Tuberculosis Treatment Outcomes: A Fifteen Year Retrospective Study in Jos North and Mangu, Plateau State, North – Central Nigeria

doi:10.21203/rs.2.11227/v4

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Research article

Tuberculosis Treatment Outcomes: A Fifteen Year Retrospective Study in Jos North and Mangu, Plateau State, North – Central Nigeria

https://doi.org/10.21203/rs.2.11227/v4

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published 11 Aug, 2020

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Background: Globally, tuberculosis (TB) is the leading cause of death from a single infectious agent. Adherence to TB therapy is an important factor in treatment outcomes, which is a critical indicator for evaluating TB treatment programs. This study assessed TB treatment outcomes using a fifteen-year record of tuberculosis patients who received treatment in Jos North and Mangu Local Government Areas of Plateau State, North-Central Nigeria.

Methods: The retrospective facility based study was done in five TB treatment centers which account for more than half of data for tuberculosis patients in Plateau State. Data were collected from 10156 TB patient’s health records between 2001 and 2015. Treatment outcomes were categorized as successful (cured, treatment completed) or unsuccessful (non-adherent, treatment failure or death). A descriptive analysis was done to assess the factors associated with treatment outcomes. Relevant bivariable and multivariable logistic regression were done. All statistical analyses were performed on Stata version 11, College station, Texas, USA.

Results: During the study period, 58.1% (5904/10156) of the TB patients who received treatment were males. The Mean age ±SD was 35.5 ±15.5 years. The overall treatment success rate was 67.4%; non-adherence/defaulting rate was 18.5%, with majority of patients defaulting at the end of intensive phase of treatment. The sputum conversion rate was 72.8% and mortality rate was 7.5%. A decrease in successful treatment outcomes rate from 83.8% in 2001 to 64.4% in 2015 was observed. After adjusting for sex, and TB category, being HIV positive was 2.8 times (95% CI: 1.11-6.83, p=0.028) more likely to be associated with treatment success than having an unknown status. Treatment after loss to follow-up, relapse and treatment failure were less likely associated with treatment success than newly diagnosed TB patients.

Conclusion: With the decrease in treatment success rates, underlying reasons for medication non-adherence and treatment failure should be resolved through adherence counseling involving the patient and treatment supporters, with education on voluntary counseling and testing for HIV among TB patients.

Health Economics & Outcomes Research

Health Policy

Infectious Diseases

Tuberculosis

Treatment Outcomes

Retrospective Study

Plateau State

Nigeria

Tuberculosis (TB) is a bacterial infection caused by Mycobacterium tuberculosis. It is a major global public health concern being the tenth leading cause of death worldwide, and the leading cause of death from a single infectious agent since 2011, ahead of the Human Immunodeficiency Virus (HIV) disease [1]. Globally, 10 million people (0.13%) were estimated to have fallen ill with TB in 2017; equivalent to 132 cases per 100,000 population, with 9% of the 10 million people being HIV- positive. Death toll globally from TB disease was 1.3 million, with an additional 300,000 deaths from TB among HIV positive patients in 2017. In Nigeria, TB mortality, including HIV associated TB death was 155,000 in 2017; the second highest reported mortality globally, after India [2]. The global treatment success rate was 82% among all new TB cases [1]. TB treatment saved 53 million lives globally (including HIV positive TB patients) and 11 million lives were saved in Africa. Nigeria recorded a treatment success of 86% in 2017. However, Nigeria was 6^th among the high TB burden countries after India, China, Indonesia, Philippines and Pakistan [1]. There are 30 high TB burden countries (HBCs) which collectively have about 87 % of the world’s TB cases. Nigeria is among the 14 countries with overlap of high burden of TB, TB/HIV and multidrug resistant-TB (MDR-TB). HBC is defined as around 100 or more cases per 100,000 population [3]. The total TB incidence rate in Nigeria was 219/100,000 population (population of 191 million people), out of which of 14% were HIV positive [1].

