Therapeutic drug monitoring
Pranger, Anna Diewerke
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Pranger, A. D. (2018). Therapeutic drug monitoring: How to improve moxifloxacin exposure in tuberculosis
patients. Rijksuniversiteit Groningen.
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4B
Chapter
Low moxifloxacin exposure
in male tuberculosis patients
and the need for monitoring
in early stages of treatment
A.D. Pranger, R. van Altena, O.W. Akkerman,W.C.M. de Lange, D. van Soolingen, D.J. Touw, D.R.A. Uges, T.S. van der Werf, J.G.W. Kosterink, and J.W.C. Alffenaar Submitted
Abstract Background
Moxifloxacin (MFX) is an important component of the current core rifampicin and multidrug-resistant tuberculosis treatment-regimen. However, low MFX exposure is frequently observed and is associated with poor response to treatment and acquired drug-resistance. We hypothesized that stage of disease and clinical condition during tuberculosis (TB) treatment influences MFX pharmacokinetics (PK).
Methods
We retrospectively reviewed the medical charts of adult TB patients treated with MFX 400 mg/day at our TB Centre from January 2006 to January 2013. Demographic, clinical, treatment and PK data were collected. We determined the correlation of time passed since start of TB treatment, and other possible explanatory variables, with MFX exposure. In patients with PK data on more than one day, we analyzed the impact of elapsed time since start of TB treatment on MFX exposure.
Results
Of 39 patients, a MFX AUC0-24h was available for analysis. The MFX exposure on 400mg QD
varied substantially from 10 to 73 mg*h*L-1. Median (IQR) time of PK sampling was after 50
(19-81) days of treatment. A disproportional increase of AUC0-24h over time was seen in
patients with PK data on more than one day. In multivariable analysis, rifampicin drug-drug interaction (P=0.004) and male gender (P=0.019) were independent predictors of low MFX exposure, but not duration of TB treatment.
Conclusions
In this TB cohort, time elapsed since start of treatment, as surrogate parameter of stage of disease, and other clinical variables, were not independent predictors of MFX exposure, but MFX AUC0-24h values changed over time for individual TB patients. Furthermore, our findings
confirm the well-known rifampicin drug-drug interaction, but also suggest that, particularly, male TB patients may benefit from MFX concentration monitoring.
Introduction
The global elimination of tuberculosis (TB) is seriously threatened by drug-resistant TB, with an estimated incidence of 600,000 cases resistant against the most powerful anti-TB agent (rifampicin) in 2016 (1). Also, patients with “extensively” and “totally” drug-resistant TB have been reported (2-4). To promote patients’ treatment compliance and thus to prevent spread of resistance against critical anti-TB agents, today’s TB drug pipeline is focused on shorter regimens for drug-susceptible and drug-resistant TB (5). However, to end the global TB epidemic, intensified efforts are needed as some of the patients acquire drug-resistance due to low drug-exposure while compliant to therapy (6-8).
Moxifloxacin (MFX) has a high bactericidal activity against M. tuberculosis and is therefore an established important component of the current core rifampicin and multidrug-resistant (MDR) treatment-regimen. Also, MFX is a useful fluoroquinolone if patients cannot tolerate one of the first-line anti-TB agents (9,10). A protein-unbound area under the concentration-time curve up to 24 hours post dosage (AUC0-24h) / minimal inhibitory concentration (MIC) of
53 is associated with optimal kill and suppression of drug-resistant mutant selection of M.
tuberculosis in log-phase growth, and 800mg/day instead of the registered daily dose of
400mg MFX is probably needed to attain this target in most of the TB patients (11). Furthermore, in our TB patients treated under direct observation (DOT), we reported a large variation in pharmacokinetics (PK) on 400mg MFX/day (12). Drug-drug interaction with rifampicin is one possible explanation for a low MFX exposure (13,14). However, a substantial MFX PK variability was also observed in a MDR-TB cohort (15). Other factors like co-morbid conditions (HIV, diabetes) or TB disease activity with wasting and loss of fat, lean body mass and reduced serum proteins, and reduced drug absorption resulting from intestinal dysfunction, could affect PK parameters of MFX (16,17). Data of the impact of malnutrition on MFX PK are lacking. However, a low geometric mean MFX exposure (25 mg*h*L-1) and a short, variable half-life (geometric mean: 8h, CV: 49%) on 400mg,
intravenously administered, was observed in patients with severe sepsis, compared to healthy volunteers (34 mg*h*L-1 and 15 h) (18,19).
We hypothesize that the stage of disease and clinical condition of TB patients influences MFX PK. Therefore, the objective of this study was to explore MFX PK variability over time during the course of TB treatment and its possible relation with different (clinical) variables.
Chapter
4
bAbstract Background
Moxifloxacin (MFX) is an important component of the current core rifampicin and multidrug-resistant tuberculosis treatment-regimen. However, low MFX exposure is frequently observed and is associated with poor response to treatment and acquired drug-resistance. We hypothesized that stage of disease and clinical condition during tuberculosis (TB) treatment influences MFX pharmacokinetics (PK).
Methods
We retrospectively reviewed the medical charts of adult TB patients treated with MFX 400 mg/day at our TB Centre from January 2006 to January 2013. Demographic, clinical, treatment and PK data were collected. We determined the correlation of time passed since start of TB treatment, and other possible explanatory variables, with MFX exposure. In patients with PK data on more than one day, we analyzed the impact of elapsed time since start of TB treatment on MFX exposure.
Results
Of 39 patients, a MFX AUC0-24h was available for analysis. The MFX exposure on 400mg QD
varied substantially from 10 to 73 mg*h*L-1. Median (IQR) time of PK sampling was after 50
(19-81) days of treatment. A disproportional increase of AUC0-24h over time was seen in
patients with PK data on more than one day. In multivariable analysis, rifampicin drug-drug interaction (P=0.004) and male gender (P=0.019) were independent predictors of low MFX exposure, but not duration of TB treatment.
Conclusions
In this TB cohort, time elapsed since start of treatment, as surrogate parameter of stage of disease, and other clinical variables, were not independent predictors of MFX exposure, but MFX AUC0-24h values changed over time for individual TB patients. Furthermore, our findings
confirm the well-known rifampicin drug-drug interaction, but also suggest that, particularly, male TB patients may benefit from MFX concentration monitoring.
Introduction
The global elimination of tuberculosis (TB) is seriously threatened by drug-resistant TB, with an estimated incidence of 600,000 cases resistant against the most powerful anti-TB agent (rifampicin) in 2016 (1). Also, patients with “extensively” and “totally” drug-resistant TB have been reported (2-4). To promote patients’ treatment compliance and thus to prevent spread of resistance against critical anti-TB agents, today’s TB drug pipeline is focused on shorter regimens for drug-susceptible and drug-resistant TB (5). However, to end the global TB epidemic, intensified efforts are needed as some of the patients acquire drug-resistance due to low drug-exposure while compliant to therapy (6-8).
