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Research
Tuberculosis-Related Deaths
within a Well-Functioning DOTS Control Program
Maria de Lourdes García-García,* Alfredo Ponce-de-León,† Maria Cecilia
García-Sancho,‡ Leticia Ferreyra-Reyes,* Manuel Palacios-Martínez,* Javier
Fuentes,§ Midori Kato-Maeda,† Miriam Bobadilla,† Peter Small,José and
Sifuentes-Osornio†
*Instituto Nacional de Salud Pública, Cuernavaca, México; †Instituto Nacional
de Ciencias Médicas y Nutrición “Salvador Zubirán,” México City, México;
‡Instituto Nacional de Enfermedades Respiratorias, México City, Mexico;
§Secretaría de Salud del Estado de Veracruz, Xalapa, México; and Stanford
University, Palo Alto, California, USA
Suggested citation for this article: García-García
M, Ponce-de-León A, García-Sancho MC, Ferreyra-Reyes L, Palacios-Martínez
M, Fuentes J, et al. Tuberculosis-related deaths within a well-functioning
DOTS control program. Emerg Infect Dis [serial online] 2002 Nov [date
cited];8. Available from: URL: http://www.cdc.gov/ncidod/EID/vol8no11/02-0021.htm
To describe the
molecular epidemiology of tuberculosis (TB)-related deaths in a well-managed
program in a low-HIV area, we analyzed data from a cohort of 454 pulmonary
TB patients recruited between March 1995 and October 2000 in southern
Mexico. Patients who were sputum acid-fast bacillus smear positive underwent
clinical and mycobacteriologic evaluation (isolation, identification,
drug-susceptibility testing, and IS6110-based genotyping and
spoligotyping) and received treatment from the local directly observed
treatment strategy (DOTS) program. After an average of 2.3 years of
follow-up, death was higher for clustered cases (28.6 vs. 7%, p=0.01).
Cox analysis revealed that TB-related mortality hazard ratios included
treatment default (8.9), multidrug resistance (5.7), recently transmitted
TB (4.1), weight loss (3.9), and having less than 6 years of formal
education (2). In this community, TB is associated
with high mortality rates.
In both humanistic and economic terms, the cost of deaths due to tuberculosis
(TB) is staggering. In 1990 alone, approximately 2.5 million people died
of TB, accounting for >25% of avoidable adult deaths in the developing
world (1,2). Directly observed treatment strategy (DOTS),
a comprehensive approach to TB control, is one of the most cost-effective
health interventions available (3,4). In the context
of a well functioning DOTS program, cure rates in excess of 80% can be
expected. While these outcomes are assumed to decrease mortality rates,
the detailed epidemiology of deaths in a well-functioning DOTS program
by using modern molecular techniques has not been described.
Since 1995, we have conducted a population-based molecular epidemiologic
study of TB in a health district in southern Mexico. Previous reports
have documented the TB control program approaches World Health Organization
benchmarks (5) and drug resistance is considerable and
has an important negative impact on treatment outcomes (6).
We now report the short- and long- term mortality rates due to TB in this
cohort of TB patients. These data suggest that, as has been described
with other diseases, excess mortality may persist for months or years
after treatment completion, default, or failure (7,8).
Methods
The study site, described previously (5,6,9), is located
in a predominantly urban region in the Orizaba Health Jurisdiction in
the state of Veracruz, which encompasses 134 square km and has a population
of 284,728 (10). The incidence rate of TB during the
year 2000 for the state was higher than that for the nation (28.0 vs.
15.9 per 100,000 inhabitants) (11).
Community-based screening of chronic coughers (>2 weeks) was performed
from March 1995 to October 2000. Patients with positive AFB sputum smears
underwent epidemiologic, clinical (standardized questionnaire, physical
exam, chest x-ray, and HIV test), and mycobacteriologic evaluation. Treatment
was provided in accordance with official norms (12,13).
Treatment outcomes were classified as previously described (6).
Annual follow-up was performed for treatment outcome and vital status.
Deaths were confirmed with death certificates. A close caregiver was interviewed
to elicit signs and symptoms of the terminal illness and “probable cause
of death” was assigned by two of the authors (JF, LF). Informed consent
was obtained from participants. The study was approved by the appropriate
institutional review boards.