Mycobacterium tuberculosis is an intracellular microorganism that replicates very slowly, therefore prolonged multi-drug treatment regimen (6 months) is the recommended treatment strategy implemented through the Directly Observed Therapy (DOT) [4]. Because of this treatment regimen, medication non-adherence remains a potential challenge. Prevention of new TB infections and their progression to (TB) disease is crucial in reducing the burden of disease and death caused by TB, and in achieving the End TB Strategy targets set for 2030 and 2035, which is linked with the target of the Sustainable Development Goal-SDG; to reduce the number of TB deaths by 90 % by 2030, cut new cases by 80 % between 2015 and 2030, and to ensure no family is burdened with catastrophic cost due to TB [5]. Current health interventions for TB prevention include: treatment of latent TB infection (LTBI), with particular attention to children aged less than 5 years and HIV positive TB patients, prevention of transmission of M. TB through infection control especially among health workers; and vaccination of children with the Bacille Calmette-Guérin (BCG) vaccine [1].

Efforts have been made to identify factors influencing medication adherence [6-12], from which interventions [12-16] have been developed to improve adherence. This is because adherence has been shown to have profound effect on other treatment outcomes [17]. Indeed, non-adherence and mortality have been shown to account for 64% and 32% poor/unsucuccessful treatment outcomes respectively [18]. A study observed that most intervention studies targetted only adherence, but improving adherence would be more valuable if it improved clinical/treatment outcomes of the patient [19]. This study therefore focused on understanding the factors associated with treatment outcomes for TB patients, since treatment outcomes are major indicators for evaluating TB treatment programs.

In Nigeria, studies have reported trends in tuberculosis treatment outcomes for the country [1], and for different states within the country [20, 21]. However assessment of treatment outcomes in individual DOT TB facilities is lacking [22]. This will enable facility-specific interventions to be implemented. Therefore we sought to assess the factors associated with TB treatment outcomes in five DOT facilities in Jos-North and Mangu Local government Areas of Plateau state, North-Central Nigeria through a fifteen year retrospective study.

Study Design and Setting

A retrospective facility-based study of TB patient’s records from January 2001 to December 2015 was done in five DOT TB treatment facilities in Jos-North and Mangu Local Government Areas of Plateau State, North-Central Nigeria, in order to assess tuberculosis treatment outcomes. Plateau State has a land mass area of 26,899 square kilometers with a population of 3,206,531 people [23]. The TB facilities were preselected because they account for more than 50% of all TB cases in Plateau State, and had the needed health records of TB patients since the onset of the DOT programme in 2001. Demographic and patient data collected by the health workers at the facilities are usually entered into the patient’s treatment cards and the facility’s register.

The study centers were: Faith Alive Foundation Hospital (FAF), Our Lady of Apostles (OLA), COCIN Hospital and Rehabilitation Centre (CHRC) Mangu, and Bingham University Teaching Hospital (BUTH), which are faith based hospitals. Plateau State Specialist Hospital (PSSH) is a tertiary health care institution owned by Plateau State Government. CHRC, FAF and OLA are secondary health care institutions, while BUTH is a tertiary health care institution.

Ethics

Ethical approval was sought and obtained form the various hospital’s Institutional review boards/ Ethical Committes. Permission to extract relevant data was obtained from the relevant institutional heads. All information obtained were treated confidentially and only de-identified patient data were collected and used for analyses.

Data Collection

Data were collected from 10156 TB facility registers and treatment cards of patients who accessed TB treatment from DOT treatment centers from 2001 to 2015 by the researcher and trained research assistants. Data were collected manually, using a pre-designed form before tranferring to the study database. Data collected included TB patient’s demographic (sex, age, address, year of enrollment) and clinical characteristics (diagnosis, TB category, retreatment, sputum Acid Fast Bacilli-AFB analysis, period of defaulting), as well as their treatment outcomes. Socioeconomic data were not recorded at the facilities during the study period. Incomplete data especially those without recorded treatment outcomes were excluded from the study.

Data Analysis

Data checking and coding was done in Microsoft Excel before exporting to STATA® version 11.0 (College Station Texas, USA) for analysis. Demographic and clinical characteristics of the TB patients were presented in proportions. Categorical variable proportions were compared using Chi-square test and where appropriate, Fisher’s exact test was used. Bivariate analysis was used to determine patient and clinical characteristics factors associated with treatment outcomes. For the multivariate analysis, factors with p values ≤0.2 were included in the model, taking into account all the potential confounders. Missing values, which were determined to be missing at random were managed using complete case analysis.

