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Neutrophil CD64 expression as marker of bacterial infection: A systematic review and meta-analysis
Journal of Infection (2010) 60, 313e319
www.elsevierhealth.com/journals/jinf
REVIEW
Neutrophil CD64 expression as marker of bacterial infection: A systematic review and meta-analysis ´nchez b, Graciano Garcı´a-Pardo c, Joan Cid a,*, Reyes Aguinaco a, Rafael Sa Andreu Llorente a a
Haematology Service, Hospital Universitari Joan XXIII, IISPV, Universitat Rovira i Virgili, Tarragona, Spain Laboratory Service, Hospital Universitari Joan XXIII, IISPV, Universitat Rovira i Virgili, Tarragona, Spain c Preventive Medicine Unit, Hospital Universitari Joan XXIII, IISPV, Universitat Rovira i Virgili, Tarragona, Spain b
Accepted 24 February 2010 Available online 3 March 2010
KEYWORDS CD64; Diagnostic accuracy; Infection; Systematic review
Summary Objective: We performed a systematic review and meta-analysis of studies to evaluate the diagnostic accuracy of expression of CD64 on polymorphonuclear neutrophils (PMN) as a marker for bacterial infection. Methods: The analysis included studies of patients from all age groups that prospectively evaluated CD64 expression on PMNs for the diagnosis of bacterial infection. We evaluated the methodological quality of the studies according to the 25-item criteria developed by the Standards for Reporting of Diagnostic Accuracy (STARD) committee. We calculated a summary receiver operating characteristic (SROC) curve across studies included in the meta-analysis. Results: The methodological quality score of the 13 included studies ranged from 9 to 16 points (maximum score was 25 points). The pooled sensitivity and specificity for CD64 expression on PMNs were 79% (95% CI: 70e86%) and 91% (95% CI: 85e95%), respectively. The area under curve (AUC) was 0.94. Conclusions: On the basis of this meta-analysis, CD64 expression on PMNs could be a useful diagnostic cell-based parameter of bacterial infections. However, published studies about this topic showed a low methodological quality. ª 2010 The British Infection Society. Published by Elsevier Ltd. All rights reserved.
Introduction Bacterial infections are a major cause of morbidity and mortality in the world.1 The incidence of sepsis in the United States of America is estimated to be 3.0 cases per
1000 inhabitants per year, or 2.2 per 100 hospital discharges.2,3 In our country, we have data from EPINE, the prevalence survey of nosocomial infections in Spain, which is performed annually. The prevalence of patients with nosocomial infections in 2007 was 6.99% with 266 participant hospitals and 61,496 included patients.4
* Corresponding author. Tel.: þ34 977295821; fax: þ34 977295822. E-mail address: [email protected] (J. Cid). 0163-4453/$36 ª 2010 The British Infection Society. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.jinf.2010.02.013
314 Diagnosis of bacterial infections is sometimes challenging, because the use of blood culture, the gold standard for diagnosis of bacteremia, is fraught with difficulties. First, incubation of bacteria may take several days (2e4 days). Second, genuine bacteremia may remain undetected in a significant proportion of infected cases because of the small volume of blood taken. Third, bacteremia in the neonate may often be transient or intermittent, especially during the early stages of infection.5 Moreover, although untreated bacterial infections may cause serious complications, treating viral illnesses or noninfective causes of inflammation with antibiotics is not only ineffective, but also contributes to the development of resistance, increases costs, and adds the risks of toxicity and allergic reactions.6 Thus, an improved diagnostic test for infection and sepsis would have both economic and therapeutic healthcare benefits. Laboratory diagnosis of infection and sepsis still relies on diagnostic tests that have been available since 1970s or before, such as leukocyte neutrophil counts, the presence of myeloid-immature forms in the peripheral blood, and laboratory tests for acute-phase reactants such as C-reactive protein (CRP).7 More recently, most of the effort in developing new-generation and improved diagnostics for infection and sepsis has been directed towards soluble biomarkers in the serum or plasma, such as procalcitonin (PCT).6 However, all these diagnostic tests have some limitations. The cellular diagnostic parameters are typically problematic, subjective and lack specificity, particularly in infants and the elderly. CRP level have been advocated as a more objective diagnostic assay but it becomes elevated in any disease process with tissue injury, not just infection. Finally, PCT has a very good negative predictive value of disease or sepsis although there remains debate as to the value of PCT in the broader context of infection diagnosis and therapeutic monitoring.7 Another approach to rapid and early diagnosis of infection or sepsis is to utilize some of the molecular changes in the cellular component of the innate immune response to detect the presence of infection or sepsis. There is published work that one of the best and most specific indicators of an early systemic acute inflammatory activation or response is the upregulation of polymorphonuclear neutrophil (PMN) expression of CD64.7 CD64 is the high affinity immunoglobulin Fc g receptor I (FcgRI) and it is expressed on monocytes, but only to a very low extent on resting PMNs. There are previous studies that show that CD64 expression on PMNs increases once PMNs become activated and could be a marker of bacterial infection and also differentiate against other inflammatory disorders.5 We therefore systematically review and performed a meta-analysis of studies to adequately evaluate the diagnostic accuracy of expression of CD64 on PMNs as a marker for bacterial infection.
Materials and methods A protocol was written before this study was undertaken, as recommended by the Quality of Reporting of Meta-analyses (QUORUM) statement.8
J. Cid et al.
Retrieving the literature All studies published in the MEDLINE database from January 1970 through 30 November 2009 that adequately evaluated the diagnostic accuracy of expression of CD64 on PMNs for the diagnosis of bacterial infections were identified. With use of a Boolean strategy, cross-searching of the following three categories was done: (1) ‘‘Sensitivity and Specificity’’ OR (2) ‘‘Mass Screening’’ AND (3) ‘‘Receptors, IgG’’. The bibliographies of relevant articles were further crosschecked to search for articles not referenced in the MEDLINE database.9
Selection of studies and data extraction Studies of patients from all age groups that prospectively evaluated CD64 expression on PMNs for the diagnosis of bacterial infection were evaluated. Retrospective studies, reviews, animal studies, and studies for which complete data was unavailable were excluded. Language of the article was limited to English and Spanish. The selection and data extraction was performed by the authors, and disagreements, if any, were resolved by consensus. Raw data from the articles were used to construct 2 2 tables; when unavailable, the tables were constructed using given measures of sensitivity and specificity.
