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

INTRODUCTION: Loss to follow-up (LTFU) and smoking during TB treatment are major challenges for TB control programs. Smoking increases the severity and prolongs TB treatment duration, which lead to a higher rate of LTFU. We aim to develop a prognostic scoring tool to predict LTFU among TB patients who smoke to improve successful TB treatment outcomes. MATERIALS AND METHODS: The development of the prognostic model utilized prospectively collected longitudinal data of adult TB patients who smoked in the state of Selangor between 2013 until 2017, which were obtained from the Malaysian Tuberculosis Information System (MyTB) database. Data were randomly split into development and internal validation cohorts. A simple prognostic score (T-BACCO SCORE) was constructed based on the regression coefficients of predictors in the final logistic model of the development cohort. Estimated missing data was 2.8% from the development cohort and was completely at random. Model discrimination was determined using c-statistics (AUCs), and calibration was based on the Hosmer and Lemeshow goodness of fit test and calibration plot. RESULTS: The model highlights several variables with different T-BACCO SCORE values as predictors for LTFU among TB patients who smoke (e.g., age group, ethnicity, locality, nationality, educational level, monthly income level, employment status, TB case category, TB detection methods, X-ray categories, HIV status, and sputum status). The prognostic scores were categorized into three groups that predict the risk for LTFU: low-risk (<15 points), medium-risk (15 to 25 points) and high-risk (> 25 points). The model exhibited fair discrimination with a c-statistic of 0.681 (95% CI 0.627-0.710) and good calibration with a nonsignificant chi-square Hosmer‒Lemeshow's goodness of fit test χ2 = 4.893 and accompanying p value of 0.769. CONCLUSION: Predicting LTFU among TB patients who smoke in the early phase of TB treatment is achievable using this simple T-BACCO SCORE. The applicability of the tool in clinical settings helps health care professionals manage TB smokers based on their risk scores. Further external validation should be carried out prior to use.

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.

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).

Seroprevalence of diphtheria toxoid IgG antibodies in the Malaysian population.

BACKGROUND: Despite high childhood immunization coverage, sporadic cases of diphtheria have been reported in Malaysia in recent years. This study aims to evaluate the seroprevalence of diphtheria among the Malaysian population. METHODS: A total of 3317 respondents age 2 years old to 60 years old were recruited in this study from August to November 2017. Enzyme-linked immunosorbent assay (ELISA) was used to measure the level of IgG antibody against the toxoid of C. diphtheriae in the blood samples of respondents. We classified respondent antibody levels based on WHO definition, as protective (≥0.1 IU/mL) and susceptible (< 0.1 IU/mL) to C. diphtheriae infection. RESULTS: Among the 3317 respondents, 57% were susceptible (38.1% of children and 65.4% of adults) and 43% (61.9% of children and 34.6% of adults) had protective antibody levels against diphtheria. The mean antibody level peaked among individuals aged 1-2 years old (0.59 IU/mL) and 6-7 years old (0.64 IU/mL) but generally decreased with age, falling below 0.1 IU/mL at around 4-6 years old and after age 20 years old. There was a significant association between age [Children: χ2 = 43.22(df = 2),p < 0.001)], gender [Adults: χ2 = 5.58(df = 1),p = 0.018] and ethnicity [Adults: χ2 = 21.49(df = 5),p = 0.001] with diphtheria toxoid IgG antibody level. CONCLUSIONS: About 57% of the Malaysian population have inadequate immunity against diphtheria infection. This is apparently due to waning immunity following childhood vaccination without repeated booster vaccination in adults. Children at age 5-6 years old are particularly vulnerable to diphtheria infection. The booster vaccination dose normally given at 7 years should be given earlier, and an additional booster dose is recommended for high-risk adults.

INFLUENZA VACCINATION UPTAKE AMONG HEALTHCARE WORKERS AT A MALAYSIAN TEACHING HOSPITAL.

Annual influenza vaccination is the most important preventive strategy against influenza illness in healthcare workers (HCWs), who could acquire influenza from and transmit influenza to patients and other HCWs. Despite the well established benefits and strong recommendations for influenza vaccination for all HCWs, influenza vaccination uptake at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC) for the past 3 years has been low and is decreasing. We aimed to determine the factors associated with influenza vaccination uptake among HCWs at UKMMC. We conducted a cross sectional study via questionnaire among 211 randomly selected HCWs, consisting of 106 HCWs who were vaccinated in 2011 and 105 HCWs who were not vaccinated in 2010 or 2011. We had a 100% response rate. Influenza vaccination uptake was significantly associated with age and previous vaccination history, with older HCWs being more likely to be vaccinated (adjusted OR = 12.494; 95% CI:6.278-24.863; p < 0.001) and HCWs with previous vaccination history being more likely to be vaccinated (adjusted OR = 1.038; 95% CI:1.001-1.077; p = 0.045). Influenza vaccination uptake was not associated with gender (p = 0.926) or job category (p = 0.220). Publicity at the workplace was the main source of information about the vaccine (51.2% of respondents), followed by colleagues (29.9%). Despite the low uptake, 85.3% of respondents believed influenza vaccination was important for disease prevention. The most common reason given for vaccination was protection against influenza infection (73.6%). The most common reason for not having the vaccine was time constraints (56.2%). An evidenced-based strategy needs to be developed to improve vaccine uptake or having mandatory vaccination.