Predictors of loss to follow-up after radiotherapy in cancer patients
2
Issued Date
2026-03-01
Resource Type
ISSN
09414355
eISSN
14337339
Scopus ID
2-s2.0-105031850208
Pubmed ID
41774163
Journal Title
Supportive Care in Cancer
Volume
34
Issue
3
Rights Holder(s)
SCOPUS
Bibliographic Citation
Supportive Care in Cancer Vol.34 No.3 (2026)
Suggested Citation
Pongpradit C., Kasemsuk W. Predictors of loss to follow-up after radiotherapy in cancer patients. Supportive Care in Cancer Vol.34 No.3 (2026). doi:10.1007/s00520-026-10486-4 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/115648
Title
Predictors of loss to follow-up after radiotherapy in cancer patients
Author(s)
Author's Affiliation
Corresponding Author(s)
Other Contributor(s)
Abstract
Introduction: Loss to follow-up after radiotherapy presents a critical challenge in cancer care, undermining treatment effectiveness and efficient use of healthcare resources. Understanding predictors of follow-up non-adherence in the Thai context is essential to improving patient outcomes. Research objective: This study aimed to determine the rate, underlying causes, and predictive factors associated with loss to follow-up appointments among cancer patients after completing radiotherapy. Methods: A predictive correlational design was employed with 294 cancer patients who had completed radiotherapy and were scheduled for follow-up appointments. Participants were selected using systematic random sampling. Data were collected through questionnaires, medical record reviews, and telephone interviews for patients who missed appointments. Research instruments included a personal and clinical data form, a radiotherapy service quality assessment based on the SERVQUAL model, and a researcher-developed questionnaire assessing knowledge of follow-up care. Data analysis involved descriptive statistics, chi-square tests, Spearman’s correlation, and multiple logistic regression. Results: The loss to follow-up rate was 20%. The most common reasons were forgetting appointments (38%), feeling unwell or bedridden (21%), and hospitalization (13%). Multivariate analysis identified two significant predictors: distance from residence to hospital (OR = 1.011, 95% CI 1.003–1.018, p = 0.007) and Eastern Cooperative Oncology Group (ECOG) performance status (OR = 1.973, 95% CI 1.355–2.871, p < 0.001). Conclusion: Distance to hospital and poorer physical performance status are key predictors of loss to follow-up. Interventions such as telemedicine, multi-channel reminder systems, and case management for high-risk patients are recommended to strengthen continuity of care and reduce missed appointments.