Quality assessment We evaluated the methodological quality of the included studies by applying the 25-item criteria developed by the Standards for Reporting of Diagnostic Accuracy (STARD) committee.10,11 Briefly, the maximum quality score that can be given to a study by this criteria was 25 points: 1 point if the study was identified as a diagnostic accuracy study in the title, abstract or the keywords; 1 point if the authors stated the research question in the introduction section of the study; up to 11 points if the authors described the characteristics of the participants, test methods and statistical methods in the methods section; up to 11 points if the authors report data about participants, test results and estimates in the results section; and 1 point if the authors discussed the clinical applicability of the study findings. A consensus was obtained among three reviewers for the criteria.
Meta-analysis We used the meta-analysis approach of Littenberg and Moses12,13 to create the summary receiver operating characteristic (SROC) curve. We investigated sources of heterogeneity between studies and we performed subgroup analyses according to the age of included patients (children vs. adult patients), technical method used to detect CD64 (flow cytometry (FCM) vs. Leuko64 kit (Trillium Diagnostics, LLC)) and definition of infection (clinical vs. proven diagnosis). We carried out all analyses with software (Review Manager (RevMan) [Computer program]. Version 5.0. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2008) and the Meta-test
Neutrophil CD64 and infection Table 1 Study
315
Main characteristics of the included studies.
ref.
Year
Population (infected vs. non infected)
Means of diagnosis of infectiona
CD64 analysis
Cut-off
Sensitivity (%)
LaysecaEspinosa14 Ng15
2002
Clinical or proven infection Proven infection
FCM
NR
25.8
96.8
FCM
88
2002
Proven infection
FCM
85
91
Ng17
2004
Proven infection
FCM
79
89
Ng18
2006
Proven infection
FCM
78
90
Livaditi19
2006
Term newborn infants (115 vs. 223) Term newborn infants (93 vs. 195) Adults (37 vs. 10)
Proven infection
FCM
Matsui20
2006
Adults (55 vs. 202)
FCM
92.7
96.5
GroseljGrenc21 Bhandari22
2008
Children (29 vs. 27)
Clinical or proven infection Proven infection
FCM
4000 mol/cell 2000 mol/cell 6136 mol/cell 6136 mol/cell 2566 mol/cell 2000 mol/cell 72 MFI/cell
95
Allen16
Neonates <28 days of life (31 vs. 17) Preterm infants (32 vs. 58) Adults (27 vs. 44)
65.5
92.6
2008
Neonates (128 vs. 165)
70
62
2008
Adults (52 vs. 60)
Leuko64 kit FCM
2.30
Cardelli23
Clinical or proven infection Proven infection
96
95
Tillinger24
2009
Adults (22 vs. 76)
Proven infection
FCM
96
97
Tanaka25
2009
Adults (46 vs. 95)
Proven infection
FCM
60.9
97.9
GroseljGrenc26 GroseljGrenc26
2009
Neonates <28 days (17 vs. 29)
Leuko64 kit
77
79
2009
Children >28 days (24 vs. 12)
Clinical or proven infection Clinical or proven infection
2398 mol/cell 10000 mol/cell 2000 mol/cell 1.86
Leuko64 kit
2.38
71
100
2002
94.6
Specificity (%)
100
FCM, flow cytometry; NR, not reported; mol/cell, molecules/cell; MFI/cell, mean fluorescence intensity/cell. a Clinical infection means infection suspected on a clinical basis whereas proven infection means culture proven infections with an identified microorganism.
program (Meta-Test version 0.6. New England Medical Center, Boston, 1997).
Results From the search of the MEDLINE database, we retrieved 64 publications. Of these, we identified 30 studies that prospectively evaluated the diagnostic accuracy of expression of CD64 on PMNs for the diagnosis of bacterial infections. Detailed review of these 30 studies indicated that 13 were deemed appropriate for the meta-analyses.14e26 We excluded for the meta-analyses 17 studies because the diagnostic accuracy was not the main objective of the study,27e34 authors did not report data to construct the 2 2 tables35e40 and authors used healthy individuals as control groups.41e43 We present a description of the main characteristics of the included studies in Table 1. One study26 reported data of diagnostic accuracy of PMN CD64 expression in two groups of patients. We present the quality evaluation of the included studies using the STARD checklist in Table 2. Fig. 1 shows the results derived from the 2 2 tables and we plot the SROC in Fig. 2. Table 3 shows the pooled
sensitivity and specificity for CD64 expression on PMNs and the characteristics of the summary ROC curve. Overall, the pooled sensitivity and specificity for CD64 expression on PMNs were 79% (95% CI: 70e86%) and 91% (95% CI: 85e95%), respectively. The intercept of the model (a) was 4.3 (95% CI: 3.2e5.3) and the regression coefficient or slope (b) was 0.3 (95% CI: 0.7e0.9). The area under curve (AUC) was 0.94. When we performed subgroup analyses, the pooled sensitivity and specificity improved when studies included only adult patients, when CD64 analysis was performed with FCM and when infection was diagnosed with a positive culture.
Discussion A laboratory test with high diagnostic sensitivity and specificity for bacterial infection would be a valuable tool for therapeutic decision-making, thus avoiding the unnecessary use of antibiotics in those patients without infection but in whom bacteremia is suspected on a clinical basis.9,44 Based on our meta-analysis, we observed a good pooled sensitivity (79%) and specificity (91%) for PMN CD64 expression as marker of bacterial infection.
316
J. Cid et al.
Table 2 Quality evaluation of the included studies using the Standard for Reporting of Diagnostic Accuracy (STARD) checklist.10,11
Maximum score for each categorya Studyref.
