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Jiangetal. BMC Infectious Diseases (2022) 22:638
https://doi.org/10.1186/s12879-022-07622-w
RESEARCH
Epidemiology ofrecurrent pulmonary
tuberculosis bybacteriological features of100
million residents inChina
Hui Jiang1,2†, Jinfeng Yin1,2†, Fangchao Liu1,2, Yuxia Yao3, Chao Cai4, Jiying Xu3, Lijun Zheng1,5,6, Chendi Zhu1,5,6,
Junnan Jia1,5,6, Xu Gao7*†, Wangli Xu8*†, Weimin Li1,5,6*† and Guolong Zhang3*†
Abstract
Background: Recurrence continues to place significant burden on patients and tuberculosis programmes world-
wide, and previous studies have rarely provided analysis in negative recurrence cases. We characterized the epidemio-
logical features of recurrent pulmonary tuberculosis (PTB) patients, estimated its probability associated with different
bacteriology results and risk factors.
Methods: Using 2005–2018 provincial surveillance data from Henan, China, where the permanent population
approximately were 100 million, we described the epidemiological and bacteriological features of recurrent PTB. The
Kaplan–Meier method and Cox proportional hazard models, respectively, were used to estimate probability of recur-
rent PTB and risk factors.
Results: A total of 7143 (1.5%) PTB patients had recurrence, and of 21.1% were bacteriological positive on both
laboratory tests (positive–positive), and of 34.9% were negative–negative. Compared with bacteriological negative
recurrent PTB at first episodes, the bacteriological positive cases were more male (81.70% vs 72.79%; P < 0.001), higher
mortality risk (1.78% vs 0.92%; P = 0.003), lower proportion of cured or completed treatment (82.81% vs 84.97%;
P = 0.022), and longer time from onset to end-of-treatment. The probability of recurrence was higher in bacteriologi-
cal positive cases than those in bacteriological negative cases (0.5% vs 0.4% at 20 months; P < 0.05).
Conclusions: Based on patient’s epidemiological characteristics and bacteriological type, it was necessary to actively
enact measures to control their recurrent.
Keywords: Pulmonary tuberculosis, Recurrence, Risk factors, Clinical diagnosed
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Background
Recurrence of tuberculosis (TB) is defined as patients
who have previously been treated for TB, and were
declared cured or treatment completed at the end of their
most recent course of treatment, and now are diagnosed
with a recurrent episode of TB (either a endogenous
reactivation of a previous infection or a new episode of
TB caused by reinfection) [1]. According to WHO global
estimates, approximately 430,000 previously treated
patients experienced bacteriologically confirmed or clini-
cally diagnosed recurrence in 2015, representing 7% of
Open Access
†Hui Jiang and Jinfeng Yin contributed equally to this work
†Xu Gao, Wangli Xu, Weimin Li and Guolong Zhang are co-senior authors on
this study
*Correspondence: xu.gao@hsc.pku.edu.cn; wlxu@ruc.edu.cn; lwm_18@aliyun.
com; 1296190445@qq.com
1 Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
3 Institute of Tuberculosis Control and Prevention, Henan Center
for Disease Control and Prevention, Henan 450016, China
7 School of Public Health, Peking University, Beijing 100191, China
8 School of Statistics, Renmin University of China, Beijing 100872, China
Full list of author information is available at the end of the article
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Page 2 of 10
Jiangetal. BMC Infectious Diseases (2022) 22:638
all notified TB cases [2]. In detail, approximately 5% of
patients with drug-susceptible tuberculosis have a recur-
rence after 6months of first-line therapy, and approxi-
mately 20% of patients have a recurrence after 4months
of short-course therapy, even when regimens include a
fluoroquinolone [3]. erefore, recurrence has become
the core stumbling block to achieve WHO’s target of
eradicating TB in 2035.
In China, extensive studies have been published on TB
recurrence; however, most of these studies have focused
on pathogens of bacteriological positive cases caused by
exogenous reinfection or endogenous relapse as well as
the relationship between recurrence and drug resistance
[4–6]. However, these studies have rarely provided analy-
sis in negative recurrence cases, which consists of 35.4%
of the total recurrence of TB in a previous study [7] and
unlike the bacteriological positive cases, most of them
are lack of timely diagnosis and treatment. erefore, it
is worthwhile to conduct a comprehensive study on this
topic to elucidate the factors that may be associated with
the different features of bacteriological positive and nega-
tive recurrence cases.
