Kundu Damitri, Sarkar Partha, Das Kiranmoy
Applied Statistics Division, Indian Statistical Institute, Kolkata, India.
Department of Statistics, University of Florida, Gainesville, Florida, USA.
J Biopharm Stat. 2023 Feb 10:1-18. doi: 10.1080/10543406.2023.2171430.
The most common type of cancer diagnosed among children is the acute lymphocytic leukemia (ALL). A study was conducted by Tata Translational Cancer Research Center (TTCRC) Kolkata, in which 236 children (diagnosed as ALL patients) were treated for the first two years (approximately) with two standard drugs (6MP and MTx) and were then followed nearly for the next three years. The goal is to identify the longitudinal biomarkers that are associated with time-to-relapse, and also to assess the effectiveness of the drugs. We develop a Bayesian joint model in which a linear mixed model is used to jointly model three biomarkers (i.e. white blood cell count, neutrophil count, and platelet count) and a semi-parametric proportional hazards model is used to model the time-to-relapse. Our proposed joint model can assess the effects of different covariates on the progression of the biomarkers, and the effects of the biomarkers (and the covariates) on time-to-relapse. In addition, the proposed joint model can impute the missing longitudinal biomarkers efficiently. Our analysis shows that the white blood cell (WBC) count is not associated with time-to-relapse, but the neutrophil count and the platelet count are significantly associated with it. We also infer that a lower dose of 6MP and a higher dose of MTx jointly result in a lower relapse probability in the follow-up period. Interestingly, we find that relapse probability is the lowest for the patients classified into the "high-risk" group at presentation. The effectiveness of the proposed joint model is assessed through the extensive simulation studies.
儿童中诊断出的最常见癌症类型是急性淋巴细胞白血病（ALL）。加尔各答的塔塔转化癌症研究中心（TTCRC）进行了一项研究，其中236名儿童（被诊断为ALL患者）在前两年（大约）使用两种标准药物（6MP和MTx）进行治疗，然后在接下来的三年里进行随访。目标是识别与复发时间相关的纵向生物标志物，并评估药物的有效性。我们开发了一个贝叶斯联合模型，其中使用线性混合模型对三种生物标志物（即白细胞计数、中性粒细胞计数和血小板计数）进行联合建模，并使用半参数比例风险模型对复发时间进行建模。我们提出的联合模型可以评估不同协变量对生物标志物进展的影响，以及生物标志物（和协变量）对复发时间的影响。此外，提出的联合模型可以有效地插补缺失的纵向生物标志物。我们的分析表明，白细胞（WBC）计数与复发时间无关，但中性粒细胞计数和血小板计数与之显著相关。我们还推断，较低剂量的6MP和较高剂量的MTx共同导致随访期内较低的复发概率。有趣的是，我们发现初诊时被归类为“高危”组的患者复发概率最低。通过广泛的模拟研究评估了所提出联合模型的有效性。
