We present and evaluate a method for predicting individual treatment benefits based on random effects logistic regression models of binary outcomes that change over time. The method uses empirical Bayes predictors based on patients’ characteristics and responses to treatment. It is applicable to both 1-dimentional and 2-dimentional personalized medicine models. Comparisons between predicted and true benefits for simulated new patients using correlations, relative biases and mean-squared errors were used to evaluate prediction performance. The predicted benefits had relatively small biases and relatively high correlations with the true benefits in the simulated new patients. The predictors also captured estimated overall population trends in the evolution of individual benefits. The proposed approach can be used to retrospectively evaluate patients’ responses in a clinical trial, or to retrospectively or prospectively predict individual benefits of different treatments for new patients using patients’ characteristics and previous responses. The method is used to examine changes in the disorganized dimension of antipsychotic-naïve patients from an antipsychotic randomized clinical trial. Retrospective prediction of individual benefits revealed that more cannabis users had slower and lower responses to antipsychotic treatment as compared to non-cannabis users, revealing cannabis use as a negative prognostic factor for psychotic disorders in the disorganized dimension.

我们提出并评估了一种基于随时间变化的二元结果的随机效应逻辑回归模型来预测个体治疗益处的方法。该方法使用基于患者特征和对治疗的反应的经验贝叶斯预测器。它适用于一维和二维个性化医疗模型。使用相关性、相对偏差和均方误差比较模拟新患者的预测和真实收益，用于评估预测性能。预测的益处具有相对较小的偏差，并且与模拟的新患者的真实益处具有相对较高的相关性。这些预测器还捕捉到了个人福利演变过程中估计的总体人口趋势。所提出的方法可用于回顾性评估临床试验中患者的反应，或使用患者的特征和先前的反应回顾性或前瞻性地预测不同治疗对新患者的个体益处。该方法用于检查抗精神病药物随机临床试验中未使用抗精神病药物患者的混乱维度的变化。对个人益处的回顾性预测表明，与非大麻使用者相比，更多的大麻使用者对抗精神病药物治疗的反应更慢和更低，这表明大麻的使用是无组织维度上精神病的负面预后因素。或使用患者的特征和先前的反应来回顾性或前瞻性地预测新患者不同治疗的个体益处。该方法用于检查抗精神病药物随机临床试验中未使用抗精神病药物患者的混乱维度的变化。对个人益处的回顾性预测表明，与非大麻使用者相比，更多的大麻使用者对抗精神病药物治疗的反应更慢和更低，这表明大麻的使用是无组织维度上精神病的负面预后因素。或使用患者的特征和先前的反应来回顾性或前瞻性地预测新患者不同治疗的个体益处。该方法用于检查抗精神病药物随机临床试验中未使用抗精神病药物患者的混乱维度的变化。对个人益处的回顾性预测表明，与非大麻使用者相比，更多的大麻使用者对抗精神病药物治疗的反应更慢和更低，这表明大麻的使用是无组织维度上精神病的负面预后因素。