Microbiologic Evaluation
Mycobacterial culture, identification, and susceptibility testing were
performed on sputa from each enrolled patient. In brief, unconcentrated
sputum was spread onto Lowenstein-Jensen media (DIFCO, Detroit, MI) at
the local laboratory, and the remaining sputum was frozen at –70°C. The
tubes were examined on a weekly basis until growth was detected. Cultures
were reported as negative if no growth occurred after 8 weeks. Cultures
with visible growth were forwarded to the department of Mycobacteriology
at the Instituto de Diagnostico y Referencia Epidemiológicos (March 1995
to December 1997) or to the Clinical Microbiology Laboratory of the Instituto
Nacional de Ciencias Médicas y Nutrición (INCMNSZ) (January 1998 to October
2000) for definitive biochemical identification at the species level (14,15).
The frozen sputum sample was processed if the first sample was contaminated
or had no growth. Identification and drug susceptibility tests were carried
out using conventional methods and the BACTEC system (Becton Dickinson,
Cockeysville, MD).
Mycobacterium tuberculosis
Fingerprinting
Mycobacteria isolated from study patients were genotyped at Stanford
University from March 1995 to February 1997 and at INCMNSZ from March
1997 to October 2000 with the internationally standardized IS6110-based
restriction fragment length polymorphism (RFLP) technique and compared
by using a computer-assisted visual approach (Bioimage AQ-1 analyzer and
Molecular Fingerprinting Analyzer, version 2.0) (16,17).
Isolates with identical IS6110 fingerprints that contained five
or fewer hybridizing bands underwent spoligotyping at INCMNSZ as described
(18,19). To assess transmission of M tuberculosis
that rapidly progressed to disease, we established a 1-year period
for defining clustering as described (20). Cases were
considered “clustered” if two or more isolates from different patients
were identified within a year that had 1) six or more IS6110 bands
in an identical pattern, or 2) five or fewer bands with identical IS6110
fingerprints and matching spoligotypes. The first patient diagnosed
in each cluster and those with unique fingerprints were classified as
having reactivated disease.
Analysis
Deaths were attributed to TB based on the death certificate (TB listed
as the cause of death), interview of close caregiver (TB identified as
probable cause of death), and active TB at the time of death (positive
AFB smear after last treatment or during treatment if the patient did
not complete treatment performed < 6 months before death). A
patient’s death was attributed to TB if two or more of these conditions
were met. Bivariate and multivariate analyses were performed to describe
association between sociodemographic (age, sex, household characteristics,
occupation, ethnicity, years of formal education, place of residence,
and social security), behavioral (usage of drugs and alcohol, and previous
incarceration), clinical (previous diagnosis of TB; other associated diseases,
previous hospitalizations; HIV infection, duration of symptoms previous
to diagnosis; time elapsed between diagnosis and initiation of treatment
and between initiation of treatment and smear conversion; and symptoms
such as cough, hemoptysis, fever, night sweats, weight loss, and general
malaise), bacteriologic (number of bacilli per microscopic field, drug
resistance, RFLP, or spoligotype pattern), therapeutic (compliance, treatment
outcome, and retreatment) variables, and death due to TB and other causes.
Survival analyses included Kaplan-Meier curves and Cox proportional hazards
model for TB and non-TB–related deaths using as reference time the period
elapsed from diagnosis. Variables were entered into the models according
to their statistical significance in univariate analysis and their biological
relevance. The percentage of population attributable risk was calculated
for variables that were included in the final model (21).
DBASE IV and STATA 5.0 programs were used for data analysis (22).
Results
During the study period, 454 patients were diagnosed with pulmonary TB.
Most patients were men (270 [59.5%] of 454) and the median age was 42
years (range 12–97 years). Most came from lower socioeconomic status as
indicated by household characteristics, formal years of education, and
occupation. Of 438 patients, 74 (17%) lived in households with earthen
floor, 214 (49.3%) of 434 had no access to potable water within the household,
293 (65.4%) of 448 had <6 years of formal education, and 104 (23.4%)
of 445 were manual workers. The prevalence of HIV was 2.1% (9 of 429),
combined resistance to isoniazid and rifampin was seen in 26 (6.7%) of
388 patients, and other resistance patterns in an additional 61 (15.7%)
of 388. One hundred fifty-one (37%) of 413 patients had chest radiographs
with evidence of pulmonary cavitation, and 72 (17.4%) of 413 patients
had interstitial pulmonary infiltrates. Median time from initiation of
symptoms to treatment was 101 days (range 3–2,307 days), median time from
diagnosis to initiation of treatment was 5 days (range 0–594 days), and
median time for sputum conversion was 42 days (range 15–1,228 days).
