Alcohol and Alcoholism Advance Access originally published online on July 30, 2008
Alcohol and Alcoholism 2008 43(5):569-576; doi:10.1093/alcalc/agn058
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Automated Measurement of Carbohydrate-Deficient Transferrin Using the Bio-Rad %CDT by the HPLC Test on a VariantTM HPLC System: Evaluation and Comparison with Other Routine Procedures
1 Laboratoire de Biochimie et Biologie Moléculaire, Pôle de Biologie, Hôpital Trousseau, CHRU de Tours, France
2 CCAA, CHRU, Tours, France
3 Addictology Unit, Hôpital Fernand Widal, Paris, France
4 INSERM U567, Hôpital Necker, Paris, France
* Corresponding author: Laboratoire de Biochimie et Biologie Moléculaire, Pôle de Biologie, Hôpital Trouseau, 37044 Tours, France. Tel: +33-2-47474684; Fax: +33-2-47474688; E-mail: f.schellenberg{at}chu-tours.fr
Received 9 November 2007; first review notified 3 January 2008; in revised form 22 May 2008; accepted 24 June 2008
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ABSTRACT |
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Aims: In this study, we evaluated the new %CDT by the HPLC method (Bio-Rad, Germany) on a VariantTM HPLC system (Bio-Rad), checked the correlation with well-known methods and calculated the diagnostic value of the test. Methods: Intra-run and day-to-day precision values were calculated for samples with extreme serum transferrin concentrations, high trisialotransferrin and interfering conditions (haemolysed, lactescent and icteric samples). The method was compared with two routine procedures, the %CDT TIA (Bio-Rad, Hercules, CA, USA) and the CapillarysTM CDT (Sebia, France). A total of 350 clinical sera samples were used for a case-control study. Results: Precision values were better in high CDT and medium CDT pools than in low CDT pools. The serum transferrin concentration had no effect on CDT measurement, except in samples with serum transferrin <1 g/L. Haemolysis was the only interfering situation. The method showed high correlation (r2 > 0.95) with the two other methods (%CDT TIA and CZE %CDT). The global predictive value of the test was >0.90 at 1.9% cut-off. Conclusions: These results demonstrate that the %CDT by the HPLC test is suitable for CDT routine measurement; the results from the high-throughput VariantTM system are well correlated with other methods and are of high diagnostic value.
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Introduction |
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Among the biological markers of alcohol abuse investigated over the past decades, CDT (carbohydrate-deficient transferrin) (Stibler, 1991) is considered the most accurate marker for the detection of alcohol abuse and possible relapse (Stibler et al., 1991; Helander 2003
; Bortolotti et al., 2006). The main transferrin (Tf) glycoform comprises one polypeptide chain bearing two bi-antennary N-linked oligosaccharide chains, and each antenna is terminated with a sialic acid residue (i.e. four sialic acid residues). The overall number of sialic acid residues (Hatton et al., 1982) is theoretically between 0 (no oligosaccharide chain) and 8 (two tetra-antennae oligosaccharide chains terminated with four sialic acid residues on each). The Tf structure is modified following an alcohol-induced mechanism, resulting in the synthesis of Tf molecules lacking one (disialotransferrin) or both (asialotransferrin) glycans. As disialotransferrin (DiST) is the main modified glycoform (Stibler et al., 1979) and the increase of asialotransferrin (AST) can be observed only in samples with considerable amount of DiST, it was proposed as the target molecule for CDT standardization and calibration (Jeppsson et al., 2007).
Over recent years, the use of CDT as a routine test for alcohol abuse has been hampered by laborious and time-consuming methods (Bortolotti et al., 2006). The methods based on microcolumn ion-exchange chromatography allow the global quantification of asialo-, monosialo-, disialo- and a variable amount of trisialotransferrin. The final result is expressed as the ratio between CDT and total Tf. More recently, new methods based on capillary zone electrophoresis (CZE) (Bortolotti et al., 2007; Schellenberg et al., 2007), high-performance liquid chromatography (HPLC) (Jeppsson et al., 1993, Helander and Bergström, 2006) and direct immunonephelometric measurement (Delanghe et al., 2007) have been developed that allow reliable and automated measurement of CDT. HPLC methodology allows the quantitative spectrometric determination of each Tf glycoform and has been proposed as a candidate reference method (Helander et al., 2003).
The aim of this study was to evaluate the analytical features and diagnostic value of the commercial kit %CDT by HPLC on the routine high-throughput VariantTM HPLC system (Bio-Rad, Munich, Germany).
