= 38
MDR, multidrug resistant (TB).
Outcome | ||||
---|---|---|---|---|
Non-adherence multivariate OR (95% CI) | Default multivariate OR (95% CI) | |||
Male | 0.66 | 0.28–1.55 | 0.85 | 0.27–2.61 |
Age > 40 | 0.84 | 0.37–1.90 | 1.98 | 0.65–6.08 |
Unemployed | 1.15 | 0.49–2.69 | 2.62 | 0.76–9.06 |
Previously incarcerated | 1.06 | 0.39–2.86 | 0.69 | 0.20–2.41 |
Baseline alcoholism noted on initiation of treatment | 4.48 | 1.58–12.68 | 15.57 | 3.46–70.02 |
Alcohol abuse first noted after initiation of treatment | 6.35 | 2.27–17.75 | 5.14 | 0.87–30.25 |
Intravenous drug user at initiation of treatment | 16.64 | 3.24–85.56 | 2.58 | 0.21–30.96 |
Any substance abuse | 7.30 | 2.89–18.46 | 11.20 | 2.55–49.17 |
Co-morbid conditions associated with side-effects | NI | 7.20 | 1.94–26.75 |
CI, confidence interval; OR, odds ratio. a Included in default model only. Other variables included in both models. b Included in model excluding alcoholism and drug use variables. c Not included.
Sputum-smear positivity was the only factor associated significantly with baseline MDR in both a univariate analysis (OR=2.4, 95% CI: 1.04–5.57) and in a multivariate logistic regression model that included age and substance abuse (OR = 3.28, 95% CI: 1.24–8.68). Factors associated significantly with MDR acquisition in a univariate analysis included substance abuse, hospitalization (both at initiation of treatment and later in the course of therapy) and failure to self-administer therapy ( Figs. 2 , ,3, 3 , ,4; 4 ; and Table 4 , available at http://www.who.int/bulletin/volumes/85/9/06-038331/en/index.html ). In the multivariate Cox proportional hazards model, treatment received in the hospital setting (either at initiation of therapy or later) was the only remaining independent risk factor for MDR acquisition. Patients who received treatment in the hospital setting had a substantially higher risk of developing MDR-TB than those whose treatment was confined to the outpatient sector. This was true for those who began DOTS treatment in the hospital setting (adjusted hazard ratio, HR: 6.34; P = 0.02) and those who were hospitalized only later in their treatment course (adjusted HR: 6.26; P = 0.04).
Kaplan-Meier survival curves for substance abuse as a factor associated with time to acquisition of multidrug resistance
Kaplan-Meier survival curves for hospitalization as a factor associated with time to acquisition of multidrug resistance
Kaplan-Meier survival curves for failure to self-administer therapy as a factor associated with time to acquisition of multidrug resistance
Cohort characteristics | Number of events | Person time in months | Univariate hazard ratio | -value | Multivariate hazard ratio | -value |
---|---|---|---|---|---|---|
Age | ||||||
≤ 40 | 7 | 2442 | 1.06 | 0.90 | 0.70 | 0.52 |
> 40 | 8 | 2586 | ||||
Gender | ||||||
male | 11 | 2920 | 1.93 | 0.24 | 1.67 | 0.39 |
female | 4 | 2108 | ||||
Not-adherent | ||||||
yes | 2 | 736 | 0.81 | 0.77 | 1.61 | 0.53 |
no | 13 | 4267 | ||||
Substance abuse | ||||||
yes | 10 | 1944 | 2.88 | 0.04 | 1.96 | 0.26 |
no | 5 | 3084 | ||||
Side-effects | NI | |||||
yes | 4 | 855 | 1.69 | 0.39 | ||
no | 11 | 4173 | ||||
Baseline cavity present | NI | |||||
yes | 11 | 3432 | 1.25 | 0.69 | ||
no | 4 | 1596 | ||||
Previously incarcerated | NI | |||||
yes | 3 | 656 | 1.56 | 0.51 | ||
no | 12 | 4372 | ||||
Smear ++ or +++ | NI | |||||
yes | 4 | 1584 | 0.79 | 0.68 | ||
no | 11 | 3444 | ||||
Began treatment in hospital | ||||||
yes | 10 | 1703 | 3.8 | 0.01 | 6.34 | 0.02 |
no | 5 | 3325 | ||||
Hospitalized later during therapy only | ||||||
yes | 13 | 2195 | 8.18 | < 0.001 | 6.26 | 0.047 |
no | 2 | 2833 | ||||
Self-administered treatment | NI | |||||
yes | 2 | 1847 | 0.25 | 0.03 | ||
no | 13 | 3181 |
a Individuals who were hospitalized at initiation of therapy as well as later were included only in the hospitalized at initiation category.
