Loss to follow-up of tuberculosis in the population deprived of liberty: predictive factors

Abstract

Objective  To analyze the predictive factors for loss to follow-up of tuberculosis treatment in people deprived of liberty in the state of São Paulo, Brazil.

Methods  Retrospective cohort study. Data were collected from secondary sources on people deprived of their liberty notified of tuberculosis in the state between 2015 and 2017. The risk of loss to follow-up according to the exposure variables (sociodemographic, case detection, clinical and follow-up) was established by the crude Odds Ratio, which, when significant, were included in the multiple model with the forward method, determining their adjusted Odds Ratio.

Results  A total of 9,153 cases were included in the study, of which 6% were closed as loss to follow-up. In the multiple analysis, the predictor variables for loss to follow-up were: female gender; notification by certain coordinating bodies; re-treatment after abandonment, ongoing drug resistance without information, type of treatment without information and need for hospitalization.

Conclusion  The study’s findings highlight the importance of raising awareness among health professionals in prisons about identifying the risk profile for loss of follow-up in tuberculosis treatment among people deprived of their liberty. This includes women detained in the metropolitan region, in pre-trial detention centers and prison progression centers. In addition, this should include people in post-abandonment retreatment, in need of hospitalization and without information on drug resistance and type of treatment.

Tuberculosis; Health profile; Lost of foloww-up; Prisons; Prisioners

Resumo

Objetivo  Analisar os fatores preditivos à perda de seguimento do tratamento da tuberculose em pessoas privadas de liberdade no estado de São Paulo, Brasil.

Métodos  Estudo de coorte retrospectivo. Foram coletados dados de fontes secundárias de pessoas privadas de liberdade notificadas com tuberculose no período de 2015 a 2017 no estado. O risco de perda de seguimento segundo as variáveis de exposição (sociodemográficas, de detecção de casos, clínicas e de acompanhamento) foi estabelecido pelas razões de chance Odds Ratio bruto, as quais, quando significativas, foram incluídas no modelo múltiplo com método forward (Likelihood Ratio), determinando seus Odds Ratio ajustado.

Resultados  Foram incluídos 9.153 casos no estudo, dos quais 6% foram encerrados como perda de seguimento. Na análise múltipla, as variáveis preditoras para a perda de seguimento foram: sexo feminino; notificação por determinadas coordenadorias; retratamento pós-abandono, resistência medicamentosa em andamento sem informação, tipo de tratamento sem informação e necessidade de internação.

Conclusão  Os achados do estudo destacam a importância de sensibilizar os profissionais de saúde nas unidades prisionais sobre a identificação do perfil de risco para a perda de seguimento no tratamento da tuberculose em pessoas privadas de liberdade. Tal identificação abrange mulheres detidas na região metropolitana, em centros de detenção provisória e de progressão penitenciária. Além disso, devem-se incluir pessoas em retratamento pós-abandono, com necessidade de internação e ausência de informações sobre resistência medicamentosa e tipo de tratamento.

Tuberculose; Perfil de saúde; Perda de Seguimento; Prisões; Prisioneiros

Resumen

Objetivo  Analizar los factores predictivos de la pérdida de seguimiento del tratamiento de tuberculosis en personas privadas de la libertad en el estado de São Paulo, Brasil.

Métodos  Estudio de cohorte retrospectivo. Se recopilaron datos de fuentes secundarias de personas privadas de la libertad notificadas con tuberculosis durante el período de 2015 a 2017 en el estado. El riesgo de pérdida de seguimiento según las variables de exposición (sociodemográficas, de detección de casos, clínicas y de seguimiento) fue establecido por razones de momios Odds Ratio brutas, que se incluyeron en el modelo múltiple con método forward (Likelihood Ratio) cuando fueron significativas, para determinar sus Odds Ratio ajustados.

Resultados  Se incluyeron 9.153 casos en el estudio y el 6 % de ellos fue cerrado como pérdida de seguimiento. En el análisis múltiple, las variables predictoras de la pérdida de seguimiento fueron: sexo femenino, notificación por determinadas coordinaciones, nuevo tratamiento luego del abandono, resistencia medicamentosa en curso sin información, tipo de tratamiento sin información y necesidad de internación.

