Decision trees for identifying predictors of treatment effectiveness in clinical trials and its application to ovulation in a study of women with polycystic ovary syndrome

Abstract

Background: Double-blind, randomized clinical trials are the preferred approach to demonstrating the effectiveness of one treatment against another. The comparison is, however, made on the average group effects. While patients and clinicians have always struggled to understand why patients respond differently to the same treatment, and while much hope has been held for the nascent field of predictive biomarkers (e.g. genetic markers), there is still much utility in exploring whether it is possible to estimate treatment efficacy based on demographic and baseline variables.

Methods: The pregnancy in polycystic ovary syndrome (PPCOS) study was a prospective, multi-center, randomized clinical trial comparing three ovulation induction regimens: clomiphene citrate (CC), metformin and the combination of the two. There were 446 women who ovulated in response to the treatments among the entire 626 participants. In this report, we focus on the 418 women who received CC (alone or combined with metformin) to determine if readily available baseline physical characteristics and/or easily obtainable baseline measures could be used to distinguish treatment effectiveness in stimulating ovulation. We used a recursive partitioning technique and developed a node-splitting rule to build decision tree models that reflected within-node and within-treatment responses.

Results: Overall, the combination of CC plus metformin resulted in an increased incidence of ovulation compared with CC alone. This is particularly so in women with relatively larger left ovarian volumes (≥ 19.5 cubic cm), and a left ovarian volume <19.5 cubic cm was related to treatment outcomes for all subsequent nodes. Women who were older, who had higher baseline insulin, higher waist-to-hip circumference ratio or higher sex hormone-binding globulin levels had better ovulatory rates with CC alone than with the combination of CC plus metformin.

Conclusions: Polycystic ovary syndrome (PCOS) is a phenotypically diverse condition. Both baseline laboratory and clinical parameters can predict the ovulatory response in women with PCOS undergoing ovulation induction. Without a priori hypotheses with regard to any predictors, the observation regarding left ovary volume is novel and worthy of further investigation and validation.

Figure 1

A Classification Tree (top). The top box, labeled #1, is the root node containing the entire study sample of 418 PCOS women. It is partitioned into two nodes 2 and 3 in the next layer. The number of subjects is also displayed next to the node number inside each node. The splitting role is beneath the internal node. The value along an arrow is the cutoff of the splitting variable. When the splitting variable has missing values, the number of affected subjects is presented in the resulting node. In the bottom panel, the vertical bars (purple for CC and red for combination) display the success rates of ovulation within each terminal node, and the terminal node number is printed on the x-axis. Terminal nodes 3, 7, 9, 13 and 15 in the tree are colored red to indicate that the combined treatment is preferred, and other terminal nodes are colored purple indicating that CC is more successful.

Figure 2

A Revised Classification Tree (top). The top box, labeled #1, is the root node containing the entire study sample of 418 PCOS women. The number of subjects is also displayed next to the node number inside each node. The splitting role is beneath the internal node. The value along an arrow is the cutoff of the splitting variable. (For further details, see the legend for Fig. 1.)

Figure 3

Internal Validation of the Ratio of the Ovulation Rates between the combined and CC treatment groups. The ratios are presented by the terminal nodes in Fig. 1. We took a random 60, 70, 80, 90 and 100% of the samples to examine the trend in the within-node preferential treatment.

Figure 4

Internal Validation of the Ratio of the Ovulation Rates between the combined and CC treatment groups with respect to the BMI groups. The ratios are presented by the terminal nodes in Fig. 1. No data were available to estimate the ratio for the lower BMI group in terminal node 9.

Figure 5

A Decision Tree for Relative Effectiveness of Treatments for Live Birth. (For further details, see the legend for Fig. 1.)