Rapid Diagnosis of Tuberculosis with the Xpert MTB/RIF Assay in High Burden Countries: A Cost-Effectiveness Analysis

A cost-effectiveness study by Frank Cobelens and colleagues reveals that Xpert MTB/RIF is a cost-effective method of tuberculosis diagnosis that is suitable for use in low- and middle-income settings

Patterns of treatment interruption among patients with multidrug-resistant TB (MDR TB) and association with interim and final treatment outcomes.

BACKGROUND: The reasons that patients with multidrug-resistant tuberculosis (MDR TB) miss treatment are multi-factorial and complex. Identifying patterns of treatment interruption that predict poor outcomes can be used to target program activities aiming to improve treatment adherence. OBJECTIVE: To characterize patterns of treatment interruption among MDR TB patients and determine the association between patterns and treatment outcomes. METHODS: Retrospective analysis of MDR TB patients. A treatment interruption was defined as any time that a patient missed a prescribed dose of treatment for at least 1 day but for a period of less than 2 consecutive months. Patients were characterized by the number, length and variability of interruptions, variability of time between interruptions, and percent of missed doses. Final treatment outcome was dichotomized as a successful (cured or completed) or poor outcome (defaulted, failed, or died). Risk ratios were calculated to determine the association between characteristics of treatment interruption and treatment outcomes. All analyses were conducted in 6 month treatment intervals. RESULTS: Only 7.0% of 583 patients completed treatment without interruption. Of the remaining 542 patients, the median time to the first interruption was 2 ½ months (70 days). In multivariate analysis, patients who had longer interruptions with sporadic variability during the 6-12 month or the 12-18 month treatment period had a significantly increased risk for poor outcomes compared to patients who had short, regular interruptions (RR(adj) 4.37, 95% CI 1.2-15.8;  = 0.03 and RR(adj) 3.38, 95% CI 1.6-7.1; p = 0.001, respectively). In addition, missing 10% or more of the prescribed doses during any 6 month period in the initial 18 months of therapy significantly increased the risk for poor outcomes (RR(adj) range 1.55-2.35; p-value range 0.01-0.005). CONCLUSION: Patients that miss more consecutive days of treatment with sporadic interruption patterns or a greater proportion of treatment are at an increased risk for poor treatment outcomes

Treatment patterns among MDR TB patients, by 6 month intervals of treatment (n = 583).

<p>Four categories of treatment interruption patterns based on the patients in the period that had at least one treatment interruption (missed dose) during that period. Cut-offs to create categories based on the median of interruption characteristics (individual mean interruption length in days and the individual standard deviation of the interruption length in days) during the period, wherein individual values below and inclusive of the median value denoted short or small/regular and values exceeding the median cut-off were categorized as long or large/sporadic. The pooled median of individual mean days of interruption and standard deviation of interruption used for cut-offs was 1.14, 0 for 0–6 months; 1.21, 0.38 for 6–12 months; 1.28, 0.50 for 12–18 months, and 1.33, 0.51 for 18–24 months. N in parentheses at the top of each column reflects number of patients who were still on treatment at the beginning of the 6 month period.</p

Illustration of 4 different treatment interruption categories, based on length of interruption in days (short or long), and variability of interruption (small/regular or long/sporadic).

<p>Y-axis indicates treatment interruption as 0 (no; on treatment) or 1 (yes; interruption/missed dose).</p

Multivariate association between treatment interruption pattern characteristics for each 6 month treatment period and poor treatment outcomes (default, failure, death) among MDR TB patients with at least one missed dose during the course of treatment (n = 542).

<p>RR, rate ratio; CI, confidence interval.</p>*<p>Each variable represents characteristic for the 6 month treatment period (e.g., 0–6 months).</p>†<p>All RRs adjusted for age, number of treatment interruptions, variability of time on treatment, and whether they were underweight (BMI<18), or received kanamycin/amikacin or clarithromycin during the treatment period. RRs presented are adjusted for all other variables in the model. Dashes (–) for RR and 95% CI indicate there were not enough observations in the interruption category for that time period to derive an estimate.</p

Sociodemographic characteristics of MDR TB patients included in the present analysis (n = 583).

<p>XDR TB = extensively drug-resistance tuberculosis.</p>*<p>5000 PHP/month equals approximately $120 US dollars/month.</p>†<p>DST missing for 25 patients who were treated empirically (n = 558 with DST). DST for 1^st line drugs included isoniazid (H), rifampin (R), pyrazinamide (Z), ethambutol (E); injectable drugs tested included streptomycin (S) and kanamycin (K); 2^nd line floroquinolones tested included ciprofloxacin (Cpx) and ofloxacin (Ofx).</p>§<p>Drugs are not mutually exclusive, and indicate number and proportion of patients who were prescribed the drug at some point during the treatment course.</p><p>Values represent number of patients and proportion unless otherwise noted.</p

Treatment interruption characteristics of MDR TB patients that missed at least one dose during the course of treatment (n = 542).

