When it’s Critical to Use eCOA in Clinical Trials

David Elario and Kelly Dumais, PhD | |

Paper versions of clinical outcome assessments (COAs) are fraught with transcription errors and missing or inaccurate data1-6, low patient compliance5,7, back-filling by patients7, and administrative burden8. Not only does using electronic clinical outcome assessments (eCOA) minimize or eliminate these problems, but it is preferred by patients2,6,9-11, reduces site burden with automated calculations, and is recommended by regulatory agencies12-15

Here we provide examples of when it’s critical to capture your endpoint data electronically rather than on paper.

Phase 3, Primary Endpoint Trials

To align with FDA and EMA guidances12,15, ISPOR ePRO Good Research Practices Task Force16, and based on our own experiences consulting with clients on submitting claims to the FDA, assessments that support primary endpoints in Phase 3 clinical trials should always be captured electronically.

Daily Diaries in Phase 3

When patients are completing daily diaries at home, the use of electronic diaries significantly increases compliance, compared to paper diaries (Figure 1). Daily alarms programmed on-device remind patients to complete their diaries at the appropriate times. ‘Electronic diaries ensure that data can only be entered within pre-determined/pre-set time windows and not, for example backfilled just prior to a clinic visit, thus aligning with the FDA PRO Guidance12. Sites can also be automatically alerted when patient compliance is below a set threshold, allowing sites to easily intervene when necessary.

Patient protocol compliances increases to 94% with eCOA

Figure 1: Patient compliance significantly improves with eCOA7

Suicidal Ideation and Behavior Monitoring

When monitoring suicidal ideation and behavior (SIB), it is imperative to detect responses that indicate self-harming thoughts or behaviors in real-time. This can only be achieved using electronic tools such as the self-reported electronic Columbia Suicide Severity Rating Scale (eC-SSRS) or the interviewer-rated C-SSRS. The eC-SSRS provides increased patient honesty, reduced effect from rater variability and allows for real-time suicide risk notification. The interviewer-rated C-SSRS includes custom programming to reduce rater burden when navigating through the assessment and provides an on-device report to guide site staff with how to follow up on positives.

Device Integrations

When studies include self-monitoring of physiological data, such as blood glucose with glucometers or expiratory flow with PEF meters, patients can inaccurately record, or forget to record meter values in their diary 3,4. With electronic capture, reminders can be set for the patient to take his/her reading, and data from the medical or consumer device can be automatically transferred onto the eCOA device it’s integrated with. This simplifies the whole process for the patient and removes transcription errors.

Complex ClinROs

Clinician reported outcome (ClinRO) assessments are frequently more complex, involving branching and/or calculations, sub-scores and overall scores. For example, assessments such as the EDSS, PASI, EASI, CDR, and VABS are either lengthy and/or involve complex calculations, whereas assessments such as the Mayo Score or Crohn’s Disease Activity Index (CDAI) require input from multiple sources, including ClinRO measures, patient-reported outcome (PRO) measures, and laboratory results culminating in critical calculations. On paper, such processes are highly prone to error and are costly to remedy. With the use of automatic calculations, however, data collection can be more efficient and data quality can be significantly improved via electronic capture of ClinROs (ie, eClinROs).

Pediatric / Observer Reported Outcomes Trials

Electronic data collection can be particularly beneficial with pediatric and adolescent populations18. Children prefer electronic versus paper assessments19, and the use of technology can help children and adolescents stay focused and engaged, improving data quality and reducing missing data. Electronic data collection can also increase compliance and engagement when caregivers are required to complete assessments, such as for Observer Reported Outcomes (ObsRO), and can confirm attribution by capturing who is completing the assessment (patient or caregiver) with the use of user-specific log-ins and passwords.

Rare Disease Studies

Electronic data capture is essential in studies of rare diseases17, where recruitment is a challenge and patient numbers are small. Missing data from just a few patients can substantially decrease the signal-to-noise ratio. Electronic data capture increases patient compliance by using alarms, and minimizes incomplete or missing data with branching and on-device edit checks. In this way, statistical power is improved, increasing the ability to detect therapeutic effects with fewer subjects.