Title/abstract/ Keywords
Introduction
Methods
Results
Discussion
Total
1
1
11
11
1
25
1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 0 1 1 1 1 1 1 1
5 6 6 8 8 8 8 7 6 7 7 8 8
1 1 4 2 2 3 2 5 3 1 2 4 5
1 1 1 1 1 1 1 1 1 1 1 1 1
9 10 13 13 13 13 13 15 12 11 12 15 16
Year
Layseca-Espinosa Ng15 Allen16 Ng17 Ng18 Livaditi19 Matsui20 Groselj-Grenc21 Bhandari22 Cardelli23 Tillinger24 Tanaka25 Groselj-Grenc26
14
2002 2002 2002 2004 2006 2006 2006 2008 2008 2008 2009 2009 2009
a
For each category, results are derived from consensus between three reviewers as the number of items from the checklist present in the original article.
In order to be clinically useful, infection markers should possess the following laboratory and clinical properties.5 First, according to the literature, a clinically useful infection marker should have a well-defined cut-off value for differentiating infected from no infected patients, and be able to identify infected cases at an early stage. For diagnostic purposes, a very high sensitivity and negative predictive value (approaching 100%) and good specificity and positive predictive value (>85%) are desirable.5 However, if the diagnostic marker is unable to satisfy the above criteria, then the optimal cut-off could be chosen so that both the sensitivity and the specificity approach 80%, as in our meta-analysis. However, we saw a great variation in the sensitivity and specificity of CD64 in the analyzed studies. We therefore performed subgroup analysis according to the age of included patients, the method of measurement of CD64 expression and the definition of the infection (Table 3). With this strategy, we saw that studies that
TN
Sensitivity
included only adult patients, studies that analyzed CD64 expression by flow cytometry, and studies that defined infection with a positive culture improved the sensitivity and specificity of the CD64 expression. Second, the kinetics of a prospective marker should be considered along with its sensitivity and specificity because a rapid increase of the marker would allow a good discrimination between health and disease. In this sense, other authors have demonstrated that PMN CD64 upregulation occurs in the short time scale of 4e6 h for cell surface expression and 1e3 h for detectable mRNA increases by northern blot analysis.35,45e48 PMN CD64 upregulation is induced by inflammatory-related cytokines, such as granulocyte colony-stimulating factor (G-CSF) and interferon (IFN)-g.49 CD64 expression on PMN significantly increased from baseline by 24 h after initiating in vivo IFN treatment, substantially decreased within 48 h of cessation of IFN and were back to normal baseline levels by day seven.45
Specificity
Study
TP FP FN
Allen et al. [16] Bhandari et al. [22] Cardelli et al. [23] Groselj-Grenc chil [26] Groselj-Grenc et al. [21] Groselj-Grenc neon [26] Layseca-Espinosa [14] Livaditi et al. [19] Matsui et al. [20] Ng et al. [15] Ng et al. [17] Ng et al. [18] Tanaka et al. [25] Tillinger et al. [24]
4 40 0.85 [0.66, 0.96] 0.91 [0.78, 0.97] 4 23 89 63 39 102 0.70 [0.61, 0.77] 0.62 [0.54, 0.69] 2 55 0.96 [0.87, 1.00] 0.92 [0.82, 0.97] 5 50 7 12 0.71 [0.49, 0.87] 1.00 [0.74, 1.00] 0 17 2 10 25 0.66 [0.46, 0.82] 0.93 [0.76, 0.99] 19 4 23 0.76 [0.50, 0.93] 0.79 [0.60, 0.92] 6 13 1 23 16 0.26 [0.12, 0.45] 0.94 [0.71, 1.00] 8 2 10 0.95 [0.82, 0.99] 1.00 [0.69, 1.00] 0 35 4 195 0.93 [0.82, 0.98] 0.97 [0.93, 0.99] 7 51 2 51 0.94 [0.79, 0.99] 0.88 [0.77, 0.95] 7 30 91 25 24 198 0.79 [0.71, 0.86] 0.89 [0.84, 0.93] 72 20 21 175 0.77 [0.68, 0.85] 0.90 [0.85, 0.94] 2 18 93 0.61 [0.45, 0.75] 0.98 [0.93, 1.00] 28 1 73 0.95 [0.77, 1.00] 0.96 [0.89, 0.99] 3 21
Sensitivity
Specificity
0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1
Fig. 1 Results derived from the 2 2 tables of individual studies involving neutrophil CD64 expression as marker of bacterial infection. The study by Groselj-Grenc et al.26 reported data in two groups of patients.
Neutrophil CD64 and infection
317
Sensitivity 1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0 1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1 0 Specificity
Fig. 2 Summary receiver operating characteristic (SROC) curve of individual studies involving neutrophil CD64 expression as marker of bacterial infection.