<p>IQR, interquartile range.</p>*<p>Characteristics measuring duration of interruptions and duration of treatment episodes were averaged within each patient; values in the table represent the median and IQR of these averages.</p

Implementation of a multidisciplinary antimicrobial stewardship programme in a Philippine tertiary care hospital : an evaluation by repeated point prevalence surveys

ABSTRACT: Objectives: Optimising antimicrobial prescribing in hospitals through antimicrobial stewardship (AMS) is essential in addressing the global threat of antimicrobial resistance. The objective of this study was to evaluate the impact of a hospital-wide programme, delivered by a multidisciplinary AMS team, on antimicrobial prescribing outcomes. Methods: The AMS programme consisted of a combination of persuasive, restrictive, and structural components and was implemented in two phases. We used data from the Global-PPS, collected every six months between September 2017 and December 2019, to measure the antimicrobial use prevalence and monitor selected antibiotic prescribing quality indicators. Results: A significantly increasing trend (P < 0.001) was observed for the indicators related to documentation of prescribing, that is the reason for treatment and stop or review date. We observed a significantly decreasing trend (P < 0.001) in the number of prescriptions for surgical antibiotic prophylaxis (SAP) prescribed for more than 24 h; however, sample sizes for surgical patients were small. For these three indicators, a sudden and pronounced improvement was seen after the second set of interventions, which consisted of (i) an antibiotic documentation policy, (ii) a 24-h automatic stop order for SAP, and (iii) dissemination of new SAP guidelines. A significantly decreasing trend was also observed for hospital-wide antimicrobial use prevalence (P < 0.001). Conclusions: The implementation of a multidisciplinary antimicrobial stewardship programme positively influenced antibiotic prescribing practices. Further research should address long-term trends in antibiotic prescribing to establish whether these coordinated activities have led to a sustained behaviour change among prescribers, thereby also evaluating clinical outcomes and antimicrobial resistance rates

Lipoarabinomannan in sputum to detect bacterial load and treatment response in patients with pulmonary tuberculosis: Analytic validation and evaluation in two cohorts.

BackgroundLipoarabinomannan (LAM) is a major antigen of Mycobacterium tuberculosis (MTB). In this report, we evaluated the ability of a novel immunoassay to measure concentrations of LAM in sputum as a biomarker of bacterial load prior to and during treatment in pulmonary tuberculosis (TB) patients.Methods and findingsPhage display technology was used to isolate monoclonal antibodies binding to epitopes unique in LAM from MTB and slow-growing nontuberculous mycobacteria (NTM). Using these antibodies, a sandwich enzyme-linked immunosorbent assay (LAM-ELISA) was developed to quantitate LAM concentration. The LAM-ELISA had a lower limit of quantification of 15 pg/mL LAM, corresponding to 121 colony-forming units (CFUs)/mL of MTB strain H37Rv. It detected slow-growing NTMs but without cross-reacting to common oral bacteria. Two clinical studies were performed between the years 2013 and 2016 in Manila, Philippines, in patients without known human immunodeficiency virus (HIV) coinfection. In a case-control cohort diagnostic study, sputum specimens were collected from 308 patients (aged 17-69 years; 62% male) diagnosed as having pulmonary TB diseases or non-TB diseases, but who could expectorate sputum, and were then evaluated by smear microscopy, BACTEC MGIT 960 Mycobacterial Detection System (MGIT) and Lowenstein-Jensen (LJ) culture, and LAM-ELISA. Some sputum specimens were also examined by Xpert MTB/RIF. The LAM-ELISA detected all smear- and MTB-culture-positive samples (n = 70) and 50% (n = 29) of smear-negative but culture-positive samples (n = 58) (versus 79.3%; 46 positive cases by the Xpert MTB/RIF), but none from non-TB patients (n = 56). Among both LAM and MGIT MTB-culture-positive samples, log10-transformed LAM concentration and MGIT time to detection (TTD) showed a good inverse relationship (r = -0.803, p ConclusionsThese results indicate that the LAM-ELISA can determine LAM concentration in sputum, and sputum LAM measured by the assay may be used as a biomarker of bacterial load prior to and during TB treatment. Additional studies are needed to examine the predictive value of this novel biomarker on treatment outcomes