Treatment of multidrug resistant tuberculosis (MDR-TB) is lengthy, toxic, expensive, and has generally poor outcomes. We undertook an individual patient data meta-analysis to assess the impact on outcomes of the type, number, and duration of drugs used to treat MDR-TB. Three recent systematic reviews were used to identify studies reporting treatment outcomes of microbiologically confirmed MDR-TB. Study authors were contacted to solicit individual patient data including clinical characteristics, treatment given, and outcomes. Random effects multivariable logistic meta-regression was used to estimate adjusted odds of treatment success. Adequate treatment and outcome data were provided for 9,153 patients with MDR-TB from 32 observational studies. Treatment success, compared to failure/relapse, was associated with use of: later generation quinolones, (adjusted odds ratio [aOR]: 2.5 [95% CI 1.1–6.0]), ofloxacin (aOR: 2.5 [1.6–3.9]), ethionamide or prothionamide (aOR: 1.7 [1.3–2.3]), use of four or more likely effective drugs in the initial intensive phase (aOR: 2.3 [1.3–3.9]), and three or more likely effective drugs in the continuation phase (aOR: 2.7 [1.7–4.1]). Similar results were seen for the association of treatment success compared to failure/relapse or death: later generation quinolones, (aOR: 2.7 [1.7–4.3]), ofloxacin (aOR: 2.3 [1.3–3.8]), ethionamide or prothionamide (aOR: 1.7 [1.4–2.1]), use of four or more likely effective drugs in the initial intensive phase (aOR: 2.7 [1.9–3.9]), and three or more likely effective drugs in the continuation phase (aOR: 4.5 [3.4–6.0]). In this individual patient data meta-analysis of observational data, improved MDR-TB treatment success and survival were associated with use of certain fluoroquinolones, ethionamide, or prothionamide, and greater total number of effective drugs. However, randomized trials are urgently needed to optimize MDR-TB treatment. Please see later in the article for the Editors' Summary. In 2010, 8.8 million people developed tuberculosis—a contagious bacterial infection—and 1.4 million people died from the disease. Mycobacterium tuberculosis, the bacterium that causes tuberculosis, is spread in airborne droplets when people with the disease cough or sneeze and usually infects the lungs (pulmonary tuberculosis). The characteristic symptoms of tuberculosis are a persistent cough, weight loss, and night sweats. Tuberculosis can be cured by taking several powerful antibiotics regularly for at least 6 months. The standard treatment for tuberculosis comprises an initial intensive phase lasting 2 months during which four antibiotics are taken daily followed by a 4-month continuation phase during which two antibiotics are taken. However, global efforts to control tuberculosis are now being thwarted by the emergence of M. tuberculosis strains that are resistant to several antibiotics, including isoniazid and rifampicin, the two most powerful, first-line (standard) anti-tuberculosis drugs. Although multi-drug resistant tuberculosis (MDR-TB) can be cured using second-line anti-tuberculosis drugs, these are more expensive and more toxic than first-line drugs and optimal treatment regimens for MDR-TB have not been determined. Notably, there have been no randomized controlled trials of treatments for MDR-TB. Such trials, which compare outcomes (cure, treatment failure, relapse, and death) among patients who have been randomly assigned to receive different treatments, are the best way to compare different anti-tuberculosis drug regimens. It is possible, however, to get useful information about the association of various treatments for MDR-TB with outcomes from observational studies using a statistical approach called “individual patient data meta-analysis.” In observational studies, because patients are not randomly assigned to different treatments, differences in outcomes between treatment groups may not be caused by the different drugs they receive but may be due to other differences between the groups. An individual patient data meta-analysis uses statistical methods to combine original patient data from several different studies. Here, the researchers use this approach to investigate the association of specific drugs, numbers of drugs and treatment duration with the clinical outcomes of patients with pulmonary MDR-TB. The researchers used three recent systematic reviews (studies that use predefined criteria to identify all the research on a given topic) to identify studies reporting treatment outcomes of microbiologically confirmed MDR-TB. They obtained individual patient data from the authors of these studies and estimated adjusted odds (chances) of treatment success from the treatment and outcome data of 9,153 patients with MDR-TB provided by 32 centers. The use of later generation quinolones, ofloxacin, and ethionamide/prothionamide as part of multi-drug regimens were all associated with treatment success compared to failure, relapse or death, as were the use of four or more likely effective drugs (based on drug susceptibility testing of mycobacteria isolated from study participants) during the initial intensive treatment phase and the use of three or more likely effective drugs during the continuation phase. The researchers also report that among patients who did not die or stop treatment, the chances of treatment success increased with the duration of the initial treatment phase up to 7.1–8.5 months and with the total duration of treatment up to 18.6–21.5 months. These findings suggest that the use of specific drugs, the use of a greater number of effective drugs, and longer treatments may be associated with treatment success and the survival of patients with MDR-TR. However, these findings need to be interpreted with caution because of limitations in this study that may have affected the accuracy of its findings. For example, the researchers did not include all the studies they found through the systematic reviews in their meta-analysis (some authors did not respond to requests for individual patient data, for example), which may have introduced bias. Moreover, because the patients included in the meta-analysis were treated at 32 centers, there were many differences in their management, some of which may have affected the accuracy of the findings. Because of these and other limitations, the researchers note that, although their findings highlight several important questions about the treatment of MDR-TB, randomized controlled trials are urgently needed to determine the optimal treatment for MDR-TB. Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001300.

