A quantitative method for measuring the relationship between an objective endpoint and patient reported outcome measures

Patient reported outcome measures (PROMs) become increasingly important for assessing the effectiveness of a drug or medical device. In order for a PROM to be claimed in labeling, the PROM has to be valid, reliable and able to detect a change if the targeted disease status changes. One approach to assess the quality of a patient reported outcome measure (PROM) is to investigate the association between the PROM and an objective clinical endpoint measuring the status of a disease/condition. However, methods assessing the association between continuous and discrete variables are limited, especially for correlated measurements. In this paper, we propose a method to assess such association with any type of samples with or without correlation. The method involves estimating the probability revealing the status of a subject's disease/condition (called truth thereafter) through the subject's reported outcomes. The probability is a conditional probability revealing truth given the relative location of the subject's objective outcome compared to the subject-specific latent threshold in the objective endpoint. A consistent estimator for the probability is derived. The operating characteristics of the consistent estimator are illustrated using simulation. Our method is applied to hypothetical clinical trial data generated for an ophthalmic device as an illustration.