Third, with reference to the laboratory characteristics, the infection marker should be biochemically stable because it might be necessary to keep blood samples stored, as flow cytometric analysis may not be available on a 24 h basis. According to the literature, we know that PMN CD64 has negligible expression in the healthy individual and shows no evidence of sensitivity to blood sample manipulation.7,35 Some authors have reported that PMN CD64 expression is stable at room temperature for more than 30 h, in contrast to the labile expression of CD11b and other PMN antigens.50e52 Moreover, other authors have measured CD64 expression at baseline, and after 24 h, 48 h, and 72 h and they did not observe significant differences in CD64 expression in stored blood samples at 4 C as compared to baseline values.24 However, the methodological quality of the included studies by applying the 25-item criteria developed by the STARD committee was low. The STARD initiative was started
to improve the quality of reporting of studies of diagnostic accuracy10 because some authors53 found mediocre methodological quality in a survey of studies of diagnostic accuracy. The result of the STARD initiative was a checklist with 25 items that readers could use to analyze the methodological quality of the diagnostic accuracy studies and to score the studies from zero to 25 points. The items analyzed different aspects of the title/abstract/keywords of the study as well as the introduction, methods, results and discussion sections of the studies. Based in our meta-analysis, we showed that our 13 included studies had a total score for the STARD checklist that ranged from 9 to 16 points. As stated in Table 2, we identified all studies as diagnostic accuracy articles in the title, abstract or keywords. All studies, except one,19 stated the research question in the introduction. However, in the methods section, all studies failed to report completely all items listed by the STARD group. Moreover, all analyzed studies had a very poor results section because the total score of this section ranged from 1 to 5 points (maximum score was 11 points). For all these reasons, it is important to perform in the future more studies to evaluate the diagnostic accuracy of expression of CD64 on PMNs as a marker for bacterial infection following well described methodological criteria for assessing risk of bias (e.g., case-control design rather than clinical cohort, different reference tests according to test result).54,55 In summary, PMN CD64 measurements offer the potential to be a clinically useful diagnostic cell-based parameter of a bacterial infection in adults, children and neonates.56 However, our meta-analysis showed low methodological quality of published studies about this topic. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) working group developed a 2-step process of how the accuracy of a test indirectly changes patientimportant outcomes. In the first step, investigators should perform a diagnostic test accuracy study. In the second step, judgments about patient-importance of test accuracy are based on the consequences of being correctly or incorrectly classified as having or not having the disease.57,58 Therefore, we encourage those making recommendations about PMN CD64 measurements to compare patientimportant outcomes (and costs) in all patients receiving this test with all patients receiving alternative test, such as CRP or PCT.
Table 3 Subgroup analyses according to the age of included patients (children vs. adults), technical method used to detect CD64 (FCM vs. Leukokit) and definition of infection (clinical vs. proven infection). Sensitivity
Specificity
Summary ROC curve
Studies
Included patients
Range
Mean
95% CI
Range
Mean
95% CI
Intercept model
Slope or regression coefficient
AUC
All Children Adults FCM Leukokit Clinical infection Proven infection
1921 1195 726 1546 375 680 1241
0.26e0.96 0.26e0.94 0.61e0.96 0.26e0.96 0.70e0.76 0.26e0.93 0.61e0.96
0.79 0.71 0.9 0.82 0.7 0.7 0.83
0.70e0.86 0.59e0.80 0.75e0.96 0.70e0.90 0.63e0.77 0.46e0.86 0.74e0.90
0.62e1.00 0.62e1.00 0.91e1.00 0.88e1.00 0.62e1.00 0.62e1.00 0.88e1.00
0.91 0.87 0.95 0.92 0.75 0.89 0.91
0.85e0.95 0.76e0.93 0.92e0.97 0.90e0.95 0.52e0.89 0.65e0.97 0.88e0.93
4.3 3.2 5.5 5 1.9 3.1 4.8
0.3 0.1 0.3 0.6 0.9 0.02 0.4
0.94 0.89 0.97 0.95 0.73 0.89 0.95
318
J. Cid et al.
Acknowledgements No financial support for the study was received.
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Neutrophil CD64 and infection 34. McCarthy DA, Macey MG, Streetly M, Schey SA, Brown KA. The neutropenia induced by the thalidomide analogue CC-4047 in patients with multiple myeloma is associated with an increased percentage of neutrophils bearing CD64. Int Immunopharmacol 2006;6:1194e203. 35. Davis BH, Bigelow NC, Curnutte JT, Ornvold K. Neutrophil CD64 expression: potential diagnostic indicator of acute inflammation and therapeutic monitor of interferon-gamma therapy. Lab Hematol 1995;1:3e12. 36. Wagner C, Deppisch R, Denefleh B, Hug F, Andrassy K, Hansch GM. Expression patterns of the lipopolysaccharide receptor CD14, and the FC gamma receptors CD16 and CD64 on polymorphonuclear neutrophils: data from patients with severe bacterial infections and lipopolysaccharide-exposed cells. Shock 2003;19:5e12. 37. Davis BH, Bigelow NC. Comparison of neutrophil CD64 expression, manual myeloid immaturity counts, and automated hematology analyzer flags as indicators of infection or sepsis. Lab Hematol 2005;11:137e47. 38. Davis BH, Olsen SH, Ahmad E, Bigelow NC. Neutrophil CD64 is an improved indicator of infection or sepsis in emergency department patients. Arch Pathol Lab Med 2006;130:654e61. 39. Song SH, Kim HK, Park MH, Cho HI. Neutrophil CD64 expression is associated with severity and prognosis of disseminated intravascular coagulation. Thromb Res 2008;121:499e507. 