Definition of Terms

Treatment outcomes of TB patients in this study were classified as successful (cured or treatment completed) or unsuccessful (defaulted, treatment failure or died), as defined from the World Health Organization (WHO) and National TB and Leprosy Control Program (NTBLCP) guidelines [1, 4, 24-25].

Cured refers to a pulmonary TB patient who was smear or culture positive at the beginning of treatment and is smear or culture negative upon completion of treatment [4].

Completed Treatment is a TB patient who completed treatment but without evidence (no laboratory test) at the end of treatment [24].

Successful treatment outcome: Cured and completed treatment together make up successful treatment outcomes which should increase towards 100% and reach at least 85% with good case management [4].

Unsuccessful Treatment outcome includes: defaulted/lost to follow-up, treatment failure or died.

Treatment Failure is a PTB patient who was smear or culture positive at beginning of treatment and remains positive at month 5 or later during their most recent course of treatment [4].

Lost to follow-up is a TB patient who did not start treatment or whose treatment was interrupted for two consecutive months or more [4].

Defaulted is defined by the WHO as missing more than 20% of the prescribed doses during the treatment period i.e. a treatment interruption of two consecutive months or more after at least one month on treatment [25]. The definition of defaulters however can vary within national programs, for example, the Federal Ministry of Health in Nigeria, defined defaulting as not taking anti-TB medications consecutively for more than two days intensive phase and more than two consecutive weeks continuation phase [24].

Retreatment is a sputum AFB positive TB patient who had a one or more month extension of intensive phase due to sputum inconversion [24].

Relapse is a patient who was cured or completed treatment, but returned sputum positive or with clinical symptoms of TB (either a true relapse or a new episode of TB caused by reinfection) [4].

Died refers to a TB patient who died for any reason during the course of treatment [24].

During the study period we utilized data from 10156 TB patients who received treatment from five treatment centers. The mean age ± SD was 35.5±15.5. The proportion of males was more (58%) than the females as seen in Table 1. Majority of the TB patients were in the productive age of 24-35 years of age (33.4%) and were HIV positive (38.4%). Patient enrollment increased from 22.0% to 39.6% over the 15-year period, with the enrollment of HIV positive TB patients also increasing from 2.3% to 57.7%. Mean time-outcome ± SD was 5.4 ± 3.0 (time in months).

Majority of the patients were new (93.3%) and had pulmonary TB (92.4 %). Most of the patients that returned after default, relapsed, developed multidrug resistance, or needed retreatment TB were HIV negative TB Patients. Non-adherence/defaulting rate was 18.5%, with majority of the patients, especially those with unknown HIV status defaulting at the end of intensive phase. The sputum conversion rate was 72.8% (Table 2). The patient enrollment in 2001 was 360 patients, which rose to a peak of 983 patients in 2013, but decreased to 721 in 2015 as shown in Figure 1.

Treatment outcomes from DOT Facilities showed treatment success rate highest in OLA hospital (86.2%) Non-adherence/defaulting rate was highest in Plateau State Specialist Hospital (26.4%). Mortality rate was highest (10.5%) in CHRC Mangu (Table 3).

TB patients with known HIV status had higher treatment success rates than those with unknown HIV status. Non-adherence/defaulting rate was highest (34.0%) among TB patients with unknown HIV status and mortality was highest (11.2%) among HIV positive TB patients (Table 4).

The trend of TB treatment outcomes in Figure 2 showed a steady increase in treatment success rates over the years, with a peak of 83.8% in 2011, but dropped to a low 64.4% in 2015. A consequent reverse trend was seen in unsuccessful treatment, with a peak in 2002 (59.9%) and 30.5% in 2015.

Compared to HIV positive TB patients, TB patients were 4.3 times more likely not to adhere if they did not know their HIV status (CI: 3.74-4.91, p<0.001). Males had 1.15 times more likelihood of medication non-adherence than females (CI: 1.036-1.272, p=0.008). TB patients with a history of non-adherence had a 2.3 higher likelihood to default again from taking their anti-TB medicines (CI: 1.34-3.87, p=0.002) as shown in Table 5.

