Latent transitions of distress risk during cancer treatment and their concordance with anxiety, depression, and quality of life in a large multicenter cohort.
Abstract
11106 Background: Distress is prevalent in patients with cancer and may change throughout treatment. However, longitudinal transitions between distress-risk states and their relationship with psychosocial outcomes in real-world oncology settings remain poorly characterized. We sought to identify latent distress-risk states, describe transitions during cancer treatment, and evaluate their clinical determinants and concordance with anxiety/depression and health-related quality of life (HRQOL). Methods: This longitudinal multicenter cohort study included adult patients with cancer treated across all Brazilian states. Distress was assessed at baseline (prior to treatment initiation), mid-treatment, and end of treatment using the Distress Thermometer (DT). Symptoms of anxiety/depression and HRQOL were assessed using the Hospital Anxiety and Depression Scale (HADS) and FACT-G. Latent Transition Analysis (LTA) identified distress-risk states and transition probabilities over time; model selection was based on Bayesian Information Criterion, entropy, and clinical interpretability. Multinomial logistic regression evaluated clinical predictors of baseline distress-risk states. Directional concordance between changes in DT and changes in HADS and FACT-G was assessed using concordance matrices and chi-square tests. Results: A total of 2197 patients were included. Median age was 58 years, 72.3% were female, and most were diagnosed with breast (40.1%) or gastrointestinal (18.8%) cancer, with 40.0% presenting with advanced-stage disease (III-IV). A four-state LTA model with optimal fit identified high critical, moderate persistent, low vulnerable, and low stable distress-risk profiles. The low stable state was the most prevalent and highly stable, with 94.5% remaining in the same state across assessments, whereas the high critical and low vulnerable states were more dynamic. Among high critical patients, 22.8% transitioned to moderate risk and 19.6% to low risk, while 28.6% of moderate persistent patients transitioned to the low stable state. Worsening occurred in up to 12.6% of patients. Male sex (OR = 1.8, 95% CI 1.08-3.09) and stage IV disease (OR = 1.8, 95% CI 1.09-2.97) were independently associated with higher-risk distress states (Ps = 0.02). Changes in distress states showed high directional concordance with psychosocial outcomes (HADS 82.9%; FACT-G 77.0%; χ² p < 0.001). Conclusions: Distinct and clinically meaningful distress-risk states and dynamic transitions were observed during cancer treatment. While most patients remained stable or improved, a relevant subgroup experienced worsening distress. These findings support repeated distress screening and adaptive, risk-based psychosocial interventions integrated into routine oncology care.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (20)
Cristiane Decat Bergerot
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Rafael Paes
Oncoclínicas&Co/MedSir, Sao Paulo, SP, Brazil
Renata Ferrari
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Rafaela Peixoto
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Bianca Gasparotto
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Emanuele Vieira
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Leticia Norata Ferreira
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Jessica Campos
Oncoclínicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Amanda Grazielle Rocha
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Patricia Campos Christo
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Ruth Vivaldo Noia
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Thayna Ferreira Reboucas
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Tatiele Santos dos Reis Santana de Jesus
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Juliana de Assis Alves Freze
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Fabiana Cristina Carvalho Boulanger
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Caroline Aguirre Souza
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Pamela Carvalho Muniz
Oncoclinicas, São Paulo, Brazil
Bruno Lemos Ferrari
Oncoclinicas & Co - Medica Scientia Innovation Research (MEDSIR), São Paulo, Brazil
Mariana Laloni
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil
Carlos Gil Ferreira
Oncoclinicas&Co - Medica Scientia Innovation Research (MEDSIR), Sao Paulo, Brazil