Moxifloxacin (MFX) has a high bactericidal activity against M. tuberculosis and is therefore an established important component of the current core rifampicin and multidrug-resistant (MDR) treatment-regimen. Also, MFX is a useful fluoroquinolone if patients cannot tolerate one of the first-line anti-TB agents (9,10). A protein-unbound area under the concentration-time curve up to 24 hours post dosage (AUC0-24h) / minimal inhibitory concentration (MIC) of
53 is associated with optimal kill and suppression of drug-resistant mutant selection of M.
tuberculosis in log-phase growth, and 800mg/day instead of the registered daily dose of
400mg MFX is probably needed to attain this target in most of the TB patients (11). Furthermore, in our TB patients treated under direct observation (DOT), we reported a large variation in pharmacokinetics (PK) on 400mg MFX/day (12). Drug-drug interaction with rifampicin is one possible explanation for a low MFX exposure (13,14). However, a substantial MFX PK variability was also observed in a MDR-TB cohort (15). Other factors like co-morbid conditions (HIV, diabetes) or TB disease activity with wasting and loss of fat, lean body mass and reduced serum proteins, and reduced drug absorption resulting from intestinal dysfunction, could affect PK parameters of MFX (16,17). Data of the impact of malnutrition on MFX PK are lacking. However, a low geometric mean MFX exposure (25 mg*h*L-1) and a short, variable half-life (geometric mean: 8h, CV: 49%) on 400mg,
intravenously administered, was observed in patients with severe sepsis, compared to healthy volunteers (34 mg*h*L-1 and 15 h) (18,19).
We hypothesize that the stage of disease and clinical condition of TB patients influences MFX PK. Therefore, the objective of this study was to explore MFX PK variability over time during the course of TB treatment and its possible relation with different (clinical) variables.
Patients and methods
Study design and data collection
We retrospectively studied TB patients, aged ≥ 18 years, receiving a once-daily dose of 400mg of MFX orally for at least five days (steady state) as part of their directly observed TB treatment at Tuberculosis Centre Beatrixoord, University Medical Center Groningen (Groningen, the Netherlands), between January 1st 2006 and January 1st 2013. Part of the
data (2006-2009) was collected earlier (12). In our Center, the attending chest physician prescribes a TB drug regimen individually tailored to the patients’ drug-tolerance and the drug susceptibility tests (DST) of the M. tuberculosis complex isolate. MFX PK curves were ordered based on clinical considerations, suspected drug-drug interactions, or part of study procedures of ongoing clinical trials (20-23).
Time points of start of clinical supervision, start of TB treatment, commencement of MFX treatment and of PK measurements were recorded and intervals were computed. At each time point, patients’ weight and length were collected. C-reactive protein (CRP) and Erythrocyte Sedimentation Rate (ESR) were collected at the moment of PK sampling. The most important drug-drug interaction (DDI) of MFX is with rifampicin (RIF), with estimated maximum liver enzyme induction after ten days of RIF-treatment and liver enzyme induction subsided two or more weeks after discontinuation of RIF-treatment (24). A RIF DDI thus was defined as ≥ 10 days of RIF-treatment or < 3 weeks washout after at least 10 days of RIF. Also, data on TB treatment, and demographic and other relevant data were collected, including geographic region of origin, co-infections (HIV, hepatitis B and hepatitis C) and diabetes mellitus.
As retrospective data were collected anonymously the Institutional Ethical Review Board of the University Medical Center Groningen waived the requirement for research subjects to give informed consent (METc 2013-492).
Pharmacokinetic parameters
MFX concentrations were determined using a validated liquid-chromatography tandem mass-spectrometry method (25). A plasma PK curve based on at least two concentration-measurements, one between 0.5 and 4 hours (absorption phase) and one more than 4 hours (elimination phase) post dosage was set as a criterion to have sufficient information about MFX PK. The AUC0-24h was estimated using an open one compartment population PK model
with Bayesian regression (26).
Correlations of variables with moxifloxacin exposure
To explore the stage of TB disease as a predictor of MFX AUC0-24h, we assessed the
correlation between the patients’ first MFX AUC0-24h (400 mg) and time since start of
treatment. Also, explanatory variables of disease severity were taken into account, such as BMI < 18.5, CRP and ESR. We compared the MFX AUC0-24h between groups, divided by
gender, RIF DDI, HIV co-infection, diabetes mellitus and geographical region of origin. Subsequently, all significant correlations, and/or factors suspected to influence PK, were eligible for multivariable analysis. Also because of the number of patients, we aimed to construct an optimal model reducing the redundant variables. If more than one PK curve was initiated, regardless of dosage, descriptive statistics were used to observe the dose-adjusted AUC0-24h in relation to time-span for each individual patient. MFX PK was expected to be
linear over the dose range 400 - 800mg QD (18,27). The AUC0-24h values on 600mg or
800mg QD were therefore considered to be dose-proportional compared to the AUC0-24h
values on 400mg QD.
Statistical analysis
Continuous variables were expressed as median plus interquartile range (IQR). For categorical variables, percentages of the category relative to the total group were described. Second, a Spearman correlation coefficient, or standardized β, using a simple linear regression, was calculated to determine correlations between continuous variables and MFX AUC0-24h or between categorical variables and MFX AUC0-24h, respectively. Finally, a
multivariable linear regression analysis was performed to determine any association between the outcome measure in the research question (i.e. AUC0-24h) and multiple variables. By
removing and hence correcting for non-significant variables, using a P-value of 0.100 or higher as criterion-to-remove, in descending P-value order, significant values, independently associated with outcome, will remain. In general, a two-sided P-value < 0.05 was considered statistically significant. The AUC0-24h value was log10-transformed for univariable and
multivariable analyses to meet the test assumptions. All statistical evaluations were performed using SPSS version 23.0 (IBM SPSS, Chicago, IL, USA).
Chapter
4
bPatients and methods
Study design and data collection
We retrospectively studied TB patients, aged ≥ 18 years, receiving a once-daily dose of 400mg of MFX orally for at least five days (steady state) as part of their directly observed TB treatment at Tuberculosis Centre Beatrixoord, University Medical Center Groningen (Groningen, the Netherlands), between January 1st 2006 and January 1st 2013. Part of the
data (2006-2009) was collected earlier (12). In our Center, the attending chest physician prescribes a TB drug regimen individually tailored to the patients’ drug-tolerance and the drug susceptibility tests (DST) of the M. tuberculosis complex isolate. MFX PK curves were ordered based on clinical considerations, suspected drug-drug interactions, or part of study procedures of ongoing clinical trials (20-23).
Time points of start of clinical supervision, start of TB treatment, commencement of MFX treatment and of PK measurements were recorded and intervals were computed. At each time point, patients’ weight and length were collected. C-reactive protein (CRP) and Erythrocyte Sedimentation Rate (ESR) were collected at the moment of PK sampling. The most important drug-drug interaction (DDI) of MFX is with rifampicin (RIF), with estimated maximum liver enzyme induction after ten days of RIF-treatment and liver enzyme induction subsided two or more weeks after discontinuation of RIF-treatment (24). A RIF DDI thus was defined as ≥ 10 days of RIF-treatment or < 3 weeks washout after at least 10 days of RIF. Also, data on TB treatment, and demographic and other relevant data were collected, including geographic region of origin, co-infections (HIV, hepatitis B and hepatitis C) and diabetes mellitus.
As retrospective data were collected anonymously the Institutional Ethical Review Board of the University Medical Center Groningen waived the requirement for research subjects to give informed consent (METc 2013-492).
Pharmacokinetic parameters
MFX concentrations were determined using a validated liquid-chromatography tandem mass-spectrometry method (25). A plasma PK curve based on at least two concentration-measurements, one between 0.5 and 4 hours (absorption phase) and one more than 4 hours (elimination phase) post dosage was set as a criterion to have sufficient information about MFX PK. The AUC0-24h was estimated using an open one compartment population PK model
with Bayesian regression (26).