A significant association between HIV status and treatment success rate was obtained after adjusting for sex and TB category. Being HIV positive was 2.8 times more likely to be associated with treatment success than having an unknown HIV status. TALF/RAD, relapse and treatment failure were less likely associated with treatment success than newly diagnosed TB patients presented in Table 6.

HIV negative TB patients were less likely to be associated with mortality than TB patients with unknown HIV status. Relapse and treatment failure were associated with higher odds of mortality than newly diagnosed TB patients. Extra pulmonary TB patients were 2.3 times more likely to be associated with mortality than pulmonary TB patients (Table 7).

This study was conceptualized to assess and understand the factors associated with treatment outcomes in TB patients who received treatment at selected treatment facilities in Plateau State, North-central Nigeria. An overall treatment success rate of 67.4% was found and this was less than the reported global success rate of 82.0% [1]. A drop in the overall treatment success rate from 83.8% in 2011 to 64.4% in 2015 was also observed. The factor significantly associated with successful treatment outcomes was being HIV positive, while having a history of non-adherence, treatment failure and relapse were less likely to be associated with treatment success. Factors associated with mortality were extrapulmonary TB, relapse and treatment failure. Being HIV negative was less likely associated with mortality. The association between positive HIV status and treatment success could be attributed to better medication adherence given that most HIV infected patients in the treatment facilities typically receive intensive adherence counseling for their antiretroviral medications including the need to be adherent to TB therapy.

Tuberculosis disease was more in males than females as similarly observed in other studies [26, 27]. The possible reasons given were; women experiencing barriers to service access, longer clinical delays in diagnosis or producing sputum of poor quality than men [28]. A community based intervention study however reported significantly more women diagnosed with TB at community level than in the health facilities because the interventions reduced barriers to services with poor women who had previously faced difficulties travelling to health centres particularly benefitting [28]. TB was found more in the productive age group (sexually active group), particularly among HIV positive TB patients as similarly observed in other studies and consistent with global epidemiological findings [20, 29-33]. Majority of the patients were from Jos North Local Government Area of Plateau State, where most of the data was collected. These centers were chosen because they had records of TB patients from the inception of the Directly Observed Treatment progam for TB in Plateau State in 2001. They also constitute about more than half of the population of TB patients in Plateau state.

CHRC Mangu, a rural DOT secondary facility had the lowest failure rate (0.2%) and defaulting rate (2.9%) but recorded the highest transfer-out (9.1%) and mortality rates (10.5%) than the urban DOT facilities. Training of health staff and treatment supporters should be encouraged so the community is more aware and educated on tuberculosis disease in order to increase case detection and decrease late reporting when the disease is advanced. Medication education and adherence counseling would further reduce treatment failure and defaulting rates. CHRC Mangu was receiving support from the Netherlands TB and Leprosy Relief. This drew a lot of patients from both Mangu and other Local Government Areas around the state because it was an active TB diagnostic and treatment centre. The Netherlands support was however withdrawn in 2016, now making Mangu more of a dignostic and less of a treatment centre. Therefore patients diagnosed with TB in Mangu were referred to DOT centers closest to their residence for treatment; the probable reason behind the high transfer-out rates.

Patient Enrollment and Treatment Outcomes

The number of TB patients that accessed treatment increased from 360 patients in 2001 to 983 in 2013, especially among HIV positive TB patients. This could likely be due to the increase in prevalence (from 2.2 % in 1991 to 25 % in 2010) of HIV disease among TB patients [33] and improved documention processes. DOT expansion resulting to an increase in DOT facilities may have also increased the case detection rate [29, 30]. The number of TB patients that accessed TB treatment in the DOT centres however dropped between 2014 and 2015, probably for lack of training and update on appropriate management of TB. The trend in treatment outcomes followed a similar pattern where the treatment success increased steadily from 2001 (52.2%) to a peak in 2011 (83.8%) but dropped to 64.4% in 2015. The Nigerian National TB and Leprosy control programme is presently training and re-training TB DOT officers to improve TB health care services.