The studies, endpoints, and patient populations outlined here are only a sample of scenarios where it’s critical for researchers to use eCOA instead of paper assessments. We’ll review other situations where the use of eCOA is recommended in the next installment to this series – check back soon!

David Elario is the Executive Vice President of eCOA at ERT and Kelly Dumais, PhD is a Senior Scientific Advisor at ERT.

 

References

  1. Gary S, et al. 2014. Improved Data Accuracy with Electronic Capture of Blood Glucose Reading in a Type 1 Diabetes Population. Abstract. American Diabetes Association 74th Scientific Sessions; 13-17 June 2014. San Francisco, CA. USA
  2. Araujo L, et al. 2012. Clinical efficacy of web-based versus standard asthma self-management. J Investig Allergol Clin Immunol; 22:28.
  3. Mazze, R et al. 1984. Reliability of blood glucose monitoring by patients with diabetes mellitus. Am J Med; 77.2: 211-217.
  4. Given J, et al. 2013. Comparing patient-generated blood glucose diary records with meter memory in diabetes: a systematic review. Diabet Med; 30, 901–913.
  5. Palermo et al. 2004. A randomized trial of electronic versus paper pain diaries in children: impact on compliance, accuracy, and acceptability. Pain; 107(3):213-9.
  6. Ryan et al. 2002. A comparison of an electronic version of the SF-36 General Health Questionnaire to the standard paper version. Qual Life Res;11(1):19-26.
  7. Stone A, et al. 2002. Patient non-compliance with paper diaries. BMJ 2002; 324:1193
  8. Dale et al. 2007. Despite technical problems personal digital assistants outperform pen and paper when collecting patient diary data. J Clin Epidemiol; 60:8–17.
  9. Ring A, et al. 2008. A Randomized Study of Electronic Diary versus Paper and Pencil Collection of Patient-Reported Outcomes in Patients with Non-Small Cell Lung Cancer. Patient; 1:105-113.
  10. Tsang LC, et al. 2001. Patient preferences for using technology to track and self-manage diabetes. Journal of Telemedecine and Telecare; 7:47-50
  11. Allena M, et al. 2012. An electronic diary on a palm device for headache monitoring: a preliminary experience J Headache Pain; 13:537-541.
  12. Food and Drug Administration, FDA. 2009. Guidance for Industry: Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims.
  13. Food and Drug Administration, FDA. 2010. Guidance for Industry: Electronic Source Documentation in Clinical Investigations.
  14. EMEA, 2005. Committee for Medicinal Products for Human Use. Reflection paper on the regulatory guidance for the use of health-related quality of life (HRQL) measures in the evaluation of medicinal products.
  15. EMA 2014, Reflection Paper on the use of patient reported outcome 5 (PRO) measures in oncology studies
  16. Coons et al. 2009. Recommendations on Evidence Needed to Support Measurement Equivalence between Electronic and Paper-Based Patient-Reported Outcome (PRO) Measures: ISPOR ePRO Good Research Practices Task Force Report. Value in Health; 12;4: 419-429
  17. Dallabrida, 2017. Optimizing rare disease outcomes though eCOA. Applied Clinical Trials.
  18. Matza et al. 2013. Pediatric Patient-Reported Outcome Instruments for Research to Support Medical Product Labeling: Report of the ISPOR PRO Good Research Practices for the Assessment of Children and Adolescents Task Force. Value in Health; 16:461-479.
  19. Mangunkusumo et al. 2006. Internet versus paper mode of health and health behavior questionnaires in elementary schools: asthma and fruit as examples. J Sch Health; 76:80–6.
  20. Yamamoto et al. 2017. Honesty in Reporting Suicidal Ideations and Behaviors in Alzheimer’s Disease, Mild Cognitive Impairment, and Dementias. Abstract. DIA; 18-22 June 2017. Chicago, IL. USA.
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