Correlations of variables with moxifloxacin exposure
To explore the stage of TB disease as a predictor of MFX AUC0-24h, we assessed the
correlation between the patients’ first MFX AUC0-24h (400 mg) and time since start of
treatment. Also, explanatory variables of disease severity were taken into account, such as BMI < 18.5, CRP and ESR. We compared the MFX AUC0-24h between groups, divided by
gender, RIF DDI, HIV co-infection, diabetes mellitus and geographical region of origin. Subsequently, all significant correlations, and/or factors suspected to influence PK, were eligible for multivariable analysis. Also because of the number of patients, we aimed to construct an optimal model reducing the redundant variables. If more than one PK curve was initiated, regardless of dosage, descriptive statistics were used to observe the dose-adjusted AUC0-24h in relation to time-span for each individual patient. MFX PK was expected to be
linear over the dose range 400 - 800mg QD (18,27). The AUC0-24h values on 600mg or
800mg QD were therefore considered to be dose-proportional compared to the AUC0-24h
values on 400mg QD.
Statistical analysis
Continuous variables were expressed as median plus interquartile range (IQR). For categorical variables, percentages of the category relative to the total group were described. Second, a Spearman correlation coefficient, or standardized β, using a simple linear regression, was calculated to determine correlations between continuous variables and MFX AUC0-24h or between categorical variables and MFX AUC0-24h, respectively. Finally, a
multivariable linear regression analysis was performed to determine any association between the outcome measure in the research question (i.e. AUC0-24h) and multiple variables. By
removing and hence correcting for non-significant variables, using a P-value of 0.100 or higher as criterion-to-remove, in descending P-value order, significant values, independently associated with outcome, will remain. In general, a two-sided P-value < 0.05 was considered statistically significant. The AUC0-24h value was log10-transformed for univariable and
multivariable analyses to meet the test assumptions. All statistical evaluations were performed using SPSS version 23.0 (IBM SPSS, Chicago, IL, USA).
Results Patients
From January 1st 2006 to January 1st 2013, 211 patients were treated with MFX for TB; 149
patients (70.6%) were classified as pulmonary TB. DST results (n = 179, 84.8%) revealed susceptibility for 1st-line drugs (n = 108, 60.3%) or multidrug-resistance (MDR) (n = 50, 28%)
in most patients. MFX exposure data were available in 39 patients. In 23/39 cases, patients had MDR-TB (Supplemental table 1). Patients’ baseline demographics are presented in
Table 1. Data on TB treatment are summarized in Supplemental table 1. Table 1: Baseline demographics of 39 patients with a known MFX exposure.
Parameter Value
Female 15 (38)
Age (years) 30 (23-42)
Weight (kg) 57.4 (49.4-62.1)
Body Mass Index (kg*m-2) 19.4 (17.9-20.3)
Geographic sub-region of origin1
East Africa 10 (26) West Asia 5 (13) West Africa 4 (10) East Asia 3 (8) South-East Asia 3 (8) East Europe 3 (8) South America 3 (8)
Rest of the world (n < 3 per sub-region) 8 (21) Comorbidities
Human immunodeficiency virus (HIV) 3 (8)
Hepatitis B 3 (8)
Hepatitis C 4 (10)
Diabetes Mellitus 3 (8)
Data are presented as n (%) or median (interquartile range).1United Nations classification.
Moxifloxacin exposure and correlations with variables
All parameters collected at the first moment of PK sampling are presented in Table 2. The
distribution of patients’ weight and BMI was not significantly different during PK sampling compared to baseline (Sign Test, P = 0.100). Median (IQR) MFX AUC0-24h (400mg QD) was
22 (16-31) mg*h*L-1 (Table 2). MFX AUC
0-24h displayed a large variation (range: 10-73
mg*h*L-1).
Table 2: Parameters at the moment of PK sampling (n=39).
Parameter Value
Dose (mg/kg) 6.66 (6.16-7.78)
Rifampicin drug-drug interaction 13 (33)‡
CRP (mg*L-1) 11 (<5 – 28)#
Time periods
Time-to-clinical supervision days 41 (22-76) Time-to-start of TB treatment days 50 (19-81) Time-to-start of Moxifloxacin days 26 (9-76) Pharmacokinetics
AUC0-24h (mg*h*L-1) 22 (16-31)
Data are presented as n (%) or median (interquartile range). ‡9/39 patients: unknown. #24/39 patients:
unknown; CRP (or ESR) is no routine marker of TB treatment response at Beatrixoord. In case of an unknown CRP, ESR was unknown as well.
Univariable analysis identified gender, a RIF DDI, an HIV co-infection and time-to-start of TB treatment as strong correlates of log10 MFX AUC0-24h (Table 3). Also, the MFX AUC0-24h of the
TB patients with Diabetes Mellitus was relatively low; 11, 13 and 24 mg*h*L-1.
Model 1 (Table 4) was the optimal multivariable linear regression model. RIF drug-drug
interaction and gender were identified as significant independent predictors of MFX AUC0-24h.
The model did not improve by including the time of PK measurement since start of TB treatment (Model 2, Table 4). RIF continued to be the strongest correlate (standardized β =
-0.46, p = 0.004). In model 1, the effect size B (95% CI) of RIF on log10AUC0-24h was estimated
as -0.18 (-0.29 - -0.062), i.e. MFX exposure was reduced from 25 (95% CI, 20-31) to 17 mg*h*L-1. Similarly, an effect size B of 0.14 (95% CI: 0.025-0.25) resulted in an estimated
MFX exposure for female patients of 100.14 x 100% = 138% compared to men (100%). The
third determinant of our model, HIV co-infection, was associated with a low MFX exposure (B = -0.18, 95% CI -0.38 – 0.030).
Chapter
4
bResults Patients
From January 1st 2006 to January 1st 2013, 211 patients were treated with MFX for TB; 149
patients (70.6%) were classified as pulmonary TB. DST results (n = 179, 84.8%) revealed susceptibility for 1st-line drugs (n = 108, 60.3%) or multidrug-resistance (MDR) (n = 50, 28%)
in most patients. MFX exposure data were available in 39 patients. In 23/39 cases, patients had MDR-TB (Supplemental table 1). Patients’ baseline demographics are presented in
Table 1. Data on TB treatment are summarized in Supplemental table 1. Table 1: Baseline demographics of 39 patients with a known MFX exposure.
Parameter Value
Female 15 (38)
Age (years) 30 (23-42)
Weight (kg) 57.4 (49.4-62.1)
Body Mass Index (kg*m-2) 19.4 (17.9-20.3)
Geographic sub-region of origin1
East Africa 10 (26) West Asia 5 (13) West Africa 4 (10) East Asia 3 (8) South-East Asia 3 (8) East Europe 3 (8) South America 3 (8)
Rest of the world (n < 3 per sub-region) 8 (21) Comorbidities
Human immunodeficiency virus (HIV) 3 (8)
Hepatitis B 3 (8)
Hepatitis C 4 (10)
Diabetes Mellitus 3 (8)
Data are presented as n (%) or median (interquartile range).1United Nations classification.
Moxifloxacin exposure and correlations with variables
All parameters collected at the first moment of PK sampling are presented in Table 2. The
distribution of patients’ weight and BMI was not significantly different during PK sampling compared to baseline (Sign Test, P = 0.100). Median (IQR) MFX AUC0-24h (400mg QD) was
22 (16-31) mg*h*L-1 (Table 2). MFX AUC
0-24h displayed a large variation (range: 10-73
mg*h*L-1).