The non-adherence/defaulting rate pattern observed an increase from 30.6% in 2001 to 54.2% in 2002, which was the highest defaulting rate observed over the years. This may be as a result of the strict compliance of DOT, where TB patients came everyday for 2-3 months (initial phase of treatment) with the DOT officers observing them take their medicines. This may have contributed to the high defaulting rate since patients could potentially get tired or experience some barrier to accessing the facilities for DOT. Some of these barriers include transportation cost, financial constraints and lack of social support system. Indeed, previous reports have offered recommendations to modify the DOT system of accessing TB treatment [34, 35]. This probably led to the susequent decrease in defaulting rate as contact tracing, community DOT and decrease in number of visits to the DOT center from daily to weekly is currently being practiced.

Factors Associated with Treatment Outcomes

Non-adherence was significantly associated with HIV status as similarly observed in other studies [36, 37]. Patients on both anti-retroviral and anti-TB medicines were more likely to adhere because they received more adherence counseling than those taking only anti-TB medicines [36]. Socioeconomic characteristics, individual behaviour and health care worker were other factors reported to be associated with non-adherence across developing countries [37]. However, socioeconomic factors were not determined in this study due to unavailability of the records. TB patients with a history of defaulting/non-adherence had a 2.3 times higher likelihood to default again from taking their anti-TB medicines and less likely to have successful treatment outcomes, consistent with findings from this study and other studies [29, 32]. A strengthening of adherence counseling is encouraged so that factors responsible can be identified and resolved. This is important because non-adherence and regular treatment interruptions can lead to development of resistant TB, treatment failure, relapse, longer infections or even death [29] - a finding similarly reported by WHO that Nigeria is among the 14 countries with overlap high burden of TB, TB/HIV and multidrug resistant-TB [1]. A study of the pattern of treatment outcomes over the years done in this study can also be carried out to identify specific areas in TB management that require intervention in order to improve outcomes and health services.

Being HIV positive was 2.8 times more likely to be associated with TB treatment success. A possible explanation for this finding is that HIV infected patients who have TB co-infection were likely to have received more/reinforced adherence counseling from trained adherence counselors prior to commencement of therapy, including adherence to TB therapy. As with HIV treatment, TB therapy also requires high (> 90 %) adherence to facilitate cure [38]. Thus, they may be more aware of the consequences of non-adherence in TB/HIV co-infection. This was however not consistent with findings from Central Ethiopia, Abuja-Nigeria and Abakaliki-Nigeria respectively [29, 33, 39], where HIV positive TB patients were significantly associated with poor TB treatment outcomes due to malabsorption of anti-TB medicines, high pill burden and poor knowledge about the diseases.

HIV negative TB patients were associated with lower odds of mortality than HIV positive TB patients, similar to studies reported in other states in Nigeria [33, 39], and other countries [40-42]. Possible reasons given were: TB treatment failure or complication of HIV disease [33], late diagnosis of HIV in TB patients [39], unavailability/inaccessibility of anti-retrovirals-ARVs [43], immunosuppression [44], lack of treatment supporters [45], and other co-morbidities such as cardiovascular diseases and diabetes mellitus [41-44] in HIV positive TB patients. If ARVs are procured, supplied and dispensed without disruption, it may go a long way to reduce the high mortality rate in Nigeria [2]. Mortality was significantly associated with extra-pulmonary TB compared to pulmonary TB patients. This was explained in previous studies that extra- pulmonary TB may be associated with immunosuppression more than pulmonary TB [46-48]. This study was limited by lack of variables such as education, occupation and income, to measure the socioeconomic status of TB patients that would have been included in the analysis.

In summary, findings from this research revealed an increase in the number of enrolments of TB and HIV positive TB patients in Plateau State. TB treatment outcomes from five DOT facilities were evaluated to show a decrease in tuberculosis treatment success rates from a fifteen- year retrospective study, with non-adherence, treatment failure and extra-pulmonary TB being factors associated with unsuccessful treatment outcomes. Appropriate interventions that would detect and resolve underlying reasons for non-adherence in TB patients, especially those with a history of defaulting by the treatment supporter and health system through medication education and adherence counseling, as well as increased education on voluntary counseling and testing of HIV among TB patients is advocated. Similar studies can be carried out in other DOT facilities to identify factors associated with treatment outcomes so that appropriate facility-specific intervention(s) can be designed and implemented.