Conclusión  Los resultados del estudio destacan la importancia de sensibilizar a los profesionales de la salud en las unidades penitenciarias sobre la identificación del perfil de riesgo de pérdida de seguimiento del tratamiento de tuberculosis en personas privadas de la libertad. Esta identificación incluye mujeres detenidas en la región metropolitana, en centros de prisión provisional y de régimen semiabierto. Además, debe incluirse a las personas en nuevo tratamiento luego del abandono, con necesidades de internación y ausencia de información sobre resistencia medicamentosa y tipo de tratamiento.

Tuberculose; Perfil de salud; Perdida de seguimento; Prisiones; Prisioneros

Introduction

Brazil reported 68,271 new cases of tuberculosis (TB) in 2021, with an incidence of 32 cases/100,000 inhabitants, making it a priority to control this disease, given that the country is among the 30 countries with a high burden of the disease and TB and Human Immunodeficiency Virus (HIV) co-infection.¹

By June 2023, the Brazilian prison system, with a capacity for 481,835 people, was facing overcrowding, housing 644,305 inmates.² According to the latest data released in 2022, new TB cases in the country in people deprived of their liberty (PDL) totaled 7,040 cases.³It is known that PDLHIV are 28 times more likely to contract TB when compared to the general population.⁴This situation is exacerbated by: inadequate prison conditions, involving overcrowding and a lack of ventilation and sunlight in cells; a high prevalence of HIV infection; difficulty in accessing health services;⁴ and the social vulnerability profile of the PDL.⁵

The National Policy for Comprehensive Health Care for PDL in the Prison System (PNAISP) ensures that incarcerated people have full access to health services, respecting the rights stipulated in the Federal Constitution. This initiative aims to provide comprehensive health care, based on the principles and guidelines of the Unified Health System (SUS).⁶

The state of Sao Paulo (SP), due to its high population density in the national context, also has the highest concentration of incarcerated individuals compared to other federal units in Brazil. In 2022, it accounted for 24% (n=1184) of new TB cases in the country’s PDLs, revealing the importance of the disease burden in the state.⁷In this sense, in order to achieve the objectives of the National Plan to End TB, it is necessary that the care provided to populations vulnerable to becoming ill with TB is aligned with the End-TB Strategy, with emphasis on the PDL, since they suffer the impacts generated by social and health inequities and inequalities.⁸

The context of the prison system has repercussions as regards the occurrence of unfavorable TB treatment outcomes, such as loss to follow-up, treatment failure and death.⁹

In Brazil, in 2021, 10.6% of TB cases occurring in the PDL had their treatment terminated as a loss to follow-up, although lower than that observed in the general population (14.0%)¹⁰ is still significantly distant from the targets set by the WHO of a maximum of 5%.¹¹ Thus, loss to follow-up is one of the obstacles to TB control, as it results in a reduction in the possibility of cure, continuity of the transmission chain, an increase in relapse and drug resistance, as well as an increase in morbidity and mortality from the disease.¹²

Considering the state’s guardianship over these people, loss to follow-up is a complex problem, as it reveals flaws in the therapeutic process and coordination of care in prison units (PU) and outpatient clinics/monitoring services for cases outside the prison system.

In order to tackle this situation, it is important to identify the associated risk factors, as well as encouraging self-care and adherence to tuberculosis treatment, since this reduces transmission and the occurrence of deaths from the disease.

In view of the above, this study aims to analyze the predictive factors for loss to follow-up of tuberculosis treatment in PLHIV in the state of Sao Paulo, contributing to the encouragement of actions for adherence to the treatment of the disease.