Henan, with approximately 100 million residents, is
one of the most populous provinces in China [8], and
the number of new cases is about 60,000 each year and
accounts for almost 10% of the national TB patients
of China mainland [9]. In this retrospective study, we
describe the epidemiological features of all recurrent
pulmonary tuberculosis (PTB) cases from 2005 to 2008
in Henan province, estimate the recurrence probability of
bacteriological positive and negative cases, and explore
the risk factors of recurrent PTB.
Methods
Data sources
e information of PTB cases from January 1, 2005 to
December 31, 2018, which were reported to the Tuber-
culosis Information Management System (TBIMS) as the
national TB surveillance system within 24h after diagno-
sis [10], were collected and included basic demographics,
time of illness onset and diagnosis, laboratory outcomes,
supervisor mode, and treatment outcomes.
Case denitions
Based on WHO guideline, clinical-diagnosed PTB
patients [1] and bacteriologically-confirmed patients
were defined respectively. We defined clinical-diag-
nosed PTB as bacteriological negative PTB, clinical
diagnosis was based on TB-specialized chest imaging,
supplemented by epidemiological investigation, clinical
manifestation (coughing, expectoration ≥ 2 weeks, or
hemoptysis), or results of an immunology test (tuber-
culin skin test and/or interferon gamma release assay),
and effective experimental treatment using antituber-
culosis drugs for 2 months. Bacteriological positive
PTB was based on laboratory evidence (sputum smear,
culture and Genxpert) of infection with Mycobacterium
tuberculosis (M.TB). Both were defined as PTB patients
in our study.
We identified patients with at least two episodes of
PTB reported in the TBIMS by matching records using
any of the following screening criteria: (1) having highly
similar patient names; (2) having highly similar patient
names and home addresses; (3) having highly similar
patient names, home addresses, and birth dates. We
considered patients to have recurrent TB if they expe-
rienced at least two independent episodes of TB. An
independent episode was defined as a case wherein a
patient who was previously diagnosed with PTB and
received anti-tuberculosis treatment was declared
cured at the end of the course or completion of treat-
ment but was subsequently diagnosed with PTB again.
Additionally, patients with at least two independent
episodes of recurrent laboratory-confirmed PTB were
classified into this group. We also excluded the follow-
ing PTB patients: (1) not cured; (2) treatment was not
completed at the end of their most recent course of
treatment.
Because of the retrospective study design, there was
no active follow-up for all of the cases. We defined the
passive follow-up time as the time after the end of the
initial tuberculosis treatment until an event (recur-
rence) or the censored date (December 31, 2018). To
aid comparison with other published studies, we also
looked at the proportion of recurrence among a subset
of all pulmonary cases, bacteriologically confirmed pul-
monary cases who completed treatment.
Data analysis
Descriptive analyses of recurrent PTB cases were
performed using a descriptive method to analyze
continuous variables and categorical variables. e
Kaplan–Meier method was used to estimate the recur-
rence curve of PTB. e probability of first and second
recurrences of PTB were both calculated. Subgroups
of interest were compared using the log rank test. e
risk factors associated were explored using Cox propor-
tional hazard models. Only the first episode of recur-
rence was included in the Cox models. Unadjusted
hazard ratios (HRs) and adjusted HRs (aHRs) were
estimated from a univariable analysis and multivariable
analysis, respectively.
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Jiangetal. BMC Infectious Diseases (2022) 22:638
All statistical analyses were performed with R (ver-
sion 3.3.0). All statistical tests were two-sided with a
significance level of p < 0.05.
