Challenges in classifying adverse events in cancer clinical trials
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Challenges in Classifying Adverse Events in Cancer Clinical Trials. Steven Joffe, MD, MPH Dave Harrington, PhD David Studdert, JD, PhD Saul Weingart, MD, PhD Damiana Maloof, RN . Disclosure. Member of clinical trial adverse event review board for Genzyme Corp (not oncology-related).

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Challenges in Classifying Adverse Events in Cancer Clinical Trials

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Challenges in classifying adverse events in cancer clinical trials

Challenges in Classifying Adverse Events in Cancer Clinical Trials

Steven Joffe, MD, MPH

Dave Harrington, PhD

David Studdert, JD, PhD

Saul Weingart, MD, PhD

Damiana Maloof, RN


Disclosure

Disclosure

  • Member of clinical trial adverse event review board for Genzyme Corp (not oncology-related)


Adverse events in clinical trials

Adverse Events in Clinical Trials

  • Adverse events (AEs) are critically important outcomes of clinical trials

    • Human subjects protection

    • Endpoints for judgments about benefits & risks of study interventions

  • Captured on Case Report Forms

  • Reported to oversight agencies


Components of ae assessment

Components of AE Assessment

  • Type

  • Severity

  • Relatedness to study agent(s)

  • Expectedness


Components of ae assessment1

Global judgment about reportability to IRB

Components of AE Assessment

  • Type

  • Severity

  • Relatedness to study agent(s)

  • Expectedness


Reporting criteria to dana farber irb

Reporting Criteria(to Dana-Farber IRB)

  • Grade 5 (fatal)

  • Grade 4, unless specifically exempted

  • Grade 2/3, if unexpected AND possibly, probably or definitely related

  • Virtually identical to NCI’s Adverse Event Expedited Reporting System (AdEERS) criteria


Ae grading in oncology

AE Grading in Oncology

  • NCI’s Common Terminology Criteria for Adverse Events (CTCAE) typically used

    • Effort to standardize nomenclature

    • developed by consensus methods; no formal process to establish reliability of grading

http://ctep.cancer.gov/protocolDevelopment/electronic_applications/ctc.htm#ctc_v30


Challenges in classifying adverse events in cancer clinical trials

Aims

  • To assess the validity of physician reviewers’ determinations about whether AEs in cancer trials meet IRB reporting criteria

  • To assess the interrater reliability of reviewers’ determinations about whether AEs that occur in cancer trials meet IRB reporting criteria

  • To assess the validity and reliability of revie-wers’ judgments about the components of AEs


Study methods

Study Methods


Panelists roles

Panelists’ Roles

  • Review primary data from criterion sets of AEs

  • Rate each AE:

    • Classification

    • Grade

    • Relatedness

    • Expectedness

    • Reportable to IRB

}

from CTCAE


Panelist demographics

Panelist Demographics


Panelists experience

Panelists’ Experience


Panelists experience1

Panelists’ Experience


Statistical analysis

Statistical Analysis

  • Validity of judgments regarding reportability to IRB

    • % agreement with gold standard

  • Interrater reliability of raters’ judgments

    • Kappa coefficients


Results

Results


Criterion set of aes

Criterion Set of AEs


Validity of judgments regarding reportability to irb

Validity of Judgments Regarding Reportability to IRB


Interrater reliability of panelists judgments

Interrater Reliability of Panelists’ Judgments


Role of experience rank

Role of Experience: Rank

Kappa


Role of experience service as pi

Role of Experience: Service as PI

Kappa


Role of experience number of ae reports filed

Role of Experience: Number of AE Reports Filed

Kappa


Conclusions

Conclusions

  • Oncologists’ judgments about whether or not AEs require reporting to the IRB show high agreement with gold standard

  • Interrater reliability of oncologists’ judgments about components of AEs varies

    • High: expectedness of AE; need for reporting

    • Moderate: grade of AE

    • Low: relationship of AE to study agents


Limitations

Limitations

  • Small sample sizes

    • Criterion set of AEs

    • Panel of physician reviewers

  • Generalizability of set of AEs

  • Reviewers may not reflect population of investigators who file AE reports

  • Judgments based on document review rather than on firsthand knowledge


Thoughts about direction of bias in agreement statistics

Thoughts About Direction of Bias in Agreement Statistics

  • Factors biasing towards less agreement

    • Reviewer experience

  • Factors biasing towards greater agreement

    • Standardized set of documents for review

    • Criterion set selected based on maximum agreement among expert panel reviewers


Implications

Implications

  • Judgments about AEs are complex

    • Human subjects: efforts to enhance reliability, or to minimize reliance on judgments about causation, are needed

    • Science: toxicity data from uncontrolled trials may be misleading

    • RCR: education about need for reporting is important but insufficient


Acknowledgments

Debra Morley

Anna Mattson-DiCecca

Physician panelists

ORI

NCI

Milton Fund

Acknowledgments


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