Table 5 (available at http://www.who.int/bulletin/volumes/85/9/06-038331/en/index.html ) demonstrates the differing risk factors for early and late acquisition of MDR – of the seven patients who developed MDR within four months of initiating treatment, all had cavitary disease at baseline and six began treatment in the hospital. In a multivariate analysis, those who initiated treatment in the hospital were more likely to develop early MDR, but this finding failed to achieve statistical significance (adjusted HR: 7.18, P = 0.07). In contrast, univariate risk factors for MDR after 6 months of treatment included male gender (HR: 5.12, P = 0.06), substance abuse (HR: 11.22, P = 0.004) and absence of smear positivity (HR: 0, P = 0.01). In a multivariate Cox proportional hazards model substance abuse was the only statistically significant factor (adjusted HR: 9.09, P = 0.04), although patients who had been hospitalized at some point during their illness were also more likely to develop late MDR (HR: 4.52, P = 0.07).
Cohort characteristics | Early MDR ( = 7) | Late MDR ( = 8) | |||||||
---|---|---|---|---|---|---|---|---|---|
Univariate HR | -value | Multivariate HR | -value | Univariate HR | -value | Multivariate HR | -value | ||
Age | NI | NI | |||||||
≤ 40 | 1.28 | 0.74 | 0.90 | 0.89 | |||||
> 40 | |||||||||
Gender | NI | ||||||||
male | 0.89 | 0.88 | 5.12 | 0.06 | 2.58 | 0.389 | |||
female | |||||||||
Not-adherent | NI | ||||||||
yes | 0 | 0.12 | 0 | NA | 1.86 | 0.47 | |||
no | |||||||||
Substance abuse | NI | ||||||||
yes | 1.04 | 0.96 | 11.22 | 0.004 | 9.09 | 0.046 | |||
no | |||||||||
Side effects | |||||||||
yes | 3.53 | 0.12 | 2.92 | 0.16 | 0.65 | 0.67 | NI | ||
no | |||||||||
Baseline cavity present | NI | NI | |||||||
yes | Inf | 0.025 | Inf | NA | 0.47 | 0.30 | |||
no | 0 | ||||||||
Previously incarcerated | NI | NI | |||||||
yes | 0.97 | 0.98 | 2.20 | 0.37 | |||||
no | |||||||||
Smear ++ or +++ | |||||||||
yes | 2.86 | 0.17 | 1.16 | 0.84 | 0 | 0.01 | 0 | ||
no | |||||||||
Began treatment in hospital | NI | ||||||||
yes | 10.87 | 0.006 | 7.18 | 0.07 | 1.98 | 0.34 | |||
no | |||||||||
Hospitalized later during therapy only | NI | ||||||||
yes | 1.50 | 0.72 | 3.53 | 0.17 | 4.52 | 0.07 | |||
no |
MDR, multidrug resistant (TB). a No early cases of acquired MDR were non-adherent. b All early cases of acquired MDR had cavitary disease. c No late cases were smear-positive.
