ABSTRACT.
Drug-resistant tuberculosis (DR-TB) continues to be a serious public health problem. The objective of this study was to evaluate the sociodemographic, radiological, clinical, and outcome characteristics and assess the determinants of unfavorable outcomes in DR-TB. The descriptive-analytical study was carried out in a reference outpatient clinic in Rio de Janeiro, Brazil, among DR-TB cases that received treatment between February 2016 and October 2020, using descriptive statistics, χ2 test, and logistic regression multivariate. Of the 148 cases, 12.2% were resistant to rifampicin, 12.2% were resistant to isoniazid, 18.2% were polyresistant, 56.1% multidrug resistant, and 1.3% were extensively drug resistant. Most of the patients were men, aged up to 44 years, with brown or black skin, having up to 8 years of schooling, unemployed or working in the informal economy, and of low income. Presenting with acquired resistance or positive sputum smear microscopy in the diagnosis, taking more than four drugs, and being unemployed were associated with unfavorable outcomes. Having no income or acquired resistance doubled the chances of unfavorable outcomes. There was a high proportion of unfavorable outcomes, thereby highlighting the need to concentrate efforts on planning and executing public policies that include the severity of DR-TB and its risk factors.
INTRODUCTION
Tuberculosis (TB) continues to be a serious public health problem, ranking among the most neglected diseases. The WHO reported that nearly 9.9 million people contracted TB in 2020.1 In 2019, among the cases of drug-resistant TB (DR-TB), it was estimated that there were ∼ 1.06 million patients with TB mono-resistant to isoniazid (IR) and 465,000 patients resistant to rifampicin (RR), of whom 78% presented multidrug-resistant TB (MDR-TB) and 9% extensively drug-resistant TB (XDR-TB). Among patients with MDR-TB and XDR-TB, the treatments’ favorable outcomes were 57% and 35%, respectively. Reports show a lower proportion of unfavorable outcomes among RR and IR patients.1,2
According to data from the epidemiological survey in Brazil from 2015 to 2020, of the 7,749 cases of DR-TB, 69.5% were RR/MDR, 22.4% IR, 7.0% polyresistant (PolyR), and 1.2% XDR. In 2018, 198 new cases of DR-TB occurred in the State of Rio de Janeiro alone.3 Rio de Janeiro has the second largest coefficient of incidence in Brazil (60 cases/100,000 inhabitants), the third largest coefficient of mortality (3.8 deaths/100,000 inhabitants), a considerable increase in primary MDR-TB, and few favorable outcomes for MDR-TB and XDR-TB—58.2% and 18.6%, respectively.3,4
Primary data on the outcome of DR-TB treatment are scarce, and thus the present study, conducted in an outpatient reference center for TB in Rio de Janeiro, evaluated the sociodemographic, radiological, clinical, and outcome characteristics in addition to the factors associated with unfavorable outcomes.
MATERIALS AND METHODS
Study model and scenario.
This is a descriptive-analytical, documental, retrospective study conducted at an outpatient reference center for DR-TB of the Federal University of Rio de Janeiro (UFRJ), financed by the Brazilian Unified Health System. In Brazil, treatment of DR-TB is free, conducted in reference centers, and linked to the Special Tuberculosis Treatment Information System (SITE TB).5,6
What stands out in this reference outpatient clinic is that drug susceptibility testing (DST) is performed for the first-line drugs using the BD BACTEC™ MGIT™ 960 SIRE kit and the RR by the Xpert® MTB/RIF, both of which have received due registration from the Brazilian Health Regulatory Agency. The detection of resistance to second-line drugs is conducted at the Professor Hélio Fraga Reference Center Laboratory using the MGIT 960 technique.
Eligible population and study period.
Of 242 cases that were notified between February 2016 and October 2020, we included 148 through a convenience sample. Inclusion criteria were as follows: patients who had begun treatment of DR-TB and had at least two doctor’s appointments (with an interval of 15 days or more), according to SITE TB data. Exclusion criteria were transferred patients or those who had begun treatment of DR-TB in other health institutions, patients with an outcome of “diagnostic change,” and those with no registration in the SITE TB.
Data collection.
The following forms were used for data collection: medical records; the Notifiable Disease Information System, which seeks to collect and process data on disease notification in Brazil, including TB; SITE TB, used for compulsory notification and special TB treatment follow-up; and the Mortality Information System. There is no interoperability among information systems; a linkage manual was used.5
Definition of terms.