Methods

A retrospective cohort was carried out, as it allows past events to be analyzed to identify patterns and associations, especially in relation to exposure to specific factors over time.¹³ The study was carried out in the state of São Paulo, Brazil, and covered 212,672 PDL in 2020, representing 32% of the national prison population, distributed in 179 prison units. These units are administered by five Regional Coordination Offices and the Health Coordination Office, which is responsible for the Custody Hospitals.¹⁴

In 2022, the state of São Paulo recorded a TB incidence in the general population of 38.3 cases/100,000 inhabitants, with a cure rate of 75.0% and loss to follow-up of 12.4%.¹⁴

The study population consisted of all PDL in the state of São Paulo aged 18 or over, diagnosed as TB cases between 2015 and 2017 and notified in the São Paulo State Tuberculosis Patient Control System (TB-WEB). Cases with the following terminations were excluded because they were different from the study object: “death”, “failure”, “drug resistance”, “change of diagnosis”, “transfer” or “change of regimen/toxicity”.

The data was collected from TB-WEB. The study’s dependent variable was loss to follow-up (yes vs. no - consisting of cured cases). The exposure variables (independent) referred to data on the start of TB treatment and corresponded to sociodemographic, clinical, detection and treatment follow-up information.

The data was analyzed by means of frequency distribution, using the R/RStudio program version 1.2.5033. The risk of occurrence of the dependent variable (loss to follow-up) according to the exposure variables was established by the crude Odds Ratio (ORc) and respective confidence intervals and p-values, adopting a significance level of 5%. The variables with significant ORc were included in the multiple model using the forward method (Likelihood Ratio), determining their adjusted Odds Ratio (ORadj).¹⁵ The final model considered the lowest Akaike Information Criterion (AIC) value, i.e. the one that best fitted the distribution of the dependent variable.¹⁶

For the final model, the pseudo coefficient of determination (McFacdden’s R²) was calculated¹⁷and the prediction capacity or accuracy of the models through the area under the Receiver Operating Characteristic (ROC) curve and their respective 95% confidence interval values. The ROC curve is interpreted as an indicator of adequacy when it shows values between 0.9-0.99-excellent, 0.8-0.89-good, 0.7-0.79-acceptable and 0.51-0.69-bad.¹⁸

This study was approved by the Research Ethics Committee of the Ribeirao Preto Nursing School of the University of São Paulo, under opinion no. 5.154.256 (Certificate of Submission for Ethical Appraisal: 52767521.1.0000.5393).

Results

Between 2015 and 2017, 9726 cases of TB were reported in the prison system in the state of Sao Paulo, of which 210 unreported closures, 121 deaths, 103 failures/resistances, 66 changes in diagnosis, 47 under-18s, 20 transfers and six changes in regimen/toxicity were excluded. As a result, the study included 9,153 people affected by TB in PDL, of whom 550 (6.0%) were lost to follow-up. In the univariable analysis, the variables associated with loss to follow-up were: gender; type of case; drug resistance; and TB/HIV co-infection (Table 1).

Table 1
Factors associated with loss to follow-up of tuberculosis treatment in people deprived of their liberty, according to sociodemographic and clinical variables