Notably, non-adherence was not a risk factor for either early or late acquisition of MDR. This finding remained true when we conducted a sensitivity analysis in which patients were classified non-adherent if they missed 40% or more of their prescribed doses.
In this study of non-adherence, default and acquisition of MDR among TB patients in Tomsk, substance abuse and in-hospital care were identified as two potential obstacles to effective treatment. These results suggest that DOTS programmes might be more likely to achieve TB control targets if they include interventions aimed at improving adherence by diagnosing and treating substance abuse concurrently with standard TB therapy. They also raise the possibility that some patients with apparent drug-sensitive disease also may be infected with drug-resistant strains that are unmasked upon initiation of therapy. Some patients also might be reinfected with drug-resistant strains in the hospital setting, a possibility which emphasizes the need for effective infection-control measures within facilities that care for patients with active disease.
Despite the implementation of a DOTS programme and the provision of extensive social services to patients undergoing TB therapy, non-adherence and default continued in a substantial proportion of those who initiated treatment in Tomsk. Like TB patients throughout the world, these patients were burdened with a wide array of social and medical problems: many were unemployed, had been in prison or had significant co-morbid conditions. Despite this, alcohol and injection drug use were the only independent risk factors for non-adherence and default that we identified. These findings echo those of numerous previous studies that found substance abuse to be the single major factor associated most strongly with non-compliance with TB regimens. 7 – 15 Our results also agree with these previous studies’ findings that non-adherence has important adverse effects on the outcomes of TB treatment 16 , 17 – 66% of all poor outcomes experienced in our cohort occurred among the 16% of patients who did not adhere to therapy.
Despite the clear need for new approaches to this problem, to date there has been relatively little research on treatment options for patients with chronic infectious diseases and concomitant substance misuse or psychiatric problems. The few TB programmes that have explicitly offered patients treatment for substance abuse generally have demonstrated better outcomes than “unexpanded” DOTS programmes. 18 Some even achieve very high cure rates among patient populations in which alcoholism or injection drug use are common. 19 Disappointingly, these successes have not yet led to widespread integration of substance-abuse care for these patients.
This failure has at least three possible explanations. The first is the general reluctance to tinker with the specialized “vertical” DOTS approach, given its success in improving case completion and cure rates in developing and less-developed countries over the past two decades. 20 Closely related to this are the numerous obstacles faced by multidisciplinary approaches to research and patient care, including the lack of a shared language and space among care providers from different specialties and mutual lack of knowledge of other treatment approaches. 21 Often the care of TB patients and those with substance-use disorders is relegated to highly specialized practitioners; this offers little opportunity for meaningful interaction or exchange between disciplines. Finally, until recently many physicians without specific expertise in managing alcohol disorders and injection drug misuse have assumed that these conditions’ treatments are too complex and intensive to be carried out simultaneously with the treatment of another complex disease. However, recent evidence suggests that brief interventions, social skills training, behaviour contracting and pharmacotherapy are among the most effective approaches for treatment of substance-use disorders. 22 – 24 These data raise the possibility that integrated management of these most vulnerable TB patients may be within the reach of a unified TB care facility.
Our study also suggests that non-adherence did not contribute to either the early or late occurrence of MDR among patients receiving DOTS in this setting. We considered several other possible explanations for the observation that a group of adherent patients developed MDR-TB within 24 months of initiating therapy. First, we speculated that MDR acquisition might be associated with disease severity, which might in turn be linked to hospitalization. Since the number of new mutations that code for drug resistance will be a function of the bacterial load, it follows that those with a greater disease burden would be at higher risk of developing these mutations. 25 Having adjusted for disease severity by controlling for the presence or absence of cavitary disease and sputum-smear status, we found that these markers of disease severity were strongly correlated with early acquisition of MDR but not associated with late acquisition. These data suggest that these patients may harbour multiple different strains of Mycobacterium TB, some of which may be drug-resistant. In these mixed infections, standard short-course therapy may have unmasked the drug-resistant strain population by suppressing the previously dominant drug-sensitive strain. Indeed, van Rie et al. have described this mechanism in a high-burden population in South Africa. 26 In that study, adherence to a first-line drug therapy was shown to select for a resistant population, while non-adherence led to re-emergence of the drug-susceptible strains.