Table 2: Parameters at the moment of PK sampling (n=39).
Parameter Value
Dose (mg/kg) 6.66 (6.16-7.78)
Rifampicin drug-drug interaction 13 (33)‡
CRP (mg*L-1) 11 (<5 – 28)#
Time periods
Time-to-clinical supervision days 41 (22-76) Time-to-start of TB treatment days 50 (19-81) Time-to-start of Moxifloxacin days 26 (9-76) Pharmacokinetics
AUC0-24h (mg*h*L-1) 22 (16-31)
Data are presented as n (%) or median (interquartile range). ‡9/39 patients: unknown. #24/39 patients:
unknown; CRP (or ESR) is no routine marker of TB treatment response at Beatrixoord. In case of an unknown CRP, ESR was unknown as well.
Univariable analysis identified gender, a RIF DDI, an HIV co-infection and time-to-start of TB treatment as strong correlates of log10 MFX AUC0-24h (Table 3). Also, the MFX AUC0-24h of the
TB patients with Diabetes Mellitus was relatively low; 11, 13 and 24 mg*h*L-1.
Model 1 (Table 4) was the optimal multivariable linear regression model. RIF drug-drug
interaction and gender were identified as significant independent predictors of MFX AUC0-24h.
The model did not improve by including the time of PK measurement since start of TB treatment (Model 2, Table 4). RIF continued to be the strongest correlate (standardized β =
-0.46, p = 0.004). In model 1, the effect size B (95% CI) of RIF on log10AUC0-24h was estimated
as -0.18 (-0.29 - -0.062), i.e. MFX exposure was reduced from 25 (95% CI, 20-31) to 17 mg*h*L-1. Similarly, an effect size B of 0.14 (95% CI: 0.025-0.25) resulted in an estimated
MFX exposure for female patients of 100.14 x 100% = 138% compared to men (100%). The
third determinant of our model, HIV co-infection, was associated with a low MFX exposure (B = -0.18, 95% CI -0.38 – 0.030).
Table 3: Univariable correlates of Moxifloxacin AUC0-24h.
Determinant Spearman’s rho Standardized β P-value
Female 0.45 0.004
Asian1,2 0.16$ 0.363
European1,2 0.037$ 0.833
American1,2 0.27$ 0.118
Human immunodeficiency virus (HIV)3 -0.36 0.027
Diabetes Mellitus3 -0.28 0.081
Rifampicin drug-drug interaction -0.58 0.001
BMI < 18.5 -0.18 0.313
Time-to-start of TB treatment ρ= 0.36 0.025
AUC0-24h was log10 transformed. 1regrouped into United Nations’ macro geographical regions: Africa,
Asia, Europe, America to create valid dummy variables. African patients originated mainly from Sub-Saharan Africa (n=15/17). Three out of four American patients originated from Suriname. 2compared
to African. 3n patients with determinant small (Table 1). $By exclusion of a visible outlier (American)
standardized β (p) for determinants Asian, European and American were 0.18 (0.334), 0.040 (0.823), 0.076 (0.670), respectively.
Table 4: Multivariable linear regression analysis: determinants of MFX AUC0-24h.
Model Determinant Standardized β P-value R2
1 Rifampicin drug-drug interaction -0.46 0.004 0.51
Female 0.35 0.019
Human immunodeficiency virus (HIV) -0.25 0.091
2 Rifampicin drug-drug interaction -0.44 0.005 0.52
Female 0.36 0.019
Human immunodeficiency virus (HIV) -0.23 0.117
Time-to-start of TB treatment 0.10 0.476
AUC0-24h was log10 transformed. Model 1 is the optimal regression model. Model 2 assessed the effect
of all significant variables from the univariable analysis.
Of 9 patients multiple MFX AUC0-24h values were available during their TB treatment (Table 5). In some patients the MFX exposure was disproportionally higher after more treatment
days. For example, on 800mg/day the AUC0-24h increased from 33 to 59 mg*h*L-1 (179%) in
63 days, but almost the same MFX exposure (57 mg*h*L-1) was measured after 28 more
treatment days for patient 7, without an HIV co-infection or RIF DDI. Also, an equal MFX exposure was observed for patient 5 on 600 and 800mg/day with 47 days in between, without an HIV co-infection and RIF DDI.
Table 5: Patients with more than one PK curve (n=9).
Patient Moment 1 Moment 2 Moment 3 Moment 4 Determinants1
Days AUC Days AUC Days AUC Days AUC
1 414 21 448 22 - - - 2 7 15(X) 24 22* - - HIV 3 6 15(X) 48 37* 89 22 - Female, HIV 4 20 25(X) 40 36 - - - 5 6 13(R) 161 46** 208 47* - - 6 8 22(X) 36 53* - - Female 7 19 20(X) 49 33** 112 59** 140 57** Female 8 82 31 172 42* 208 55* - - 9 41 62* 103 48 - - Female
MFX AUC0-24h on 400 mg/day unless indicated otherwise. *600mg/day. **800mg/day. AUC, indication
of disproportional PK compared to the previous AUC. (R), rifampicin drug-drug interaction (RIF DDI). (X), RIF DDI due to any pre-clinical RIF treatment unknown. 1female, HIV and/or Diabetes Mellitus.
Chapter
4
bTable 3: Univariable correlates of Moxifloxacin AUC0-24h.
Determinant Spearman’s rho Standardized β P-value
Female 0.45 0.004
Asian1,2 0.16$ 0.363
European1,2 0.037$ 0.833
American1,2 0.27$ 0.118
Human immunodeficiency virus (HIV)3 -0.36 0.027
Diabetes Mellitus3 -0.28 0.081
Rifampicin drug-drug interaction -0.58 0.001
BMI < 18.5 -0.18 0.313
Time-to-start of TB treatment ρ= 0.36 0.025
AUC0-24h was log10 transformed. 1regrouped into United Nations’ macro geographical regions: Africa,
Asia, Europe, America to create valid dummy variables. African patients originated mainly from Sub-Saharan Africa (n=15/17). Three out of four American patients originated from Suriname. 2compared
to African. 3n patients with determinant small (Table 1). $By exclusion of a visible outlier (American)
standardized β (p) for determinants Asian, European and American were 0.18 (0.334), 0.040 (0.823), 0.076 (0.670), respectively.
Table 4: Multivariable linear regression analysis: determinants of MFX AUC0-24h.
Model Determinant Standardized β P-value R2
1 Rifampicin drug-drug interaction -0.46 0.004 0.51
Female 0.35 0.019
Human immunodeficiency virus (HIV) -0.25 0.091
2 Rifampicin drug-drug interaction -0.44 0.005 0.52
Female 0.36 0.019
Human immunodeficiency virus (HIV) -0.23 0.117
Time-to-start of TB treatment 0.10 0.476
AUC0-24h was log10 transformed. Model 1 is the optimal regression model. Model 2 assessed the effect
of all significant variables from the univariable analysis.
Of 9 patients multiple MFX AUC0-24h values were available during their TB treatment (Table 5). In some patients the MFX exposure was disproportionally higher after more treatment
days. For example, on 800mg/day the AUC0-24h increased from 33 to 59 mg*h*L-1 (179%) in
63 days, but almost the same MFX exposure (57 mg*h*L-1) was measured after 28 more
treatment days for patient 7, without an HIV co-infection or RIF DDI. Also, an equal MFX exposure was observed for patient 5 on 600 and 800mg/day with 47 days in between, without an HIV co-infection and RIF DDI.
