2 diabetes were used to profile the target patients for type 2 diabetes trials. A set of 1691 type 2 diabetes trials was identified from ClinicalTrials.gov, and their population representativeness was calculated using the published Generalizability Index of Study Traits 2.0 metric. The relationships between population representativeness and number of traits and between trial duration and trial metadata were statistically analyzed. A focused analysis with only phase 2 and 3 interventional trials was also conducted. Results: A total of 869 of 1691 trials (51.4{\%}) and 412 of 776 phase 2 and 3 interventional trials (53.1{\%}) had a population representativeness of <5{\%}. The overall representativeness was significantly correlated with the representativeness of the Hba1c criterion. The greater the number of criteria or the shorter the trial, the less the representativeness. Among the trial metadata, phase, recruitment status, and start year were found to have a statistically significant effect on population representativeness. For phase 2 and 3 interventional trials, only start year was significantly associated with representativeness. Conclusions: Our study quantified the representativeness of multiple type 2 diabetes trials. The common low representativeness of type 2 diabetes trials could be attributed to specific study design requirements of trials or safety concerns. Rather than criticizing the low representativeness, we contribute a method for increasing the transparency of the representativeness of clinical trials.",
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The representativeness of eligible patients in type 2 diabetes trials : A case study using GIST 2.0. / Sen, Anando; Goldstein, Andrew; Chakrabarti, Shreya; Shang, Ning; Kang, Tian; Yaman, Anil; Ryan, Patrick B.; Weng, Chunhua.

In: Journal of the American Medical Informatics Association, Vol. 25, No. 3, 01.03.2018, p. 239-247.

Research output: Contribution to journalArticleAcademicpeer-review

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AU - Goldstein, Andrew

AU - Chakrabarti, Shreya

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AU - Kang, Tian

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N2 - Objective: The population representativeness of a clinical study is influenced by how real-world patients qualify for the study. We analyze the representativeness of eligible patients for multiple type 2 diabetes trials and the relationship between representativeness and other trial characteristics. Methods: Sixty-nine study traits available in the electronic health record data for 2034 patients with type 2 diabetes were used to profile the target patients for type 2 diabetes trials. A set of 1691 type 2 diabetes trials was identified from ClinicalTrials.gov, and their population representativeness was calculated using the published Generalizability Index of Study Traits 2.0 metric. The relationships between population representativeness and number of traits and between trial duration and trial metadata were statistically analyzed. A focused analysis with only phase 2 and 3 interventional trials was also conducted. Results: A total of 869 of 1691 trials (51.4%) and 412 of 776 phase 2 and 3 interventional trials (53.1%) had a population representativeness of <5%. The overall representativeness was significantly correlated with the representativeness of the Hba1c criterion. The greater the number of criteria or the shorter the trial, the less the representativeness. Among the trial metadata, phase, recruitment status, and start year were found to have a statistically significant effect on population representativeness. For phase 2 and 3 interventional trials, only start year was significantly associated with representativeness. Conclusions: Our study quantified the representativeness of multiple type 2 diabetes trials. The common low representativeness of type 2 diabetes trials could be attributed to specific study design requirements of trials or safety concerns. Rather than criticizing the low representativeness, we contribute a method for increasing the transparency of the representativeness of clinical trials.

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