Types of DR-TB, with the treatment regimens and average duration, followed the preferential scheme recommended by the Ministry of Health of Brazil7:
RR-TB: only resistant to rifampicin (RMP) with DST. The recommended treatment lasted for 12 months, with 2 months of intensive treatment on capreomycin (Cm) 5 days a week plus isoniazid (H), levofloxacin (Lfx), ethambutol (E), and pyrazinamide (Z); the 10-month maintenance phase included treatment with H, Lfx, E, and Z.
IR-TB: only resistant to isoniazid (INH). The recommended treatment was a 2-month intensive phase using R, Lfx, Z, and E and a 7-month maintenance phase with R, Lfx, and E.
PolyR-TB is resistant to two or more drugs, except for the association of RMP and INH. In this case, the definition of the treatment regimen depended on the resistance pattern, the clinical evolution, and the treatment history. In Brazil, there are currently five recommended treatments, with an average duration of 9 to 12 months.
MDR-TB is resistant to at least RMP and INH. The most frequently recommended treatment includes an 8-month intensive phase with Cm (three times a week), Lfx, terizidone (Trd), E, and Z, in addition to a 10-month maintenance with Lfx, Trd, and E.
XDR-TB is resistant to RMP and INH plus to a fluoroquinolone and a second-line injectable drug. The proposed regimen for XDR-TB is 8 months of amikacin (3 days a week), moxifloxacin (Mfx), linezolid (Lzd), clofazimine (Clz), PAS (paraminosalicylic acid), and H and 10 months of Mfx, Lzd, Clz, PAS, and H.
Types of resistance to drugs7:
Primary resistance: a new case of TB without prior treatment.
Acquired resistance: patients with prior treatment of TB.
Types of adverse events7:
“Lesser” adverse events: in these cases, it is often unnecessary to suspend anti-TB drugs (e.g., diarrhea, nausea, or fever).
“Greater” adverse events: events that often cause the suspension of treatment (e.g., hepatotoxicity or psychosis).
Types of treatment outcome7,8:
Favorable outcome: cure (minimum of three consecutive negative cultures after month 12 of treatment) or complete treatment (patient who finished the treatment with a favorable clinical and radiological evaluation, without follow-up cultures).
Unfavorable outcome: failure (absence of bacteriological conversion and clinical improvement after 8 months of treatment, using second-line drugs; or bacteriological reversion (two positive cultures) and a clinical worsening after the favorable evolution), loss of follow-up (discontinued treatment of 30 days or more), or death.
The present study chose to conduct the data analysis by dividing the cases into two groups: Group 1—cases with a favorable outcome; Group 2—cases with unfavorable outcomes.
Directly observed treatment (DOT)7:
DOT includes observation by health professionals or other trained professionals of the patient ingesting the prescribed medications, ideally on all working days. If patients were observed taking medication a minimum of three times per week throughout treatment, this was also considered DOT.
Statistical analysis.
This study used descriptive statistics to calculate the absolute and relative frequency. Pearson’s χ2 test was used to analyze the association between categorical data. Multivariate logistic regressions were used to estimate the associated factors and unfavorable treatment outcomes. The results were expressed as odds ratios (OR) with a 95% confidence interval (CI). A P value ≤ 0.05 was considered statistically significant. The data analysis was conducted using Excel, Microsoft Office, Python, and R.
Ethical considerations.
Data collection began after approval by the Research Ethics Committee of the Clementino Fraga Filho University Hospital at UFRJ. It was evaluated and authorized using report number 3.716.709, which waived the use of the Free and Informed Consent Form because the study was based on secondary data and involved minimal risk.
RESULTS
Descriptive analysis.
The difference between the number of cases and patients resulted from administering more than one treatment to the same patient. From 2016 to 2020, 242 cases of 211 patients received DR-TB diagnosis in the TB reference outpatient clinic of UFRJ. In this study, 148 cases were included. Group 1 comprised 84 (56.8%) cases with favorable outcomes, and group 2 comprised 64 (43.2%) cases with unfavorable outcomes (Figure 1).
Figure 1.
Study population flowchart. 1Drug-resistant tuberculosis. 2Special Tuberculosis Treatment Information System.
