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Published online before print November 7, 2006, 10.1148/radiol.2421052011
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(Radiology 2007;242:101-108.)
© RSNA, 2006

Evidence-based Practice

Prosthesis Infection: Diagnosis after Total Joint Arthroplasty with Antigranulocyte Scintigraphy with 99mTc-labeled Monoclonal Antibodies—A Meta-Analysis1

Emilios E. Pakos, MD, Thomas A. Trikalinos, MD, Andreas D. Fotopoulos, MD and John P. A. Ioannidis, MD

1 From the Clinical Trials and Evidence-Based Medicine Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, Ioannina, 45110, Greece (E.E.P., T.A.T., J.P.A.I.); Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts–New England Medical Center, Boston, Mass (T.A.T., J.P.A.I.); and Department of Nuclear Medicine, University Hospital of Ioannina, School of Medicine, Ioannina, Greece (A.D.F.). Received December 10, 2005; revision requested January 24, 2006; revision received February 2; accepted March 3; final version accepted April 12. Address correspondence to J.P.A.I. (e-mail: jioannid{at}cc.uoi.gr).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Purpose: To perform a meta-analysis of diagnostic studies regarding the accuracy of antigranulocyte scintigraphy (AGS) with monoclonal antibodies in the identification of prosthesis infection after total hip or knee arthroplasty.

Materials and Methods: PubMed and EMBASE searches were conducted for the identification of relevant studies. Data on the diagnostic performance of AGS with monoclonal antibodies were combined quantitatively across eligible studies, and the overall sensitivity and specificity, along with summary receiver operating characteristic (ROC) curves and likelihood ratios (LRs), were estimated. The above parameters were evaluated for all patients and for various subgroups among the eligible studies. The reference standard used in the individual studies was accepted.

Results: Thirteen eligible studies on nonoverlapping patient groups were included in the meta-analysis; there was a total sample size of 522 implants. The independent random effects summary estimates of sensitivity and specificity were 83% and 80%, respectively. The summary ROC curve estimate for weighted analysis was a sensitivity of 90% for a specificity of 80%. LR syntheses gave a weighted positive LR of 3.99 (95% confidence interval [CI]: 3.13, 5.09) and a weighted negative LR of 0.22 (95% CI: 0.15, 0.34); there was no statistically significant between-study heterogeneity for either metric. Various subgroup analyses did not reveal any statistically significant differences.

Conclusion: AGS with monoclonal antibodies had a reasonably high discriminating ability to identify prosthesis infection in patients who underwent total joint arthroplasty.

© RSNA, 2006


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Infection associated with prosthetic implants after total joint arthroplasty is a major complication that carries substantial morbidity (1). The presence of a foreign body confers increased susceptibility to infection (2). Infection may ensue despite the use of perioperative antimicrobial prophylaxis and competent surgical technique. Moreover, infection may occur by means of hematogenous spread during the lifetime of the implant (3). Especially for delayed and late prosthesis-associated infection in which the clinical manifestation is subtle, the differential diagnosis with aseptic implant failure is often difficult.

Among the several imaging options, antigranulocyte scintigraphy (AGS) with monoclonal antibodies is increasingly used in the diagnostic evaluation of such patients. Radiolabeled monoclonal antibodies or antibody fragments directly target leukocyte antigens or receptors in vivo and allow exploitation of the concentration of granulocytes in the inflamed tissue surrounding the prosthesis (4,5). The most commonly used monoclonal antibodies in the imaging of prosthesis infection are the immunogloblin G–class antibody (BW 250/183) against normal cross-reactive antigen-95 and the Fab fragment of the immunogloblin G antibody (sulesomab) against the glycoprotein cross-reactive antigen-90. The diagnostic accuracy of these antibodies for this purpose has been assessed with several studies (6–18). All these studies, however, had a limited sample size. The purpose of our study, therefore, was to perform a meta-analysis of diagnostic studies regarding the accuracy of AGS with monoclonal antibodies in the identification of prosthesis infection after total hip or knee arthroplasty.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Identification and Eligibility of Relevant Studies
We considered all studies of AGS with monoclonal antibodies or antibody fragments labeled with technetium 99m (99mTc) for the diagnosis of prosthesis infection in patients who had undergone joint arthroplasty. We considered all relevant studies regardless of the type of monoclonal antibody used (sulesomab or BW 250/183) and regardless of the location of joint arthroplasty (hip or knee). Studies were considered eligible regardless of the exact definition of the reference standard used for determining infection, as long as AGS was not part of the reference standard. Studies including patients with prosthesis infection and without prosthesis infection and including at least five patients were considered eligible. We set no language restrictions.