Treatment and Follow-Up
Of 11 patients who refused treatment, 4 died. Of 443 initiating treatment,
75.4% initiated treatment <10 days after diagnosis; 96.5% received
supervised treatment. Outcomes for patients were as follows: 357 (80.6%)
were cured of whom 314 (70.9%) were bacteriologically confirmed, 41 (9.3%)
defaulted, and 20 (4.5%) failed treatment; 16 (3.6%) died during treatment,
and 9 (2%) transferred out of study area. Patients were tracked for a
median of 839 days (range 3–2,402). Sixty-one additional patients died
during follow-up after treatment. Death was due to TB in 34 (41.9%) of
81 instances; 2 deaths were in patients who did not receive treatment,
11 in patients receiving treatment, and 21 after treatment. Tuberculosis
mortality rates were higher during treatment versus after treatment (1.3/10,000
days vs. 0.7/10,000 days, p<0.01). Crude comparison of sociodemographic,
bacteriologic, and clinical characteristics of patients who died from
TB or from other causes and surviving patients are shown in Table
1. Patients who died from TB had a higher probability of having been
treated for a previous TB episode, showed more severe clinical symptoms,
and had drug-resistant isolates. Less frequently they had other coexisting
chronic conditions, such as HIV infection or hepatic cirrhosis. The patients
who died from TB also had longer delays before diagnosis, treatment, and
sputum conversion. These patients had higher probabilities of default,
failure, and having subsequent TB episodes. The most common non-TB causes
of death included diabetes (12), cirrhosis and other
liver diseases (9), AIDS (6), cancer
(2), and cardiovascular diseases (3).
Kaplan Meier survival probabilities from TB deaths were 97.3% after the
first 6 months, 95.8% after 1 year, 93.7% after 2 years, and 91% after
3 years.
RFLP and Spoligotyping Results
M. tuberculosis culture, drug test, and IS6110 RFLP and
spoligotyping were available for 326 (72%) isolates. Comparison of patients
whose isolates were available for genotyping to those whose isolates were
unavailable indicated that patients for whom fingerprint analysis was
not performed had a higher probability of being of native origin in Mexico
(30 [24.2%] of 124 vs. 39 [12%] of 324, p= 0.001)
and of living in households with earthen floor (31 [25.8%] of 120 vs.
43 [13.5%] of 318, p=0.002). Forty (12.3%) of the 326 evaluated cases
were in clusters. The frequency of being members of clusters of recently
transmitted disease was higher among patients dying from TB than among
those dying from other causes or surviving (8 [28.5%] of 28 patients who
died from TB vs. 32 [10.7%] of 298 patients who died from other causes
and survivors, p=0.01).
Factors Associated with Mortality
Rates
Predictors of death due to TB by Cox regression analysis included treatment
default, resistance to isoniazid and rifampin, and recently transmitted
TB controlling for time of occurrence of death, weight loss >15%, and
years of formal education (Table 2). The effect
was not modified when gender, age, HIV infection, crowding in the household,
household characteristics, occupation, ethnicity, previous treatment,
delay in seeking treatment, specific symptoms, type of radiologic lesions,
and other kinds of diseases were introduced into the model.
After controlling for age, predictors of non-TB death included HIV-infection,
hepatic cirrhosis, and weight loss. Recently transmitted TB was not associated
with other causes of death (Table 2).
The proportion of death due to TB and to other causes attributable to
the different categories of risk factors is shown in Table
2. In the study population, 60% of deaths due to TB were attributable
to drug resistance and treatment default.
Patients with recently transmitted disease had a lower probability of
survival compared with patients with reactivated disease (p=0.007) (Figure).
When causes of death were analyzed according to genotype, we found that
TB was the cause of death in 8 (20%) of 40 patients with recently transmitted
disease and in 20 (7%) of 286 patients with reactivated disease (p=0.01).
Sensitivity Analysis
Analysis of the distribution of the time between diagnosis dates of successive
matching fingerprints indicated that 49.4% (95% confidence interval [CI]
44% to 54%) of all isolates with matching fingerprints patterns were identified
within 1 year. When the interval was modified to 6, 18, 24, 30, and 36
months, we found that the proportion of clustered cases increased (8.3%,
13.8%, 13.8%, 14.4%, and 14.7%, respectively), (Chi square trend, p=0.02).