Results
From 2005 to 2018, a total of 976,526 PTB episodes
occurring in Henan province were reported to the
TBIMS. Excluding single TB episodes, extrapulmo-
nary tuberculosis, and non-independent episodes, 7143
patients (having 14,717 [1.5%] episodes) were identified
as having recurrent PTB. Among all PTB and bacterio-
logical confirmed PTB cases, who completed treatment
for the first episode, the proportion of recurrence was
1.8% and 2.2% respectively. Among the 7143 recurrent
patients, 94.3% (6739) of these patients had two epi-
sodes and 5.7% had more than two episodes: 379 (5.3%)
patients had three episodes and 25 (0.4%) had at least
four episodes. Bacteriological results revealed that 21.1%
of patients with recurrence tested bacteriological posi-
tive on both laboratory tests, 34.9% tested bacteriological
negative on both tests, 23.4% tested bacteriological posi-
tive on the first test and bacteriological negative on the
second, and 13.6% tested bacteriological negative on
the first test and bacteriological positive on the second
(Fig.1; Additional file1: Fig. S1).
Demographic characteristics
e overall male to female ratio was 3.4:1. e median
age at primary onset of all patients with recurrent PTB
was 54years (interquartile range [IQR]: 40–64), which
was higher than that of non-recurrent cases (48 [IQR:
28–63]). In addition, the median ages of patients with
one recurrence, two recurrences, and three or more
recurrences were 57 (IQR: 42–67), 59 (IQR: 48–68),
and 63 (IQR: 54–68), respectively. 50.7% of recurrent
cases received enhanced supervision, 49.2% received
a directly observed treatment short course chemo-
therapy (DOTS), and 0.1% performed self-medication.
Additionally, the proportion of death in recurrent cases
was higher than that in non-recurrent cases, and the
Fig. 1 Flowchart showing screening and analysis of patients with recurrent PTB from the national TB surveillance database in Henan province,
China from 2005 to 2018
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Jiangetal. BMC Infectious Diseases (2022) 22:638
proportions of death with one recurrence, two recur-
rences and three recurrences were 1.4%, 1.9%, and 4.0%,
respectively (Table1). Compared with bacteriological
negative recurrent PTB at first episodes, bacteriological
positive cases had higher proportion of male patients
(81.70% vs 72.79%; p < 0.001) and DOTS management
mode (99.08% vs 5.45%; p < 0.001). And higher lev-
els of mortality risk (1.78% vs 0.92%; p = 0.003), lower
proportion of cured or treatment completed patients
(82.81% vs 84.97%; p = 0.022), and longer time from
onset to course end were also observed for bacteriolog-
ical positive recurrent PTB at first episodes (Table2).
Probability ofrecurrence
e median times from the completion of first episode
to recurrent tuberculosis were 17.6 months (IQR: 8.3–
33.9), 17.6 months (IQR: 8.3–32.5), and 17.5 months
(IQR: 8.3–35.5) for all pulmonary cases, bacteriological
negative cases, and bacteriological positive cases, respec-
tively (p = 0.121). Figure 2 depicted the probabilities of
the recurrences of the three types of TB cases. Specifi-
cally, after the primary episode of PTB (Fig.2A, B), the
recurrences of all PTB and bacteriological positive PTB
were similar along with the probabilities of 0.4%, 0.6%,
and 0.7% at 20, 40, and 60 months, respectively, and
then remained stable after 60 months. e recurrence
Table 1 Characteristics of pulmonary tuberculosis (PTB) patients with different recurrence frequency, Henan province, 2005–2018