Table 5: Patients with more than one PK curve (n=9).
Patient Moment 1 Moment 2 Moment 3 Moment 4 Determinants1
Days AUC Days AUC Days AUC Days AUC
1 414 21 448 22 - - - 2 7 15(X) 24 22* - - HIV 3 6 15(X) 48 37* 89 22 - Female, HIV 4 20 25(X) 40 36 - - - 5 6 13(R) 161 46** 208 47* - - 6 8 22(X) 36 53* - - Female 7 19 20(X) 49 33** 112 59** 140 57** Female 8 82 31 172 42* 208 55* - - 9 41 62* 103 48 - - Female
MFX AUC0-24h on 400 mg/day unless indicated otherwise. *600mg/day. **800mg/day. AUC, indication
of disproportional PK compared to the previous AUC. (R), rifampicin drug-drug interaction (RIF DDI). (X), RIF DDI due to any pre-clinical RIF treatment unknown. 1female, HIV and/or Diabetes Mellitus.
Discussion
The main finding of our multivariable analysis is that not time elapsed since start of TB treatment, as surrogate parameter of stage of disease, but rifampicin drug-drug interaction (P=0.004) and gender (P=0.019) were independent predictors of MFX exposure. An HIV co-infection (P=0.091) was associated with a lower MFX AUC0-24h. Second, in some individual
patients with multiple PK curves, without RIF DDI, we clearly observed a disproportional increase of the dose-adjusted MFX AUC0-24h over time.
To our knowledge a gender-related difference in MFX concentration has not been previously described, but relatively high concentrations of other anti-TB drugs have been found in female TB patients (28,29). The lower MFX AUC0-24h in our male TB patients tends to be
(partly) driven by a lower peak-level (Figure 1), indicating a reduced MFX bioavailability. A
gender-difference in intestinal P-glycoprotein expression due to a worse clinical condition (17), could be a possible mechanism for a reduced MFX absorption in male patients. A prospective crossover PK study of oral and intravenous administration of MFX in TB patients, investigating a gender-difference in absolute bioavailability, is needed to test this hypothesis.
Figure 1: Moxifloxacin peak-level in male (n=24) and female (n=15) TB patients.
Low concentrations of first-line anti-TB drugs are not uncommon in HIV co-infected patients, but the underlying cause is not entirely unraveled (30). Drug-absorption might be influenced by acquired immune deficiency syndrome (AIDS)-related intestinal malfunction, which often presents as diarrhea (16,31). Data on anti-retroviral drugs influencing MFX PK is limited to one recent population PK study in TB patients estimating a -30% change in MFX exposure and a +42% change in hepatic clearance in HIV co-infected patients treated with efavirenz, possibly due to induction of UDP-glucuronosyltransferase (32). Two-out-of-three HIV co-infected patients in our cohort were on efavirenz-based antiretroviral treatment during the period of PK sampling, and for one of them defecation problems, for which no specific cause could be found, were also reported. The pharmacological challenge of treating both HIV and TB with an effective and less-toxic drug-regimen for a longer period warrants for more knowledge on potential PK DDI’s.
In our TB center, a TB drug regimen is individually tailored to the patients’ drug-tolerance and the drug susceptibility tests. Therefore, by using the surrogate parameter ‘time of PK measurement since start of TB treatment’, the assumption was made that every patient was treated with a regimen of initially effective anti-TB drugs with equal gradual improvement of their clinical condition. Although this surrogate parameter did not emerge in our cohort by correcting for a RIF DDI, gender and an HIV co-infection (n=39, Table 4), a disproportional
increase of MFX AUC0-24h was observed over time for individual patients with multiple PK
curves (n=9, Table 5). A longitudinal analysis of the effect of inflammation and nutrition on
MFX PK in a larger cohort might therefore be more informative.
Our study has several limitations. Out of 211 patients treated with MFX, a MFX AUC0-24h
value was available in only 39 patients. First, the small sample size is a limitation of the intensive PK evaluation needed to assess MFX AUC0-24h (see method section). Also, PK
sampling was typically driven by suspected problems with drug exposure, e.g. a RIF DDI or a high MIC value, or by the study procedure of clinical trials, investigating safety and efficacy of an escalated MFX dose (20,22), evaluating dried-blood spot sampling (21), or describing the population PK of anti-TB drugs (23). The retrospective nature of our study makes these results thus sensitive for bias incurred by selection by indication. However, the PK variability observed in this broad selection of patients, only partly explained by three variables, justifies therapeutic drug monitoring (TDM) in patients at risk for a mismatch between exposure and antimicrobial activity. The significant impact of the well-known RIF DDI (13,14) supports the
Chapter
4
bDiscussion
The main finding of our multivariable analysis is that not time elapsed since start of TB treatment, as surrogate parameter of stage of disease, but rifampicin drug-drug interaction (P=0.004) and gender (P=0.019) were independent predictors of MFX exposure. An HIV co-infection (P=0.091) was associated with a lower MFX AUC0-24h. Second, in some individual
patients with multiple PK curves, without RIF DDI, we clearly observed a disproportional increase of the dose-adjusted MFX AUC0-24h over time.
To our knowledge a gender-related difference in MFX concentration has not been previously described, but relatively high concentrations of other anti-TB drugs have been found in female TB patients (28,29). The lower MFX AUC0-24h in our male TB patients tends to be
(partly) driven by a lower peak-level (Figure 1), indicating a reduced MFX bioavailability. A
gender-difference in intestinal P-glycoprotein expression due to a worse clinical condition (17), could be a possible mechanism for a reduced MFX absorption in male patients. A prospective crossover PK study of oral and intravenous administration of MFX in TB patients, investigating a gender-difference in absolute bioavailability, is needed to test this hypothesis.
Figure 1: Moxifloxacin peak-level in male (n=24) and female (n=15) TB patients.
Low concentrations of first-line anti-TB drugs are not uncommon in HIV co-infected patients, but the underlying cause is not entirely unraveled (30). Drug-absorption might be influenced by acquired immune deficiency syndrome (AIDS)-related intestinal malfunction, which often presents as diarrhea (16,31). Data on anti-retroviral drugs influencing MFX PK is limited to one recent population PK study in TB patients estimating a -30% change in MFX exposure and a +42% change in hepatic clearance in HIV co-infected patients treated with efavirenz, possibly due to induction of UDP-glucuronosyltransferase (32). Two-out-of-three HIV co-infected patients in our cohort were on efavirenz-based antiretroviral treatment during the period of PK sampling, and for one of them defecation problems, for which no specific cause could be found, were also reported. The pharmacological challenge of treating both HIV and TB with an effective and less-toxic drug-regimen for a longer period warrants for more knowledge on potential PK DDI’s.
In our TB center, a TB drug regimen is individually tailored to the patients’ drug-tolerance and the drug susceptibility tests. Therefore, by using the surrogate parameter ‘time of PK measurement since start of TB treatment’, the assumption was made that every patient was treated with a regimen of initially effective anti-TB drugs with equal gradual improvement of their clinical condition. Although this surrogate parameter did not emerge in our cohort by correcting for a RIF DDI, gender and an HIV co-infection (n=39, Table 4), a disproportional
increase of MFX AUC0-24h was observed over time for individual patients with multiple PK
curves (n=9, Table 5). A longitudinal analysis of the effect of inflammation and nutrition on
MFX PK in a larger cohort might therefore be more informative.
