Exclusion criteria of breast cancer clinical trial protocols: a descriptive analysis

Clara Wan1, Nicole E Caston1, Stacey A Ingram1

  • 1University of Alabama at Birmingham, WTI 240E, Birmingham, AL, 35294, USA.

Abstract

Insights

Cancer clinical trial eligibility criteria vary widely, impacting patient enrollment. This study highlights significant heterogeneity in lab values and comorbidities, suggesting a need for standardized guidelines.

Area of Science:

  • Oncology
  • Clinical Trial Design
  • Biostatistics

Background:

  • Limited clinical trial enrollment (3-8% of US cancer patients) is a significant challenge.
  • Existing eligibility criteria lack standardized guidelines, contributing to enrollment barriers.

Purpose of the Study:

  • To evaluate the variability of eligibility criteria in therapeutic breast cancer protocols.
  • To identify specific areas of heterogeneity in laboratory values and comorbid conditions.

Main Methods:

  • Descriptive analysis of 102 therapeutic breast cancer protocols (2004-2020) at the University of Alabama at Birmingham.
  • Abstraction of exclusion criteria, including laboratory values (liver function, hematologic) and comorbid conditions (heart failure, cardiovascular disease, CNS metastases, prior cancer).
  • Analysis of timeframes required for comorbidity-free status.

Main Results:

  • Significant variability observed in inclusion/exclusion criteria for laboratory values (e.g., bilirubin, AST, ALT) and hematologic labs (e.g., absolute neutrophil count).
  • Wide ranges in exclusion criteria for comorbid conditions like congestive heart failure (49%), cardiovascular disease exacerbation (80%), CNS metastases (59%), and prior cancer (66%).
  • Inconsistent timeframes for comorbidity-free status across protocols.

Conclusions:

  • Substantial heterogeneity exists in clinical trial eligibility criteria for laboratory values and comorbid conditions.
  • Development of standardized eligibility criteria is recommended, with flexibility for drug-specific requirements.
  • Addressing this variability may improve clinical trial accessibility and patient enrollment.

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