Multivariate Markov models for the conditional probability of toxicity in phase II trials.
Multivariate Markov models for the conditional probability of toxicity in phase II trials.
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II 期试验中毒性条件概率的多变量马尔可夫模型。
DOI：
10.1002/bimj.201400047
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Taylor,JeremyMG
中科院分区：
文献类型：
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作者：
Fernandes,LauraL;Murray,Susan;Taylor,JeremyMG
除了对疗效进行初步评估外，II 期试验还可以帮助确定在重复周期中具有可接受的毒性特征的剂量，以及识别毒性特征特别差的亚组。在肿瘤学试验中接受多个周期相同剂量的患者的剂量毒性关系的正确建模至关重要。一个主要挑战在于利用数据收集的条件性质，即观察每个周期的条件是早期周期中没有先前的毒性。我们针对一个治疗周期期间的毒性概率开发了一种新颖且简约的模型，条件是使用马尔可夫模型在之前的任何周期中都没有看到毒性，下文中我们将这些概率称为毒性的条件概率。我们的模型允许毒性的条件概率取决于随机剂量组、先前周期的累积剂量、患者对相同剂量暴露的反应一致性的测量以及影响耐受治疗方案的能力的个体风险因素。给出了研究模型的有限样本特性的模拟。最后，该方法在一项 II 期试验中得到了证明，该试验研究了软组织肉瘤患者在四个周期内使用两种剂量水平的异环磷酰胺加阿霉素和粒细胞集落刺激因子。马尔可夫模型提供了有限样本模拟中毒性概率的正确估计。它还正确地模拟了 II 期临床试验的数据，并确定了女性中特别高的累积毒性。
In addition to getting a preliminary assessment of efficacy, phase II trials can also help to determine dose(s) that have an acceptable toxicity profile over repeated cycles as well as identify subgroups with particularly poor toxicity profiles. Correct modeling of the dose‐toxicity relationship in patients receiving multiple cycles of the same dose in oncology trials is crucial. A major challenge lies in taking advantage of the conditional nature of data collection, that is each cycle is observed conditional on having no previous toxicities on earlier cycles. We develop a novel and parsimonious model for the probability of toxicity during a cycle of therapy, conditional on not seeing toxicity in any of the previous cycles using a Markov model, hereafter we refer to these probabilities as conditional probabilities of toxicity. Our model allows the conditional probability of toxicity to depend on randomized dose group, cumulative dose from prior cycles, a measure of how consistently a patient responds to the same dose exposure and individual risk factors influencing the ability to tolerate the treatment regimen. Simulations studying finite sample properties of the model are given. Finally, the approach is demonstrated in a phase II trial studying two dose levels of ifosfamide plus doxorubicin and granulocyte colony‐stimulating factor in soft tissue sarcoma patients over four cycles. The Markov model provides correct estimates of the probabilities of toxicity in finite sample simulations. It also correctly models the data from the phase II clinical trial, and identifies particularly high cumulative toxicity in females.