Data are presented as n (%) of patients unless otherwise indicated
DOTS directly obser ved treatment short course chemotherapy, IQR interquartile range
Characteristic No recurrence
(n = 961,809) Recurrence PTB
Primary onset
(n = 7143) Recurrence 1 (n = 6739) Recurrence 2 (n = 379) Recurrence ≥ 3 (n = 25)
Sex
Male 676,648 (70.4) 5505 (77.1) 5505 (77.2) 313 (77.8) 18 (72.0)
Female 285,161 (29.6) 1638 (22.9) 1638 (22.8) 91 (22.2) 9 (28.0)
Median (IQR) 48 (28–63) 54 (40–64) 57 (42–67) 59 (48–68) 63 (54–68)
Age group (years)
0–14 9407 (1.0) 22 (0.3) 5 (0.1) 0 (0.0) 0 (0.0)
15–29 246,098 (25.6) 1198 (16.8) 993 (14.7) 35 (9.2) 3 (12.0)
30–44 180,552 (18.8) 1065 (14.9) 912 (13.5) 39 (10.3) 0 (0.0)
45–59 218,838 (22.8) 2150 (30.1) 1819 (27.0) 118 (31.1) 7 (28.0)
≥ 60 306,504 (31.9) 2708 (37.9) 3010 (44.7) 187 (49.3) 15 (60.0)
Unknown 410 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Median of time delay (days, range)
Time from onset to
first hospital visit 13 (2–30) 11 (1–31) 11 (1–30) 12 (1–31) 2 (0–16)
Time from onset to
confirm 23 (10–40) 14 (30–59) 27 (14–44) 31 (16–50) 28 (17–36)
Time from onset to
course end 208 (192–234) 215 (198–249) 223 (200–274) 240 (203–284) 220 (207–255)
Time from hospitaliza-
tion to course end 185 (182–198) 189 (184–215) 199 (183–249) 210 (184–258) 211 (191–246)
Management mode
Enhanced supervision 479,607 (49.9) 3624 (50.7) 3733 (55.4) 198 (52.2) 11 (44.0)
DOTS 450,977 (46.9) 3511 (49.2) 2922 (43.4) 175 (46.2) 13 (52.0)
Self-medication 8119 (0.8) 7 (0.1) 12 (0.2) 3 (0.8) 1 (4.0)
Unknown 23,106 (2.4) 1 (0.0) 72 (1.1) 3 (0.8) 0 (0.0)
Outcome
Cured 292,466 (30.4) 3212 (45.0) 1749 (26.0) 85 (22.4) 5 (20.0)
Treatment completed 483,794 (50.3) 3931 (55.0) 3783 (56.1) 208 (54.9) 15 (60.0)
Death 8112 (0.8) 0 (0.0) 92 (1.4) 7 (1.9) 1 (4.0)
Unknown 177,437 (18.4) 0 (0.0) 1115 (16.6) 79 (20.8) 4 (16.0)
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Jiangetal. BMC Infectious Diseases (2022) 22:638
probabilities of bacteriological negative cases were
slightly lower than the positive cases (p < 0.05), but still
showed an increasing trend.
Compared to the first scenario, during the median time
of 15.7 (IQR: 7.5–24.4) months after the second PTB epi-
sode in patients with recurrence, the recurrence prob-
abilities were much higher regardless of the types of PTB
cases (Fig. 2C, D). All PTB and bacteriological positive
cases shared similar probabilities of 3.6%, 5.2%, and 5.6%
at 20, 40, and 60months, respectively. And bacteriologi-
cal negative PTB had significantly lower probabilities at
the same time point. After 62 months, all probabilities
kept stable like that in the first scenario.
Risk factors associated withrecurrence
Compared to female, males had higher risk of recurrence
with aHRs of 1.29 (95% CI 1.22–1.36). Patients with
older age had higher risk of recurrence, compared to the
0–14 years group (reference group), the aHR was 2.32
(95% CI 1.49–3.62) for patients aged 45–59 years, and
was 2.07 (95% CI 1.32–3.22) for subjects aged ≥ 60years
(p < 0.001). Bacteriological positive cases also exhibited
consistently higher risk of recurrence, and the aHRs was
1.27 (95% CI 1.21–1.33) comparing to the negative cases.
A longer time from illness onset to cure was associated
with greater risk of recurrence, compared to the group
of cases with time from illness onset to cure < 6months
(reference group), the aHR was 7.01 (95% CI 5.43–9.04)
for cases with time from illness onset to cure between
6 and 12months, and was 8.32 (95% CI 6.34–10.93) for
cases with time from illness onset to cure > 12 months
(p < 0·001) (Table3).
