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Profit Evaluations When Adaptation by Design Is Applied.

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Summary
This summary is machine-generated.

Conservative sample size estimation (CSSE) balances trial success probability with increased costs. Optimizing phase II sample size and conservativeness maximizes expected profit and utility in clinical trials.

Keywords:
assuranceconservative sample size estimationphase II sample size determinationprofit utilityprofit volatility

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Area of Science:

  • Clinical trial design
  • Biostatistics
  • Pharmaceutical economics

Background:

  • Conservative sample size estimation (CSSE) adjusts phase III sample size based on phase II data.
  • CSSE aims to increase clinical trial success rates but may increase phase III sample size, time, and cost.
  • Balancing the increased revenue from higher success probability against greater costs is a key consideration.

Purpose of the Study:

  • To develop a profit model for clinical trials employing CSSE.
  • To evaluate the impact of phase II sample size and conservativeness on profit.
  • To provide guidance on optimizing phase II sample size and conservativeness based on utility theory.

Main Methods:

  • A profit model was constructed incorporating income per patient, incidence, market factors, and phase III success probability.
  • Profit was modeled as a random variable influenced by phase II sample size and the degree of conservatism.
  • Profit moments and utility were calculated using closed-form formulas and investment performance theory.

Main Results:

  • Profit is a random variable dependent on phase II sample size and conservativeness.
  • Profit moments (expectation and volatility) were derived using closed-form formulas.
  • Utility optimization provided a framework for determining optimal phase II sample size and conservativeness.

Conclusions:

  • CSSE is applicable to a wide range of statistical problems in clinical research.
  • The proposed profit evaluation framework can be broadly applied to studies using CSSE.
  • The study offers a method for deriving optimal phase II sample size and conservativeness based on utility.