JOINTNESS BOX: A NOVEL METHOD TO CONTEMPLATE VALUE OF INDIVIDUALIZED CARE FROM TRADITIONAL TRIAL DATA

Purpose: Presence of heterogeneity alone in the comparative effects of treatments is not enough to call for investments in Patient-Centered Outcome Research (PCOR). Even in the presence of heterogeneous effects, individual outcomes from one treatment can stochastically dominate outcomes from an alternative, which would imply that PCOR has minimal value. Here, we develop a simple and novel method, called the “Jointness Box (JB)” that may be used to contemplate the value of PCOR based on marginal distributions of counterfactual outcomes obtained in traditional studies, helping in the prioritization of PCOR.

Methods: Let Q₀ and Q₁ denote outcomes generated under two treatments. Data from a standard clinical trial, where patients are randomly allocated to one or the other treatment, can be used to identify the marginal distributions of Q₀ and Q₁, but not their joint distribution since we lack information on the dependence of Q₀ on Q₁ at the individual level. However, the identified supports (ranges) of the marginal distributions define a “Jointness Box” (henceforth, JB) representing the plausible spread of heterogeneous treatment effects. In a plot of Q₀ againt Q₁, where the 45-degree line represents the locus of equality for Q₀ and Q₁ at the individual–level, the JB represents an area where the joint-distribution of Q₀ and Q₁ lie.  We study two features: 1) JB-dominance i.e. if the JB lies entirely above or below this 45-degree line. 2) JB-area i.e. the proportion of the full area within JB that falls above the 45-degree line.  Using bootstrap methods, with attention to sampling order statistics, joint distributions of {Max(Q₀), Min(Q₀)} and {Max(Q₁), Min(Q₁)} are obtained and used to study (1) Likelihood of JB-dominance; and (2) the 95% CI for JB-area. Various microsimulation exercises are set up to study the relationship between the JB-dominance and JB-area criteria with the value of PCOR.

Results:  We found that the likelihood of JB-dominance is negatively correlated with the value of PCOR, irrespective of the dependence between Q₀ and Q₁.  Additionally the JB area has a u-shaped relationship with the value of PCOR, and also varies with the nature of dependence between Q₀ and Q₁. The JB metrics are found to be useful tools to envision heterogeneity and prioritize PCOR.

Conclusion: Future work will apply JB metrics to various clinical applications.