The association between clustered cases and death due to TB continued
to be positive for each of the other definitions of interval for clustering:
3.6 (1.1 to 10.5), p=0.01; 2.8 (1.0 to 7.3), p=0.03; 2.8
(1.0 to 7.3), p=0.03; 2.7 (0.9 to 6.8), p=0.04; and 2.6
(0.9 to 6.6) p=0.04.
Discussion
This study describes high mortality rates from TB in a cohort of pulmonary
TB patients who resided in an area with a low rate of HIV infection and
were treated in the context of a well-functioning DOTS program. Patients
were followed for an average of 2.3 years after diagnosis. Tuberculosis
was associated with high rates of deaths both during treatment and after
treatment completion, default, or failure. The main independent risk factors
for death due to TB were treatment default and being infected with multidrug-resistant
M. tuberculosis. Additionally, data indicate that cases due to
ongoing transmission of TB may have higher mortality rates than cases
due to reactivation of latent disease. These results suggest that current
techniques underestimate death associated with TB and provide further
impetus not only to treat but also to prevent TB.
Case completion rates are the standard by which the effectiveness of
DOTS-based treatment programs are judged. A large body of evidence collected
under diverse settings demonstrates completion rates of 81% and cure rates
of 73% (23). The epidemiology of death in these programs
is less well studied. Studies performed in HIV-endemic settings constitute
an exception as the high rate of deaths occurring while patients are still
on antituberculous therapy are cited as an impediment to achieving desired
cure rates (24).
Our study reports TB mortality rates both during and after treatment
completion, default, or failure. Of the 443 patients who were started
on therapy, 16 died before completing therapy. This frequency (3.6%) compares
favorably to that reported in other studies (4% in the Gambia [25],
15% in Bolivia [26], 25% in Malawi [27],
and 28% in India [28]). However, in contrast to previous
reports, we had a median of 833 days of follow-up after the completion
of therapy, during which 21 additional patients (4.6%) died of TB, comparable
with reports from the 1960s and 1970s (29). This mortality
rate exceeds that expected according to age-adjusted state mortality statistics
(30).
Although not novel, the risk factors for death due to TB identified in
this cohort are noteworthy; these findings suggest that, even in a high-quality
TB control program, additional efforts could yield important benefits.
Treatment default has been previously described as associated with higher
mortality rates in Mexico (31) and elsewhere (32,33).
Concerted efforts to further reduce default may disproportionately decrease
deaths. We also found that drug resistance, and particularly multidrug
resistance, are associated with death (6,14,34).
Although the most appropriate strategy for managing drug-resistant TB
is debated, these data provide additional impetus for evaluating novel
approaches, such as those recently introduced in Mexico, for managing
drug-resistant TB (13,35). We
estimate that 60% of deaths due to TB in this setting were attributable
to treatment default and multidrug-resistance. Additional studies are
needed to quantitate the presumably greater mortality rates that result
from default and drug resistance in other settings.
Although relatively uncommon in this setting, HIV was associated with
a high overall mortality rate. Most of these deaths were due to non-TB–related
death. HIV/AIDS was the main predictor for non-TB deaths in this cohort.
In our study, eight of the nine HIV-seropositive persons died, three of
them a year or more after completing antituberculous therapy. Several
studies have demonstrated excess mortality rates after successful TB treatment
in HIV-infected patients (24,36,37);
the high rates have been attributed to HIV-related disease (38).
These data emphasize the need to improve integration of quality treatment
for both TB- and HIV-infected persons in populations that suffer from
both diseases.
The most striking finding of the molecular epidemiologic component of
this study is the association between clustering, which we interpret as
indicative of recently transmitted disease, and TB-related death. Death
due to TB was significantly more common among those who had recently transmitted
disease than those with reactivated disease (28.6% vs. 7%, p=0.01). This
association was independent of treatment default, multidrug resistance,
time of occurrence of death, weight loss, and years of formal education.