Table 1 describes the characteristics of cases of DR-TB according to treatment outcome. Of the total cases, 86 (58.1%) were men, 100 (67.6%) were 44 years of age or younger, 97 (65.5%) were Brown or Black, 85 (57.4%) reported having completed up to 8 years of schooling, and 86 (58.1%) had no partner. Twenty-three (15.5%) were beneficiaries of governmental income transfer. When comparing the groups, in the patients with an unfavorable treatment outcome, there was a greater proportion of unemployed individuals and, consequently, a lower income.
Table 1.
Characteristics of cases of DR-TB, according to treatment outcome
| Characteristics | Favorable outcome N = 84 (%) | Unfavorable outcome N = 64 (%) | Total N = 148 (%) | P value* |
|---|---|---|---|---|
| Sex | 0.57 | |||
| Male | 51 (60.7) | 35 (54.7) | 86 (58.1) | |
| Female | 33 (39.3) | 29 (45.3) | 62 (41.9) | |
| Age range | 0.552 | |||
| 0–24 | 18 (21.4) | 12 (18.8) | 30 (20.3) | |
| 25–44 | 38 (45.2) | 32 (50) | 70 (47.3) | |
| 45–64 | 23 (27.4) | 19 (29.7) | 42 (28.4) | |
| ≥ 65 | 5 (6) | 1 (1.6) | 6 (4.1) | |
| Self-reported skin color | 0.372 | |||
| White | 32 (38.1) | 19 (29.7) | 51 (34.5) | |
| Brown or Black | 52 (61.9) | 45 (70.3) | 97 (65.5) | |
| Years of schooling | 0.931 | |||
| ≤ 8 | 48 (57.1) | 37 (57.8) | 85 (57.4) | |
| > 8 | 36 (42.9) | 27 (42.2) | 63 (42.6) | |
| Civil status | 0.426 | |||
| With partner | 19 (22.6) | 12 (18.8) | 31 (20.9) | |
| No partner | 45 (53.6) | 41 (64.1) | 86 (58.1) | |
| Unknown | 20 (23.8) | 11 (17.2) | 31 (20.9) | |
| Do you currently work? | <0.001 | |||
| Yes, formal work | 21 (25) | 8 (12.5) | 29 (19.6) | |
| Yes, informal work | 22 (26.2) | 13 (20.3) | 35 (23.6) | |
| Retired | 7 (8.3) | 2 (3.1) | 9 (6.1) | |
| School/university | 9 (10.7) | 2 (3.1) | 11 (7.4) | |
| Unemployed | 15 (17.9) | 36 (56.3) | 51 (34.5) | |
| Unknown | 10 (11.9) | 3 (4.7) | 13 (8.8) | |
| Income | 0.221 | |||
| No | 27 (32.1) | 28 (43.8) | 55 (37.2) | |
| < 1 MS | 13 (15.5) | 14 (21.9) | 27 (18.2) | |
| 1–2 MS | 31 (36.9) | 16 (25) | 47 (31.8) | |
| 2–4 MS | 2 (2.4) | 0 (0) | 2 (1.4) | |
| Unknown | 11 (13.1) | 6 (9.4) | 17 (11.5) | |
| Beneficiary of a government income transfer program? | 0.225 | |||
| Yes | 13 (15.5) | 10 (15.6) | 23 (15.5) | |
| No | 67 (79.8) | 46 (71.9) | 113 (76.4) | |
| Unknown | 4 (4.8) | 8 (12.5) | 12 (8.1) | |
| Unilateral or bilateral TB? | 0.815 | |||
| Unilateral | 41 (48.8) | 34 (53.1) | 75 (50.7) | |
| Bilateral | 41 (48.8) | 28 (43.8) | 69 (46.6) | |
| Normal | 2 (2.4) | 2 (3.1) | 4 (2.7) | |
| Cavitary TB? | 0.961 | |||
| Yes | 52 (61.9) | 39 (60.9) | 91 (61.5) | |
| No | 30 (35.7) | 23 (35.9) | 53 (35.8) | |
| Normal | 2 (2.4) | 2 (3.1) | 4 (2.7) | |
| Sputum smear microscopy in diagnosis | 0.02 | |||
| Negative | 27 (32.1) | 9 (14.1) | 36 (24.3) | |
| Positive | 57 (67.9) | 55 (86) | 112 (75.8) | |