Ethics approval and consent to participate

Ethical approval and permission to collect data was obtained form the institutional review board of Jos University Teaching Hospital’s Institutional Health Research Ethical Committee with reference number: JUTH/DCS/ADM/127/XIX/6058 before data collection. All information obtained were treated confidentially. De-identified patient data were used for analyses, so that anonymity of the patients was maintained throughout the study.

Consent for publication

Not Applicable.

Availability of data and materials

The datasets generated and analyzed during the current study are available from the corresonding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

The design of the study, collection and analysis of the data was funded by the Africa Centre of Excellence in Phytomedicine Research and Development (ACEPRD) with grant award number 126974 from the World Bank.

The analysis and interpretation of data, the manuscript writing and publication charge was funded by the Fogarty International Center of the National Institutes of Health under Award Number D43TW010130. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Authors’ Contributions

CS and PO conceptualized the research idea, CS designed the study, MD and JA supervised the research, JM analyzed most of the data and LI read and reviewed the manuscript. CS wrote the first draft of the manuscript and all co-authors read and approved the final version.

Acknowledgements

The support of Joshua Dung in data collection data is highly appreciated. The contribution of Dr. Adamu Onu in data analysis is acknowledged.

Authors’ information

¹Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical Sciences, University of Jos, Plateau State, Nigeria. ²Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, University of Jos, Plateau State, Nigeria. ³Department of Obstetrics and Gynaecology, Faculty of Medical Sciences, University of Jos, Plateau State, Nigeria. ⁴Department of Public Health, Ministry of Health, Plateau State, Nigeria. ⁵Department of Pharmacology, Faculty of Pharmaceutical Sciences, University of Jos, Plateau State, Nigeria.

TB: Tuberculosis; MDR-TB: Multidrug Resistant-Tuberculosis; AFB: Acid Fast Bacilli-AFB; NTBLCP; National Tuberculosis and Leprosy Control Program; WHO: World Health Organization; PTB: Pulmonary Tuberculosis; TALF: Treatment after lost to follow up, RAD: Return after Default; DOT: Directly Observed Therapy, OLA: Our Lady of Apostles Hospital; FAF: Faith Alive Foundation Hospital; CHRC: COCIN Hospital and Rehabilitation Centre Mangu; BUTH: Bingham University Teaching Hospital; PSSH: Plateau State Specialist Hospital.

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Table 1 Demographic Characteristics of TB Patients by HIV Status (n=10156)

Variable	HIV Negative (n=3733) Freq. (%)	HIV Positive (n=2968) Freq. (%)	Unknown HIV Status (n=3455) Freq. (%)	Total Freq. (%)
Sex
Male	2467(66.1)	1343(45.2)	2094(60.6)	5904(58.1)
Female	1266(33.9)	1625(54.8)	1361(39.4)	4252(41.9)
Age (Years)
0-14	159(4.5)	93(3.3)	297(14.5)	549(6.5)
15-24	503(14.2)	237(8.5)	261(12.7)	1001(11.9)
25-34	1135(31.9)	1069(38.4)	598(29.2)	2802(33.4)
35-44	686(19.3)	856(30.8)	431(21.0)	1973(23.5)
45-54	489(13.8)	364(13.1)	238(11.6)	1091(13.0)
>54	582(16.4)	163(5.9)	228(11.1)	972(11.6)
Not Recorded				1768(17.4)
Patient Residence
Jos North	1393(37.3)	1188(40.0)	1992(57.7)	4573(45.0)
Jos South	390(10.4)	446(15.0)	594(17.2)	1430(14.1)
Jos East	139(3.7)	127(4.3)	194(5.6)	460(4.5)
Other LGAs in Plateau	992(26.6)	531(17.9)	540(15.6)	2063(20.3)
Other States Outside Plateau	133(3.6)	138(4.6)	134(3.9)	405(4.0)
Not recorded				1229(12.1)
Year of Enrollment
2001-2005	0(0.0)	67(2.3)	2169(62.8)	2236(22.0)
2006-2010	1531(41.0)	1188(40.0)	1179(34.1)	3898(38.4)
2011-2015	2202(59.0)	1713(57.7)	107(3.1)	4022(39.6)

