- Email: [email protected]
Authors’ reply
Letters to the Editor / International Journal of Antimicrobial Agents 24 (2004) 622–630
Besides PEARLS, there are many other surveillance studies or systems that collect resistance data worldwide [8,9]. However, with the exception of EARSS, none reports data on patient demography and on the incidence of infections due to antimicrobial-resistant micro-organisms, and no or little attempt is made to obtain data that are representative of the participating countries, or at least to provide data on the number and the characteristics of the participating centres. Despite accumulating surveillance data, estimating the burden of antimicrobial resistance remains a challenge. The pharmaceutical industry invests a lot of resources in post-marketing surveillance such as the PEARLS study. Because susceptibility testing is performed centrally by a reference laboratory, the quality of the results is considered excellent. When the participating centres represent a representative sample of centres in these countries, the results can be used to update national guidelines for empirical antimicrobial therapy. However, in the absence of information on the characteristics and demographics of the participating centres, these results are of little use for public health research. We challenge the PEARLS study, as well as all other corporate surveillance studies, to report not only on the percentage of antimicrobialresistant isolates, but also on the incidence of infections due to these antimicrobial-resistant micro-organisms, to report on the number and the characteristics of the participating centres, and to aim at including a representative panel of centres in each country. Only then will we have the possibility of estimating the burden of antimicrobial resistance as a joint effort from pharmaceutical industry and academia.
References [1] Bouchillon SK, Johnson BM, Hoban DJ, et al. Determining incidence of extended spectrum -lactamase producing Enterobacteriaceae, vancomycin-resistant Enterococcus faecium and methicillinresistant Staphylococcus aureus in 38 centres from 17 countries: the PEARLS study 2001–2002. Int J Antimicrob Agents 2004;24:119–24. [2] Cornaglia G, Hryniewicz W, Jarlier V, et al., on behalf of the ESCMID Study Group for Antimicrobial Resistance Surveillance. European recommendations for antimicrobial resistance surveillance. Clin Microbiol Infect 2004;10:349–83, Erratum in: Clin Microbiol Infect 2004;10:following 497. [3] Armitage P, Berry G. Statistical methods in medical research. 2nd ed. London: Blackwell; 1987. [4] WHO Global Strategy for Containment of Antimicrobial Resistance. Geneva, Switzerland: World Health Organization, 2001. WHO/CDS/CSR/DRS/2001.2 Available from: URL: http://www. who.int/csr/resources/publications/drugresist/en/EGlobal Strat.pdf (Accessed 2 August 2004). [5] European Antimicrobial Surveillance System (EARSS). Available from: URL: http://www.earss.rivm.nl/ (Accessed 2 August 2004). [6] Antibiotic Resistance Prevention and Control (ARPAC). Available from: URL: http://www.abdn.ac.uk/arpac/ (Accessed 2 August 2004). [7] Strategic Council on Resistance in Europe (SCORE) report, EijkmanWinkler Institute, University Medical Center Utrecht. Utrecht, The Netherlands; 2004. [8] Bax R, Bywater R, Cornaglia G, et al. Surveillance of antimicrobial resistance-what, how and whither? Clin Microbiol Infect 2001;7:316–25.
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[9] Monnet DL. Toward multinational antimicrobial resistance surveillance systems in Europe. Int J Antimicrob Agents 2000;15:91–101.