| Drug resistance type | 0.007 | |||
| Primary | 54 (64.3) | 26 (40.6) | 80 (54.1) | |
| Acquired | 30 (35.7) | 38 (59.4) | 68 (45.9) | |
| Initial symptoms | ||||
| Fever | 42 (50) | 35 (54.7) | 77 (52) | 0.69 |
| Cough | 71 (84.5) | 57 (89.1) | 128 (86.5) | 0.577 |
| Expectoration | 58 (69) | 42 (65.6) | 100 (67.6) | 0.792 |
| Hemoptoic or hemoptysis | 17 (20.2) | 12 (18.8) | 29 (19.6) | 0.986 |
| Sweating | 34 (40.5) | 27 (42.2) | 61 (41.2) | 0.967 |
| Chest pain | 27 (32.1) | 21 (32.8) | 48 (32.4) | 0.927 |
| Weight loss | 54 (64.3) | 47 (73.4) | 101 (68.2) | 0.314 |
| Dyspnea | 42 (50) | 36 (56.3) | 78 (52.7) | 0.556 |
| Anorexia | 38 (45.2) | 36 (56.3) | 74 (50) | 0.245 |
| Comorbidities | 0.343 | |||
| Yes | 53 (63.1) | 46 (71.9) | 99 (66.9) | |
| No | 31 (36.9) | 18 (28.1) | 49 (33.1) | |
| Comorbidities/lifestyle habits | ||||
| HIV infection | 16 (19) | 9 (14.1) | 25 (16.9) | 0.561 |
| Mental health disorder | 4 (4.8) | 6 (9.4) | 10 (6.8) | 0.437 |
| Hypertension | 12 (14.3) | 4 (6.3) | 16 (10.8) | 0.196 |
| Diabetes | 5 (6) | 4 (6.3) | 9 (6.1) | 0.785 |
| Use of illicit drugs and/or alcohol | 26 (31) | 29 (45.3) | 55 (37.2) | 0.105 |
| Smoking | 24 (28.6) | 25 (39.1) | 49 (33.1) | 0.243 |
| Entry type (SITE TB) | <0.001 | |||
| Case new | 72 (85.7) | 42 (65.6) | 114 (76.3) | |
| Relapse or first therapeutic failure | 6 (7.1) | 3 (4.7) | 9 (6.1) | |
| Re-entry after loss to follow-up | 3 (3.6) | 18 (28.1) | 21 (14.2) | |
| Resistance or diagnostics change | 3 (3.6) | 1 (1.6) | 4 (2.7) | |
| Directly observed treatment? | 0.346 | |||
| Yes | 63 (75) | 53 (82.8) | 116 (78.4) | |
| No | 21 (25) | 11 (17.2) | 32 (21.6) | |
| Number of drugs | 0.042 | |||
| ≤ 4 drugs | 18 (21.4) | 5 (7.8) | 23 (15.5) | |
| > 4 drugs | 66 (78.6) | 59 (92.2) | 125 (84.5) | |
| Adverse drug events | ||||
| Nausea | 51 (60.7) | 36 (56.3) | 87 (58.8) | 0.705 |
| Vomiting | 35 (41.7) | 27 (42.2) | 62 (41.9) | 0.868 |
| Abdominal pain | 13 (15.5) | 3 (4.7) | 16 (10.8) | 0.068 |
| Joint pain | 46 (54.8) | 26 (40.6) | 72 (48.6) | 0.124 |
| Weakness and/or astenia | 5 (6) | 6 (9.4) | 11 (7.4) | 0.638 |
| Taste change | 13 (15.5) | 4 (6.3) | 17 (11.5) | 0.138 |
MS = minimum salary; SITE = Special Tuberculosis Treatment Information System; TB = tuberculosis.
Chi-square test.
Bilateral lesions and cavitary images were identified in 69 (46.6%) and 91 (61.5%) cases, respectively. In the majority of the patients, positive sputum smear microscopy, comorbidity, and primary drug resistance were observed in the diagnosis—112 (75.8%), 99 (66.9%), and 80 (54.1%), respectively. Comorbidities and lifestyle habits included the use of illicit drugs and alcohol, smoking, and HIV/AIDS infection—55 (37.2%), 49 (33.1%), and 25 (16.9%), respectively. Cough, weight loss, expectoration, dyspnea, and fever were the most common symptoms.
