Symptom cluster experience profiles in adult survivors of childhood cancers

Abstract

Although aggressive medical treatment protocols have led to 80% five-year survival rates for most childhood cancer patients, many long-term survivors experience multiple troubling symptoms. Using data from 100 adult survivors of childhood cancers (ACC-survivors), we used latent variable mixture modeling to generate unique subgroups of survivors based on their experiences with a cluster of eight symptoms: lack of energy, worry, pain, difficulty sleeping, feeling irritable, feeling nervous, difficulty concentrating, and feeling sad (as measured by the Memorial Symptom Assessment Scale). We also examined factors that were likely to predict subgroup membership (chronic health conditions [CHCs], health-promoting lifestyle, and demographic variables) and determined the extent to which satisfaction with quality of life (QoL) varied across the subgroups. The final mixture model included three subgroups of ACC-survivors: high symptoms (HS; n=21), moderate symptoms (MS; n=45), and low symptoms (LS; n=34). ACC-survivors who reported at least one CHC were six times as likely to be classified in the HS subgroup as compared with the LS subgroup. Mean health-promoting lifestyle scores were lowest in the HS subgroup and highest in the LS subgroup. Differences in QoL among the subgroups were statistically significant, thus validating that the subgroups were characterized uniquely for identifying those symptoms with highest life impact. To our knowledge, we are the first to identify distinct subgroups of ACC-survivors differentiated by symptom cluster experience profiles. The findings warrant additional research to confirm the subgroup-specific symptom cluster experience profiles in larger studies of ACC-survivors.

Figure 1

NOTE: Although three subgroups are shown, models may have less than or more than subgroups

Figure 2

Symptom characteristic probabilty plots: 3 subgroup model