Quality of life assessment for colorectal cancer follow-up: A latent profile analysis of EORTC measures.

Abstract

To identify distinct health-related quality of life (HRQoL) profiles among colorectal cancer (CRC) patients using patient-reported outcome measures (PROMs), with the aim of informing more personalised follow-up strategies. Baseline HRQoL data from CRC patients enrolled in the FUTURE-primary study, a multicentre implementation study on home-based follow-up, were analysed. Patients completed the EORTC QLQ-C30 and QLQ-CR29 questionnaires. Aggregated symptom and function scales were developed using factor analysis and expert consensus. Latent profile analysis (LPA) was applied to identify subgroups based on PROM responses. Model selection was guided by the Bayesian Information Criterion (BIC), entropy, average posterior probabilities (AvePP), class sizes, clinical interpretability, and additional sensitivity and stability analyses. Three HRQoL profiles were identified: low HRQoL (n = 62), intermediate HRQoL (n = 95), and high HRQoL (n = 42). The profiles followed a gradient-like pattern, with consistently high, moderate, or low scores across symptom burden and functional outcomes. Classification quality was high, as indicated by high entropy (>0.93) and average posterior probabilities (>0.96), although profile assignment should be interpreted probabilistically. This study highlights variation in HRQoL among CRC patients. LPA identified three profiles that primarily reflected differences in overall symptom burden and functioning. These profiles may provide a preliminary framework for describing differences in supportive care needs, but their clinical applicability for tailoring follow-up or allocating care resources requires longitudinal validation. Identifying HRQoL profiles may support more personalised follow-up, ensuring targeted care for those with higher symptom burden and lower functional scores, while reducing unnecessary interventions for others.