Randomized controlled trials are the gold standard for evaluating the effects of medical interventions, primarily providing estimates of the average effect of an intervention in the overall study population. However, there may be significant differences in the effect of the same intervention across sub-populations with different characteristics, that is, treatment heterogeneity. Traditional subgroup analysis and interaction analysis tend to have low power to examine treatment heterogeneity or identify the sources of heterogeneity. With the recent development of machine learning techniques, causal forest has been proposed as a novel method to evaluate treatment heterogeneity, which can help overcome the limitations of the traditional methods. However, the application of causal forest in the evaluation of treatment heterogeneity in medicine is still in the beginning stage. In order to promote proper use of causal forest, this paper introduces its purposes, principles and implementation, interprets the examples and R codes, and highlights some attentions needed for practice.
Objective To analyze the causal relationship between gut microbiota and tic disorder based on Mendelian randomization (MR). Methods A total of 196 known microbiota (9 phyla, 16 classes, 20 orders, 32 families, and 119 genera) in the human intestinal microbiota dataset downloaded from the MiBioGen database were selected as the exposure factors, and the dataset of tic disorder (finn-b-KRA_PSY_TIC) containing 172 patients and 218620 controls was downloaded from the genome-wide association study database as the outcome variable. Inverse variance weighted was used as the main analysis method, and the causal relationship between gut microbiota and tic disorder was evaluated using odds ratio (OR) and its 95% confidence interval (CI). Horizontal pleiotropy was tested by MR-Egger intercept and MR-PRESSO global test, heterogeneity was assessed by Cochran’s Q test, and sensitivity analysis was performed by leave-one-out method. Results Inverse variance weighted results showed that the Family Rhodospirillaceae [OR=0.398, 95%CI (0.191, 0.831), P=0.014], Order Rhodospirillales [OR=0.349, 95%CI (0.164, 0.743), P=0.006], and Parasutterella [OR=0.392, 95%CI (0.171, 0.898), P=0.027] had negative causal relationships with tic disorder. The Genus Lachnospira [OR=8.784, 95%CI (1.160, 66.496), P=0.035] and Candidatus Soleaferrea [OR=2.572, 95%CI (1.161, 5.695), P=0.020] had positive causal relationships with tic disorder. In addition, MR-Egger intercept and MR-PRESSO global test showed no horizontal pleiotropy, Cochran’s Q test showed no heterogeneity, and leave-one-out sensitivity analysis showed the results were stable. Conclusions A causal relationship exists between gut microbiota and tic disorder. The Family Rhodospirillaceae, Order Rhodospirillales, and Parasutterella are associated with a decreased risk of tic disorder, while the Genus Lachnospira and Candidatus Soleaverea can increase the risk of tic disorder.