Variables	Response categories	Cure n(%)	Loss of follow-up n(%)	ORc (95%CI)	p-value
Sex	Male	8474(98.5)	529(96.2)	1
	Female	129(1.5)	21(3.8)	2.48(1.47-3.97)	<0.001
Age group	18-29 years old	4822(56.2)	305(55.7)	1
	30-39 years	2839(33.1)	175(31.9)	0.97(0.80-1.17)	0.792
	40-49 years	741(8.6)	56(10.2)	1.19(0.88-1.59)	0.237
	50 years and over	176(2.1)	12(2.2)	1.07(0.56-1.87)	0.805
Skin color	White	3266(38.0)	186(33.8)	1
	Brown	3545(41.2)	238(43.3)	1.14(0.93-1.40)	0.195
	Black	841(9.8)	62(11.3)	1.30(0.95-1.76)	0.085
	Yellow/Indigenous	22(0.3)	3(0.5)	0.75(0.04-3.60)	0.779
	Ignored/empty	929(10.8)	61(11.1)	1.12(0.82-1.52)	0.435
Years of study	None	66(0.8)	8(1.5)	1.93(0.74-4.47)	0.142
	1-3 years	490(5.7)	27(4.9)	1
	4-7 years	3115(36.2)	212(38.5)	1.21(0.80-1.92)	0.382
	8-11 years	2524(29.3)	152(27.6)	1.08(0.70-1.72)	0.730
	12 years or older	217(2.5)	9(1.6)	0.79(0.34-1.67)	0.561
	Ignored/empty	2191(25.5)	142(25.8)	1.16(0.76-1.86)	0.500
Type of case	New	6778(78.8)	400(72.7)	1
	Relapse	1363(15.8)	93(16.9)	1.17(0.91-1.48)	0.193
	Post-abandonment retreatment	381(4.4)	50(9.1)	2.12(1.51-2.90)	<0.001
	Retreatment (failure / change of regimen)	81(0.9)	7(1.3)	1.41(0.59-2.87)	0.380
Clinical form	Pulmonary	8361(97.2)	534(97.1)	1
	Extrapulmonary	242(2.8)	16(2.9)	1.06(0.61-1.72)	0.806
X-ray	Normal	161(1.9)	8(1.5)	1
	Suspicious/cavity	1453(16.9)	109(19.8)	2.08(0.97-5.39)	0.087
	Other pathology	31(0.4)	4(0.7)	3.41(0.83-12.68)	0.068
	Not performed	5929(68.9)	352(64.0)	1.67(0.80-4.28)	0.220
	No information	1029(12.0)	77(14.0)	1.94(0.90-5.09)	0.123
Drug resistance	Sensitive	4826(56.1)	235(42.7)	1
	DR-TB / MDR-TB	106(1.2)	11(2.0)	2.03(1.02-3.68)	0.028
	Walk./No information	3671(42.7)	304(55.3)	1.64(1.37-1.97)	<0.001
Diabetes Mellitus	Yes	65(0.8)	5(0.9)	1
	No	8538(99.2)	545(99.1)	0.78(0.34-2.26)	0.608
TB/HIV co-infection	No	8169(95.0)	503(91.5)	1
	Yes	434(5)	47(8.5)	0.55(0.40-0.76)	<0.001
Mental disorder	Yes	42(0.5)	2(0.4)	1
	No	8561(99.5)	548(99.6)	1.33 (0.40-8.22)	0.688
Smoking	Yes	2107(24.5)	137(24.9)	1
	No	6496(75.5)	413(75.1)	0.96(0.78-1.18)	0.712
Alcoholism	No	7945(92.4)	493(89.6)	1
	Yes	658(7.6)	57(10.4)	0.75(0.56-1.02)	0.063
Use of illicit drugs	Yes	1697(19.7)	120(21.8)	1
	No	6906(80.3)	430(78.2)	0.89(0.71-1.11)	0.319

• ORc-Crude Odds Ratio; 95%CI-95% Confidence Interval; Retreatment; DR-TB-drug-resistant tuberculosis; MDR-TB-multidrug-resistant tuberculosis; Ongoing

Also in the univariable analysis, the following factors were associated with loss to follow-up: the coordinating body that notified the case; the notification unit; discovery of the case; sputum culture; and MDR-TB (Table 2).

Table 2
Factors associated with loss to follow-up of tuberculosis treatment in people deprived of their liberty, according to case detection and follow-up variables