Furthermore, the effect was not modified when other variables indicative
of sociodemographic level (such as occupation, characteristics of the
household, or ethnicity) or clinical variables indicating other diseases,
including HIV infection were introduced in the model. Inferring causality
from such associations is difficult, it seems biologically implausible
that being more likely to die made people more likely to acquire recently
transmitted TB. A more plausible explanation is that rapidly progressing
to disease contributes to deterioration of the health of these patients
and thus increases their likelihood of death. The phenomenon is well described
for other diseases such as measles. However, why this would be more pronounced
for recently transmitted disease is unclear.
The association between clustering and death could be spurious because
of limitations in molecular or conventional epidemiology. The validity
of clustering as a proxy for recent transmission might be challenged by
the fact that we did not perform fingerprint analysis on all isolates
(39). Comparison between patients whose isolates were
genotyped and those whose isolates were not genotyped showed that results
of this study may not be generalizable to indigenous or lower socioeconomic
groups. Our selection of the time interval allowed us to consider TB that
was transmitted very recently and progressed to disease. The validity
of using a 1-year interval was confirmed with the sensitivity analysis
using different time periods (6, 18, 24, 30, and 36 months) as association
between clustered cases and death persisted, despite modification of the
time interval and by the fact that almost 50% of isolates with matching
DNA fingerprint patterns occurred within 1 year of identification of the
previous case. Conventional epidemiologic approaches to studying the cause
of death are difficult. Death certificate data are notoriously unreliable,
and whether patients died of TB or other causes is not certain (40).
Therefore, we added other criteria that included the interview of a close
caregiver and activity of TB at the time of death to validate our definition
of death due to TB. The cause-of-death profile derived from interview
of a close caregiver has been demonstrated to be useful for planning purposes
(41). We consider that this definition adequately identified
TB-related death as characteristics of patients dying from TB differed
from patients dying from other causes in several important aspects (drug
resistance, coexisting chronic conditions, and clinical severity) and
allowed the identification of different risk factors for TB-related death
and for death due to other causes.
If confirmed in other settings, the conclusions of this study have important
implications for control programs. Most importantly, given that current
surveillance data are collected at the conclusion of therapy, this method
probably underestimates the true impact of TB on a population’s death.
Given the increasing role of cost-efficacy modeling in setting health-care
priorities, this oversight has important consequences. In addition, if
recently acquired TB exhorts a greater mortality rate than that due to
reactivated infection, the importance of interrupting TB transmission
is further elevated.
Acknowledgments
We thank Luis Juarez and Bulmaro Cano for data processing; Ed Desmond,
Travis Jobe, and Areli Martínez-Gamboa for training and technical support
with spoligotyping; Carmen Soler for support for HIV tests; Manuel Tielve
and Rubén Acevedo for support in interpreting chest x-rays; and the physicians,
nurses, chemists, health promoters, recruiters, and interviewers in Orizaba
who supported the diagnosis, treatment, and follow-up of patients.
This study was supported by the National Institutes of Health of the
United States project no. A135969, by the Wellcome Trust, by the Howard
Hughes Medical Institute (ID 55000632) and by the Mexican Council of Science
and Technology, project nos. G26264M and 30987-M.
Dr. García-García is senior researcher and head of the Tuberculosis Unit
at the National Institute of Public Health in Cuernavaca, Mexico, and
International Research Scholar of the Howard Hughes Medical Institute.
Her research interests lie in the epidemiology of TB.
References
- Murray CJL, Styblo K, Rouillon A. Tuberculosis
in developing countries: burden, intervention and cost. Bulletin
of the International Union against Tuberculosis and Lung Disease1990;65:6–24.
- Visschedijk J, Simeant S. Targets
for health for all in the 21st century. World Health Stat Q 1998;51:56–67.
- Floyd K, Wilkinson D, Gilks C. Comparison
of cost effectiveness of directly observed treatment (DOT) and conventionally
delivered treatment for tuberculosis: experience from rural South Africa.
BMJ 1997;315:1407–11.
- Migliori GB, Ambrosetti M, Besozzi G, Farris B, Nutini S, Saini, et
al. Cost-comparison
of different management policies for tuberculosis patients in Italy.
AIPO TB Study Group. Bull World Health Organ 1999;77:467–76.
- García-García ML, Small PM, Garcia-Sancho C, Mayar ME, Ferreyra RL,
Palacios M, et.al. Tuberculosis
epidemiology and control in Veracruz, Mexico. Int J Epidemiol 1999;28:135–40.