We conducted PubMed (January 1966 to September 2005) and EMBASE (January 1994 to December 2000) searches. The search strategy was based on the combination of the terms (a) "antigranulocyte scintigraphy," "WBC-scintigraphy," or "leukocyte scintigraphy;" (b) "monoclonal antibodies," "sulesomab," "Leukoscan," "Fab," or "BW 250/183;" (c) "prosthesis infection" or "septic loosening;" and (d) "total joint arthroplasty," "total hip arthroplasty," or "total knee arthroplasty." Searches were limited to human subjects. Searches were performed by the first author (E.E.P.).

References of retrieved articles were screened for additional studies (E.E.P., A.D.F.). Investigators of eligible studies were contacted and asked to provide additional information when key information relevant to the meta-analysis was missing (T.A.T.). Whenever studies pertained to overlapping patients, we retained only the largest study to avoid duplication of information.

Data Extraction
Two investigators (E.E.P., A.D.F.) extracted data from eligible studies independently, discussed discrepancies, and reached consensus for all items with the help of a third investigator (T.A.T.). We extracted data on characteristics of studies and patients, measurements performed, and results. For each study we recorded author names, journal and year of publication, country of origin, years of patient enrollment, number of eligible patients, number of patients analyzed, inclusion and exclusion criteria, study design (prospective, retrospective, or unclear), demographic characteristics of patients, type of joint arthroplasty (hip or knee), use of cement or not, time from prosthesis implantation to AGS, type of monoclonal antibody or antibody fragment used and technical characteristics of AGS, methods used for the interpretation of the results (qualitative or semiquantitative) and the definition of positivity, and the number of readers who assessed the results of AGS and whether any blinding of the readers to the final diagnosis was reported. We also recorded any data on intra- or interobserver variability among the readers who assessed the outcomes. We noted the description of the reference standard used in each study to document infection. For each study, we recorded in a 2 x 2 table the number of true-positive findings, false-positive findings, true-negative findings, and false-negative findings at AGS with monoclonal antibodies when compared with those at the reference standard employed in each study.

Statistical Analysis
Data on the diagnostic performance of AGS with monoclonal antibodies were combined quantitatively across eligible studies. Three approaches were used. First, we independently combined sensitivities and specificities across studies. Between-study heterogeneity was assessed with the Fisher exact test. We estimated the weighted sensitivities and specificities by using a random effects model that incorporated between-study heterogeneity.

Second, we constructed summary receiver operating characteristic (ROC) curves. For a diagnostic or predictive test, there is a trade-off between sensitivity and specificity; therefore, it is suboptimal to summarize these two quantities independently. To bypass this problem, the summary ROC method is used. The summary ROC curve is estimated with the regression formula D = a + bS, where D is the difference of the logits of the true-positive rate and the false-positive rate and S is the sum of these logits. Both weighted and unweighted regressions were estimated (19). The summary ROC curve shows the trade-off between sensitivity and specificity across the included studies. Summary ROC–based analyses may not be applicable when the sensitivities and specificities of all studies operate in the same range of values. On the basis of the summary ROC curves, we estimated the sensitivity that would correspond to a specificity of 80%. We then calculated the probability that an implant with a positive finding at AGS is infected (positive predictive value) and the probability that an implant with a negative finding at AGS is not infected (negative predictive value) if the prevalence of infected prostheses were 10%, 50%, or 80%.

Third, we estimated the weighted positive and negative likelihood ratio (LR) across studies by using random effects calculations. LRs are metrics that express how much the odds change for an implant to be infected if there is a positive finding at AGS (LR+) and how much the odds change for an implant to be infected if there is a negative finding at AGS (LR–). LR+ and LR– are defined with the following formulas: LR+ = sensitivity/(1 – sensitivity) and LR– = (1 – sensitivity)/specificity. LRs in a meta-analysis can be treated like risk ratios; thus, the weights are calculated as are those in a meta-analysis of risk ratios.