Our study has several limitations. Out of 211 patients treated with MFX, a MFX AUC0-24h
value was available in only 39 patients. First, the small sample size is a limitation of the intensive PK evaluation needed to assess MFX AUC0-24h (see method section). Also, PK
sampling was typically driven by suspected problems with drug exposure, e.g. a RIF DDI or a high MIC value, or by the study procedure of clinical trials, investigating safety and efficacy of an escalated MFX dose (20,22), evaluating dried-blood spot sampling (21), or describing the population PK of anti-TB drugs (23). The retrospective nature of our study makes these results thus sensitive for bias incurred by selection by indication. However, the PK variability observed in this broad selection of patients, only partly explained by three variables, justifies therapeutic drug monitoring (TDM) in patients at risk for a mismatch between exposure and antimicrobial activity. The significant impact of the well-known RIF DDI (13,14) supports the validity of our multivariable linear regression model.
Conclusions
In conclusion, the MFX AUC0-24h on 400mg/day orally is highly variable. Low MFX exposure
was found in male TB patients and in patients with a RIF-based TB regimen. The AUC0-24h
tended to be lower in HIV-TB patients and at the early stage of TB disease.
References
1. World Health Organization (WHO) (ed.). 2017. Global tuberculosis report 2017. World Health Organization, Geneva, Switzerland.
2. Migliori G.B., De laco G., Besozzi G., Centis R., and Cirillo D.M. 2007. First tuberculosis cases in Italy resistant to all tested drugs. Eurosurveillance. 12(5):E070517.1.
3. Velyati A.A., Masjedi M.R., Farnia P., Tabarsi P., Ghanavi J., Ziazarifi A.H., and Hoffner S.E. 2009. Emergence of new forms of totally drug-resistant tuberculosis bacilli: super extensively drug-resistant tuberculosis or totally drug-resistant strains in iran. Chest. 136(2):420-5. 4. Udwadia Z.F., Amale R.A., Ajbani K.K., and Rodrigues C. 2012. Totally drug-resistant
tuberculosis in India. Clin Infect Dis. 54(4):579-81.
5. Stop TB Partnership (ed.). Drug pipeline. Stop TB Partnership. Accessed: March 18th 2018
via www.newtbdrugs.org.
6. Srivastava S., Pasipanodya J.G., Meek C., Leff R., and Gumbo T. 2011.Multidrug-resistant tuberculosis not due to non-compliance but due to between-patient pharmacokinetic variability. J Infect Dis. 204(12):1951-9.
7. Alffenaar J.C., Migliori G.B., and Gumbo T. 2017.Multidrug-resistant tuberculosis: pharmacokinetic and pharmacodynamic science. Lancet Infect Dis. 17(9):898.
8. Sharma A., Hill A., Kurbatova E., van der Walt M., Kvasnovsky C., Tupasi T.E., Caoili J.C., Gler M.T., Volchenkov G.V., Kazennyy B.Y., Demikhova O.V., Bayona J., Contreras C., Yagui M., Leimane V., Cho S.N., Kim H.J., Kliiman K., Akksilp S., Jou R., Ershova J., Dalton T., Cegielski P.; Global Preserving Effective TB Treatment Study Investigators. 2017. Estimating the future burden of multidrug-resistant and extensively drug-resistant tuberculosis in India, the Philippines, Russia, and South Africa: a mathematical modelling study. Lancet Infect Dis. 17(7):707-715.
9. Pranger A.D., Alffenaar J.W., and Aarnoutse R.E. 2011. Fluoroquinolones, the cornerstone of treatment of drug-resistant tuberculosis: a pharmacokinetic and pharmacodynamic approach. Curr Pharm Des. 17(27):2900-30.
10. World Health Organization (WHO) (ed.). 2016. WHO treatment guidelines for drug-resistant tuberculosis. World Health Organization, Geneva, Switzerland.
11. Gumbo T., Louie A., Deziel M.R., Parsons L.M., Salfinger M., and Drusano G.L. 2004. Selection of a moxifloxacin dose that suppresses drug resistance in Mycobacterium tuberculosis, by use of an in vitro pharmacodynamic infection model and mathematical modeling. J Infect Dis. 190(9):1642-51.
12. Pranger A.D., van Altena R., Aarnoutse R.E., van Soolingen D., Uges D.R., Kosterink J.G., van der Werf T.S., and Alffenaar J.W. 2011. Evaluation of moxifloxacin for the treatment of tuberculosis: 3 years of experience. Eur Respir J. 38(4):888-94.
13. Nijland H.M., Ruslami R., Suroto A.J., Burger D.M., Alisjahbana B., van Crevel R., and Aarnoutse R.E. 2007. Rifampicin reduces plasma concentrations of moxifloxacin in patients with tuberculosis. Clin Infect Dis. 45(8): 1001-7.
Chapter
4
bConclusions
In conclusion, the MFX AUC0-24h on 400mg/day orally is highly variable. Low MFX exposure
was found in male TB patients and in patients with a RIF-based TB regimen. The AUC0-24h
tended to be lower in HIV-TB patients and at the early stage of TB disease.
References
1. World Health Organization (WHO) (ed.). 2017. Global tuberculosis report 2017. World Health Organization, Geneva, Switzerland.
2. Migliori G.B., De laco G., Besozzi G., Centis R., and Cirillo D.M. 2007. First tuberculosis cases in Italy resistant to all tested drugs. Eurosurveillance. 12(5):E070517.1.
3. Velyati A.A., Masjedi M.R., Farnia P., Tabarsi P., Ghanavi J., Ziazarifi A.H., and Hoffner S.E. 2009. Emergence of new forms of totally drug-resistant tuberculosis bacilli: super extensively drug-resistant tuberculosis or totally drug-resistant strains in iran. Chest. 136(2):420-5. 4. Udwadia Z.F., Amale R.A., Ajbani K.K., and Rodrigues C. 2012. Totally drug-resistant
tuberculosis in India. Clin Infect Dis. 54(4):579-81.
5. Stop TB Partnership (ed.). Drug pipeline. Stop TB Partnership. Accessed: March 18th 2018
via www.newtbdrugs.org.
6. Srivastava S., Pasipanodya J.G., Meek C., Leff R., and Gumbo T. 2011.Multidrug-resistant tuberculosis not due to non-compliance but due to between-patient pharmacokinetic variability. J Infect Dis. 204(12):1951-9.
7. Alffenaar J.C., Migliori G.B., and Gumbo T. 2017.Multidrug-resistant tuberculosis: pharmacokinetic and pharmacodynamic science. Lancet Infect Dis. 17(9):898.
8. Sharma A., Hill A., Kurbatova E., van der Walt M., Kvasnovsky C., Tupasi T.E., Caoili J.C., Gler M.T., Volchenkov G.V., Kazennyy B.Y., Demikhova O.V., Bayona J., Contreras C., Yagui M., Leimane V., Cho S.N., Kim H.J., Kliiman K., Akksilp S., Jou R., Ershova J., Dalton T., Cegielski P.; Global Preserving Effective TB Treatment Study Investigators. 2017. Estimating the future burden of multidrug-resistant and extensively drug-resistant tuberculosis in India, the Philippines, Russia, and South Africa: a mathematical modelling study. Lancet Infect Dis. 17(7):707-715.
9. Pranger A.D., Alffenaar J.W., and Aarnoutse R.E. 2011. Fluoroquinolones, the cornerstone of treatment of drug-resistant tuberculosis: a pharmacokinetic and pharmacodynamic approach. Curr Pharm Des. 17(27):2900-30.