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Materials and Methods |
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Analytical procedures
%CDT by the HPLC technique The Bio-Rad %CDT by HPLC was run on a VariantTM HPLC system. This system comprises a two dual-piston pump system, a thermostated (20°C) 100-sample auto sampler and a column compartment (35°C) and a dual wavelength (460 nm and 690 nm) detector. The system is connected to the CDM software (Bio Rad). Before analysis, the samples are pre-treated by 30-min incubation with a ferrous and dextran sulphate solution, followed by 10-min (10,000 g) centrifugation, for both iron saturation and lipid precipitation. The supernatant is then ready for chromatographic analysis. The Tf fractions are separated using an ion-exchange column (600 tests) protected by a guard column (100 tests). The absorbance of the ferrous iron–Tf complex is measured at 460 nm; the secondary 690 nm wavelength is used for background noise reduction. The system calculates the area of each Tf glycoform peak following baseline integration from disialo- to pentasialotransferrin. The hexasialotransferrin peak is not integrated; asialotransferrin, when present, is integrated in a separate baseline mode (Fig. 1A and C). The area of each identified peak is expressed as the ratio of its surface to the total under-peak area. The total analysis time is
10 min.
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%CDT TIA technique This assay is based on separation of the Tf glycoforms on micro anion exchange chromatography columns followed by nephelometric, or turbidimetric, measurement of the Tf in each eluate, allowing CDT quantification (Schwarz et al., 2003
). The Tf glycoforms contained in the CDT eluate are mainly di-, mono- and asialotransferrin, and a minor part of trisialotransferrin (Aldén et al., 2005). In this study, nephelometric determinations were run using an Immage 800 (Beckman Coulter, Brea, CA, USA). The cut-off limit was 2.60% according to the manufacturer's recommendations (Schwan et al., 2004).
CapillarysTM CDT technique
This capillary zone electrophoresis (CZE) technique has been developed by SEBIA (Evry, France) on the routine multicapillary system CapillarysTM (Bortolotti et al., 2007). In this assay, the Tf glycoforms are separated by high voltage electrophoresis (8200 V) in an alkaline buffer (pH 8.8) according to pH and electro-osmotic flow. The Tf glycoforms are detected by absorbance measurement at 200 nm wavelength.
Samples
Six pools of sera with low (1 and 2), medium, critical and high (1 and 2) CDT concentrations were prepared from anonymous routine samples, in which CDT had been previously measured by the routine method %CDT TIA (Bio-Rad). CDT values were <1.9% for the low pools, 2.0–2.6% for the normal pool, 2.6–3.0% for the critical pool and >5% and >9% for the high pools 1 and 2, respectively.
A panel of 402 samples was analysed in this study: (a) 169 samples from patients with an AUDIT (Alcohol Use Disorders Identification Test) score >10, daily ethanol intake >50 g or BAC (Blood Alcohol Concentration) >0, which constituted the "alcohol abusers" group; (b) 112 hospital patients who had no history or suspicion of alcohol abuse and no biological signs (excluding CDT levels) of alcohol abuse, and 69 patients with an AUDIT score <7 and a daily alcohol intake <40 g, constituting a control group (181 patients); (c) 52 samples, surplus of routine examinations, characterized by serum Tf concentration outside the "alert" values (1.50–3.00 g/L) or trisialotransferrin >6% (according to CZE CDT determination).
Thirty lipaemic samples were also included upon criteria of high triglyceride concentration, lactescent aspect and high lipemic index determined by a routine chemistry analyser Olympus 2700 (Olympus Corp., Japan). Thirty samples with various CDT concentrations were enriched with non-conjugated bilirubin to a final bilirubin concentration of 200–500 µmol/L. Thirty samples with various CDT concentrations were enriched with haemoglobin by addition of haemolysed and centrifuged erythrocytes to a final haemoglobin concentration of 1–4 g/L.
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Study Design |
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Precision
Intra-run precision was calculated from the repeated measurement of low[1], medium and high[1] pools. These samples were tested 10 times each day for three consecutive days. Intra-day precision was also calculated for each pool. The total precision was determined as described in the CLSI protocol EP5-A2 using low[2], critical and high[2] pools. Each pool was analysed in duplicate 5 days a week by two runs separated by at least 2 h for four consecutive weeks.