Freq.=Frequency, LGAs=Local Government Areas

Table 2 Clinical Characteristics of Tuberculosis Patients by HIV Status (n = 10156)

Variable	HIV Negative (n=3733) Freq. (%)	HIV Positive (n=2968) Freq. (%)	Unknown HIV Status (n=3455) Freq. (%)	Total Freq. (%)
TB Diagnosis
Pulmonary TB	3311(88.7)	2818(94.9)	3258(94.3)	9387(92.4)
TB Spine	227(6.1)	29(1.0)	92(2.7)	348(3.4)
TB Adenitis	39(1.0)	22(0.7)	19(0.5)	80(0.8)
TB Abdomen	135(3.6)	91(3.1)	61(1.8)	287(2.8)
Others*	21(0.6)	8(0.3)	25(0.7)	54(0.5)
TB Category
New	3405(91.2)	2778(93.6)	3290(95.2)	9473(93.3)
RAD/TALF	104(2.8)	59(2.0)	55(1.6)	218(2.1)
Relapse	161(4.3)	72(2.4)	49(1.4)	282(2.8)
MDR-TB	11(0.3)	7(0.2)	1(0.0)	19(0.2)
Transfer-In	52(1.4)	52(1.8)	60(1.7)	164(1.6)
Needing Retreatment
No	3290(88.1)	2704(91.1)	2979(86.2)	8973(88.3)
Yes	282(7.6)	136(4.6)	104(3.0)	522(5.1)
Indeterminate⁺	161(4.3)	128(4.3)	372(10.8)	661(6.5)
Sputum AFB on Diagnosis
Sputum Negative	2355(63.1)	2398(80.8)	2480(71.8)	7233(71.2)
Sputum AFB Positive	1378(36.9)	570(19.2)	975(28.2)	2923(28.8)
Sputum AFB After Intensive Phase
Sputum Negative	3510(94.0)	2806(94.5)	3044(88.1)	9360(92.2)
Sputum AFB Positive	39(1.0)	18(0.6)	12(0.3)	69(0.7)
Indeterminate⁺	184(4.9)	144(4.9)	398(11.5)	726(7.1)
Defaulting Period (n=1874)
During Intensive Phase	97(2.6)	65(2.2)	271(7.8)	433(4.3)
End of Intensive Phase	190(5.1)	191(6.4)	559(16.2)	940(9.3)
Continuation Phase	96(2.6)	62(2.1)	343(9.9)	501(4.9)
Binary Outcome
Unsuccessful	919(24.6)	781(26.3)	1599(46.3)	3299(32.5)
Successful	2814(75.4)	2187(73.7)	1855(53.7)	6856(67.5)

*=Disseminated TB, Miliary TB, Ovarian TB, Pleural TB, Skin TB, Heart TB;

⁺Indeterminate due to lost to follow-up or death during intensive phase of treatment

TALF=Treatment after lost to follow up, RAD = Return after Default

Table 3 Treatment Outcomes from DOT Facilities (n=10156)

Hosp.	Successful Treatment Freq. (%)	Defaulted Freq. (%)	Treatment Failure Freq. (%)	Died Freq. (%)	Discontinued Treatment Freq. (%)	Transfer-Out Freq. (%)	Total
OLA	1189 (86.2)	58 (4.2)	15 (1.1)	79 (5.7)	2 (0.2)	36 (2.6)	1379 (13.6)
FAF	1126 (85.6)	81 (6.2)	4 (0.3)	84 (6.4)	0 (0.0)	20 (1.5)	1315 (12.9)
CHRC	1467 (77.3)	55 (2.9)	4 (0.2)	199 (10.5)	1 (0.1)	172 (9.1)	1898 (18.7)
PSSH	1872 (58.2)	848 (26.4)	17 (0.5)	236 (7.3)	11 (0.3)	233 (7.2)	3217 (31.7)
BUTH	1190 (50.7)	846 (36.1)	11 (0.5)	161 (6.9)	4 (0.2)	135 (5.8)	2347 (23.1)
Total	6844 (67.4)	1888 (18.6)	51 (0.5)	759 (7.5)	18 (0.2)	596 (5.9)	10156 (100.0)