In the unfavorable outcome group, positive sputum smear microscopy (86% versus 67.9%) and acquired drug resistance (59.4% versus 35.7%) were significantly more common in the diagnosis.
The majority of the patients who participated in the DOT (78.4%) program were new cases (76.3%) and used more than four drugs (84.5%). The more frequent adverse events were nausea (58.8%), joint pain (48.6%), and vomiting (41.9%); all were considered “lesser” side effects.
Compared with group 1, the cases with unfavorable outcomes presented a significantly greater recurrence after a loss to follow-up (28.1% versus 3.6%) and used more than four drugs (92.2% versus 78.6%).
Of the total cases, 18 (12.2%) were RR, 18 (12.2%) IR, 27 (18.2%) PolyR, 83 (56.1%) MDR, and 2 (1.3%) XDR. Among the patients with unfavorable outcomes, there was 27% loss to follow-up. A greater proportion of patients who were lost to follow-up was observed among the cases of TB-RR, TB-MDR/XDR, and TB-IR—38.9%, 29.4%, and 27.8%, respectively. Death was most frequent among patients with TB-MDR/XDR and TB-RR, with 12.9% and 11.1%, respectively (Table 2).
Table 2.
Treatment outcomes, according to DR-TB type
| Characteristics | RR-TB N = 18 (%) | IR-TB N = 18 (%) | PolyR TB N = 27 (%) | MDR-TB and XDR-TB N = 85 (%) | Total N = 148 (%) |
|---|---|---|---|---|---|
| Treatment outcomes | |||||
| Favorable | 9 (50) | 11 (61.1) | 22 (81.5) | 42 (49.4) | 84 (56.8) |
| Unfavorable | 9 (50) | 7 (38.9) | 5 (18.5) | 43 (50.6) | 64 (43.2) |
| Types of outcome | |||||
| Complete treatment | 7 (38.9) | 5 (27.8) | 6 (22.2) | 23 (27.1) | 41 (27.7) |
| Cure | 2 (11.1) | 6 (33.3) | 16 (59.3) | 19 (22.4) | 43 (29.1) |
| Lost of follow-up | 7 (38.9) | 5 (27.8) | 3 (11.1) | 25 (29.4) | 40 (27.0) |
| Therapeutic failure or schema change | 0 (0) | 1 (5.6) | 1 (3.7) | 7 (8.3) | 9 (6.1) |
| Death by TB or other causes | 2 (11.1) | 1 (5.6) | 1 (3.7) | 11 (12.9) | 15 (10.1) |
IR = mono-resistant to isoniazid; MDR = multidrug resistant; PolyR = polyresistant; RR = resistant to rifampicin; TB = tuberculosis; XDR = extensively drug resistant.
Among patients with PolyR-TB, resistance to RMP, INH, streptomycin, and ethambutol was predominant; seven patients (25.9%) presented with RR and 20 patients (74.1%) with resistance to INH.
Factors associated with unfavorable treatment outcomes in patients with DR-TB.
Table 3 describes the multivariate analysis of factors associated with unfavorable outcomes. People with no income and acquired resistance had more than twice the chance of unfavorable outcomes. No statistically significant difference was observed in the diagnosis in the treatment outcome according to sex, HIV/AIDS, type of DR-TB, and sputum smear microscopy. Cases with positive sputum smear microscopy diagnosis had a 2-fold higher chance of an unfavorable outcome. Cases of MDR/XDR had a nearly 60% higher chance of unfavorable outcome.
Table 3.
Multivariate logistic regression of factors associated with unfavorable outcomes between cases of DR-TB
| Characteristics | OR (CI 95%) | P value |
|---|---|---|
| Sex | ||
| Male | 0.64 (0.3–1.32) | 0.227 |
| Female | 1.0 | |
| Income | ||
| Yes | 1.0 | |
| No | 2.58 (1.21–5.55) | 0.014 |
| Unknown | 0.51 (0.1–2.0) | 0.365 |
| HIV infection | ||
| Positive | 0.89 (0.32–2.4) | 0.824 |
| Negative | 1.0 | |
| Type of DR-TB | ||
| RR-TB, IR-TB, and PolyR | 1.0 | |
| MDR-TB and XDR-TB | 1.59 (0.76–3.37) | 0.217 |
| Drug resistance type | ||
| Primary | 1.0 | |
| Acquired | 2.14 (1.04–4.48) | 0.04 |
| Sputum smear microscopy in diagnosis | ||
| Positive | 2.02 (0.82–5.26) | 0.132 |
| Negative | 1.0 | |
IR = mono-resistant to isoniazid; MDR = multidrug resistant; OR = odds ratio; PolyR = polyresistant; RR = resistant to rifampicin; TB = tuberculosis; XDR = extensively drug resistant.