When a diagnostic test has no discriminating ability, both LRs equal 1. The discriminating ability is better when LR+ is high and LR– is low. Although there is no absolute cutoff, a good diagnostic test may have a LR+ above 5 and a LR– below 0.2 (20).

We combined all data for the main analysis regardless of the definition of positivity at AGS (qualitative or semiquantitative), type of monoclonal antibody used, type of joint arthroplasty (hip or knee), type of reference standard (which was typically a combination of histopathologic examination, cultures and other microbiologic or laboratory examination, clinical follow-up examination, or radiologic examination), study design (prospective or retrospective), and reported blinding or no or unreported blinding of the readers of the diagnostic test to the results of the reference standard. Subgroup analyses, however, were also performed for each of these parameters, and inferences were drawn based on the observed between-subgroup heterogeneity.

Analyses were conducted with software (Intercooled 8.2, Stata, College Station, Tex; Meta-Test, Joseph Lau, Boston, Mass). Between-study and between-subgroup heterogeneity statistics are relatively insensitive, and therefore inferences on heterogeneity are traditionally considered to indicate a significant difference if P < .10 (21). All other P values were two-tailed and were considered to indicate a significant difference if P < .05.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 
Eligible Studies
Nineteen potentially eligible studies were retrieved. We excluded a study of 22 patients (22) with a variety of clinical conditions because we could not obtain separate results for those with potentially infected implants. We excluded two studies (23,24) that extensively overlapped with two larger studies (11,15). We retained only the largest (9) of three overlapping studies from the same center (9,25,26). Finally, we excluded a study of 23 arthroplasties because it did not provide the necessary data in sufficient detail (27).

Thirteen eligible studies of nonoverlapping patient groups were included in the meta-analysis. We had a total sample size of 522 prostheses (317 total hip arthroplasties, 178 total knee arthroplasties, four total elbow arthroplasties, and four total shoulder arthroplasties; one study [10] with a total of 78 patients with prostheses included 19 patients with implants other than arthroplasties, and separate results were not given). Study sample sizes ranged between eight and 81 examined prostheses. Thus, 495 (95%) of 522 of the examined prostheses were in hip and knee joints. Nine studies were reported in English, three in German, and one in Spanish. Table 1 summarizes the characteristics of the patient groups included in the meta-analysis.


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  		Table 1. Characteristics of Patient Groups in Included Diagnostic Studies

 
The monoclonal antibody sulesomab was used in nine studies and BW 250/183 was used in four studies at AGS after the administration of varying doses of 99mTc (Table 2). In seven studies, at least two independent readers assessed the AGS scans for signs of implant infection; in four of these studies, all readers were blinded to the clinical condition of the patients. Studies that did not report at all on blinding and independent reading of results, however, may not have necessarily failed to fulfill these criteria. Investigators of five studies used similar semiquantitative criteria to interpret AGS scans on the basis of the increase in the activity quotient during the late phase versus that during the early phase of AGS examination. Different reference standards were employed to verify the clinical condition of each patient and pertained to different combinations of histopathologic examination, cultures and other microbiologic examination, clinical follow-up examination, and radiologic examination (including radiography, computed tomography (CT), magnetic resonance (MR) imaging, and indium white blood cell scintigraphy) (Table 2).


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  		Table 2. Characteristics of AGS in Included Diagnostic Studies

 
Data Synthesis: Statistical Analysis
The sensitivity of AGS with monoclonal antibodies for the diagnosis of prosthesis infection after total joint arthroplasty ranged from 57% (four of seven) to 100% (17 of 17) across the eligible studies. The respective specificity ranged from 65% (15 of 23) to 100% (four of four). When all studies were considered, there were 177 implants with a positive finding at AGS with monoclonal antibodies and documentation of prosthesis infection (true-positive findings), 59 with a positive finding at AGS with monoclonal antibodies and no documentation of prosthesis infection (false-positive findings), 27 with a negative finding at AGS with monoclonal antibodies and no documentation of prosthesis infection (false-negative findings), and 259 with a negative finding at AGS with monoclonal antibodies and no documentation of prosthesis infection (true-negative findings).