We then assessed the multivariate analysis of hazard
ratios of characteristics of bacteriological positive cases
Table 2 Characteristics of recurrent PTB patients at first episodes
a Treatment outcome at rst recurrent episodes for recurrent PTB patients
Characteristic Recurrent PTB at rst episodes P value
Bacteriological negative cases
(n = 3639, 52.44%) Bacteriological positive cases
(n = 3300, 47.56%)
Sex < 0.001
Male 2649 (72.79) 2696 (81.70)
Female 990 (27.21) 604 (18.30)
Age group 0.233
0–14 years 18 (0.49) 2 (0.06)
15–29 years 636 (17.48) 506 (15.33)
30–44 years 520 (14.29) 499 (15.12)
45–59 years 1055 (28.99) 1054 (31.94)
≥ 60 years 1410 (38.75) 1239 (37.55)
Treatment history 0.577
New case 3463 (95.16) 3147 (95.36)
Retreatment case 176 (4.84) 154 (4.67)
Time from the completion to recurrent tuberculosis
(month, range) 17.6 (8.3–32.5) 17.5 (8.3–35.5) 0.121
Median of time delay (days, range)
Time from onset to first hospital visit 10 (1–29) 13 (1–34) < 0.001
Time from onset to confirm 26 (13–48) 32 (15–62) < 0.001
Time from onset to course end 213 (197–245) 216 (199–252) < 0.001
Time from hospitalization to course end 189 (184–213) 189 (184–215) 0.592
Management mode < 0.001
Enhanced supervision 3397 (94.41) 29 (0.89)
DOTS 196 (5.45) 3234 (99.08)
Self-medication 5 (0.14) 1 (0.03)
Outcomea< 0.001
Cured 749 (20.82) 1134 (34.74)
Treatment completed 2308 (64.15) 1569 (48.07) 0.022
Death 33 (0.92) 58 (1.78) 0.003
Others 549 (15.26) 539 (16.51)
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Jiangetal. BMC Infectious Diseases (2022) 22:638
and bacteriological negative cases, respectively. In the
multivariate analysis, bacteriological negative patients
aged 45–59 years and ≥ 60years were at high risk for
recurrence (aHR: 1.92 [1.19–3.07]; aHR: 1.92 [1.20–3.08])
but bacteriological positive patients only had a higher
risk on those aged 45–59years (aHR: 5.09 [1.27–20.44]).
ere were no other significant differences in risk factors
between the two groups (Table4).
Discussion
e findings from this study showed the overall propor-
tion of recurrent tuberculosis to be 1.5%. e hazard of
recurrent tuberculosis was significantly higher for tuber-
culosis patients who were male, older age, bacteriological
positive cases, and with a longer time from illness onset
to cure. Notably, bacteriological positive recurrence cases
had higher mortality risk (1.78% vs 0.92%; p = 0.003) and
lower cure or treatment completement rate (82.81% vs
84.97%; p = 0.022) than bacteriological negative cases.
A WHO report estimated that 6.8% of TB cases
recurred worldwide in 2019 [11], and recurrence occurs
not only in high TB incidence countries, but also in
low countries [12–14]. A retrospective study of sur-
veillance data and clinical records in Finland showed
0.6% of TB cases were recurrent from 1995 to 2013
[15], and 1.3% of TB cases were recurrent in Barcelona
from 2003 to 2006 [12], and the proportion of recur-
rent cases between 4.2 and 5.7% in the United States
Fig. 2 The probability of PTB recurrence after primary PTB diagnosis in Henan province, China from 2005 to 2018. A Probability of recurrence in
primary PTB patients. B Probability of recurrence in primary PTB patients with bacteriological positive and negative cases. C Probability of recurrence
after first recurrence. D Probability of recurrence after first recurrence with bacteriological positive and negative cases
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Page 7 of 10
Jiangetal. BMC Infectious Diseases (2022) 22:638
during 1993–2010 [16]. In addition, 5.3% of success-
fully treated bacteriologically confirmed cases had a
recurrence in Shanghai [5], China, and 6.8% in Beijing
[6]. In comparison, 2.2% of bacteriological confirmed
PTB cases who completed treatment recurred in Henan
province from 2005 to 2018. Shanghai and Beijing had
more comprehensive PTB case detection, treatment
and management strategies, compared with the area
of Henan, which helped find more PTB and recurrent
patients. For example, the administrative department of
Shanghai required all pulmonary tuberculosis patients
to test sputum culture, and the pathogenic positive rate
to be above 50% [17], and extended free tuberculosis
treatment to all migrants [18] (free treatment was not
available outside individuals’ originally registered resi-
dence in Henan). Of course, differences in enrollment
patients, the criteria for defining cases as recurrent TB,
and the length of the study varied between studies and
limit the comparisons.