- García-García ML, Ponce de Leon A, Jimenez Corona MA, Jimenez Corona
AJ, Palacios Martinez M, Balandrano Campos S, et al. Clinical
consequences and transmissibility of drug resistant tuberculosis in
Southern Mexico. Arch Intern Med 2000;160:630–6.
- Koster FT, Curling GC, Aziz KM, Haque A. Synergistic impact of measles
and diarrhoea on nutrition and mortality in Bangladesh. Bull World Health
Organ 1981;59:90:1–8.
- Aaby P, Andersen M, Knudsen K. Excess
mortality after early exposure to measles. Int J Epidemiol 1993;22:156–62.
- García-García ML, Palacios Martínez M, Ponce de Leon A, Jimenez Corona
ME, Jimenez Corona A, Balandrano-Campos S, et al. The
role of core groups in transmitting tuberculosis in a high prevalence
community in Southern Mexico. Int J Tuberc Lung Dis 2000;4:12–7.
- Instituto Nacional de Estadística, Geografía e informática. Estados
Unidos Mexicanos. XII censo general de población y vivienda 2000. Resultados
preliminares. Aguascalientes; Ags; Instituto Nacional de Estadística,
Geografía e Informática; 2000. p. 10.
- Dirección General de Epidemiología. Sistema Único
de Información. Secretaría de Salud 2001;18:4–7.
- Secretaría de Salud. Norma Oficial Mexicana NOM-006-SSA2 1993, para
la prevención y control de la tuberculosis en la atención primaria a
la salud. Diario Oficial de la Federación, 1995;26 de enero:20–29.
- Modificación a la Norma Oficial Mexicana NOM-006-SSA2-1993. Para
la prevención y control de la tuberculosis en la atención primaria a
la salud. Diario Oficial de la Federación, 2000;octubre 31.
- Nolte FS, Mechock B. Mycobacterium. In: Murray PR, Baron EJ, Pfaller
MA, Tenover FC, Yolken RH, editors. Manual of clinical microbiology.
6th ed. Washington (DC): ASM Press; 1995. p. 400–37.
- Instituto Nacional de Diagnóstico y Referencia Epidemiológicas. Manual
de técnicas y procedimientos de laboratorio en tuberculosis. México:
Secretaría de Salud, 1992. p. 9–20.
- van Embden JD, Cave MD, Crawford JT, Dale JW, Eisenach KD, Gicquel
B, et al.
Strain identification of Mycobacterium tuberculosis by DNA fingerprinting:
recommendations for a standardized methodology. J Clin Microbiol
1993;31:406–9.
- Woelffer GB, Bradford WZ, Paz A, Small PM. A
computer-assisted molecular epidemiologic approach to confronting the
reemergence of tuberculosis. Am J Med Sci 1996;311:17–22.
- Kamerbeek J, Schouls L, Kolk A, van Agterveld M, van Soolingen D,
Kuijper S, et al. Simultaneous
detection and strain differentiation of Mycobacterium tuberculosis
for diagnosis and epidemiology. J Clin Microbiol 1997;35:907–14.
- Van Soolingen D, Qian L, de Haas PE, Douglas JT, Traore H, Portaels
F, et al. Predominance
of a single genotype of Mycobacterium tuberculosis in countries
of east Asia. J Clin Microbiol 1995;33:3234–8.
- Jasmer RM, Hahn JA, Small PM, Daley CL, Behr MA, Moss AR, et al.
A
molecular epidemiologic analysis of tuberculosis trends in San Francisco,
1991–1997. Ann Intern Med 1999;130:971–8.
- Hennekens CH, Buring J. Epidemiology in medicine.
Boston: Little, Brown and Company; 1986. p. 87–90.
- Computing Resource Center. Stata reference manual: release 3. 5th
ed. Santa Monica (CA): The Center; 1992.
- World Health Organization. Global tuberculosis control (WHO/CDS/TB/2001.287).
Geneva, Switzerland: The Organization; 2001.
- Connolly C, Davies GR, Wilkinson D. Impact
of the human immunodeficiency virus epidemic on mortality among adults
with tuberculosis in rural South Africa, 1991–1998. Int J Tuberc
Lung Dis 1998;2:919–25.
- Lienhardt C, Manneh K, Bouchier V, Lahai G, Milligan PJ , McAdam
KP. Factors
determining the outcome of treatment of adult smear-positive tuberculosis
cases in The Gambia. Int J Tuberc Lung Dis 1998;2:712–8.