Variables	Response categories	Cure n(%)	Loss of follow-up n(%)	ORc (95%CI)	p-value
Coordination office that reported the case	Outside the prison system	2036(23.7)	100(18.2)	1
	Metropolitan	1518(17.6)	151(27.5)	2.02(1.56-2.60)	<0.001
	Central	675(7.8)	46(8.4)	1.38(0.96-1.97)	0.074
	Northwest	873(10.1)	49(8.9)	1.14(0.79-1.61)	0.455
	West	2123(24.7)	79(14.4)	0.75(0.55-1.02)	0.070
	Paraíba Valley and Coast	1136(13.2)	99(18.0)	1.77(1.33-2.36)	<0.001
	Health	242(2.8)	26(4.7)	2.18(1.36-3.38)	<0.001
Notification unit	Penitentiary	4000(46.5)	144(26.6)	1
	CPP	715(8.3)	147(26.7)	5.71(4.47-7.28)	<0.001
	CDP	1608(18.7)	132(24.0)	2.28(1.78-2.90)	<0.001
	CHP	242(2.8)	26(4.7)	2.98(1.88-4.54)	<0.001
	Other Health Units	2036(23.7)	100(18.2)	1.60(1.18-2.15)	<0.001
TB case discovered	Active search institution	2589(30.1)	182(33.1)	1
	Active community search	39(0.5)	6(1.1)	2.18(0.82-4.86)	0.078
	Outpatient demand	4613(53.6)	253(46.0)	0.78(0.64-0.95)	0.013
	Diagnostic elucidation	251(2.9)	21(3.8)	1.19(0.72-1.86)	0.467
	Contact investigation	439(5.1)	16(2.9)	0.51(0.29-0.84)	0.013
	Urgency / emergency	401(4.7)	46(8.4)	1.63(1.14-2.27)	0.004
	No information	271(3.2)	26(4.7)	1.36(0.86-2.06)	0.155
Escherichia bacilloscopy	Positive	4800(55.8)	309(56.2)	1
	Negative	1800(20.9)	125(22.7)	1.06(0.84-1.32)	0.601
	Not done	1947(22.6)	113(20.5)	0.92(0.72-1.15)	0.482
	No information	56(0.7)	3(0.5)	0.82(0.20-2.25)	0.750
Rust culture	Positive	5644(65.6)	314(57.1)	1
	Negative	1160(13.5)	60(10.9)	0.92(0.67-1.23)	0.592
	Not carried out	1518(17.6)	150(27.3)	1.74(1.40-2.14)	<0.001
	No information	281(3.3)	26(4.7)	1.47(0.92-2.24)	0.083
MDR-TB	MTB Rifamp. Sensitive	3409(39.6)	199(36.2)	1
	MTB Rifamp. Resistant	40(0.5)	7(1.3)	2.99(1.21-6.37)	0.008
	MTB Rifamp. Indeterm.	30(0.3)	2(0.4)	1.14(0.18-3.81)	0.856
	MTB not detectable	348(4.0)	28(5.1)	1.37(0.89-2.04)	0.125
	Not Performed	3207(37.3)	202(36.7)	1.07(0.88-1.32)	0.459
	Invalid test	21(0.2)	3(0.5)	2.44(0.57-7.17)	0.149
	Empty	1548(18)	109	1.20(0.94-1.53)	0.127
Type of treatment	Directly Observed	7979(92.7)	467(84.9)	1
	Self-administered	155(1.8)	26(4.7)	0.46(0.29-0.76)	0.001
	No information	469(5.5)	57(10.4)	1.08(0.63-1.90)	0.775
Hospitalization	No	7917(92.0)	460(83.6)	1
	Yes	686(8.0)	90(16.4)	0.44(0.35-0.56)	<0.001

• ORc-Crude Odds Ratio; 95%CI Confidence Interval; PPC-Prison Progression Center; PDC-Provisional Detention Center; PHC-Prison Hospital Center; UP-prison units; Andam.-in progress; Rifamp.-Rifampicin

In the multiple analysis, the variables identified as predictors of loss to follow-up were: female gender; notification by the Metropolitan Region Coordination Office; notification by the Penitentiary Progression Center (PPC) and Provisional Detention Center (PDC); post-dropout re-treatment; ongoing drug resistance/no information; type of treatment/no information; and occurrence of hospitalization. (Table 3).

