This study indicates that TB screening among PL HIV is the most cost-effective strategy. The result consistent with past studies, which revealed TB screening among HIV is cost effective in both community and hospital settings (15, 16). HIV is a well-known risk factor for TB infection in low- and middle-income countries (1). In comparison to the non-HIV, there are 16 to 27 times risks of getting TB infection among PL HIV. This is reflected in the prevalence of TB/HIV co-infection in Malaysia of 6% for 2018 (17). From the results of this study, it was also estimated that the cost to detect one TB case from PL HIV screening would be around MYR 2,597.00. The key driver for cost effectiveness model is the probability of TB case detected among the symptomatic cases. The higher the probability of TB case detected among the symptomatic, the lower the ICER; thus, the lower the cost for detecting one TB case.
In addition, TB screening among elderly and prisoners also showed to be cost-effective. It would cost around MYR 2,868.62 and MYR 3,065.24 to detect one TB case by screening the elderly and prisoners respectively. Studies done in US and Soviet Union also revealed similar results, in which screening of prisoners was more cost effective than those of conventional community screening (2). The high prevalence of TB among the jailed population is well documented in previous reports and studies (1). This is due to the environmental condition such as enclosed space and poor ventilation, which lead to poor air circulation and subsequently precipitate TB infection (18, 19). Apart from that, there was enough evidence to show that TB incidence increases with age. However, TB problem among elderly is likely underestimated due to the difficulty of diagnosing TB among older age group (20). Hence, there was suggestion that TB screening among elderly should focus on active case detection (21).
On the other hand, TB screening among Diabetic patient was shown to have the highest cost per one TB case detected among the high-risk groups, with MYR 13,214.26. This might be due to low TB case detection despite of large amount of screening done compared to the other high-risk groups. The association between TB and DM is well documented. However, there are several well-known micro factors that precipitate TB infection in DM patients (22). For example, patient with uncontrolled glycaemic level and low BMI are known to have a higher risk of contracting TB (23). Thus, past studies recommend focusing on TB screening among low Body Mass Index (BMI), high Fasting Blood Sugar and low Triglycerides rather than the entire DM patients (24). Similarly, cost per one TB case detected was also high for CCRC inmates, with MYR 12,809.08. People Who Use Drugs (PWUD) is also known to be at higher risk for TB infection (25). Plus, living in a closed, packed and condensed environment such as in rehabilitation centre put them at much higher risk for TB infection (18, 19). A study done on TB screening at substance abuse treatment centres in Malaysia revealed that the PWUD is at much higher risk of Latent Tuberculosis Infection (LTBI), which can later progress into active disease (26). Nevertheless, MOH report showed only small percentage actually being diagnosed as TB (27).
The decision to focus TB screening on one strategy or to expand it to other strategies should depend on the ICER value. This study suggests that to implementation of TB screening among PL HIV will incur additional cost per screening even though the benefit outweigh the reference strategy, i.e. TB screening among the prisoners. Hence, it would cost additional MYR 735.82 to switch the strategy from prisoners to PL HIV with an additional one TB case being diagnosed. Considering the number of screening will affect the number of TB case detected, the availability of those specific high-risk group will affect how much it will cost for each TB screening strategy.
This study main strength is the comprehensiveness of analysis method with the inclusion of various high-risk groups. Hence, this study provides better understanding for TB screening among the high-risk groups in term of its’ cost-effectiveness. While providing better overview of each high-risk groups cost-effectiveness, this study will be useful for policy makers in strategizing future TB elimination programme. Besides that, this study also received input from MOH and programme owner, who directly involved in managing TB screening programme.
Notwithstanding the above, this study may provide significant input to the policy makers. Screening among high risk groups has been recognized as the cornerstone for TB elimination (28). However, different strategies are required due to the variability in term of resource availability and disease transmission in local setting (29). In re-strategizing national TB programme, prioritisation is necessary to make sure the current available resources are being allocated in the best possible manner. In a limited budget availability, focusing TB screening among the highly cost-effective strategies seems to be the way forward for the policymakers. For example, in Japan and US, older people are given priority for TB screening (30). Hence, in Malaysia, TB screening among PL HIV, elderly and prisoners should be the focus for TB screening programme as suggested by this study. In addition, this study is also useful for budgetary planning. By setting target for TB case detection, the cost for each TB case detection can be used to estimate the required budget for TB programme implementation.
Nevertheless, there are several limitations to this study. The measure of effectiveness used in this study was generic, i.e. cost per TB case detected. Most of the cost effectiveness studies among TB high risk group expressed the effectiveness measure using Quality Adjusted Life Years (QALY), Disability Adjusted Life Years (DALY) averted or death averted, but there are some which expressed the measure of effectiveness in term of TB cases detected (2). The lack of standardisation for outcome measurement makes it difficult to compare the findings with other studies. Besides, the benefit of current study might be overestimated or underestimated due to this outcome measures. For example, the overestimation of benefit in screening among the elderly versus younger age group due to the effect of time horizon analysis, as well as the screening for cases in confined space versus non-confined space. Data used in this study also confined to Sabah and Sarawak state. Thus, probabilities for certain high-risk groups might not represents the exact probabilities for the country. This was particularly noticeable especially on probabilities for old folks’ home residents, clients of Methadone Clinic, and Rheumatoid Arthritis patients. By using secondary data, the current study also limits further detail analysis.