Factors Reported By Tuberculosis Patients Lost to Follow-Up during Treatment at Port Moresby General Hospital, Papua New Guinea: A Cross-Sectional Study

Background: Tuberculosis (TB) treatment loss to follow-up (LTFU) is an important public health problem because treatment interruption may contribute to unsuccessful treatment outcomes and ongoing transmission. This study describes characteristics and issues reported by TB patients who were lost to follow-up during treatment at Port Moresby General Hospital (PMGH), Papua New Guinea.
Methods: A cross-sectional descriptive study was conducted among confirmed pulmonary and extrapulmonary TB patients who had received TB treatment for more than one month and subsequently stopped treatment for more than two months. Eighty-eight patients were selected from the medical ward, TB ward and TB clinic at PMGH between May 2015 and May 2016. Data were collected using a standardized questionnaire through face-to-face interviews after informed consent. Descriptive statistics were used.
Results: Of 88 participants, 54 (61%) were female and 34 (39%) male. The largest age group was 23–32 years (36, 41%). Primary education was reported by 46 (52%) and no formal education by 14 (16%). HIV infection was reported in 20 (23%), alcohol use in 40 (46%), smoking in 39 (44%), and betel-nut chewing in 60 (68%). Personal factors were reported in 64 (72%), socioeconomic factors in 37 (42%), and health-system factors in 76 (86%). Symptom resolution was reported in 31 participants, belief in sorcery in 18, and TB-drug adverse effects in 15. Treatment interruption occurred during the continuation phase in 51 (58%) and intensive phase in 37 (42%).
Conclusion: Health-system factors were the most frequently reported category among TB patients experiencing LTFU, followed by personal and socioeconomic factors. Patient education, adverse-effect management, treatment support, improved follow-up systems and attention to transportation barriers may improve treatment continuity. Because the study included only patients who experienced LTFU, the findings should be interpreted as descriptive rather than as statistically demonstrated risk factors.

tuberculosis; loss to follow-up; treatment interruption; Papua New Guinea; treatment adherence

1. World Health Organization. Global tuberculosis report 2025. Geneva: World Health Organization; 2025. [Google Scholar] [Crossref]

2. World Health Organization. WHO consolidated guidelines on tuberculosis: module 4: treatment and care. Geneva: World Health Organization; 2025. [Google Scholar] [Crossref]

3. World Health Organization. Adherence to long-term therapies: evidence for action. Geneva: World Health Organization; 2003. [Google Scholar] [Crossref]

4. Santha T, Garg R, Frieden TR, Chandrasekaran V, Subramani R, Gopi PG, et al. Risk factors associated with default, failure and death among tuberculosis patients treated in a DOTS programme in Tiruvallur District, South India, 2000. Int J Tuberc Lung Dis. 2002;6(9):780–788. [Google Scholar] [Crossref]

5. Dooley KE, Lahlou O, Knudsen J, Elmessaoudi MD, Cherkaoui I, El Aouad R, et al. Risk factors for tuberculosis treatment failure, default, or relapse and outcomes of retreatment in Morocco. BMC Public Health. 2011;11:140. [Google Scholar] [Crossref]

6. Chen J, Chen M, Chen Y, Zhang Z, Ma Z, et al. Which urban migrants default from tuberculosis treatment in Shanghai, China? PLoS One. 2013;8(11):e81351. [Google Scholar] [Crossref]

7. Vijay S, Balasangameswara VH, Jagannatha PS, Saroja VN, Kumar P. Risk factors associated with default among new smear-positive TB patients treated under DOTS in India. PLoS One. 2010;5(4):e10043. [Google Scholar] [Crossref]

8. Kendall EA, Theron D, Franke MF, van Helden PD, Victor TC, Murray MB, et al. Alcohol, hospital discharge, and socioeconomic risk factors for default from multidrug-resistant tuberculosis treatment in rural South Africa. PLoS One. 2013;8(12):e83480. [Google Scholar] [Crossref]

9. Kruk ME, Schwalbe NR, Aguiar CA. Timing of default from tuberculosis treatment: a systematic review. Trop Med Int Health. 2008;13(5):703–712. [Google Scholar] [Crossref]

10. Bam TS, Gunneberg C, Gunaratne W, Purana-Ingram S, Enarson DA, Reid A, et al. Factors affecting patient adherence to directly observed treatment short-course in Kathmandu, Nepal. Int J Tuberc Lung Dis. 2006;10(3):270–276. [Google Scholar] [Crossref]

11. Muture BN, Keraka MN, Kimuu PK, Kabiru EW, Ombeka VO, Oguya F. Factors associated with default from treatment among tuberculosis patients in Nairobi Province, Kenya: a case-control study. BMC Public Health. 2011;11:696. [Google Scholar] [Crossref]

12. Chida N, Ansari Z, Hussain H, Jaswal M, Khan AJ, Amanullah F. Determinants of default from tuberculosis treatment among patients with drug-susceptible tuberculosis in Karachi, Pakistan: a mixed methods study. PLoS One. 2015;10(11):e0142384. [Google Scholar] [Crossref]

13. Commons RJ, Aia P, Kuao J, Bang P, Phelan J, et al. Factors associated with loss to follow-up among TB patients in rural Papua New Guinea. Public Health Action. 2021;11(4):177–184. [Google Scholar] [Crossref]

• Assessment of the Role of Artificial Intelligence in Repositioning TVET for Economic Development in Nigeria
• Teachers’ Use of Assure Model Instructional Design on Learners’ Problem Solving Efficacy in Secondary Schools in Bungoma County, Kenya
• “E-Booksan Ang Kaalaman”: Development, Validation, and Utilization of Electronic Book in Academic Performance of Grade 9 Students in Social Studies
• Analyzing EFL University Students’ Academic Speaking Skills Through Self-Recorded Video Presentation
• Major Findings of The Study on Total Quality Management in Teachers’ Education Institutions (TEIs) In Assam – An Evaluative Study