40. Daryapeyma A, Pedersen G, Laxdal E, Corbascio M, Johannessen HB, Aune S, et al. Neutrophil CD64 as a marker for postoperative infection: a pilot study. Eur J Vasc Endovasc Surg 2009;38:100e3. 41. Nuutila J, Hohenthal U, Laitinen I, Kotilainen P, Rajamaki A, Nikoskelainen J, et al. Simultaneous quantitative analysis of Fc gamma RI (CD64) expression on neutrophils and monocytes: a new, improved way to detect infections. J Immunol Methods 2007;328:189e200. 42. Danikas DD, Karakantza M, Theodorou GL, Sakellaropoulos GC, Gogos CA. Prognostic value of phagocytic activity of neutrophils and monocytes in sepsis. Correlation to CD64 and CD14 antigen expression. Clin Exp Immunol 2008;154:87e97. 43. Rudensky B, Sirota G, Erlichman M, Yinnon AM, Schlesinger Y. Neutrophil CD64 expression as a diagnostic marker of bacterial infection in febrile children presenting to a hospital emergency department. Pediatr Emerg Care 2008;24:745e8. 44. Vamvakas EC. Diagnostic accuracy and clinical value of laboratory tests used to screen the allogeneic blood supply for infectious disease markers. In: Vamvakas EC, editor. Evidence-based practice of transfusion medicine. Bethesda: AABB Press; 2001. p. 65e100. 45. Schiff DE, Rae J, Martin TR, Davis BH, Curnutte JT. Increased phagocyte Fc gamma RI expression and improved Fc gammareceptor-mediated phagocytosis after in vivo recombinant
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human interferon-gamma treatment of normal human subjects. Blood 1997;90:3187e94. Pan LY, Mendel DB, Zurlo J, Guyre PM. Regulation of the steady state level of Fc gamma RI mRNA by IFN-gamma and dexamethasone in human monocytes, neutrophils, and U-937 cells. J Immunol 1990;145:267e75. Petroni KC, Shen L, Guyre PM. Modulation of human polymorphonuclear leukocyte IgG Fc receptors and Fc receptormediated functions by IFN-gamma and glucocorticoids. J Immunol 1988;140:3467e72. Cassatella MA, Flynn RM, Amezaga MA, Bazzoni F, Vicentini F, Trinchieri G. Interferon gamma induces in human neutrophils and macrophages expression of the mRNA for the high affinity receptor for monomeric IgG (Fc gamma R-I or CD64). Biochem Biophys Res Commun 1990;170:582e8. Greenberg S, Dale BM. Fc receptors and phagocytosis. In: Russell DG, Gordon S, editors. Phagocyte-pathogen interactions. Macrophags and the host response to infection. Washington, D.C.: ASM Press; 2009. p. 71e92. Briggs C, Kunka S, Fujimoto H, Hamaguchi Y, Davis BH, Machin SJ. Evaluation of immature granulocyte counts by the XE-IG master: upgraded software for the XE-2100 automated hematology analyzer. Lab Hematol 2003;9:117e24. Luzzani A, Polati E, Dorizzi R, Rungatscher A, Pavan R, Merlini A. Comparison of procalcitonin and C-reactive protein as markers of sepsis. Crit Care Med 2003;31:1737e41. Sauer M, Tiede K, Fuchs D, Gruhn B, Berger D, Zintl F. Procalcitonin, C-reactive protein, and endotoxin after bone marrow transplantation: identification of children at high risk of morbidity and mortality from sepsis. Bone Marrow Transpl 2003; 31:1137e42. Reid MC, Lachs MS, Feinstein AR. Use of methodological standards in diagnostic test research. Getting better but still not good. JAMA 1995;274:645e51. Rutjes AW, Reitsma JB, Di Nisio M, Smidt N, van Rijn JC, Bossuyt PM. Evidence of bias and variation in diagnostic accuracy studies. CMAJ 2006;174:469e76. Lijmer JG, Mol BW, Heisterkamp S, Bonsel GJ, Prins MH, van der Meulen JH, et al. Empirical evidence of design-related bias in studies of diagnostic tests. JAMA 1999;282:1061e6. Hoffmann JJ. Neutrophil CD64: a diagnostic marker for infection and sepsis. Clin Chem Lab Med 2009;47:903e16. Schunemann HJ, Oxman AD, Brozek J, Glasziou P, Bossuyt P, Chang S, et al. GRADE: assessing the quality of evidence for diagnostic recommendations. Evid Based Med 2008;13:162e3. Schunemann HJ, Oxman AD, Brozek J, Glasziou P, Jaeschke R, Vist GE, et al. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies. BMJ 2008; 336:1106e10.
www.elsevierhealth.com/journals/jinf
REVIEW
Neutrophil CD64 expression as marker of bacterial infection: A systematic review and meta-analysis ´nchez b, Graciano Garcı´a-Pardo c, Joan Cid a,*, Reyes Aguinaco a, Rafael Sa Andreu Llorente a a
Haematology Service, Hospital Universitari Joan XXIII, IISPV, Universitat Rovira i Virgili, Tarragona, Spain Laboratory Service, Hospital Universitari Joan XXIII, IISPV, Universitat Rovira i Virgili, Tarragona, Spain c Preventive Medicine Unit, Hospital Universitari Joan XXIII, IISPV, Universitat Rovira i Virgili, Tarragona, Spain b
Accepted 24 February 2010 Available online 3 March 2010
KEYWORDS CD64; Diagnostic accuracy; Infection; Systematic review
Summary Objective: We performed a systematic review and meta-analysis of studies to evaluate the diagnostic accuracy of expression of CD64 on polymorphonuclear neutrophils (PMN) as a marker for bacterial infection. Methods: The analysis included studies of patients from all age groups that prospectively evaluated CD64 expression on PMNs for the diagnosis of bacterial infection. We evaluated the methodological quality of the studies according to the 25-item criteria developed by the Standards for Reporting of Diagnostic Accuracy (STARD) committee. We calculated a summary receiver operating characteristic (SROC) curve across studies included in the meta-analysis. Results: The methodological quality score of the 13 included studies ranged from 9 to 16 points (maximum score was 25 points). The pooled sensitivity and specificity for CD64 expression on PMNs were 79% (95% CI: 70e86%) and 91% (95% CI: 85e95%), respectively. The area under curve (AUC) was 0.94. Conclusions: On the basis of this meta-analysis, CD64 expression on PMNs could be a useful diagnostic cell-based parameter of bacterial infections. However, published studies about this topic showed a low methodological quality. ª 2010 The British Infection Society. Published by Elsevier Ltd. All rights reserved.