Dominique L. Monnet∗ Niels Frimodt-Møller National Centre for Antimicrobials and Infection Control Statens Serum Institut, Artillerivej 5, DK-2300 Copenhagen S, Denmark ∗ Corresponding author. Tel.: +45 3268 8190 fax: +45 3268 3231 E-mail address: [email protected] (D.L. Monnet) doi:10.1016/j.ijantimicag.2004.09.009
Author’s replay Sir, The comments offered by Monnet and Møller enlighten the reader on several interesting points of concern to this author and others. The use of ‘incidence’ or ‘incidence rate’ as a measure of new disease entities per patient population (usually expressed in terms of 1000 or 100,000) over time (usually a year or subject-days) is most appropriately applied to epidemiological studies and ensuing statistical analysis [1,2]. The most frequently encountered use of the term in medical literature is derived from its colloquial definition as a general measure of ‘occurrence, rate, or frequency of disease’ [3], often expressed in terms of raw numbers or percentage of cohort populations. One needs only a cursory review of the available literature to find more than 46,000 publications with ‘incidence’ in the title and more than 3000 titles with both terms ‘incidence’ and ‘disease’. A detailed analysis of the most recent 100 titles demonstrates wide latitude in favour of the more colloquial usage by four of five authors. The majority of authors refer to incidence in terms of rate occurrence or percentage of population. The reverse is true, although not universally, of authors of epidemiological publications where the stricter and more correct usage is applied. Monnet has previously pointed out that a simple resistant percentage, such as % MRSA, can show excellent correlation with the number of MRSA per 1000 patientdays [4]. From this point of view, the broader definition of incidence serves a useful purpose in peer communications, cohort comparison and in extracting cause and effect of methodological intervention with the appropriate application of the principles of probability. Also, be they right or wrong, the majority of academic writers are not going to change in the near future. The PEARLS study was not designed along epidemiological parameters nor does it attempt to determine incidence of disease. The stated purpose of this study was to set a baseline prevalence of certain resistant phenotypes at a discrete point in time and revisit these populations following a customized intervention programme within each investigating centre. The term ‘prevalence’, unlike ‘incidence’, is more apt to be used in its correct context, defined as the to-
624
Letters to the Editor / International Journal of Antimicrobial Agents 24 (2004) 622–630
tal number of existing cases of a disorder as a proportion of a population (usually per 100,000 people) at a specific time [5]. Unfortunately, this author succumbed to the vernacular and should have employed the less precise but more correct ‘rate’ or ‘percentage’. Although occasionally these terms are used interchangeably, from a statistical point of view they differ. As a published authority on antimicrobial surveillance studies, Monnet has described the intricacies and complexities of existing programmes [4]. As the owner of the Surveillance Data Link Network (http://www.sdln.com/) and publisher of the Alexander Network (http://www. alexandernetwork.com/), and several others, this author acknowledges the inherent limitations of large surveillance studies. Demographic data such as isolate source, location, patient age, and sex, among others, was obtained on all isolates in the PEARLS study as were the number and characteristics of the participating centres. We agree with Monnet and Møller that these data should be presented. However, the exclusion of such data is frequently mandated by the constraints of publication guidelines. Many journals/reviewers demand that authors remove tables or limit their number, especially if the demographic features are not directly pertinent to the data presented. Even discerning readers skip over verbose text and the simple acknowledgement of investigators and centres, as in the PEARLS publication, is becoming increasingly more archaic. Contrary to the assertion of Monnet and Møller, and pertinent to the question of incidence, hospital and laboratory demographics are not always readily available and such data frequently rely on unverifiable entries from questionnaires filled out by the lower echelons of uninformed sources. It is also a fact of life that good surveillance studies consume considerable financial resources, one of the chief limiting factors of national, corporate and privately sponsored surveillance programmes [4,6]. Our experience has shown that the addition of a single demographic parameter may add as much as $5 (USD) to the cost of an already expensive study isolate, ballooning to tens of thousands of dollars at the bottom line and many times becoming cost prohibitive. The finite nature of state, national and corporate budgets in these days of economic uncertainty dictates which parameters are included more often than not. We join Monnet, Møller and others in the ongoing challenge to further delineate and more accurately quantify the burden of antimicrobial resistance at the local, state and global levels. ‘Although good quality data should only be included in a system’s databases, one should bear in mind that the objective of antimicrobial resistance surveillance systems is not to measure the exact level of antimicrobial resistance within one hospital, region or country, but to get a reasonable estimate of this level to ‘evaluate’ the extent of the problem, possibly by comparison to other institutions with similar characteristics and initiate actions for its control.’—Monnet, 2000 [4].
We trust the PEARLS study attains these modest expectations.