We analyzed a global collection ofMycobacterium tuberculosisstrains using 212 single nucleotide polymorphism (SNP) markers. SNP nucleotide diversity was high (average across all SNPs, 0.19), and 96% of the SNP locus pairs were in complete linkage disequilibrium. Cluster analyses identified six deeply branching, phylogenetically distinct SNP cluster groups (SCGs) and five subgroups. The SCGs were strongly associated with the geographical origin of theM. tuberculosissamples and the birthplace of the human hosts. The most ancestral cluster (SCG-1) predominated in patients from the Indian subcontinent, while SCG-1 and another ancestral cluster (SCG-2) predominated in patients from East Asia, suggesting thatM. tuberculosisfirst arose in the Indian subcontinent and spread worldwide through East Asia. Restricted SCG diversity and the prevalence of less ancestral SCGs in indigenous populations in Uganda and Mexico suggested a more recent introduction ofM. tuberculosisinto these regions. The East African Indian and Beijing spoligotypes were concordant with SCG-1 and SCG-2, respectively; X and Central Asian spoligotypes were also associated with one SCG or subgroup combination. Other clades had less consistent associations with SCGs. Mycobacterial interspersed repetitive unit (MIRU) analysis provided less robust phylogenetic information, and only 6 of the 12 MIRU microsatellite loci were highly differentiated between SCGs as measured byG_ST. Finally, an algorithm was devised to identify two minimal sets of either 45 or 6 SNPs that could be used in future investigations to enable global collaborations for studies on evolution, strain differentiation, and biological differences ofM. tuberculosis.

The molecular basis for isoniazid resistance in Mycobacterium tuberculosis is complex. Putative isoniazid resistance mutations have been identified in katG , ahpC , inhA , kasA , and ndh . However, small sample sizes and related potential biases in sample selection have precluded the development of statistically valid and significant population genetic analyses of clinical isoniazid resistance. We present the first large-scale analysis of 240 alleles previously associated with isoniazid resistance in a diverse set of 608 isoniazid-susceptible and 403 isoniazid-resistant clinical M. tuberculosis isolates. We detected 12 mutant alleles in isoniazid-susceptible isolates, suggesting that these alleles are not involved in isoniazid resistance. However, mutations in katG , ahpC , and inhA were strongly associated with isoniazid resistance, while kasA mutations were associated with isoniazid susceptibility. Remarkably, the distribution of isoniazid resistance-associated mutations was different in isoniazid-monoresistant isolates from that in multidrug-resistant isolates, with significantly fewer isoniazid resistance mutations in the isoniazid-monoresistant group. Mutations in katG 315 were significantly more common in the multidrug-resistant isolates. Conversely, mutations in the inhA promoter were significantly more common in isoniazid-monoresistant isolates. We tested for interactions among mutations and resistance to different drugs. Mutations in katG , ahpC , and inhA were associated with rifampin resistance, but only katG 315 mutations were associated with ethambutol resistance. There was also a significant inverse association between katG 315 mutations and mutations in ahpC or inhA and between mutations in kasA and mutations in ahpC . Our results suggest that isoniazid resistance and the evolution of multidrug-resistant strains are complex dynamic processes that may be influenced by interactions between genes and drug-resistant phenotypes.

Objective To determine the clinical consequences of pulmonary tuberculosis (TB) among patients with diabetes mellitus (DM). Methods We conducted a prospective study of patients with TB in Southern Mexico. From 1995 to 2010, patients with acid-fast bacilli or Mycobacterium tuberculosis in sputum samples underwent epidemiological, clinical and microbiological evaluation. Annual follow-ups were performed to ascertain treatment outcome, recurrence, relapse and reinfection. Results The prevalence of DM among 1262 patients with pulmonary TB was 29.63% (n=374). Patients with DM and pulmonary TB had more severe clinical manifestations (cavities of any size on the chest x-ray, adjusted OR (aOR) 1.80, 95% CI 1.35 to 2.41), delayed sputum conversion (aOR 1.51, 95% CI 1.09 to 2.10), a higher probability of treatment failure (aOR 2.93, 95% CI 1.18 to 7.23), recurrence (adjusted HR (aHR) 1.76, 95% CI 1.11 to 2.79) and relapse (aHR 1.83, 95% CI 1.04 to 3.23). Most of the second episodes among patients with DM were caused by bacteria with the same genotype but, in 5/26 instances (19.23%), reinfection with a different strain occurred. Conclusions Given the growing epidemic of DM worldwide, it is necessary to add DM prevention and control strategies to TB control programmes and vice versa and to evaluate their effectiveness. The concurrence of both diseases potentially carries a risk of global spreading, with serious implications for TB control and the achievement of the United Nations Millennium Development Goals.

OBJECTIVE—To determine the impact of diabetes on the rates of tuberculosis in a region where both diseases are prevalent. RESEARCH DESIGN AND METHODS—Data from a population-based cohort of patients with pulmonary tuberculosis undergoing clinical and mycobacteriologic evaluation (isolation, identification, drug-susceptibility testing, and IS6110-based genotyping and spoligotyping) were linked to the 2000 National Health Survey (ENSA2000), a national probabilistic, polystage, stratified, cluster household survey of the civilian, noninstitutionalized population of Mexico. RESULTS—From March 1995 to March 2003, 581 patients with Mycobacterium tuberculosis culture and fingerprint were diagnosed, 29.6% of whom had been diagnosed previously with diabetes by a physician. According to the ENSA2000, the estimated prevalence of diabetes in the study area was 5.3% (95% CI 4.1–6.5). The estimated rates of tuberculosis for the study area were greater for patients with diabetes than for nondiabetic individuals (209.5 vs. 30.7 per 100,000 person-years, P < 0.0001). CONCLUSIONS—In this setting, the rate of tuberculosis was increased 6.8-fold (95% CI 5.7–8.2, P < 0.0001) in patients with diabetes due to increases in both reactivated and recently transmitted infection. Comorbidity with diabetes may increase tuberculosis rates as much as coinfection with human immunodeficiency virus (HIV), with important implications for the allocation of health care resources.