Measuring Patient Experience: How longitudinal symptom trends impact quality of life in cancer patients

Patient experience can be accurately measured and effectively analyzed for scientific understanding and clinical decision support.  Longitudinal symptom assessments of cancer patients are an emerging best practice.  OBJECTIVE:  We aim to better understand symptoms patterns and trends and their impact on cancer patients’ quality of life (QOL).  METHOD:  We retrospectively analyzed a set of longitudinal data (CareTrack) based on Patient Reported Outcome Measurement Information System (PROMIS) with use of mixed effect models.  We included demographic factors, cancer types, and selected symptom scores as predictor variables.  QOL, both as a continuous variable and a binary variable, were used as the target variable.  RESULT:  All symptoms and functions worsened significantly over time except anxiety and faith.  Anorexia or fatigue were the most burdensome symptom across all included cancer types while depression was the least.   Gender, age, and race had limited impact on symptoms.  Selected CareTrack scores were found to be associated with QOL.  A linear mixed effect regression (lmer) model included gender, anorexia, depression, fatigue, pain interference, ECOG, and quarters before death (QfromDeath) as predictors for QOL.  A generalized linear mixed effect regression (glmer) model included depression, pain interference, ECOG, and QfromDeath as predictors for poor QOL (score of 4 or less).   CONCLUSION:  Symptoms generally differ by cancer types and worsened over time with exception of anxiety and faith.  Key predictors of QOL were ECOG, pain interference and depression.  Additional contributors were anorexia, fatigue, and gender.