References [1] “incidence” n. In epidemiology, the frequency of occurrence or onset of new cases of a disorder as a proportion of a population in a specific time period, usually expressed as the number of new cases per 100,000 per annum. Colman AM. A dictionary of psychology. Oxford University Press; 2001. Oxford Reference Online. Oxford University Press. Vanderbilt University; 20 August 2004. [2] “incidence rate” The number of new cases of a disease occurring during a given period as a proportion of the number of people in the population. It is usually expressed as cases per 1,000 or 100,000 per annum. Upton G, Cook I. A dictionary of statistics. Oxford University Press; 2002. Oxford Reference Online. Oxford University Press. Vanderbilt University; 20 August 2004 (A Dictionary of Statistics in Physical Sciences & Mathematics.). [3] “incidence” n. The occurrence, rate, or frequency of a disease, crime, or other undesirable thing. Pearsall J, editor. The concise oxford dictionary. Oxford University Press; 2001. Oxford Reference Online. Oxford University Press. Vanderbilt University; 20 August 2004. [4] Monnet DL. Toward multinational antimicrobial resistance surveillance systems in Europe. Int J Antimicrob Agents 2000;15(2): 91–101. [5] “prevalence” n. In epidemiology, the total number of existing cases of a disorder as a proportion of a population (usually per 100,000 people) at a specific time. Colman AM. A dictionary of psychology. Oxford University Press; 2001. Oxford reference online. Oxford University Press. Vanderbilt University; 20 August 2004. [6] Bax R, et al. Surveillance of antimicrobial resistance—what, how and whether? Clin Microbiol Infect 2001;7(6):316–25.
S.K. Bouchillon∗ B.M. Johnson D.J. Hoban J.L. Johnson M.J. Dowzicky D.H. Wu M.A. Visalli P.A. Bradford International Health Management Associates 2122 Palmer Drive, Schaumburg, IL 60173, USA ∗ Corresponding
author. Tel.: +1 615 599 8429 fax: +1 847 745 0495 E-mail address: [email protected] (S.K. Bouchillon)
doi:10.1016/j.ijantimicag.2004.09.010
Lower gastrointestinal bleeding in a patient with typhoid fever Sir, We read with interest the paper ‘Treatment of typhoid fever in children with a flexible-duration of ceftriaxone, compared with 14-day treatment with chloramphenicol’ by
Besides PEARLS, there are many other surveillance studies or systems that collect resistance data worldwide [8,9]. However, with the exception of EARSS, none reports data on patient demography and on the incidence of infections due to antimicrobial-resistant micro-organisms, and no or little attempt is made to obtain data that are representative of the participating countries, or at least to provide data on the number and the characteristics of the participating centres. Despite accumulating surveillance data, estimating the burden of antimicrobial resistance remains a challenge. The pharmaceutical industry invests a lot of resources in post-marketing surveillance such as the PEARLS study. Because susceptibility testing is performed centrally by a reference laboratory, the quality of the results is considered excellent. When the participating centres represent a representative sample of centres in these countries, the results can be used to update national guidelines for empirical antimicrobial therapy. However, in the absence of information on the characteristics and demographics of the participating centres, these results are of little use for public health research. We challenge the PEARLS study, as well as all other corporate surveillance studies, to report not only on the percentage of antimicrobialresistant isolates, but also on the incidence of infections due to these antimicrobial-resistant micro-organisms, to report on the number and the characteristics of the participating centres, and to aim at including a representative panel of centres in each country. Only then will we have the possibility of estimating the burden of antimicrobial resistance as a joint effort from pharmaceutical industry and academia.
