A Factor Analysis Approach for Clustering Patient Reported Outcomes.

ABSTRACT:

Background

In the field of radiation oncology, the use of extensive patient reported outcomes is increasingly common to measure adverse side effects after radiotherapy in cancer patients. Factor analysis has the potential to identify an optimal number of latent factors (i.e., symptom groups). However, the ultimate goal of treatment response modeling is to understand the relationship between treatment variables such as radiation dose and symptom groups resulting from FA. Hence, it is crucial to identify clinically more relevant symptom groups and improved response variables from those symptom groups for a quantitative analysis.

Objectives

The goal of this study is to design a computational method for finding clinically relevant symptom groups from PROs and to test association

SUBMITTER: Oh JH 

PROVIDER: S-EPMC5518610 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature