1 Department of Medical Microbiology, University College London, Royal Free Campus, Rowland Hill Street, London NW3 2PF, UK; 2 Mycobacteriology Clinical Reference Laboratory, National Jewish Medical and Research Center, Denver, CO 80206, USA
Received 20 September 2002; returned 15 April 2003; revised 17 April 2003; accepted 29 May 2003
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Abstract |
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Keywords: tuberculosis, clinical trials, Phase II, mathematical models
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Introduction |
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Jindani et al. developed a method to investigate the effect of anti-tuberculosis agents given singly or in combination.5 They determined the viable count of Mycobacterium tuberculosis over 12 h overnight in sputa collected sequentially. The linear regression coefficient of the fall in mean log10 cfu/day for 02, 214 and 014 day periods in the different treatment groups was calculated. As the differences in the mean fall in counts during days 02 between regimens were highly significant, whereas those for days 214 were not, it was decided that early bactericidal activity (EBA) would be defined as the rate of fall of colony forming units during the first 2 days of treatment and expressed as log10 cfu/day. Since this original work, there have been many studies examining EBA.613
There are several problems associated with this approach to evaluating antimicrobial activity of anti-tuberculosis drugs. First, using this technique, only isoniazid and ciprofloxacin have been identified as having significant bactericidal activity.10 Other drugs such as pyrazinamide have little activity expressed as EBA using the 48 h definition.5 Thus if this approach were adopted in studying candidate drugs, some important agents could be dismissed as being inactive. Second, the reported studies have shown considerable variation in results between patients, between centres and between specimens from the same patient.11,14 It has been variously suggested that this is due to the admixture of saliva with sputum, deficient training of the patient and the amount of physiotherapy provided affecting the quality of the sputum sample. Alternatively, it has been suggested that variation is greater among patients with more chronic disease.14
A novel reiterative exponential decay model has recently been reported.15 If this approach is to be useful, it must address the issue of intra-patient and inter-patient variability. Additionally, it should permit the activity of new drugs to be compared with that of the currently available anti-tuberculosis agents.6 In this paper, using data from a number of previously published early bactericidal studies, a hierarchy of bactericidal activity is demonstrated with different drugs, and also patients from different centres can be compared.
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Materials and methods |
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Exponential decay regression analysis was carried out on the data using Graphpad Prism, USA using the equation:
V = S + Mekt (Equation 1)
where V is the viable count, M the population of bacteria susceptible to the test drug, S the population susceptible only to sterilizing agents, t the day of sputum collection as related to start of therapy, k the rate constant for the bacteria killed each day and e the Napierian constant.
The goodness of fit to the calculated exponential decay curve was estimated by calculating r2 using the formula:
(Equation 2)
using the Graphpad Prism program. The results of the curve fitting was accepted if the r2 value calculated from at least four points was greater than 0.95. If this was not the case, then a single point was removed sequentially, and taking the remaining points, a new value for r2 recalculated. All possible combinations of data were then calculated and the best fit compared. If only one change brought the r2 to above 0.95, that result was accepted but if more than one of the deletions brought a value of r2 > 0.95, the data set with the lowest variance was accepted as the best estimate and included in further calculations. If removal of a single point was insufficient then an additional point was removed provided that at least four points were available. The results of the recalculation were treated as above.
Using values of k derived from the curve-fitting, it was possible to calculate the time (in days) to reduce the viable count by 50% (vt50) using the formula:
vt50 = ln(0.5)/k (Equation 3)
Statistics
All statistical assessments were calculated using the GraphPad Instat program. The significance of differences between the means of vt50 for isoniazid obtained from different centres was determined by the KruskalWallis non-parametric ANOVA.
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Results |
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If the reiterative exponential decay model is to be useful, it should permit the results of clinical trials to be compared. In most published studies, EBA results for isoniazid are used as a gold standard because it has the highest bactericidal activity among the anti-tuberculosis drugs. The comparability of results was investigated by determining the vt50 for isoniazid using raw data from three different trials, one carried out in Nairobi, Kenya in the 1970s, one in Moshi, Tanzania in 1990 and a multicentre study from the United States in 19931995.5,12,13 The mean value for vt50 obtained was for the Kenyan study 0.58 S.E.M. 0.18, for the Tanzanian study 0.41 S.E.M. 0.04, and for the United States study 0.55 S.E.M. 0.12. These differences were not statistically significant (P = 0.77 KruskalWallis non-parametric ANOVA).
For a new drug under evaluation, it would be useful to be able to place the test agent in a spectrum of activity. The mean values of vt50 for all of the agents were plotted (Figure 1). This shows that there is an overlapping spectrum of activity from isoniazid 300 mg (0.58 days) to para-amino-salicylic acid (2.9 days) The variation between column means was greater than could be expected by chance (P = 0.0002 KruskalWallis non-parametric ANOVA).
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Discussion |
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An alternative approach to evaluating mono-therapy clinical trials has been described previously.15 This depends on measuring the sputum viable count for at least 5 days giving a minimum of six data points and plotting an exponential decay curve using these values. Modern computers allow the use of non-linear analysis for this sort of data. This overcomes the problems imposed by log transforming data which assumes that variation around each point follows a Gaussian distribution and that the standard deviation is the same at each value of x. Experience shows that this is not the case for EBA data and thus log transformation is inappropriate.
Additionally, it has been shown that data from mono-therapy studies fit an exponential decay model and those discrepant points can be identified and removed. The use of a rule based method means that the removal of a point is not influenced by the investigators but rather is made in a way that attempts to produce the best fit to the exponential model. The results reported in this study indicate that this approach produces smaller patient-to-patient variation and distinguishes between discrepant results and true biological variation.15 In this study, the reiterative exponential decay model is tested by determining whether it permits comparison between centres and provides a hierarchical activity with which to compare a new agent.
It is essential that the results of clinical trials be reproducible from centre to centre if they are to be widely applicable, a problem that handicapped earlier methods of evaluating early bactericidal activity.11,14 Using the reiterative exponential decay model, the results of the early bactericidal activity of isoniazid at three centres at different times and with disparate patient populations were shown to be comparable. This suggests that the reiterative decay model will permit new studies to be compared more easily than previous methods.
When evaluating a new drug in Phase IIa, the question being asked is whether the new drug is active against tuberculosis in the human host.16 It was found that all anti-tuberculosis agents exhibited early antimicrobial activity when the available data were re-evaluated using our model. Also, there is a hierarchy of activity ranging from isoniazid which has the highest activity to para-amino-salicylic acid which has the lowest activity (Figure 1). This outcome accords with clinical experience with these drugs with the exception of pyrazinamide which is known to be a vital component of therapy.17,18 It is notable that for the drugs with the least activity, pyrazinamide, thiacetazone and para-amino-salicylic acid, an increasing proportion did not follow an exponential decay curve. This arises because in drugs with weaker activity, variation caused intermittent excretion of bacteria into the sputum which overwhelms the apparent bactericidal effect of the drug. This phenomenon has been reported previously in studies of the decline in FEV1.19 Thus, for a new drug, if the sputum viable count follows an exponential decay curve, this provides evidence of activity against tuberculosis. The degree of activity can then be defined by the value of vt50 and compared with other drugs.
The antimicrobial activity defined by the vt50 measured in this study can only be considered a preliminary estimate as the number of patients in many of the groups was small. This may be a major reason that the differences between the drugs failed to achieve statistical significance. Further studies are required to generate larger sample sizes to increase the confidence in the mono-therapy results obtained. Although the exponential decay model evaluated over 5 days is a useful tool in the evaluation of new anti-tuberculosis drugs, it could not be applied to drugs only active against dormant organisms. The reiterative exponential decay model also leaves unanswered questions as to the influence of patient immune response, acetylator status and differing virulence of the infecting organisms. It may be that with further refinement of the model and with larger patient studies, the influence of these factors could be studied in the critical early phase of therapy.
In conclusion, the method using the reiterative exponential decay model has been evaluated using data from studies investigating a range of anti-tuberculosis agents. The results show that it is possible to compare the results of clinical trials from different locations and times. Also that it is possible to generate a hierarchy of anti-tuberculosis activity ranging from isoniazid (highly active) to thiacetazone and para-amino-salicylic acid. This conforms with clinical experience and the results of large-scale clinical trials.