- Olle-Goig JE.
Patients with tuberculosis in Bolivia: why do they die? Rev Panam
Salud Publica 2000;8:151–5.
- Harries AD, Nyirenda TE, Banerjee A, Boeree MJ, Salaniponi FM. Treatment
outcome of patients with smear-negative and smear-positive pulmonary
tuberculosis in the National Tuberculosis Control Programme, Malawi.
Trans R Soc Trop Med Hyg 1999;93:443–6.
- Datta M, Radhamani MP, Selvaraj R, Paramasivan CN, Gopalan BN, Sudeendra
CR, et al. Critical
assessment of smear-positive pulmonary tuberculosis patients after chemotherapy
under the district tuberculosis programme. Tuber Lung Dis 1993;74:180–6.
- Grzybowski S, Enarson D. [Results in pulmonary tuberculosis patients
under various treatment program conditions]. Bulletin of the International
Union against Tuberculosis.1978;53:70–5.
- Mexican Ministry of Health. Vital statistics. [cited 2001 Jul 4] Available
from: URL: http://www.ssa.gob.mx/unidades/dgied/sns/vitales/cuadro3.htm
- Bustamante-Montes LP, Escobar-Mesa A, Borja-Aburto
VH, Gomez-Muñoz A, Becerra-Posada F. Predictors
of death from pulmonary tuberculosis: the case of Veracruz, Mexico.
Int J Tuberc Lung Dis 2000;4:208–15.
- Lawn SD, Acheampong JW. Pulmonary
tuberculosis in adults: factors associated with mortality at a Ghanaian
teaching hospital. West Afr J Med 1999;18:270–4.
- Burman WJ, Cohn DL, Rietmeijer CA, Judson FN, Sbarbaro JA, Reves
RR. Noncompliance
with directly observed therapy for tuberculosis. Epidemiology and effect
on the outcome of treatment. Chest 1997;111:1168–73.
- Espinal MA, Kim SJ, Suarez PG, Kam KM, Khomenko AG, Migliori GB,
et al. Standard
short-course chemotherapy for drug-resistant tuberculosis: treatment
outcomes in 6 countries. JAMA 2000;283:2537–45.
- Espinal MA, Dye C, Raviglione M, Kochi A. Rational
'DOTS plus' for the control of MDR-TB. Int J Tuberc Lung Dis 1999;3:561–3.
- Connolly C, Reid A, Davies G, Sturm W, McAdam KP, Wilkinson D. Relapse
and mortality among HIV-infected and uninfected patients with tuberculosis
successfully treated with twice weekly directly observed therapy in
rural South Africa. AIDS 1999;13:1543–7.
- Perriens JH, St. Louis ME, Mukadi YB, Brown C, Prignot J, Pouthier
F, et al. Pulmonary
tuberculosis in HIV-infected patients in Zaire. A controlled trial of
treatment for either 6 or 12 months. N Engl J Med 1995;332:779–84.
- Lucas SB, Hounnou A, Peacock C, Beaumel D, Djomand G, N´gbichi JM,
et al. The
mortality and pathology of HIV infection in a West African city.
AIDS 1993;7:1569–79.
- Glynn JR, Vynnycky E, Fine PE. Influence
of sampling on estimates of clustering and recent transmission of Mycobacterium
tuberculosis derived from DNA fingerprinting techniques. Am
J Epidemiol 1999;149:366–71.
- Heldal E, Naalsund A, Kongerud J, Tverdal A, Boe J. Deaths
from active tuberculosis: can we rely on notification and mortality
figures? Tuber Lung Dis 1996;77:215–21.
- Kahn K, Tollman SM, Garenne M, Gear JS. Who
dies from what? Determining cause of death in South Africa's rural north-east.
Trop Med Int Health 1999;4:433–41.