References [1] Bouchillon SK, Johnson BM, Hoban DJ, et al. Determining incidence of extended spectrum -lactamase producing Enterobacteriaceae, vancomycin-resistant Enterococcus faecium and methicillinresistant Staphylococcus aureus in 38 centres from 17 countries: the PEARLS study 2001–2002. Int J Antimicrob Agents 2004;24:119–24. [2] Cornaglia G, Hryniewicz W, Jarlier V, et al., on behalf of the ESCMID Study Group for Antimicrobial Resistance Surveillance. European recommendations for antimicrobial resistance surveillance. Clin Microbiol Infect 2004;10:349–83, Erratum in: Clin Microbiol Infect 2004;10:following 497. [3] Armitage P, Berry G. Statistical methods in medical research. 2nd ed. London: Blackwell; 1987. [4] WHO Global Strategy for Containment of Antimicrobial Resistance. Geneva, Switzerland: World Health Organization, 2001. WHO/CDS/CSR/DRS/2001.2 Available from: URL: http://www. who.int/csr/resources/publications/drugresist/en/EGlobal Strat.pdf (Accessed 2 August 2004). [5] European Antimicrobial Surveillance System (EARSS). Available from: URL: http://www.earss.rivm.nl/ (Accessed 2 August 2004). [6] Antibiotic Resistance Prevention and Control (ARPAC). Available from: URL: http://www.abdn.ac.uk/arpac/ (Accessed 2 August 2004). [7] Strategic Council on Resistance in Europe (SCORE) report, EijkmanWinkler Institute, University Medical Center Utrecht. Utrecht, The Netherlands; 2004. [8] Bax R, Bywater R, Cornaglia G, et al. Surveillance of antimicrobial resistance-what, how and whither? Clin Microbiol Infect 2001;7:316–25.
623
[9] Monnet DL. Toward multinational antimicrobial resistance surveillance systems in Europe. Int J Antimicrob Agents 2000;15:91–101.
Dominique L. Monnet∗ Niels Frimodt-Møller National Centre for Antimicrobials and Infection Control Statens Serum Institut, Artillerivej 5, DK-2300 Copenhagen S, Denmark ∗ Corresponding author. Tel.: +45 3268 8190 fax: +45 3268 3231 E-mail address: [email protected] (D.L. Monnet) doi:10.1016/j.ijantimicag.2004.09.009
Author’s replay Sir, The comments offered by Monnet and Møller enlighten the reader on several interesting points of concern to this author and others. The use of ‘incidence’ or ‘incidence rate’ as a measure of new disease entities per patient population (usually expressed in terms of 1000 or 100,000) over time (usually a year or subject-days) is most appropriately applied to epidemiological studies and ensuing statistical analysis [1,2]. The most frequently encountered use of the term in medical literature is derived from its colloquial definition as a general measure of ‘occurrence, rate, or frequency of disease’ [3], often expressed in terms of raw numbers or percentage of cohort populations. One needs only a cursory review of the available literature to find more than 46,000 publications with ‘incidence’ in the title and more than 3000 titles with both terms ‘incidence’ and ‘disease’. A detailed analysis of the most recent 100 titles demonstrates wide latitude in favour of the more colloquial usage by four of five authors. The majority of authors refer to incidence in terms of rate occurrence or percentage of population. The reverse is true, although not universally, of authors of epidemiological publications where the stricter and more correct usage is applied. Monnet has previously pointed out that a simple resistant percentage, such as % MRSA, can show excellent correlation with the number of MRSA per 1000 patientdays [4]. From this point of view, the broader definition of incidence serves a useful purpose in peer communications, cohort comparison and in extracting cause and effect of methodological intervention with the appropriate application of the principles of probability. Also, be they right or wrong, the majority of academic writers are not going to change in the near future. The PEARLS study was not designed along epidemiological parameters nor does it attempt to determine incidence of disease. The stated purpose of this study was to set a baseline prevalence of certain resistant phenotypes at a discrete point in time and revisit these populations following a customized intervention programme within each investigating centre. The term ‘prevalence’, unlike ‘incidence’, is more apt to be used in its correct context, defined as the to-
624
Letters to the Editor / International Journal of Antimicrobial Agents 24 (2004) 622–630