Table 3
Predictive factors for loss to follow-up of tuberculosis treatment in the population deprived of liberty

Variables	Response categories	ORadj(95%CI)	p-value
Sex	Male	1
	Female	1.81(1.04-2.29)	0.027*
Coordination office that notified the case	Outside the prison system	1.00
	Metropolitan	22.87(1.04-248.85)	0.012*
	Central	15.28(0.69-167.50)	0.290
	Northwest	11.89(0.54-128.71)	0.460
	West	11.80(0.54-126.52)	0.460
	Paraíba Valley and Coast	16.54(0.75-179.91)	0.240
	Health	-
Notification unit	Penitentiary	1.00
	Penitentiary Progression Center	5.27(4.08-6.82)	<0.001*
	Prison Detention Center	1.42(1.06-1.91)	0.019*
	Prison Hospital Center	19.02(0.84-213.88)	0.190
	Other Health Units	19.37(0.89-205.79)	0.160
Sputum culture	Positive	1.00
	Negative	0.72(0.52-0.99)	0.051
	Not done	1.07(0.83-1.38)	0.587
	In progress + no information	1.09(0.67-1.72)	0.706
Type of case	New	1
	Recurrence	1.14(0.88-1.46)	0.321
	Retreatment after loss to follow-up	1.48(1.02-2.09)	0.031*
	Retreatment (failure/change of regimen)	0.62(0.18-2.08)	0.438
Clinical form	Pulmonary	1
	Extrapulmonary	0.63(0.34-1.09)	0.117
Drug resistance	Sensitive	1
	DR TB / MDR TB	1.90(0.67-4.68)	0.192
	In progress + no information	1.34(1.08-1.67)	0.007*
Alcoholism	No	1
	Yes	1.24(0.90-1.69)	0.177
Type of treatment indicated	Directly observed	1
	Self-administered	1.40(0.82-2.26)	0.195
	No information	2.14(1.53-2.94)	<0.001*
Occurrence of hospitalization	No	1
	Yes	2.44(1.78-3.33)	<0.001*

• ORadj-Adjusted odds ratio; 95%CI - 95% confidence interval; *Significant value; AIC: 3587; Pseudo R² (McFadden): 0.08

According to the Pseudo R² (McFadden), the model has the capacity to explain 8% of TB treatment follow-up losses in the prison system. The area under the Receiver Operating Characteristic (ROC) curve of the final model was 0.7 (95%CI 0.61-0.77), which means that the model has a moderate to high ability to predict the loss to follow-up of TB treatment in PDLs.

Discussion

The present study showed that females were more likely to be lost to TB treatment follow-up, a result that is different from other studies on PDL carried out in Brazil and Uganda, identified in the literature.¹⁹,²⁰In Brazil, the female prison population grew by 656% between 2000 and 2016, while the male population grew by 293%,²¹ This growth has not been accompanied by a resizing of the number of places in the prison system or of its health and security teams. In addition, one study shows that women deprived of their liberty have little access to health care, and that there is little specificity in health actions aimed at this gender.²²Although a national policy to care for these women was published in 2014,²³it shows the violation of rights and the invisibility of this population.²⁴

In this context, the rate of loss to follow-up in the prison population was substantially lower (6%) than in the general population (12.4%). This disparity may suggest more effective adherence to treatment or more effective supervision of patients in the prison environment. This scenario can be explained by various factors, such as the implementation of specific tuberculosis control programs in prisons and a possible increased awareness among inmates of the importance of treatment, given the greater risk of contracting the disease in this environment.

Individuals notified by the Metropolitan Coordination Office were more likely to lose their TB treatment. However, it is important to note that the Metropolitan Coordination has a higher number of nurses,²⁵ raising the question of how the care of people with TB has been carried out in these settings. This care may be hampered by the multiple functions that nurses perform in this context or by the number of professionals that is still not enough to cover the occupation of the units.²⁶

In this Coordination, there are also a greater number of PDCs, jeopardizing the continuity of treatment, since PDLs stay in these units for a limited time. The same happens in the PPC, where there were also higher chances of losing follow-up when compared to the penitentiaries. It is therefore possible to assume that there is no integration between these units and the units where the cases are sent, which should provide continuity of treatment.²⁷

As for the clinical aspects, having a history of previous loss to follow-up presented a greater risk of a new loss to follow-up treatment compared to new TB cases. Side effects and the burden of drugs used to treat the disease represent a challenge to completing the treatment, and loss of previous follow-up may be a warning sign of a new loss of follow-up.²⁸In this sense, it is necessary to plan effective actions focused on these individuals, through health education, surveillance actions and treatment follow-up, in order to ensure that TB is cured.