Table
1. Sociodemographic, clinical, bacteriologic,
and therapeutic characteristics of smear-positive pulmonary tuberculosis
(TB) patients according to cause of death, Orizaba, Veracruz, 1995–2000 |
|
Variables
|
Died from TB (n=34) (%)
|
Died from other causes (n=47) (%)
|
Survived (n=373) (%)
|
p valuea
|
|
Sociodemographic
|
|
|
|
|
Median age (range)
|
30 (24–73)
|
47 (22–70)
|
40.5 (12–82)
|
0.05
|
Men
|
52.9
|
76.6
|
57.9
|
0.04
|
Indigenous origin
|
20.6
|
4.3
|
16.1
|
0.07
|
<6 years formal education
|
73.5
|
76.6
|
62.2
|
0.02
|
Rural and industrial workers
|
11.8
|
25.5
|
23.6
|
0.2
|
Previous imprisonment
|
14.7
|
34.0
|
27.9
|
0.2
|
Previous TB treatment
|
47.1
|
34.0
|
14.2
|
<0.0001
|
Previous hospitalization
|
58.8
|
51.1
|
45.6
|
0.2
|
Residence in shelters
|
5.9
|
10.6
|
5.1
|
0.3
|
Alcohol use
|
38.2
|
66.0
|
43.7
|
0.005
|
Household crowding
|
47.1
|
27.7
|
37.5
|
0.2
|
Household with earthen floor
|
20.6
|
10.6
|
16.6
|
0.4
|
Clinical
|
|
|
|
HIV infection
|
8.8
|
10.6
|
.3
|
<0.0001
|
Hepatic cirrhosis
|
0
|
6.4
|
1.3
|
0.06
|
Body mass index (<18)
|
47.1
|
27.7
|
20.4
|
<0.0001
|
Hemoptysis
|
26.5
|
38.3
|
37.8
|
0.5
|
Fever
|
44.1
|
61.7
|
44
|
0.04
|
Night sweats
|
58.8
|
59.6
|
57.6
|
0.2
|
Weight loss (>15 %)
|
47.1
|
46.8
|
29.2
|
0.002
|
Radiologic nodes
|
5.9
|
6.4
|
7.0
|
0.9
|
Cavities
|
44.1
|
25.5
|
33.2
|
0.2
|
Median time interval between
initiation of symptoms and
treatment (range in days)
|
17 (1–212)
|
8 (0–158)
|
5 (0–322)
|
0.004
|
Median time interval between diagnosis
and treatment (range in days)
|
141.5 (78–991)
|
126 (4–439)
|
99.5 (4–1,723)
|
0.01
|
Bacteriologic
|
|
|
|
Resistance to isoniazid and rifampin
|
29.4
|
17.0
|
2.1
|
<0.0001
|
Other resistance
|
11.8
|
19.1
|
12.9
|
0.2
|
<10 bacilli per 100 fields
|
79.4
|
87.2
|
86.1
|
0.5
|
Median time interval between treatment
and sputum conversion (range in days)
|
95 (35–530)
|
44 (19–182)
|
42.5 (15–348)
|
0.03
|
Treatment
outcome |
|
|
|
Cure
|
5.9
|
61.7
|
87.4
|
<0.0001
|
Failure
|
20.6
|
10.6
|
2.1
|
<0.0001
|
Default
|
32.4
|
10.6
|
6.7
|
<0.0001
|
Retreatment
|
17.6
|
23.4
|
5.4
|
<0.0001
|
|
aChi
square test, analysis of variance test. |
Table
2. Population attributable-risk percent
and hazard ratios for death among smear-positive tuberculosis (TB)
patients, Orizaba, Veracruz, 1995–2000a |
|
Variables
|
Population attributable risk (%)
|
Adjusted
hazard ratio
|
95% CI
|
p valueb
|
|
Death due to TBc
|
Treatment default
|
28.7
|
8.9
|
3.3 to 24.4
|
<0.0001
|
Resistance to isoniazid and rifampin
|
25.9
|
5.7
|
2.0 to 16.3
|
<0.001
|
Clustered
|
18.8
|
4.1
|
1.6 to 10.0
|
0.002
|
Weight loss (>15%)
|
—
|
3.9
|
1.5 to 10.9
|
0.007
|
Formal education <6 yr
|
—
|
1.8
|
0.6 to 5.2
|
0.3
|
Death due to other causes
|
HIV/AIDS
|
11.1
|
33.1
|
11.4 to 95.4
|
<0.0001
|
Hepatic cirrhosis
|
6.6
|
5.7
|
1.6 to 19.7
|
0.006
|
Weight loss (>15% )
|
—
|
3.3
|
1.6 to 6.7
|
0.001
|
Age (yrs)
|
—
|
1.02
|
0.99 to 1.04
|
0.07
|
|
aCI,
confidence interval; —, not applicable.
bCox proportional hazards model.
cControlling for death before or after treatment completion,
default or failure. |
|