We also assessed the possibility that patients who developed MDR did so through “amplification” of existing drug resistance. While this mechanism may have accounted for MDR acquisition in some cases, eight of the thirteen hospitalized patients with this outcome had fully susceptible disease on initiation of therapy.
Finally, we considered the possibility that some of these patients developed MDR-TB as a result of reinfection with a drug-resistant strain of TB. Reinfection of patients on therapy for drug-sensitive disease has been described in several different high-incidence settings and has been associated with nosocomial transmission. 27 – 31 Usually, MDR-TB patients in the Russian Federation are not placed on respiratory precautions in the hospitals or clinics where they receive care, so there is opportunity for further spread of drug-resistant strains among patients receiving therapy for drug-sensitive disease. The finding that substance abuse was a risk factor for late occurrence of MDR also raises the possibility that these patients are at higher risk of exposure to drug-resistant disease or are more susceptible to reinfection than other patients. Future studies on the association between adherence and development of MDR would benefit from molecular typing of sequential isolates in patients undergoing therapy.
This study was limited by its retrospective study design, as sociodemographic and behavioural variables were abstracted from routine medical assessments conducted upon initiation of therapy. In particular, the diagnoses of alcohol and drug disorders were based on clinicians’ reports and were not made using a standardized instrument. Hence, it is likely that alcohol disorders were underreported and that only more severe cases came to clinical attention. This could have resulted in an underestimation of the effect of alcoholism if less severe cases were also associated with non-adherence. Systematic studies using standardized and validated alcohol assessment instruments will be needed to ascertain the full impact of alcohol disorders on patients’ ability to comply with TB treatment. ■
The authors wish to thank Natasha Arlyapova, Donna Barry, Doreen Balbuena, Lauren Doctoroff, Paul Farmer, Jennifer Furin, Timothy Holtz, Gwyneth Jones, Jim Yong Kim, Tatyana Lyagoshina, Sergey Pavlovich Mishustin, Joia Mukherjee, Ed Nardell, Michael Nikiforov, Alexander Pasechnikov, Genady Giorgevich Peremitin, Oksana Ponomarenko, Michael Rich, Sonya Shin, Olga Sirotkina, Tamara Tonkel and Askar Yedilbayev for their contributions to this study.
Funding and competing interests: Two authors (Keshavjee and Gelmanova) received partial salary support and/or travel support from the Bill & Melinda Gates Foundation and from the Eli Lilly International Foundation. Keshavjee received salary support from the Frank Hatch Scholars Program at Brigham & Women’s Hospital. No funder played any role in study design, data collection, analysis or interpretation; or in preparing, reviewing or approving the manuscript.
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Schools have adopted random drug testing to hopefully reduce drug use among students (Frequently Asked Questions About Drug Testing in Schools). Drug tests usually test for marijuana, cocaine, opioids pain relievers oxycontin and vicodin, amphetamines, and PCP.
Document Date: July 7, 2002. These days, more and more schools are testing kids for drug use. The theory is that if students know they might be tested, they'll just say no to drugs. Unfortunately, what these schools don't realize is that drug testing is NOT the answer to their drug problems. For one thing, there is no concrete evidence that ...
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Starting in January, students at the high school will be tested at least once a year for illicit drugs, alcohol, nicotine and other banned substances: Students are required to consent to the ...
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Those who are culture-positive also undergo drug sensitivity testing to isoniazid, rifampicin, ethambutol, streptomycin and kanamycin. Susceptibility is determined using the absolute concentration method on Lowenstein-Jensen medium, based on the following drug concentrations: isoniazid 1 μg/ml, rifampicin 40 μg/ml, ethambutol 5 μg/ml and ...
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