The independent random effects summary estimates of sensitivity and specificity were 83% (95% confidence interval [CI]: 75%, 89%) and 80% (95% CI: 75%, 84%), respectively. There was significant between-study heterogeneity in the sensitivity estimates (P = .029) but not in the specificity estimates (P = .38). Removal of the study that included 19 implants other than arthroplasties from the calculation yielded similar results (sensitivity, 84%; 95% CI: 74%, 91%; specificity, 80%; 95% CI: 74%, 84%). Furthermore, removal also of the study that included four elbow and four shoulder arthroplasties from the calculation yielded similar results (sensitivity, 83%; 95% CI: 72%, 91%; specificity, 80%; 95% CI: 74%, 84%).

With the summary ROC curve, a sensitivity of 83% corresponded to a specificity of 84% and a specificity of 80% corresponded to a sensitivity of 92% (Figure) in the unweighted analysis. The respective weighted pairs were 83% and 83% and 80% and 90%. By using a sensitivity of 90%, a specificity of 80% and a 10% prior probability of infection, a positive finding at AGS would increase the probability of infection to 33.3%, whereas a negative finding at AGS would decrease the probability of infection to 1.4%, thus nearly excluding infection. With 50% prior probability of infection, a positive finding at AGS would increase the probability to 81.8%, whereas a negative finding at AGS would make infection quite unlikely (11.11%). With 80% prior probability of infection, a positive finding at AGS would make infection almost certain (92.3%), whereas a negative finding at AGS would make infection much less probable (33.3%).


Figure 1
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  		Summary ROC curves of AGS with monoclonal antibodies for diagnosis of prosthesis infection. Both weighted (thick line) and unweighted (thin line) curves are shown. Each study is represented by an ellipse with diameter proportional to its weight in sensitivity and specificity dimensions. Independent summary estimate of sensitivity and specificity (x; 83% and 80%, respectively) determined with random effects calculations is shown with 95% CIs (shaded box).

 
LR syntheses gave a weighted LR+ of 3.99 (95% CI: 3.13, 5.09) and a weighted LR– of 0.22 (95% CI: 0.15, 0.34); there was no statistically significant between-study heterogeneity for either metric (P = .49 and P = .13, respectively).

Subgroup Analyses
The subgroup analyses did not reveal any statistically significant differences between studies with prospective design and those with retrospective design, between studies with sulesomab as the monoclonal antibody and those with BW 250/183 as the monoclonal antibody, between studies that reported blinding and those that did not blind or did not report blinding, and between studies with semiquantitative methods for the assessment of AGS results and those with only qualitative methods for the assessment of AGS results (P > .15 in all instances) (Table 3). The subgroup analyses regarding the type of arthroplasty showed slightly worse diagnostic performance for total hip arthroplasty than for total knee arthroplasty, but the difference was not significant (P > .15 in all instances) (Table 3). It was not possible to address subgroup analyses according to reference standard used, because different combinations of tests were used even within the same study for different patients and data were not available according to different combinations of tests.


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  		Table 3. Subgroup Analyses among 13 Studies of Diagnostic Performance of AGS with Monoclonal Antibodies

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
ADVANCES IN KNOWLEDGE
 References
 
Our meta-analysis showed that AGS with monoclonal antibodies had reasonably high discriminating ability to identify prosthesis infection among patients who underwent total joint arthroplasty. Sensitivity and specificity pairs were slightly less than 85%. LRs yielded a similar inference, falling slightly short of passing the thresholds of LR+ > 5 and LR– < 0.2. No significant differences were observed in diagnostic performance sensitivities and specificities of the various subgroup analyses regarding type of antibody used, type of arthroplasty, type of study design, blinding reporting, and methods used for the assessment of AGS. On the basis of these findings, AGS seems to have definite merits as a complementary diagnostic test to traditional diagnostic procedures such as biopsy or culture. AGS, however, cannot yet fully replace the current methods used for the diagnosis of prosthesis infection.