DISCUSSION
This study showed a predominance of DR-TB cases in Brown or Black men at an economically active age and with a low level of education. Between 2015 and 2020, of the new cases of DR-TB in Brazil, 69% occurred in males, 46% were aged between 30 and 49 years, and 66% occurred in Black individuals.3 In agreement with the results, of the cases notified from 2000 to 2016 in Rio de Janeiro State, 60.4% were Black, and 62.6% had less than 8 years of schooling and were aged up to 44 years.4 In a study conducted in China, 67.3% of the patients with MDR/XDR-TB were men, and 65.6% were aged up to 45 years.9
Our study showed that more than half of the cases of DR-TB had no form of income or received less than $247.60, and this was even greater in group 2. There was a statistically significant difference in the variable “currently working” between groups; among the cases with unfavorable outcomes, more than half were unemployed. Similar findings were found in a national study conducted in Brazil in which 60% of TB patients were unemployed or working in the informal economy.10
Such findings reinforce the close relationship between TB and poverty because low-income individuals are subject to social and health conditions that increase vulnerability, such as unsanitary housing, living in places with high population density, and inadequate working and living conditions. In addition, such situations often co-occur with low education; consequently, difficulty understanding the importance of DR-TB treatment11,12 and insufficient income to maintain basic life needs act as risk factors for unfavorable outcomes, especially for those patients who discontinue treatment.
Governmental income transfer programs are means of social protection that provide money to vulnerable families. Such programs have a positive influence on TB treatment outcomes.11 In Rio de Janeiro State, only 38% of the DR-TB patients reported being beneficiaries of the income transfer program.13 This number is even smaller in the present study, which included patients treated between 2016 and 2020, a period marked by the beginning of the extreme right government that reinforced the implementation of neoliberalism in Brazil from 2018.
Of the cases, 61.5% presented cavitary TB and 46.6% bilateral TB. In a national retrospective cohort, 65% had bilateral TB, and 79% had cavitary TB.14 In another study carried out in Rio de Janeiro State, 75.3% had bilateral TB and 80.9% cavitary.4
In this study, most DR-TB cases were smear-positive. When selecting only cases that evolved to unfavorable outcomes, this variable was statistically significantly associated with positive smear results. This finding is similar to that reported in Vietnam.15 In agreement with these results, a large cohort carried out in Brazil found that 84% of MDR/XDR-TB cases were smear-positive at the start of treatment.14
Compared with primary drug resistance, acquired drug resistance was associated with significantly more unfavorable outcomes. In a study conducted in Vietnam, the history of prior treatment of DR-TB was also associated with unfavorable outcomes.15
In this study, a high proportion of cases had primary resistance. Some factors may have contributed to the high detection of cases of primary drug resistance, highlighting the incorporation of Xpert MTB/RIF in the Brazilian Unified Health System in 2014 and its large-scale implementation in the scenario of this study, especially compared with other public health services. Another factor is the low performance of diagnosis and treatment of the latent TB infection cascade, infection control activities, and TB care in the Rio de Janeiro State, which can increase the transmission of primary DR-TB.16 Thus, improving referral systems and access to early diagnosis and treatment is important.12
In a study carried out in a reference center in São Paulo, Brazil, it was observed that 36% had primary drug resistance.17 In a European study, the authors reported that 52.4% of the DR-TB patients had not undergone prior TB treatment.18 One national study on MDR-TB, conducted with SITE TB data, and another carried out in a referral center for DR-TB in Sao Paulo State concluded that those who had not undergone prior treatments showed an increased chance of favorable outcomes.14,17
Most cases were diagnosed after the symptoms appeared—in particular, cough, weight loss, expectoration, dyspnea, and fever. In one study conducted with MDR-TB patients in Brazil, hemoptysis, dyspnea, fever, and cough predominated.19 Most cases had at least one comorbidity, most commonly, drug and alcohol use, smoking, and HIV/AIDS. In a national study conducted with data from SITE TB, 56.5% of the patients showed some type of comorbidity, including 13.1% with HIV/AIDS and 11.3% with diabetes.20
The majority of the cases underwent DOT. The high number of patients who were lost of follow-up despite high DOT program use can be explained by the different types and definitions of DOT strategies—that is, they were heterogeneous and, in many situations, implemented incorrectly.7,14
Most treatment regimens used four drugs, with this proportion higher in cases that evolved to unfavorable outcomes, with a statistically significant difference. This finding reinforces the need to develop new therapeutic schemes that use fewer drugs for a shorter period.
