# Symptom profiles in lung cancer survivors: A latent class approach

**Authors:** Tehreem Hussain, Elisa H. Son, Gwenyth R. Wallen, Li Yang, Lena J. Lee, Ming-Ching Lee, Made Satya Nugraha Gautama, Made Satya Nugraha Gautama, Made Satya Nugraha Gautama

PMC · DOI: 10.1371/journal.pone.0309272 · PLOS One · 2025-10-31

## TL;DR

This study identifies distinct symptom profiles in lung cancer survivors and finds that sociodemographic factors influence these profiles more than clinical ones.

## Contribution

The study introduces a novel approach to understanding symptom clusters in lung cancer survivors using latent profile analysis.

## Key findings

- Four distinct symptom profiles were identified in lung cancer survivors.
- Sociodemographic factors like age and income influence symptom profiles more than clinical factors.
- Symptom profiles differ significantly in physical and social function outcomes.

## Abstract

Lung cancer survivors experience multiple concurrent symptoms after cancer treatments. However, the majority of symptom research has focused on assessing and managing individual symptoms. Furthermore, little is known about the risk factors and adverse outcomes of complex symptoms in lung cancer survivors. The purpose of the study was to: (1) identify symptom profiles in lung cancer survivors; (2) determine influencing factors of the symptom profiles; and (3) examine differences in health outcomes among the symptom profiles. A cross-sectional secondary analysis of data from the Measuring Your Health (MY-Health) study was conducted with 526 lung cancer survivors. Symptom profiles were identified using latent profile analysis based on four patient-reported symptoms (pain, fatigue, sleep disturbance, and depression) with custom PROMIS® short forms. We conducted multinomial logistic regression analysis to determine influencing factors of the symptom profiles and multivariate analysis of variance to examine differences in physical function and social function among the symptom profiles. Four latent class symptom profiles were identified: (1) Within Normal Limits (Class 1), (2) Pain with Fatigue and Sleep Disturbance (Class 2), (3) Depression with Fatigue and Sleep disturbance (Class 3), and (4) All High Symptom Burden (Class 4). Age, income, employment status, and number of comorbidities were the influencing factors of the symptom profiles. There were significant differences in physical function and social function among the symptom profiles. This study found that the influencing factors of the symptom profiles in lung cancer survivors tended to be more sociodemographic in nature, rather than clinical. Researchers and healthcare providers use findings such as these when establishing symptom management strategies for lung cancer survivors by integrating demographic and socioeconomic determinants of health in conjunction with targeted clinical variables.

## Linked entities

- **Diseases:** lung cancer (MONDO:0005138)

## Full-text entities

- **Diseases:** Lung cancer (MESH:D008175), Sleep Disturbance (MESH:D012893), Depression (MESH:D003866), Symptom (MESH:D012816), Pain (MESH:D010146), Fatigue (MESH:D005221), cancer (MESH:D009369)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12578159/full.md

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12578159/full.md

## References

52 references — full list in the complete paper: https://tomesphere.com/paper/PMC12578159/full.md

---
Source: https://tomesphere.com/paper/PMC12578159