The diagnosis of prosthesis infection after total joint arthroplasty remains a challenge. Numerous preoperative and intraoperative tests are employed. Unfortunately, no test has perfect sensitivity and specificity (28–30). Even with the seemingly most accurate methods, such as cultures (either of synovial fluid or of periprosthetic tissue intraoperatively) and histopathologic examination of periprosthetic tissue, the diagnosis of infection is not entirely reliable (31–33). The diagnostic ability of cultures depends on whether these are from aspiration of the synovial fluid or from intraoperative sampling. Cultures from aspiration are not as definitive as those obtained intraoperatively, because occasional false-positive results are observed with cultures from aspiration (31–33). The ability of intraoperative cultures to help diagnose infection also depends on the number of specimens obtained. Five or six specimens obtained at surgery have been reported to be necessary to produce an accurate diagnostic test (34). Even for those patients for whom three or more specimens yielded positive cultures, it was usual for at least one other specimen to show no growth. On the other hand, the histopathologic findings of periprosthetic tissue seem to provide the most reliable diagnostic information. Histopathologic findings, however, provide no information on the infecting organism, which is an essential element for the patient treatment, and the interpretation depends on the pathologist's experience.

In our meta-analysis, a variety of reference standards were used in the individual studies, including cultures and other microbiologic examination, histopathologic examination, clinical follow-up examination, and radiologic examination in various combinations. None of these methods is perfect as a reference standard for establishing the diagnosis of prosthesis infection. Thus, it was appropriate that these tests were typically used in combination for the assessment of each patient. Misclassification bias resulting from the imperfect reference standard may affect the estimates of diagnostic accuracy of a tested method. Consequently, if the reference standards had been flawed we might have underestimated the sensitivity, specificity, LR+, and LR– of AGS with monoclonal antibodies, in particular if there had been nondifferential misclassification. The combination of several reference standards in the eligible studies, however, probably decreases this effect. Biased differential misclassification may inflate or deflate the estimated diagnostic performance. Reassuringly, the blinded studies (ie, those with least bias) showed similar results.

AGS with monoclonal antibodies has been used extensively for the diagnosis of infection in several clinical entities, such as osteomyelitis and soft-tissue infections (35,36), spondylitis (37), fever of unknown origin (38), endocarditis (39), arthritis, pericarditis, and infections of vascular implants (12); various sensitivities and specificities were reported. Systematic evaluation of diagnostic performance in these settings would be useful in order to define the optimal spectrum of applications for this technology.

Some limitations of our meta-analysis should be acknowledged. First, the sample size was limited. Even though the number of total joint replacements in clinical practice was very large, collating large series of patients with possible infection was a challenge. The meta-analysis is many times larger than the largest included study and reveals the need to accumulate more large-scale evidence. Small subgroup differences may have been missed as a result of the sample size limitations. Second, although we were all inclusive and tried to retrieve additional data, the fact that there were some missing data was unavoidable. Third, the eligible studies showed a remarkable variability in the reference standards used. It was not possible to perform sensitivity analyses according to the type of reference standard used because most studies did not provide separate results based on the reference standard. Fourth, the dose of 99mTc and time of scanning from the administration of injection varied across studies, but it is unclear how this might influence the results. The interpretation of AGS was based on qualitative or semiquantitative methods, and therefore some misdiagnoses are inevitable. Whether quantitative methods achieve better accuracy when compared with semiquantitative methods remains to be seen.

When we allow for these caveats, the meta-analysis reveals that AGS may have a role in the diagnosis of prosthesis infection. Other nuclear diagnostic tests, such as those based on labeling white blood cells, the use of ciprofloxacin scintigraphy, or positron emission tomographic examination (40–42), need to be compared with AGS with monoclonal antibodies against leukocyte antigens. The optimal combination of different diagnostic tests in this setting may need further large-scale evidence to validate.


   ADVANCES IN KNOWLEDGE
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
References
 


   FOOTNOTES
 

Abbreviations: AGS = antigranulocyte scintigraphy • CI = confidence interval • LR = likelihood ratio • ROC = receiver operating characteristic

Authors stated no financial relationship to disclose.

Author contributions: Guarantor of integrity of entire study, E.E.P.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; literature research, E.E.P., T.A.T., A.D.F.; statistical analysis, E.E.P., T.A.T., J.P.A.I.; and manuscript editing, E.E.P., T.A.T., J.P.A.I.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCES IN KNOWLEDGE
 References
 

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