The treatment of drug resistance is still considered one of the biggest problems for TB control in the world, since it can require longer treatment and the use of more toxic drugs that often don’t have an impact on clinical improvement,²⁹ resulting in loss to follow-up treatment. In this sense, this study reveals the importance of filling in the TB information system, since individuals who had an ongoing susceptibility test result and no information were more likely to be lost to follow-up when compared to individuals with a drug-sensitive TB result.

When analyzing the type of treatment, individuals who did not have information related to this variable were more likely to be lost to follow-up compared to those who underwent Directly Observed Treatment (DOT). In a Brazilian study (n=24,692), the factors that predicted adherence to TB treatment in PDL indicated the importance of maintaining this type of treatment throughout the period of incarceration.¹⁹A retrospective cohort in the states of Rondônia and São Paulo, Brazil (n=24,732), showed that those PDL who underwent treatment independently were 2.5 times more likely to have an unfavorable outcome, compared to those who underwent DOT in prisons in the state of Sao Paulo.⁸

In this sense, it is important to emphasize the potential of prison units for carrying out DOT, given the proximity of cases to health professionals. However, it is worth remembering the limited number of these agents in the prison system, most of whom rely on the support of prison guards, whose role can transcend surveillance and security actions.³⁰

There was evidence of an association between loss of follow-up treatment and hospitalization in the multivariable analysis. A qualitative study carried out in João Pessoa, Paraíba, points to hospitalization as the moment when users understand the importance of TB treatment as the only alternative for their cure. However, there are reports of difficulties in the continuous use of medication outside of hospitalization. Among the PDL, the following are mentioned: lack of human and financial resources for prison health services, insufficient information about TB and, above all, the PDL’s restricted autonomy in terms of access to medication, participation in treatment and prevention actions.³¹

It is also worth noting that the discontinuation of treatment may reflect the lack of an integrated approach in the referral and counter-referral system, with difficulties in accessing health actions and coordinating care when hospitalization is required or even when leaving or transferring from prison units. Thus, some authors emphasize the need to overcome the fragmentation of services with integrated strategies for tuberculosis control.³²

Finally, some aspects deserve to be mentioned in order to reduce the loss to follow-up of tuberculosis in prisons, which include: recognizing the right of PDL to health actions, understanding the profile of illness and vulnerability of these people and adapting prison structures and routines to meet these peculiarities, which should include the qualification of prison health teams.

As a limitation of the study, we highlight a possible information bias, justified by the use of secondary sources, with the possibility of errors in the records, lack of standardization of information and the impossibility of collecting relevant variables for the study.

Conclusion

The findings of this study revealed some predictors of loss to follow-up of TB treatment among PDL in the state of São Paulo, such as: female gender, notification in the Metropolitan Region Coordination and in PDC and PPC, cases being re-treated after abandonment, lack of information on drug resistance and type of treatment, as well as the need for hospitalization. In view of the above, it is recommended that professionals in prison health units be sensitized to the process of identifying individuals with a risk profile for loss of TB treatment follow-up, in order to: promote the effectiveness and sustainability of DOT in prison units, offer health education actions for treatment adherence and adopt strategies to improve communication with other prison units and Health Network services. In addition, it is worth highlighting the need to adapt physical structures and organizational routines to meet the needs and vulnerabilities of PDL, as well as the adequate sizing and qualification of health professionals working in the prison context to monitor TB cases.

Acknowledgements

This work was carried out with the support of the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES) - Funding Code 001.

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Edited by

• Associate Editor
  Rafaela Gessner Lourenço (https://orcid.org/0000-0002-3855-0003) Universidade Federal do Paraná, Curitiba, PR, Brazil

Publication Dates

• Publication in this collection
  04 Oct 2024
• Date of issue
  2024

History

• Received
  16 Oct 2023
• Accepted
  10 June 2024