tal number of existing cases of a disorder as a proportion of a population (usually per 100,000 people) at a specific time [5]. Unfortunately, this author succumbed to the vernacular and should have employed the less precise but more correct ‘rate’ or ‘percentage’. Although occasionally these terms are used interchangeably, from a statistical point of view they differ. As a published authority on antimicrobial surveillance studies, Monnet has described the intricacies and complexities of existing programmes [4]. As the owner of the Surveillance Data Link Network (http://www.sdln.com/) and publisher of the Alexander Network (http://www. alexandernetwork.com/), and several others, this author acknowledges the inherent limitations of large surveillance studies. Demographic data such as isolate source, location, patient age, and sex, among others, was obtained on all isolates in the PEARLS study as were the number and characteristics of the participating centres. We agree with Monnet and Møller that these data should be presented. However, the exclusion of such data is frequently mandated by the constraints of publication guidelines. Many journals/reviewers demand that authors remove tables or limit their number, especially if the demographic features are not directly pertinent to the data presented. Even discerning readers skip over verbose text and the simple acknowledgement of investigators and centres, as in the PEARLS publication, is becoming increasingly more archaic. Contrary to the assertion of Monnet and Møller, and pertinent to the question of incidence, hospital and laboratory demographics are not always readily available and such data frequently rely on unverifiable entries from questionnaires filled out by the lower echelons of uninformed sources. It is also a fact of life that good surveillance studies consume considerable financial resources, one of the chief limiting factors of national, corporate and privately sponsored surveillance programmes [4,6]. Our experience has shown that the addition of a single demographic parameter may add as much as $5 (USD) to the cost of an already expensive study isolate, ballooning to tens of thousands of dollars at the bottom line and many times becoming cost prohibitive. The finite nature of state, national and corporate budgets in these days of economic uncertainty dictates which parameters are included more often than not. We join Monnet, Møller and others in the ongoing challenge to further delineate and more accurately quantify the burden of antimicrobial resistance at the local, state and global levels. ‘Although good quality data should only be included in a system’s databases, one should bear in mind that the objective of antimicrobial resistance surveillance systems is not to measure the exact level of antimicrobial resistance within one hospital, region or country, but to get a reasonable estimate of this level to ‘evaluate’ the extent of the problem, possibly by comparison to other institutions with similar characteristics and initiate actions for its control.’—Monnet, 2000 [4].
We trust the PEARLS study attains these modest expectations.
References [1] “incidence” n. In epidemiology, the frequency of occurrence or onset of new cases of a disorder as a proportion of a population in a specific time period, usually expressed as the number of new cases per 100,000 per annum. Colman AM. A dictionary of psychology. Oxford University Press; 2001. Oxford Reference Online. Oxford University Press. Vanderbilt University; 20 August 2004. [2] “incidence rate” The number of new cases of a disease occurring during a given period as a proportion of the number of people in the population. It is usually expressed as cases per 1,000 or 100,000 per annum. Upton G, Cook I. A dictionary of statistics. Oxford University Press; 2002. Oxford Reference Online. Oxford University Press. Vanderbilt University; 20 August 2004 (A Dictionary of Statistics in Physical Sciences & Mathematics.). [3] “incidence” n. The occurrence, rate, or frequency of a disease, crime, or other undesirable thing. Pearsall J, editor. The concise oxford dictionary. Oxford University Press; 2001. Oxford Reference Online. Oxford University Press. Vanderbilt University; 20 August 2004. [4] Monnet DL. Toward multinational antimicrobial resistance surveillance systems in Europe. Int J Antimicrob Agents 2000;15(2): 91–101. [5] “prevalence” n. In epidemiology, the total number of existing cases of a disorder as a proportion of a population (usually per 100,000 people) at a specific time. Colman AM. A dictionary of psychology. Oxford University Press; 2001. Oxford reference online. Oxford University Press. Vanderbilt University; 20 August 2004. [6] Bax R, et al. Surveillance of antimicrobial resistance—what, how and whether? Clin Microbiol Infect 2001;7(6):316–25.
S.K. Bouchillon∗ B.M. Johnson D.J. Hoban J.L. Johnson M.J. Dowzicky D.H. Wu M.A. Visalli P.A. Bradford International Health Management Associates 2122 Palmer Drive, Schaumburg, IL 60173, USA ∗ Corresponding
author. Tel.: +1 615 599 8429 fax: +1 847 745 0495 E-mail address: [email protected] (S.K. Bouchillon)
doi:10.1016/j.ijantimicag.2004.09.010
Lower gastrointestinal bleeding in a patient with typhoid fever Sir, We read with interest the paper ‘Treatment of typhoid fever in children with a flexible-duration of ceftriaxone, compared with 14-day treatment with chloramphenicol’ by