In this study, we found male gender and older age
were related to recurrence, which were in line with
some previous reports [19–22]. We also observed that
more proportion of men had bacteriological positive
PTB recurrent PTB at first episodes (81.70% vs 72.79%),
because men tended to have radiographic abnormalities,
positive results on smear microscopy, and culture posi-
tivity compared with women [23–25]. e time from ill-
ness onset to cure within 6months was associated with a
lower risk of recurrence than that for the period beyond
6months. e aHR also increased with prolongation of
treatment time. is demonstrates that longer treatment
periods are associated with a higher chance of recur-
rence and could be due to the treatment noncompliance
[22]. Compared with bacteriological negative PTB cases,
Table 3 Hazard ratios (HRs) by characteristics of recurrent PTB cases, by univariate and multivariable analysis, Henan province, 2005–
2018
HRs hazards ratios
a The multivariable model adjusted for sex, age, occupation and all the other variables in the table
Number of all
cases Number of
Recurrent cases Univariate Multivariablea
HRs (95% CI) P value Adjusted HRs (95% CI) P value
Sex
Female 286,799 1638 1.00 1.00
Male 682,153 5505 1.42 (1.34–1.49) < 0.001 1.29 (1.22–1.36) < 0.001
Age group, year
0–14 9429 22 1.00 1.00
15–29 247,296 1198 2.08 (1.36–3.17) < 0.001 1.18 (0.76–1.85) 0.449
30–44 181,617 1065 2.52 (1.65–3.84) < 0.001 1.43 (0.92–2.24) 0.109
45–59 220,988 2150 4.19 (2.75–6.38) < 0.001 2.32 (1.49–3.62) < 0.001
≥ 60 309,212 2708 3.77 (2.48–5.74) < 0.001 2.07 (1.32–3.22) 0.001
Farmer
No 180,805 1077 1.00 1.00
Yes 788,139 6058 1.27 (1.19–1.36) < 0.001 0.98 (0.90–1.06) 0.631
Residence
Urban 178,955 1248 1.00 1.00
Rural 780,090 5843 1.07 (1.00–1.14) 0.025 0.99 (0.92–1.07) 0.855
Bacterial test results
Negative 522,340 3639 1.00 1.00
Positive 382,335 3300 1.25 (1.19–1.31) < 0.001 1.27 (1.21–1.33) < 0.001
Time from illness onset to first hospital visit (month)
0–1 640,371 5263 1.00 1.00
1–2 118,170 951 0.98 (0.91–1.05) 0.054 0.95 (0.88–1.01) 0.110
2–3 40,780 388 1.16 (1.05–1.29) 0.005 1.09 (0.98–1.22) 0.089
> 3 53,070 534 1.23 (1.12–1.35) < 0.001 1.04 (0.94–1.16) 0.426
Time from illness onset to cure (month)
0–6 46,647 64 1.00 1.00
6–12 709,329 6459 7.02 (5.49–8.98) < 0.001 7.01 (5.43–9.04) < 0.001
> 12 60,517 611 7.52 (5.81–9.73) < 0.001 8.32 (6.34–10.93) < 0.001
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Jiangetal. BMC Infectious Diseases (2022) 22:638
bacteriological positive PTB cases were more likely to
recur. We found that patients with bacteriological posi-
tive results had a longer treatment period and some
researches showed that bacteriology-negative PTB can
be treated for a shorter duration [26]. During the longer
treatment period, because of factors such as adverse
reactions, cost and stigma [27], there was a lower treat-
ment completion or cure rate on bacteriological positive
patients (82.81% vs 84.97%). Furthermore, incomplete
or irregular treatment could increase disease recurrence
[22]. e health system needs to pay attention to the case
management of recurrent patients to ensure patients fin-
ish the treatment or take the drugs irregularly, having a
benefit impact on reducing recurrence. In addition, bac-
teriologically positive PTB presented with more symp-
toms and were more likely to have cavitary lesions than
patients with bacteriologically negative PTB [28]. Cavi-
tation on radiology was the risk factor for tuberculosis
recurrence [29], which may make bacteriologically con-
firmed PTB more likely to recur.