In our study, “lesser” adverse events predominated. However, one study conducted in Africa found that 25% of the patients with DR-TB had “greater” adverse events.21
Regarding the treatment outcome, less than 60% evolved to cure or complete treatment. The proportion of cases that evolved to an unfavorable outcome was highest among patients with MDR/XDR-TB and RR. Among the unfavorable outcomes, patients who were lost to follow-up predominated (27% of the total number of cases; 62.5% of the cases that evolved to unfavorable outcomes), which was considered high compared with the levels stipulated by the WHO (5%).1 Likewise, according to data from the Brazilian Ministry of Health, RR/MDR-TB patients who were lost of follow-up in 2018 represented 27%, therapeutic failure 6.3%, and death 10.1%.3 Of these cases, reported between 2000 and 2016 in Rio de Janeiro State (Brazil), 55.7% had favorable outcomes and 44.3% unfavorable outcomes; 19.1% were lost to follow-up, 15.3% died, and 9.9% had therapeutic failure.4 By contrast, a study from China with DR-TB patients found that 19.1% evolved to therapeutic failure, and 13.7% were patients who were lost to follow-up. Only the proportion of deaths was similar to the present study (9.4%).22
Among the risk factors associated with unfavorable outcomes, it is important to highlight that those with no income had a 2-fold greater chance of having unfavorable outcomes. This finding follows the study conducted in Ukraine, which found that unemployed individuals showed almost double the chance of unfavorable outcomes.23 Another risk factor was having acquired resistance, as seen in other studies.14,17 It is inferred that primary cases of DR-TB constitute a different method of transmission but are related less to vulnerable socioeconomic groups.16
Risk factors, including social issues (unemployment), clinical factors (diagnosis of smear-positive at diagnosis), treatment format (number of drugs used), and occurrence of retreatment (acquired resistance), have been highlighted in other studies.16,23 Solutions for these concerns include the implementation of a risk stratification protocol, with more individualized conducts that corresponds to the individualization of health care, with adaptation to the particularities of each individual; expansion of income transfer programs for socially vulnerable individuals, updating values according to inflation; effective implementation of the DOT, with a welcoming rather than a “controlling” format; joint monitoring with primary healthcare of patients with treatment completed, or not, for TB (mainly for DR-TB).16,23
This study has limitations, including the collection of secondary data; the specific population studied, which included a single health service; and the restricted sample size, which does not allow the findings to be generalized.
Treatment of DR-TB should not be only focused on clinical aspects because socioeconomic factors are associated with the health–disease process and are therefore important predictors of the DR-TB treatment outcomes—in particular, the occurrence of unfavorable outcomes, which lead to worsening of drug resistance. This includes longer duration of future treatments, the occurrence of adverse reactions, greater probability of future follow-up losses and dissemination of DR-TB to the community, and, consequently, higher costs to the health system.
The relationship between previous TB treatments and unfavorable outcomes highlights the need to build public policies that enhance adherence to the first treatment through DOT, provide financial and psychological support, and strengthen accessibility to public health services with comprehensive and multidisciplinary follow-up. In summary, it is necessary to focus efforts on the planning and execution of public policies that understand the severity of TB and its effects on people’s lives, most of whom are on the margins of the economy and social programs.
ACKNOWLEDGMENTS
We thank the professionals of the Newton Bethlem Tisiology Outpatient clinic involved in the care of TB patients in Rio de Janeiro. We also thank Editage (www.editage.com) for English language editing. The American Society of Tropical Medicine and Hygiene (ASTMH) assisted with publication expenses.
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