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Acknowledgements |
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Footnotes |
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References |
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2 . WHO/IUATLD Global Project on Anti-tuberculosis Drug Resistance Surveillance. (1997). Anti-Tuberculosis Drug Resistance in the World. WHO, Geneva.
3 . Walley, J. D., Khan, M. A., Newell, J. N. et al. (2001). Effectiveness of the direct observation component of DOTS for tuberculosis: a randomised controlled trial in Pakistan. Lancet 357, 6649.[CrossRef][ISI][Medline]
4 . Pablos-Mendez, A. (2000). Working alliance for TB drug development, Cape Town, South Africa, February 8th, 2000. International Journal of Tuberculosis and Lung Disease 4, 48990.[ISI][Medline]
5 . Jindani, A., Aber, V. R., Edwards, E. A. et al. (1980). The early bactericidal activity of drugs in patients with pulmonary tuberculosis. American Review of Respiratory Diseases 121, 93949.
6 . Botha, F. J., Sirgel, F. A., Parkin, D. P. et al. (1996). Early bactericidal activity of ethambutol, pyrazinamide and the fixed combination of isoniazid, rifampicin and pyrazinamide (Rifater) in patients with pulmonary tuberculosis. South African Medical Journal 86, 1558.[ISI][Medline]
7
.
Donald, P. R., Sirgel, F. A., Botha, F. J. et al. (1997). The early bactericidal activity of isoniazid related to its dose size in pulmonary tuberculosis. American Journal of Respiratory and Critical Care Medicine 156, 895900.
8
.
Donald, P. R., Sirgel, F. A., Kanyok, T. P. et al. (2000). Early bactericidal activity of paromomycin (aminosidine) in patients with smear-positive pulmonary tuberculosis. Antimicrobial Agents and Chemotherapy 44, 32857.
9 . Sirgel, F. A., Botha, F. J., Parkin, D. P. et al. (1993). The early bactericidal activity of rifabutin in patients with pulmonary tuberculosis measured by sputum viable counts: a new method of drug assessment. Journal of Antimicrobial Chemotherapy 32, 86775.[Abstract]
10
.
Sirgel, F. A., Botha, F. J., Parkin, D. P. et al. (1997). The early bactericidal activity of ciprofloxacin in patients with pulmonary tuberculosis. American Journal of Respiratory and Critical Care Medicine 156, 9015.
11
.
Sirgel, F. A., Donald, P. R., Odhiambo, J. et al. (2000). A multicentre study of the early bactericidal activity of anti-tuberculosis drugs. Journal of Antimicrobial Chemotherapy 45, 85970.
12 . Kennedy, N., Fox, R., Kisyombe, G. M. et al. (1993). Early bactericidal and sterilizing activities of ciprofloxacin in pulmonary tuberculosis. American Review of Respiratory Diseases 148, 154751.
13
.
Hafner, R., Cohn, J. A., Wright, D. J. et al. (1997). Early bactericidal activity of isoniazid in pulmonary tuberculosis. Optimization of methodology. The DATRI 008 Study Group. American Journal of Respiratory and Critical Care Medicine 156, 91823.
14
.
Sirgel, F., Venter, A. & Mitchison, D. (2001). Sources of variation in studies of the early bactericidal activity of anti-tuberculosis drugs. Journal of Antimicrobial Chemotherapy 47, 17782.
15
.
Gillespie, S. H., Gosling, R. D. & Charalambous, B. M. (2002). A reiterative method for calculating the early bactericidal activity of anti-tuberculosis drugs. American Journal of Respiratory and Critical Care Medicine 166, 315.
16 . OBrien, R. J. (2001). Scientific blueprint for tuberculosis drug development. Tuberculosis 81, 1945.
17
.
OBrien, R. J. (2002). Studies of the early bactericidal activity of new drugs for tuberculosis: a help or a hindrance to anti-tuberculosis drug development? American Journal of Respiratory and Critical Care Medicine 166, 34.
18 . Mitchison, D. A. (1985). The action of anti-tuberculosis drugs in short-course chemotherapy. Tubercle 66, 21925.[ISI][Medline]
19 . Fletcher, C., Peto, R., Tinker, C. et al. (1976). Variance of measurement and real variance of FEV1 slopes. In The Treatment of Chronic Bronchitis and Emphysema, pp. 1704. Oxford University Press, Oxford, UK.