Introduction Bacterial infections are a major cause of morbidity and mortality in the world.1 The incidence of sepsis in the United States of America is estimated to be 3.0 cases per
1000 inhabitants per year, or 2.2 per 100 hospital discharges.2,3 In our country, we have data from EPINE, the prevalence survey of nosocomial infections in Spain, which is performed annually. The prevalence of patients with nosocomial infections in 2007 was 6.99% with 266 participant hospitals and 61,496 included patients.4
* Corresponding author. Tel.: þ34 977295821; fax: þ34 977295822. E-mail address: [email protected] (J. Cid). 0163-4453/$36 ª 2010 The British Infection Society. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.jinf.2010.02.013
314 Diagnosis of bacterial infections is sometimes challenging, because the use of blood culture, the gold standard for diagnosis of bacteremia, is fraught with difficulties. First, incubation of bacteria may take several days (2e4 days). Second, genuine bacteremia may remain undetected in a significant proportion of infected cases because of the small volume of blood taken. Third, bacteremia in the neonate may often be transient or intermittent, especially during the early stages of infection.5 Moreover, although untreated bacterial infections may cause serious complications, treating viral illnesses or noninfective causes of inflammation with antibiotics is not only ineffective, but also contributes to the development of resistance, increases costs, and adds the risks of toxicity and allergic reactions.6 Thus, an improved diagnostic test for infection and sepsis would have both economic and therapeutic healthcare benefits. Laboratory diagnosis of infection and sepsis still relies on diagnostic tests that have been available since 1970s or before, such as leukocyte neutrophil counts, the presence of myeloid-immature forms in the peripheral blood, and laboratory tests for acute-phase reactants such as C-reactive protein (CRP).7 More recently, most of the effort in developing new-generation and improved diagnostics for infection and sepsis has been directed towards soluble biomarkers in the serum or plasma, such as procalcitonin (PCT).6 However, all these diagnostic tests have some limitations. The cellular diagnostic parameters are typically problematic, subjective and lack specificity, particularly in infants and the elderly. CRP level have been advocated as a more objective diagnostic assay but it becomes elevated in any disease process with tissue injury, not just infection. Finally, PCT has a very good negative predictive value of disease or sepsis although there remains debate as to the value of PCT in the broader context of infection diagnosis and therapeutic monitoring.7 Another approach to rapid and early diagnosis of infection or sepsis is to utilize some of the molecular changes in the cellular component of the innate immune response to detect the presence of infection or sepsis. There is published work that one of the best and most specific indicators of an early systemic acute inflammatory activation or response is the upregulation of polymorphonuclear neutrophil (PMN) expression of CD64.7 CD64 is the high affinity immunoglobulin Fc g receptor I (FcgRI) and it is expressed on monocytes, but only to a very low extent on resting PMNs. There are previous studies that show that CD64 expression on PMNs increases once PMNs become activated and could be a marker of bacterial infection and also differentiate against other inflammatory disorders.5 We therefore systematically review and performed a meta-analysis of studies to adequately evaluate the diagnostic accuracy of expression of CD64 on PMNs as a marker for bacterial infection.
Materials and methods A protocol was written before this study was undertaken, as recommended by the Quality of Reporting of Meta-analyses (QUORUM) statement.8
J. Cid et al.
Retrieving the literature All studies published in the MEDLINE database from January 1970 through 30 November 2009 that adequately evaluated the diagnostic accuracy of expression of CD64 on PMNs for the diagnosis of bacterial infections were identified. With use of a Boolean strategy, cross-searching of the following three categories was done: (1) ‘‘Sensitivity and Specificity’’ OR (2) ‘‘Mass Screening’’ AND (3) ‘‘Receptors, IgG’’. The bibliographies of relevant articles were further crosschecked to search for articles not referenced in the MEDLINE database.9
Selection of studies and data extraction Studies of patients from all age groups that prospectively evaluated CD64 expression on PMNs for the diagnosis of bacterial infection were evaluated. Retrospective studies, reviews, animal studies, and studies for which complete data was unavailable were excluded. Language of the article was limited to English and Spanish. The selection and data extraction was performed by the authors, and disagreements, if any, were resolved by consensus. Raw data from the articles were used to construct 2 2 tables; when unavailable, the tables were constructed using given measures of sensitivity and specificity.
Quality assessment We evaluated the methodological quality of the included studies by applying the 25-item criteria developed by the Standards for Reporting of Diagnostic Accuracy (STARD) committee.10,11 Briefly, the maximum quality score that can be given to a study by this criteria was 25 points: 1 point if the study was identified as a diagnostic accuracy study in the title, abstract or the keywords; 1 point if the authors stated the research question in the introduction section of the study; up to 11 points if the authors described the characteristics of the participants, test methods and statistical methods in the methods section; up to 11 points if the authors report data about participants, test results and estimates in the results section; and 1 point if the authors discussed the clinical applicability of the study findings. A consensus was obtained among three reviewers for the criteria.
Meta-analysis We used the meta-analysis approach of Littenberg and Moses12,13 to create the summary receiver operating characteristic (SROC) curve. We investigated sources of heterogeneity between studies and we performed subgroup analyses according to the age of included patients (children vs. adult patients), technical method used to detect CD64 (flow cytometry (FCM) vs. Leuko64 kit (Trillium Diagnostics, LLC)) and definition of infection (clinical vs. proven diagnosis). We carried out all analyses with software (Review Manager (RevMan) [Computer program]. Version 5.0. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2008) and the Meta-test
Neutrophil CD64 and infection Table 1 Study
315
Main characteristics of the included studies.
ref.
Year
Population (infected vs. non infected)
Means of diagnosis of infectiona
CD64 analysis
Cut-off
Sensitivity (%)
LaysecaEspinosa14 Ng15
2002
Clinical or proven infection Proven infection
FCM
NR
25.8
96.8
FCM
88
2002
Proven infection
FCM
85
91
Ng17
2004
Proven infection
FCM
79
89
Ng18
2006
Proven infection
FCM
78
90
Livaditi19
2006
Term newborn infants (115 vs. 223) Term newborn infants (93 vs. 195) Adults (37 vs. 10)
Proven infection
FCM
Matsui20
2006
Adults (55 vs. 202)
FCM
92.7
96.5
GroseljGrenc21 Bhandari22
2008
Children (29 vs. 27)
Clinical or proven infection Proven infection
FCM
4000 mol/cell 2000 mol/cell 6136 mol/cell 6136 mol/cell 2566 mol/cell 2000 mol/cell 72 MFI/cell
95
Allen16
Neonates <28 days of life (31 vs. 17) Preterm infants (32 vs. 58) Adults (27 vs. 44)
65.5
92.6
2008
Neonates (128 vs. 165)
70
62
2008
Adults (52 vs. 60)
Leuko64 kit FCM
2.30
Cardelli23
Clinical or proven infection Proven infection
96
95
Tillinger24
2009
Adults (22 vs. 76)
Proven infection
FCM
96
97
Tanaka25
2009
Adults (46 vs. 95)
Proven infection
FCM
60.9
97.9
GroseljGrenc26 GroseljGrenc26
2009
Neonates <28 days (17 vs. 29)
Leuko64 kit
77
79
2009
Children >28 days (24 vs. 12)
Clinical or proven infection Clinical or proven infection
2398 mol/cell 10000 mol/cell 2000 mol/cell 1.86
Leuko64 kit
2.38
71
100
2002
94.6
Specificity (%)
100
FCM, flow cytometry; NR, not reported; mol/cell, molecules/cell; MFI/cell, mean fluorescence intensity/cell. a Clinical infection means infection suspected on a clinical basis whereas proven infection means culture proven infections with an identified microorganism.