More intriguingly, our study specifically evaluated
the recurrence of bacteriological negative cases though
it had a lower mortality risk than bacteriological posi-
tive recurrence cases as previously reported (0.92% vs.
1.78%) but with a more complicated diagnosis criteria.
Even if not bacteriological confirmed, such bacteriology-
negative PTB may be hindered in routine clinical practice
and with high likelihood of progression to transmissible
bacteriology-positive disease if left untreated or treated
inappropriately [30]. Recent studies suggested the detec-
tion from the perspective of immunology mechanisms
including the T cell dysfunction and the transitional
changes in interferon (IFN)-γ responses [31], as well as
the alterations of MTB-specific IgG profiles [32]. ese
suggest a potential exploration of immunological bio-
markers for the detection of bacteriology-negative PTB
Table 4 Hazard ratios (HRs) by characteristics of recurrent PTB cases stratified by Bacteriology results, by univariate and multivariable
analysis
HRs hazards ratios
a The multivariable model adjusted for sex, age, occupation and all the other variables in the table
Bacteriological negative cases Bacteriological positive cases
Univariate
HRs (95% CI)
P value Multivariablea
Adjusted HRs (95% CI)
P value Univariate
HRs (95% CI)
P value Multivariablea
Adjusted HRs (95% CI)
P value
Sex
Female 1.00 1.00 1.00 1.00
Male 1.26 (1.17–1.35) < 0.001 1.20 (1.12–1.29) < 0.001 1.53 (1.40–1.67) < 0.001 1.43 (1.31–1.57) < 0.001
Age group, years
0–14 1.00 1.00 1.00 1.00
15–29 1.21 (0.75–1.93) 0.433 1.01 (0.63–1.63) 0.954 3.11 (0.78–12.47) 0.109 2.55 (0.63–10.23) 0.187
30–44 1.37 (0.85–2.19) 0.190 1.18 (0.73–1.90) 0.492 3.83 (0.96–15.36) 0.058 3.18 (0.79–12.77) 0.103
45–59 2.29 (1.44–3.65) < 0.001 1.92 (1.19–3.07) 0.007 6.30 (1.57–25.22) 0.009 5.09 (1.27–20.44) 0.022
≥ 60 2.27 (1.42–3.61) < 0.001 1.92 (1.20–3.08) 0.006 4.88 (1.22–19.52) 0.025 4.01 (0.99–16.07) 0.053
Farmer
No 1.00 1.00 1.00 1.00
Yes 1.33 (1.21–1.45) < 0.001 1.01 (0.91–1.13) 0.833 1.09 (0.98–1.19) 0.102 0.95 (0.85–1.66) 0.381
Residence
Urban 1.00 1.00 1.00 1.00
Rural 1.16 (1.06–1.26) < 0.001 1.08 (0.98–1.20) 0.108 0.93 (0.85–1.01) 0.095 0.90 (0.81–1.00) 0.051
Time from illness onset to first hospital visit (month)
0–1 1.00 1.00 1.00 1.00
1–2 0.93 (0.84–1.03) 0.154 0.91 (0.82–1.01) 0.062 0.98 (0.89–1.08) 0.645 0.98 (0.89–1.08) 0.662
2–3 1.13 (0.97–1.32) 0.124 1.08 (0.93–1.27) 0.301 1.12 (0.97–1.29) 0.114 1.10 (0.96–1.27) 0.182
> 3 1.17 (1.02–1.34) 0.029 0.95 (0.81–1.11) 0.524 1.17 (1.04–1.32) 0.009 1.13 (0.98–1.30) 0.082
Time from illness onset to cure (month)
0–6 1.00 1.00 1.00 1.00
6–12 5.85 (4.23–8.08) < 0.001 6.03 (4.32–8.41) < 0.001 8.88 (5.99–13.17) < 0.001 8.40 (5.67–12.45) < 0.001
> 12 8.09 (5.74–11.42) < 0.001 8.31 (5.79–11.90) < 0.001 9.85 (6.54–14.83) < 0.001 8.73 (5.76–13.23) < 0.001
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 9 of 10
Jiangetal. BMC Infectious Diseases (2022) 22:638
cases, which may help increase its detection rate in clini-
cal setting and further reduce the recurrence of PTB.