Hosp.=Hospital; Freq.=Frequency; OLA=Our Lady of Apostles Hospital; FAF= Faith Alive Foundation Hospital; CHRC= COCIN Hospital and Rehabilitation Centre Mangu; BUTH=Bingham University Teaching Hospital; PSSH= Plateau State Specialist Hospital

Table 4 Distribution of Tuberculosis Treatment Outcomes by HIV Status

Treatment Outcome	HIV Negative Freq. (%)	HIV Positive Freq. (%)	Unknown HIV Status Freq. (%)	Total Freq. (%)
Transfer-Out	227(6.1)	117(3.9)	251(7.3)	595(5.9)
Cured	1037(27.8)	488(16.4)	514(14.9)	2039(20.1)
Treatment Completed	1777(47.6)	1699(57.2)	1341(38.8)	4817(47.4)
Treatment Success	2814(75.4)	2,187(73.7)	1855(53.7)	6856(67.5)
Defaulted	383(10.3)	318(10.7)	1173(34.0)	1874(18.5)
Treatment Failure	33(0.9)	11(0.4)	9(0.3)	53(0.5)
Died	266(7.1)	331(11.2)	163(4.7)	760(7.5)
Discontinued Trt.	10(0.3)	4(0.1)	4(0.1)	18(0.2)
Total	3733(36.8)	2968(29.2)	3455(34.0)	10156(100.0)

Trt=Treatment, Freq.=Frequency

Table 5 Factors Associated with Tuberculosis Medication Non-adherence

Variable	OR	95 % Confidence Interval Upper Lower		p
Sex
Male	1.150	1.036	1.272	0.008*
Female
HIV Status
Negative	0.950	0.810	1.110	0.546
Unknown	4.290	3.740	4.910	0.001*
Positive
TB Category
New	1.380	0.890	2.160	0.147
TALF/RAD	2.270	1.340	3.870	0.002*
Relapse	0.950	0.550	1.670	0.871
MDR-TB	2.830	0.980	8.190	0.055
Others

TALF/RAD=Treatment After Lost to Follow-up/Return After Default; MDR-TB=Multi-Drug Resistant TB; OR= Odds ratio; *Statistically significant at p<0.05; Others=Transfer-In

Table 6 Factors Associated with Treatment Success (n=10,156)

Variable	OR	95 % CI. Upper Lower		p
Sex
Female	1.060	0.961	1.170	0.243
Male
HIV Status
HIV negative	2.003	0.811	4.946	0.132
HIV Positive	2.758	1.114	6.826	0.028*
Unknown status
TB Category
TALF/RAD	0.351	0.142	0.869	0.024*
Relapse	0.757	0.589	0.972	0.029*
Treatment Failure	0.627	0.475	0.827	0.001*
New

TALF/RAD=Treatment After Lost to Follow-up/Return After Default

CI.=Confidence Interval; OR=Odds Ratio

Table 7 Factors Associated with Mortality

Variable	OR	95 % Confidence Interval Upper Lower		p
Sex
Female	0.879	0.752	1.027	0.104
Male
HIV Status
HIV negative	0.434	0.371	0.508	0.001*
HIV Positive	0.312	0.089	1.092	0.068
Unknown status
TB Category
RAD	1.535	0.478	4.930	0.472
Relapse	5.131	1.459	18.045	0.011*
Treatment Failure	4.191	1.323	13.273	0.015*
New
TB Diagnosis
EPTB	2.346	1.848	2.978	0.001*
PTB
Needing Retreatment
No	1.022	0.687	1.522	0.913
Yes	0.239	0.192	0.297	0.001*
Indeterminate¹

¹= Indeterminate due to lost to follow up or death during intensive phase;

*=Significant at p<0.05; OR=Odds Ratio

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Tuberculosis Treatment Outcomes: A Fifteen Year Retrospective Study in Jos North and Mangu, Plateau State, North – Central Nigeria

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