program (Meta-Test version 0.6. New England Medical Center, Boston, 1997).
Results From the search of the MEDLINE database, we retrieved 64 publications. Of these, we identified 30 studies that prospectively evaluated the diagnostic accuracy of expression of CD64 on PMNs for the diagnosis of bacterial infections. Detailed review of these 30 studies indicated that 13 were deemed appropriate for the meta-analyses.14e26 We excluded for the meta-analyses 17 studies because the diagnostic accuracy was not the main objective of the study,27e34 authors did not report data to construct the 2 2 tables35e40 and authors used healthy individuals as control groups.41e43 We present a description of the main characteristics of the included studies in Table 1. One study26 reported data of diagnostic accuracy of PMN CD64 expression in two groups of patients. We present the quality evaluation of the included studies using the STARD checklist in Table 2. Fig. 1 shows the results derived from the 2 2 tables and we plot the SROC in Fig. 2. Table 3 shows the pooled
sensitivity and specificity for CD64 expression on PMNs and the characteristics of the summary ROC curve. Overall, the pooled sensitivity and specificity for CD64 expression on PMNs were 79% (95% CI: 70e86%) and 91% (95% CI: 85e95%), respectively. The intercept of the model (a) was 4.3 (95% CI: 3.2e5.3) and the regression coefficient or slope (b) was 0.3 (95% CI: 0.7e0.9). The area under curve (AUC) was 0.94. When we performed subgroup analyses, the pooled sensitivity and specificity improved when studies included only adult patients, when CD64 analysis was performed with FCM and when infection was diagnosed with a positive culture.
Discussion A laboratory test with high diagnostic sensitivity and specificity for bacterial infection would be a valuable tool for therapeutic decision-making, thus avoiding the unnecessary use of antibiotics in those patients without infection but in whom bacteremia is suspected on a clinical basis.9,44 Based on our meta-analysis, we observed a good pooled sensitivity (79%) and specificity (91%) for PMN CD64 expression as marker of bacterial infection.
316
J. Cid et al.
Table 2 Quality evaluation of the included studies using the Standard for Reporting of Diagnostic Accuracy (STARD) checklist.10,11
Maximum score for each categorya Studyref.
Title/abstract/ Keywords
Introduction
Methods
Results
Discussion
Total
1
1
11
11
1
25
1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 0 1 1 1 1 1 1 1
5 6 6 8 8 8 8 7 6 7 7 8 8
1 1 4 2 2 3 2 5 3 1 2 4 5
1 1 1 1 1 1 1 1 1 1 1 1 1
9 10 13 13 13 13 13 15 12 11 12 15 16
Year
Layseca-Espinosa Ng15 Allen16 Ng17 Ng18 Livaditi19 Matsui20 Groselj-Grenc21 Bhandari22 Cardelli23 Tillinger24 Tanaka25 Groselj-Grenc26
14
2002 2002 2002 2004 2006 2006 2006 2008 2008 2008 2009 2009 2009
a
For each category, results are derived from consensus between three reviewers as the number of items from the checklist present in the original article.
In order to be clinically useful, infection markers should possess the following laboratory and clinical properties.5 First, according to the literature, a clinically useful infection marker should have a well-defined cut-off value for differentiating infected from no infected patients, and be able to identify infected cases at an early stage. For diagnostic purposes, a very high sensitivity and negative predictive value (approaching 100%) and good specificity and positive predictive value (>85%) are desirable.5 However, if the diagnostic marker is unable to satisfy the above criteria, then the optimal cut-off could be chosen so that both the sensitivity and the specificity approach 80%, as in our meta-analysis. However, we saw a great variation in the sensitivity and specificity of CD64 in the analyzed studies. We therefore performed subgroup analysis according to the age of included patients, the method of measurement of CD64 expression and the definition of the infection (Table 3). With this strategy, we saw that studies that
TN
Sensitivity
included only adult patients, studies that analyzed CD64 expression by flow cytometry, and studies that defined infection with a positive culture improved the sensitivity and specificity of the CD64 expression. Second, the kinetics of a prospective marker should be considered along with its sensitivity and specificity because a rapid increase of the marker would allow a good discrimination between health and disease. In this sense, other authors have demonstrated that PMN CD64 upregulation occurs in the short time scale of 4e6 h for cell surface expression and 1e3 h for detectable mRNA increases by northern blot analysis.35,45e48 PMN CD64 upregulation is induced by inflammatory-related cytokines, such as granulocyte colony-stimulating factor (G-CSF) and interferon (IFN)-g.49 CD64 expression on PMN significantly increased from baseline by 24 h after initiating in vivo IFN treatment, substantially decreased within 48 h of cessation of IFN and were back to normal baseline levels by day seven.45
Specificity
Study
TP FP FN
Allen et al. [16] Bhandari et al. [22] Cardelli et al. [23] Groselj-Grenc chil [26] Groselj-Grenc et al. [21] Groselj-Grenc neon [26] Layseca-Espinosa [14] Livaditi et al. [19] Matsui et al. [20] Ng et al. [15] Ng et al. [17] Ng et al. [18] Tanaka et al. [25] Tillinger et al. [24]
4 40 0.85 [0.66, 0.96] 0.91 [0.78, 0.97] 4 23 89 63 39 102 0.70 [0.61, 0.77] 0.62 [0.54, 0.69] 2 55 0.96 [0.87, 1.00] 0.92 [0.82, 0.97] 5 50 7 12 0.71 [0.49, 0.87] 1.00 [0.74, 1.00] 0 17 2 10 25 0.66 [0.46, 0.82] 0.93 [0.76, 0.99] 19 4 23 0.76 [0.50, 0.93] 0.79 [0.60, 0.92] 6 13 1 23 16 0.26 [0.12, 0.45] 0.94 [0.71, 1.00] 8 2 10 0.95 [0.82, 0.99] 1.00 [0.69, 1.00] 0 35 4 195 0.93 [0.82, 0.98] 0.97 [0.93, 0.99] 7 51 2 51 0.94 [0.79, 0.99] 0.88 [0.77, 0.95] 7 30 91 25 24 198 0.79 [0.71, 0.86] 0.89 [0.84, 0.93] 72 20 21 175 0.77 [0.68, 0.85] 0.90 [0.85, 0.94] 2 18 93 0.61 [0.45, 0.75] 0.98 [0.93, 1.00] 28 1 73 0.95 [0.77, 1.00] 0.96 [0.89, 0.99] 3 21
Sensitivity
Specificity
0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1
Fig. 1 Results derived from the 2 2 tables of individual studies involving neutrophil CD64 expression as marker of bacterial infection. The study by Groselj-Grenc et al.26 reported data in two groups of patients.
