ASSESSING THE INFLUENCE OF REVERSIBLE DISEASE INDICATORS ON SURVIVAL
ASSESSING THE INFLUENCE OF REVERSIBLE DISEASE INDICATORS ON SURVIVAL
复制标题
DOI：
10.1002/sim.4780100706
复制
发表时间：
1991-07-01
影响因子：
2
通讯作者：
KEIDING, N
中科院分区：
文献类型：
--
作者：
ANDERSEN, PK;HANSEN, LS;KEIDING, N
在一项泼尼松与安慰剂对肝硬化患者生存率影响的随机临床试验中，在治疗3个月、6个月和12个月后安排随访，此后每年一次。 在每次随访时，记录凝血酶原指数（衡量肝功能的指标），并将其分为低或正常。 治疗和凝血酶原指数之间的相互作用进行了分析，使用三态疾病-死亡模型与恢复。 Kay建议的具有恒定或分段恒定强度的连续时间马尔可夫过程模型允许进行推断，即使疾病指标的状态，这里是凝血酶原指数，仅在每次访视时而不是在访视之间已知。 我们将分析与理论上不正确，但实际上相当常见的近似值进行比较，其中疾病指标的状态假设从一次访视直到下一次访视之前保持不变。 在这种近似下，Aalen和Johansen开发的标准参数方法和非参数方法都可用。
In a randomized clinical trial of the effect of prednisone versus placebo on survival in patients with liver cirrhosis, follow-up visits were scheduled after 3, 6 and 12 months of treatment and thereafter once a year. At each follow-up the prothrombin index, a measure of liver function, was recorded and scored as either low or normal. The interaction between treatment and prothrombin index was analysed using a three-state illness-death model with recovery. The continuous-time Markov process model with constant or piecewise constant intensities suggested by Kay allows inference to proceed even though the status of the disease indicator, here the prothrombin index, is only known at the time of each visit and not between visits. We compare the analysis with the theoretically incorrect, but practically rather common approximation, where the status of the disease indicator is assumed to remain constant from one visit until just before the next. Under this approximation both standard parametric methods and non-parametric approaches developed by Aalen and Johansen are available.