10. World Health Organization (WHO) (ed.). 2016. WHO treatment guidelines for drug-resistant tuberculosis. World Health Organization, Geneva, Switzerland.
11. Gumbo T., Louie A., Deziel M.R., Parsons L.M., Salfinger M., and Drusano G.L. 2004. Selection of a moxifloxacin dose that suppresses drug resistance in Mycobacterium tuberculosis, by use of an in vitro pharmacodynamic infection model and mathematical modeling. J Infect Dis. 190(9):1642-51.
12. Pranger A.D., van Altena R., Aarnoutse R.E., van Soolingen D., Uges D.R., Kosterink J.G., van der Werf T.S., and Alffenaar J.W. 2011. Evaluation of moxifloxacin for the treatment of tuberculosis: 3 years of experience. Eur Respir J. 38(4):888-94.
13. Nijland H.M., Ruslami R., Suroto A.J., Burger D.M., Alisjahbana B., van Crevel R., and Aarnoutse R.E. 2007. Rifampicin reduces plasma concentrations of moxifloxacin in patients with tuberculosis. Clin Infect Dis. 45(8): 1001-7.
14. Weiner M., Burman W., Luo C.C., Peloquin C.A., Engle M., Goldberg S., Agarwal V., and Vernon A. 2007. Effects of rifampin and multidrug resistance gene polymorphism on concentrations of moxifloxacin. Antimicrob Agents Chemother. 51(8):2861-6.
15. Manika K., Chatzika K., Zaroqoulidis K., and Kioumis I. 2012. Moxifloxacin in multidrug-resistant tuberculosis: is there any indication for therapeutic drug monitoring? Eur Respir J. 40(4):1051-3.
16. Daskapan A., de Lange W.C., Akkerman O.W., Kosterink J.G., van der Werf T.S., Stienstra Y., and Alffenaar J.W. 2015. The role of therapeutic drug monitoring in individualised drug dosage and exposure measurement in tuberculosis and HIV co-infection. Eur Respir J. 45(2): 569-71.
17. Macallan D.C. 1999. Malnutrition in tuberculosis. Diagn Microbiol Infect Dis. 34(2):153-7. 18. Stass H., Kubitza D., and Schühly U. 2001. Pharmacokinetics, safety and tolerability of
moxifloxacin, a novel 8-methoxyfluoroquinolone, after repeated oral administration. Clin Pharmacokinet. 40 Suppl 1:1-9.
19. Pletz M.W., Bloos F., Burkhardt O., Brunkhorst F.M., Bode-Böger S.M., Martens-Lobenhoffer J., Greer M.W., Stass H, and Welte T. 2010. Pharmacokinetics of moxifloxacin in patients with severe sepsis or septic shock. Intensive Care Med. 36(6):979-83.
20. National Institute of Health (NIH) (ed.). ClinicalTrials.gov Id. NCT01329250. U.S. National Library of Health, Bethesda, United States of America. Accessed: March 24th 2018 via
clinicaltrials.gov.
21. Vu D.H., Koster R.A., Alffenaar J.W., Brouwers J.R., and Uges D.R. 2011. Determination of moxifloxacin in dried blood spots using LC-MS/MS and the impact of hematocrit and blood volume. J Chromatogr B Analyt Technol Biomed Life Sci. 879(15-16):1063-70.
22. Alffenaar J.W., van Altena R., Bökkerink H.J., Luijckx G.J., van Soolingen D., Aarnoutse R.E., and van der Werf T.S. 2009. Pharmacokinetics of moxifloxacin in cerebrospinal fluid and plasma in patients with tuberculous meningitis. Clin Infect Dis. 49(7):1080-2.
23. Magis-Escurra C., Later-Nijland H.M., Alffenaar J.W., Broeders J., Burger D.M., van Crevel R., Boeree M.J., Donders A.R., van Altena R., van der Werf T.S., and Aarnoutse R.E. 2014. Population pharmacokinetics and limited sampling strategy for first-line tuberculosis drugs and moxifloxacin. Int J Antimicrob Agents. 44(3):229-34.
24. Medicines Evaluation Board (MEB) (ed.). 2017. Summary of product characteristics. Rifampicin. Medicines Evaluation Board, Utrecht, The Netherlands.
25. Pranger A.D., Alffenaar J.W., Wessels A.M., Greijdanus B., and Uges D.R. 2010.
Determination of moxifloxacin in human plasma, plasma ultrafiltrate, and cerebrospinal fluid by a rapid and simple liquid chromatography-tandem mass spectrometry method. J Anal Toxicol. 34(3):135-41.
26. Pranger A.D., Kosterink J.G., van Altena R., Aarnoutse R.E., van der Werf T.S., Uges D.R., and Alffenaar J.W. 2011. Limited-sampling strategies for therapeutic drug monitoring of moxifloxacin in patients with tuberculosis. Ther Drug Monit. 33(3):350-4.
27. Stass H. and Kubitza D. 1999. Pharmacokinetics and elimination of moxifloxacin after oral and intravenous administration in man. J Antimicrob Chemother. 43 Suppl B:83-90.
28. Ray J., Gardiner I., and Marriott D. 2003. Managing antituberculosis drug therapy by therapeutic drug monitoring of rifampicin and isoniazid. Intern Med J. 33(5-6):229-34. 29. Mcllleron H., Wash P., Burger A., Norman J., Folb P.I., and Smith P. 2006. Determinants of
rifampin, isoniazid, pyrazinamide, and ethambutol pharmacokinetics in a cohort of tuberculosis patients. Antimicrob Agents Chemother. 50(4):1170-7.
30. Verbeeck R.K, Günther G., Kibuule D., Hunter C., and Rennie T.W. 2016. Optimizing treatment outcome of first-line anti-tuberculosis drugs: the role of therapeutic drug monitoring. Eur J Clin Pharmacol. 72(8):905-16.
31. Cello J.P. and Day L.W. 2009. Idiopathic AIDS enteropathy and treatment of gasterointestinal oppertunistic pathogens. Gastroenterology. 136(6):1952-65.
32. Naidoo A., Chirehwa M., Mcllleron H., Naidoo K., Essack S., Yende-Zuma N., Kimba-Phongi E., Adamson J., Govender K., Padayatchi N., and Denti P. 2017. Effect of rifampicin and efavirenz on moxifloxacin concentrations when co-administered in patients with drug-susceptible TB. J Antimicrob Chemother. 72(5):1441-1449.
Chapter
4
b14. Weiner M., Burman W., Luo C.C., Peloquin C.A., Engle M., Goldberg S., Agarwal V., and Vernon A. 2007. Effects of rifampin and multidrug resistance gene polymorphism on concentrations of moxifloxacin. Antimicrob Agents Chemother. 51(8):2861-6.
15. Manika K., Chatzika K., Zaroqoulidis K., and Kioumis I. 2012. Moxifloxacin in multidrug-resistant tuberculosis: is there any indication for therapeutic drug monitoring? Eur Respir J. 40(4):1051-3.
16. Daskapan A., de Lange W.C., Akkerman O.W., Kosterink J.G., van der Werf T.S., Stienstra Y., and Alffenaar J.W. 2015. The role of therapeutic drug monitoring in individualised drug dosage and exposure measurement in tuberculosis and HIV co-infection. Eur Respir J. 45(2): 569-71.