Neutrophil CD64 and infection
317
Sensitivity 1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0 1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1 0 Specificity
Fig. 2 Summary receiver operating characteristic (SROC) curve of individual studies involving neutrophil CD64 expression as marker of bacterial infection.
Third, with reference to the laboratory characteristics, the infection marker should be biochemically stable because it might be necessary to keep blood samples stored, as flow cytometric analysis may not be available on a 24 h basis. According to the literature, we know that PMN CD64 has negligible expression in the healthy individual and shows no evidence of sensitivity to blood sample manipulation.7,35 Some authors have reported that PMN CD64 expression is stable at room temperature for more than 30 h, in contrast to the labile expression of CD11b and other PMN antigens.50e52 Moreover, other authors have measured CD64 expression at baseline, and after 24 h, 48 h, and 72 h and they did not observe significant differences in CD64 expression in stored blood samples at 4 C as compared to baseline values.24 However, the methodological quality of the included studies by applying the 25-item criteria developed by the STARD committee was low. The STARD initiative was started
to improve the quality of reporting of studies of diagnostic accuracy10 because some authors53 found mediocre methodological quality in a survey of studies of diagnostic accuracy. The result of the STARD initiative was a checklist with 25 items that readers could use to analyze the methodological quality of the diagnostic accuracy studies and to score the studies from zero to 25 points. The items analyzed different aspects of the title/abstract/keywords of the study as well as the introduction, methods, results and discussion sections of the studies. Based in our meta-analysis, we showed that our 13 included studies had a total score for the STARD checklist that ranged from 9 to 16 points. As stated in Table 2, we identified all studies as diagnostic accuracy articles in the title, abstract or keywords. All studies, except one,19 stated the research question in the introduction. However, in the methods section, all studies failed to report completely all items listed by the STARD group. Moreover, all analyzed studies had a very poor results section because the total score of this section ranged from 1 to 5 points (maximum score was 11 points). For all these reasons, it is important to perform in the future more studies to evaluate the diagnostic accuracy of expression of CD64 on PMNs as a marker for bacterial infection following well described methodological criteria for assessing risk of bias (e.g., case-control design rather than clinical cohort, different reference tests according to test result).54,55 In summary, PMN CD64 measurements offer the potential to be a clinically useful diagnostic cell-based parameter of a bacterial infection in adults, children and neonates.56 However, our meta-analysis showed low methodological quality of published studies about this topic. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) working group developed a 2-step process of how the accuracy of a test indirectly changes patientimportant outcomes. In the first step, investigators should perform a diagnostic test accuracy study. In the second step, judgments about patient-importance of test accuracy are based on the consequences of being correctly or incorrectly classified as having or not having the disease.57,58 Therefore, we encourage those making recommendations about PMN CD64 measurements to compare patientimportant outcomes (and costs) in all patients receiving this test with all patients receiving alternative test, such as CRP or PCT.
Table 3 Subgroup analyses according to the age of included patients (children vs. adults), technical method used to detect CD64 (FCM vs. Leukokit) and definition of infection (clinical vs. proven infection). Sensitivity
Specificity
Summary ROC curve
Studies
Included patients
Range
Mean
95% CI
Range
Mean
95% CI
Intercept model
Slope or regression coefficient
AUC
All Children Adults FCM Leukokit Clinical infection Proven infection
1921 1195 726 1546 375 680 1241
0.26e0.96 0.26e0.94 0.61e0.96 0.26e0.96 0.70e0.76 0.26e0.93 0.61e0.96
0.79 0.71 0.9 0.82 0.7 0.7 0.83
0.70e0.86 0.59e0.80 0.75e0.96 0.70e0.90 0.63e0.77 0.46e0.86 0.74e0.90
0.62e1.00 0.62e1.00 0.91e1.00 0.88e1.00 0.62e1.00 0.62e1.00 0.88e1.00
0.91 0.87 0.95 0.92 0.75 0.89 0.91
0.85e0.95 0.76e0.93 0.92e0.97 0.90e0.95 0.52e0.89 0.65e0.97 0.88e0.93
4.3 3.2 5.5 5 1.9 3.1 4.8
0.3 0.1 0.3 0.6 0.9 0.02 0.4
0.94 0.89 0.97 0.95 0.73 0.89 0.95
318
J. Cid et al.
Acknowledgements No financial support for the study was received.
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