March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Ophthalmic Study Subject Population Trends
Author Affiliations & Notes
  • Beverly A. Mersing
    Clinical Data Management,
    SDC, Tempe, Arizona
  • Dale J. Kennedy
    Clinical Data Management,
    SDC, Tempe, Arizona
  • Richard Abelson
    Executive Management,
    SDC, Tempe, Arizona
  • Mark Talbert
    Clinical Data Management,
    SDC, Tempe, Arizona
  • Kathryn Kennedy
    Biostatistics,
    SDC, Tempe, Arizona
  • Dale Usner
    Biostatistics,
    SDC, Tempe, Arizona
  • Footnotes
    Commercial Relationships  Beverly A. Mersing, SDC (E); Dale J. Kennedy, SDC (E); Richard Abelson, SDC (E); Mark Talbert, SDC (E); Kathryn Kennedy, SDC (E); Dale Usner, SDC (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 2367. doi:
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    • Get Citation

      Beverly A. Mersing, Dale J. Kennedy, Richard Abelson, Mark Talbert, Kathryn Kennedy, Dale Usner; Ophthalmic Study Subject Population Trends. Invest. Ophthalmol. Vis. Sci. 2012;53(14):2367.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : Effective resource planning for an ophthalmic clinical trial depends on knowledge of your potential subject population. Understanding the expected medical and medication history and potential adverse events, whether ophthalmic or general, should assist the team to reasonably estimate enrollment rate, data entry, data cleaning, and monitoring time. Resources need to be estimated at the site for screening procedures, entry of data into source documents and Case Report Forms (whether electronic or paper), and discrepancy or query management. Resource planning is also needed for Clinical Data Management and Clinical Monitoring providers.

Methods: : The counts per subject of medical history, medications, and adverse events recorded were compared in Dry Eye (DE) and Ocular Allergy (OA) studies. A discrepancy rate was computed for each of these data types. Additionally, the reasons for screen failure were assessed and the number of screen failures which were due to history or medications were compared to the number of screen failures due to assessments performed during screening study visits.

Results: : Within Dry Eye and Ocular Allergy therapeutic areas, the counts of medical history and medication terms were relatively consistent. However, when the two therapeutic areas were compared, there were more history and medication terms in Dry Eye studies (DE: 10 history terms and 7 medications. OA: 4 history terms and 3 medications). Consistency was observed in the rate of discrepancies per medical history and concomitant medication terms, regardless of therapeutic area (60% of history terms and 80% of medication terms required a query). At least 20% of screen failures due to inclusion or exclusion criteria could have been assessed prior to an initial screening visit.

Conclusions: : Reviewing history and medications for Inclusion and Exclusion Criteria during review of potential subjects’ medical files when referred by a physician will reduce the rate of screen failures during the initial visits of an ophthalmic study. Once a subject is screened into a study, sites, data management, and monitoring staff can expect to spend twice as much time entering, cleaning, and reviewing the data for Dry Eye studies than will be spent performing those tasks for Ocular Allergy studies.

Keywords: clinical (human) or epidemiologic studies: biostatistics/epidemiology methodology 
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