17. Macallan D.C. 1999. Malnutrition in tuberculosis. Diagn Microbiol Infect Dis. 34(2):153-7. 18. Stass H., Kubitza D., and Schühly U. 2001. Pharmacokinetics, safety and tolerability of
moxifloxacin, a novel 8-methoxyfluoroquinolone, after repeated oral administration. Clin Pharmacokinet. 40 Suppl 1:1-9.
19. Pletz M.W., Bloos F., Burkhardt O., Brunkhorst F.M., Bode-Böger S.M., Martens-Lobenhoffer J., Greer M.W., Stass H, and Welte T. 2010. Pharmacokinetics of moxifloxacin in patients with severe sepsis or septic shock. Intensive Care Med. 36(6):979-83.
20. National Institute of Health (NIH) (ed.). ClinicalTrials.gov Id. NCT01329250. U.S. National Library of Health, Bethesda, United States of America. Accessed: March 24th 2018 via
clinicaltrials.gov.
21. Vu D.H., Koster R.A., Alffenaar J.W., Brouwers J.R., and Uges D.R. 2011. Determination of moxifloxacin in dried blood spots using LC-MS/MS and the impact of hematocrit and blood volume. J Chromatogr B Analyt Technol Biomed Life Sci. 879(15-16):1063-70.
22. Alffenaar J.W., van Altena R., Bökkerink H.J., Luijckx G.J., van Soolingen D., Aarnoutse R.E., and van der Werf T.S. 2009. Pharmacokinetics of moxifloxacin in cerebrospinal fluid and plasma in patients with tuberculous meningitis. Clin Infect Dis. 49(7):1080-2.
23. Magis-Escurra C., Later-Nijland H.M., Alffenaar J.W., Broeders J., Burger D.M., van Crevel R., Boeree M.J., Donders A.R., van Altena R., van der Werf T.S., and Aarnoutse R.E. 2014. Population pharmacokinetics and limited sampling strategy for first-line tuberculosis drugs and moxifloxacin. Int J Antimicrob Agents. 44(3):229-34.
24. Medicines Evaluation Board (MEB) (ed.). 2017. Summary of product characteristics. Rifampicin. Medicines Evaluation Board, Utrecht, The Netherlands.
25. Pranger A.D., Alffenaar J.W., Wessels A.M., Greijdanus B., and Uges D.R. 2010.
Determination of moxifloxacin in human plasma, plasma ultrafiltrate, and cerebrospinal fluid by a rapid and simple liquid chromatography-tandem mass spectrometry method. J Anal Toxicol. 34(3):135-41.
26. Pranger A.D., Kosterink J.G., van Altena R., Aarnoutse R.E., van der Werf T.S., Uges D.R., and Alffenaar J.W. 2011. Limited-sampling strategies for therapeutic drug monitoring of moxifloxacin in patients with tuberculosis. Ther Drug Monit. 33(3):350-4.
27. Stass H. and Kubitza D. 1999. Pharmacokinetics and elimination of moxifloxacin after oral and intravenous administration in man. J Antimicrob Chemother. 43 Suppl B:83-90.
28. Ray J., Gardiner I., and Marriott D. 2003. Managing antituberculosis drug therapy by therapeutic drug monitoring of rifampicin and isoniazid. Intern Med J. 33(5-6):229-34. 29. Mcllleron H., Wash P., Burger A., Norman J., Folb P.I., and Smith P. 2006. Determinants of
rifampin, isoniazid, pyrazinamide, and ethambutol pharmacokinetics in a cohort of tuberculosis patients. Antimicrob Agents Chemother. 50(4):1170-7.
30. Verbeeck R.K, Günther G., Kibuule D., Hunter C., and Rennie T.W. 2016. Optimizing treatment outcome of first-line anti-tuberculosis drugs: the role of therapeutic drug monitoring. Eur J Clin Pharmacol. 72(8):905-16.
31. Cello J.P. and Day L.W. 2009. Idiopathic AIDS enteropathy and treatment of gasterointestinal oppertunistic pathogens. Gastroenterology. 136(6):1952-65.
32. Naidoo A., Chirehwa M., Mcllleron H., Naidoo K., Essack S., Yende-Zuma N., Kimba-Phongi E., Adamson J., Govender K., Padayatchi N., and Denti P. 2017. Effect of rifampicin and efavirenz on moxifloxacin concentrations when co-administered in patients with drug-susceptible TB. J Antimicrob Chemother. 72(5):1441-1449.
Supplemental table 1: Tuberculosis treatment (n = 39). Parameter Value Tuberculosis Culture-positive 38 (97) Localization Pulmonary 28 (72) Extrapulmonary 11 (28) Resistance pattern Drug-sensitive 11 (28)
Intermediate INH resistant 1 (3)
INH resistant 2 (5) MDR 23 (59) XDR 1 (3) Co-treatment for TB1 First-line agents2 Isoniazid 13 (33) Rifampicin 15 (39) Pyrazinamide 17 (44) Ethambutol 24 (62) Rifabutin 1 (3)
Data are presented as n (%). 1TB regimen based on drug-tolerance and
drug susceptibility tests. 2WHO classification.
Supplemental table 1: Tuberculosis treatment (n = 39) (continued).
Co-treatment for TB1
Second-line agents2
Group A. Fluoroquinolones
Levofloxacin 1 (3)
Group B. Second-line injectable agents
Amikacin 19 (49)
Kanamycin 5 (13)
Capreomycin 1 (3)
Group C. Other core second-line agents
Prothionamide 8 (21)
Cycloserine 2 (5)
Linezolid 25 (64)
Clofazimine 17 (44)
Group D. Add-on agents
p-Aminosalicylic acid 1 (3) Thioacetazone 1 (3) Other drugs Clarithromycin 3 (8) Doxycycline 1 (3) Co-trimoxazole 7 (18) Azithromycin 2 (5)
Data are presented as n (%). 1TB regimen based on drug-tolerance and
Chapter
4
bSupplemental table 1: Tuberculosis treatment (n = 39).
Parameter Value Tuberculosis Culture-positive 38 (97) Localization Pulmonary 28 (72) Extrapulmonary 11 (28) Resistance pattern Drug-sensitive 11 (28)
Intermediate INH resistant 1 (3)
INH resistant 2 (5) MDR 23 (59) XDR 1 (3) Co-treatment for TB1 First-line agents2 Isoniazid 13 (33) Rifampicin 15 (39) Pyrazinamide 17 (44) Ethambutol 24 (62) Rifabutin 1 (3)
Data are presented as n (%). 1TB regimen based on drug-tolerance and
drug susceptibility tests. 2WHO classification.
Supplemental table 1: Tuberculosis treatment (n = 39) (continued).
Co-treatment for TB1
Second-line agents2
Group A. Fluoroquinolones
Levofloxacin 1 (3)
Group B. Second-line injectable agents
Amikacin 19 (49)
Kanamycin 5 (13)
Capreomycin 1 (3)
Group C. Other core second-line agents
Prothionamide 8 (21)
Cycloserine 2 (5)
Linezolid 25 (64)
Clofazimine 17 (44)
Group D. Add-on agents
p-Aminosalicylic acid 1 (3) Thioacetazone 1 (3) Other drugs Clarithromycin 3 (8) Doxycycline 1 (3) Co-trimoxazole 7 (18) Azithromycin 2 (5)
Data are presented as n (%). 1TB regimen based on drug-tolerance and
4C
Chapter
Rifampicin and moxifloxacin
for tuberculous meningitis
O.W. Akkerman, A.D. Pranger, R. van Altena, T.S. van der Werf, and J.W.C. Alffenaar
