Pepe Margaret Sullivan, Feng Ziding, Longton Gary, Koopmeiners Joseph
Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N., M2-B500, Seattle, WA 98109, U.S.A.
Stat Med. 2009 Feb 28;28(5):762-79. doi: 10.1002/sim.3506.
Development of a disease screening biomarker involves several phases. In phase 2 its sensitivity and specificity is compared with established thresholds for minimally acceptable performance. Since we anticipate that most candidate markers will not prove to be useful and availability of specimens and funding is limited, early termination of a study is appropriate, if accumulating data indicate that the marker is inadequate. Yet, for markers that complete phase 2, we seek estimates of sensitivity and specificity to proceed with the design of subsequent phase 3 studies. We suggest early stopping criteria and estimation procedures that adjust for bias caused by the early termination option. An important aspect of our approach is to focus on properties of estimates conditional on reaching full study enrollment. We propose the conditional-UMVUE and contrast it with other estimates, including naïve estimators, the well-studied unconditional-UMVUE and the mean and median Whitehead-adjusted estimators. The conditional-UMVUE appears to be a very good choice.
疾病筛查生物标志物的开发涉及多个阶段。在第2阶段,会将其敏感性和特异性与最低可接受性能的既定阈值进行比较。由于我们预计大多数候选标志物将被证明无用,且样本和资金的可用性有限,如果积累的数据表明该标志物不充分,那么提前终止研究是合适的。然而,对于完成第2阶段的标志物,我们需要敏感性和特异性的估计值,以便进行后续第3阶段研究的设计。我们提出了早期停止标准和估计程序,以调整因早期终止选项导致的偏差。我们方法的一个重要方面是关注以达到完整研究入组为条件的估计值的性质。我们提出了条件一致最小方差无偏估计量,并将其与其他估计值进行对比,包括朴素估计量、经过充分研究的无条件一致最小方差无偏估计量以及均值和中位数怀特海德调整估计量。条件一致最小方差无偏估计量似乎是一个非常不错的选择。