Characteristics and determinants of loss to follow-up among tuberculosis (TB) patients who smoke in an industrial state of Malaysia: a registry-based study of the years 2013-2017

Abstract

Background The increased risk of loss to follow-up among TB smokers raises concern over the secondary spread within the community. This study aimed to determine the factors associated with loss to follow-up among TB patients who smoke. Methods All registered TB patients who smoke in the state of Selangor between 2013 and 2017 via the Malaysian Tuberculosis Information System (MyTB) database were included for analysis. TB patients who smoke were considered those who are “current smoker” during the notification, while loss to follow-up was defined as a TB patient who had interrupted treatment for 2 months or longer. There were 3 main variable domains included for analysis: sociodemographic profiles, disease profiles, and comorbidities. Logistic regression analysis was used to identify determinants of loss to follow-up among TB patients who smoke. Results A total of 14.1% (N = 813) of TB patients who smoke loss to follow-up. The determinants of loss to follow-up among TB smokers were working age population aged 32-41 and 42-53 years old (AOR 1.08; 95%CI 1.23,2.08) and (AOR 1.44; 95%CI 1.11,1.87) respectively, Malaysian nationality (AOR 2.34; 95%CI 1.66,3.30), patients staying in urban area (AOR 1.55; 95% CI 1.23,1.97), income level less than RM2160 (AOR 1.59; 95% CI 1.14,2.20), un-employed (AOR 1.30; 95%CI 1.09-1.55), have low education level i.e., secondary school education, primary school education and no formal education (AOR 1.60; 95%CI 1.22,2.10), (AOR 1.73; 95%CI 1.16,2.57) and (AOR 2.29; 95% CI 1.57,3.33) respectively, previously treated TB cases (AOR 2.19; 95% CI 1.71,2.81), active TB case detection methods (AOR 2.06; 95%CI 1.40,3.02), moderate lesion x-ray (AOR 1.60; 95%CI 1.13,2.27) and HIV positive (AOR 1.36; 95%CI 1.02,1.82). All the significant factors gave rise to the final model of determinants, with a predictability of 67.2% (95% CI 65.0,69.3). Conclusions The high proportion of loss to follow-up among TB patients who smoke highlight the importance of providing early risk detection that examines the three main domains of risk factors such as socioeconomic, disease profiles and comorbidities. Potential integrated intervention should aim to reduce the proportion of smoking among TB patients through the stop smoking programme together with directly observed therapy (DOT).

T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers

“…In comparison with other prognostic models for loss to follow-up among general TB patients [ 33 , 34 ], our model identifies several predictive factors that are significant for TB smokers, such as young adults (age <50 years old) and HIV-positive individuals. Young adult who are in their working age population are mostly associated with smoking behavior and are at risk for LTFU from TB treatment [ 8 , 14 , 35 ]. While, smoking among TB-HIV patients had a synergistic impact on the burden of both TB and HIV, as smoking leads to worse TB treatment outcomes and inhibits the effectiveness of life-saving ART(anti-retroviral treatment), which worsens the overall health outcomes of patients [ 36 ].…”

“…At the same time, financial limitations and poor social support aggravated the issues of treatment interruption and LTFU among TB-smoking patients with HIV [ 37 ]. It also reflects the performance of our management and control activities at the ground level for TB-HIV patients under the National TB and HIV/AIDS control program [ 14 ].…”

“…Noncompliance with anti-tuberculosis treatments and LTFU among TB patients are serious issues in our TB control program, yet this is preventable. In Selangor state itself, the rate of LTFU among general TB patients ranged from 5.8% to 13% from 2014 to 2017 [ 14 ]. This rate is higher than the national target rate for loss to follow-up of <2% (NSPTB 2015–2020) [ 38 ].…”

“…Many of these factors require qualitative input and further exploration of losses to follow-up TB cases, which is beyond the scope of this study. In industrialized urban areas, where smoking and TB are prevalent, the determinants for LTFU consist of low socioeconomic status, working-age population, previously treated TB cases, TB-HIV coinfection, and patients with moderate lesions on chest X-rays [ 14 ]. Smokers tend to have a lower socioeconomic status, which suggests potential additional financial barriers for them to travel and complete their TB treatment [ 15 ].…”

A Gamified Real-time Video Observed Therapies (GRVOTS) Mobile App via the Modified Nominal Group Technique: Development and Validation Study

“…Specifically, the problems currently facing DOTS can be categorized according to the 3 main stakeholders. For patients with TB, the compulsory need for daily DOTS monitoring results in stigma by the public and absence from home or work responsibilities [5][6][7]. Health workers and policy makers are hesitant to fully implement DOTS, as there are inadequate human resources, increased TB management costs, less participation from lower management, and a lack of public awareness [8,9].…”