AI 中文总结
本文使用gsDesign R包推导两阶段组序贯与条件功效设计，指出虽部分场景下条件功效设计有小幅优势，但易出现低效情况，结合其可能泄露中期治疗效应的问题，认为组序贯设计通常仍是首选。
AI 中文摘要
在临床试验开始前，通常无法充分理解确定临床试验样本量所需的效应量和干扰参数。通过预先计划的早期终止规则，采用保守规划的组序贯设计可有效调整新疗法临床试验的样本量，以应对疗法无效、疗效极佳或疗效微乎其微的情况。这类设计存在一个潜在问题：中期分析的数据截止后，在数据录入、清理、分析和讨论期间，可能会招募大量患者。有研究提出，在中期分析时基于条件功效重新估计样本量的策略，可在一定程度上减少这种入组超量问题。该策略有时被声称的一个优势是，与保守规划的组序贯设计相比，前期规划的样本量更小。本文演示了如何使用gsDesign R包推导两阶段组序贯设计和条件功效设计，并建议使用预期样本量计算来比较具有可比功效的设计。虽然在某些情况下条件功效设计可能具有小幅优势，但很容易推导出效率极低的条件功效设计。此外，由于条件功效设计可能会揭示中期治疗效应的相关信息，因此组序贯设计往往仍是首选设计。
英文摘要
The effect size and nuisance parameters needed to appropriately size a clinical trial are generally not adequately understood before a trial begins. Through pre-planned early stopping rules, a conservatively planned group sequential design can effectively adapt the sample size for a clinical trial for a new treatment that is ineffective, very effective or minimally effective. One potential issue with such designs is that a substantial number of patients can be enrolled after a data cutoff for an interim analysis while data are being entered, cleaned, analyzed and discussed. A strategy of re-estimating the sample size at an interim analysis based on conditional power has been proposed to reduce somewhat this enrollment overrun issue. A purported advantage sometimes claimed is a smaller up-front planned sample size than a conservatively planned group sequential design. We demonstrate derivation of 2-stage group sequential and conditional power designs using the gsDesign R package and suggest comparing designs with comparable power using expected sample size calculations. While there are cases where conditional power designs may have small advantages, it is quite easy to derive very inefficient conditional power designs. This, along with the fact that a conditional power design may reveal something about the interim treatment effect, will often leave a group sequential design as the design of choice.
Comments16 pages, 8 figures