is study has several limitations. First, although most
of the clinically diagnosed PTB were caused by M.TB,
Non-tuberculosis mycobacteria (NTM) infection can-
not be ruled out, because the symptom, image feature
and treatment scheme of NTM infection are almost
the same as that of M.TB infection. Second, we did not
obtain M.TB and blood samples; therefore, we were una-
ble to distinguish between recurrent cases due to reac-
tivation and those due to re-infection, or to investigate
their respective risk factors. ird, we were limited to the
information routinely collected in the TBIMS, which at
the time did not include potentially important variables
such as underlying medical conditions, drug resistance
status, and clinical symptoms. Further implementation
of clinical and treatment characteristics of recurrent TB
stratified by bacteriology results will provide more infor-
mation to understand recurrence. In addition, due to the
lack of patient identification numbers, there may be some
misclassification of recurrence cases, which caused an
underestimation of the proportion of recurrences. And
we do not get the national recurrent data, and there is no
literature to report the epidemiological characteristics of
recurrent cases in China in the national scale, therefore,
we cannot compare it with the national recurrent level.
Conclusions
In conclusion, our study provides a detailed overview of
the epidemiology of PTB recurrence from 100 million
residents in China. Our findings suggest although bac-
teriological positive cases had higher risk of recurrence
than bacteriological negative cases, and bacteriological
positive recurrence cases had higher mortality risk, it
was not neglected the clinical diagnosis PTB recurrence
cases. It was necessary for the increase of recurrent cases
to actively targeted interventions to control based on its
epidemiological characteristics.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12879- 022- 07622-w.
Additional le1: Figure S1. Flow chart of showing screening of tubercu-
losis cases with completed treatment or cured.
Acknowledgements
Not applicable.
Author contributions
WL, GZ and WX conceived, designed and supervised the study. YY and JX
collected the data. CC, LZ, CZ, and JJ cleaned the data. HJ, JY and FL analyzed
the data. HJ wrote the drafts of the manuscript. HJ, WL and XG interpreted the
findings. WL and GZ commented on and revised the drafts of the manuscript.
All authors read and approved the final manuscript.
Funding
This study was funded by grants from the National Key Research and Develop-
ment Program (2018YFC2000300); National Natural Science Foundation of
China (U1903118); Beijing Natural Science Foundation (No. Z200001); Natural
Science Foundation of China (No. 11971478); Public Health & Disease Control
and Prevention, fund for building World-Class Universities (Disciplines) of Ren-
min University of China.
Availability of data and materials
The data comes from the Henan Provincial Center for Disease Control and
Prevention. If you want data, you can contact Guolong Zhang. The email is
1296190445@qq.com.
Declarations
Ethics approval and consent to participate
Data of this study is from the China Tuberculosis Information Management
System (TBIMS) Tuberculosis is one of the legal infectious diseases in China,
based on the law of the People’s Republic of China on prevention and control
of infectious diseases, all cases of PTB need to be reported through the
National Notifiable Infectious Disease Surveillance System, and TBIMS is part
of this system. As a part of continuing public health, the collection of data
from TB cases was exempted from institutional review board assessment by
the National Health Commission of the People’s Republic of China. Moreover,
although the data of this study were not anonymous, all methods in this study
were carried out in accordance with relevant guidelines and regulations in the
declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
All authors declare no competing interests.
Author details
1 Beijing Chest Hospital, Capital Medical University, Beijing 101149, China. 2 Bei-
jing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China.
3 Institute of Tuberculosis Control and Prevention, Henan Center for Disease
Control and Prevention, Henan 450016, China. 4 Beijing Youan Hospital, Capital
Medical University, Beijing 100069, China. 5 Beijing Municipal Key Laboratory
of Clinical Epidemiology, School of Public Health, Capital Medical University,
Beijing 100069, China. 6 Beijing Key Laboratory in Drug Resistance Tuberculosis
Research, National Tuberculosis Clinical Lab of China, Beijing Tuberculosis
and Thoracic Tumour Research Institute, Beijing 101149, China. 7 School
of Public Health, Peking University, Beijing 100191, China. 8 School of Statistics,
Renmin University of China, Beijing 100872, China.
Received: 30 June 2021 Accepted: 13 July 2022
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