Interfering situations
A. Tf concentration
A panel of samples covering the range of Tf serum concentrations was selected among samples of the (b) and (c) panels to determine if there was a relationship between total Tf concentration and CDT values. The samples were selected according to the following criteria: serum Tf concentrations 0.5–4.5 g/L in 0.1 g/L increments; CDT was assumed as having no reason to be increased, based on a lack of suspected alcohol abuse, according to usual liver parameters (ALT, GGT) and normal CDT values when measured by the routine laboratory method. The relationship between Tf concentration and CDT values was assessed by measuring the slope of the curve CDT = f(Tf).
B. Serum aspect Thirty lipaemic samples were analysed in duplicate before and after centrifugation (60,000 g, 30 min). Prior to CDT determination, all samples were submitted to the pre-treatment described by the manufacturer. Thirty samples with various CDT concentrations were enriched with non-conjugated bilirubin to a final bilirubin concentration of 200–500 µmol/L. CDT levels were measured before and after bilirubin addition using the %CDT by the HPLC technique. Thirty samples with various CDT concentrations were enriched with haemoglobin and the interference with haemolysis was measured by the %CDT by the HPLC technique before and after haemoglobin addition.
C. High trisialotransferrin Thirty samples with a trisialotransferrin (TriST) level >6% of the total Tf, determined by the Capillarys CDT technique, were selected in the (b) and (c) panels to validate the accuracy of the present method in high TriST samples.
Correlation study
A total of 302 samples from panels (a), (b) and (c) covering the full range of CDT values were analysed in parallel with the %CDT by HPLC, the %CDT TIA and the Capillarys CDT techniques. Highly discrepant results were reanalysed. The methods were compared using the Pearson correlation coefficient and the Passing and Bablock method for regression. The linearity was assessed by the Cusum test for linearity, which tests the random (or not) distribution of the points on each side of the regression line.
Case-control study
A case-control study was performed to evaluate the diagnostic efficacy of the method and to validate the cut-off proposed by the manufacturer. Samples of panels (a) and (b) were analysed in this purpose. They were 350 participants, aged 18–75 years, divided into 181 control subjects (115 males, 66 females) and 169 patients with alcohol abuse disorders (AUD) (136 males, 33 females). The participation of these patients and control individuals in the clinical study was approved by the ethical committee of Hôpital Fernand Widal (Paris, France). The %CDT by the HPLC procedure was compared to the %CDT TIA and Capillarys CDT procedures.
Statistical calculations were performed using MedCalc 9.2 (MedCalc Software, Mariakerke, Belgium) and Analyse-it (Analyse-it Software, Leeds, UK) software. Pearson's correlation coefficient for non-Gaussian distribution was used in the correlation studies.
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Results |
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Precision
Intra-run precision (Table 1) was inversely correlated to the CDT concentrations of the sample. In the low[1] pool, individual measurements varied from simple to double between runs, resulting in daily coefficient of variation (CV) ranging from 9.01% to 19.01%. The precision of CDT determinations in samples with higher CDT concentrations was better, with CVs ranging from 7.84% to 11.74% in the medium pool and 1.43% to 2.90% in the high[1] pool. The high CDT concentration in this pool made possible the integration of the AST peak. The results presented in Table 1 are the sum AST + DiST. Excluding AST did not significantly increase the precision of the technique (data not shown).
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The EP5-A protocol was applied for day-to-day precision evaluation. In this protocol, within-run, between-run and between-day are not considered as independent factors and consequently a poor within-run precision, as observed in low[2] pool, did not allow the calculation of between-run and between-day precision (Table 2). We made the same calculations using the EP EvaluatorTM software and obtained similar results.
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Consequently, we calculated separately the within-run precision using the mean of each duplicate as individual value; the CVs ranged from 16.7% (low[2] pool) to 3.60% (high[2] pool excluding AST). Similarly, we used the mean of results from each day as individual value to calculate the day-to-day precision. The CVs ranged from 7.18% (low[2] pool) to 2.96% (high[2] pool excluding AST).
As observed previously in the intra-run precision study, the coefficients of variation were inversely correlated to CDT concentration in the samples, and the total imprecision according to the EP-5A protocol spread out from 16.7% (low[2] pool) to 5.1% (high[2] pool). In the high[2] pool, AST was not quantifiable in all samples. The exclusion of AST in this pool, as previously recommended (Jeppsson et al., 2007), improved the precision of the technique, resulting in a total imprecision of 4.3%.
Interfering situations
Peak detection
Technically, the limit of detection (LOD) has been set in the Variant's software at 500 area counts (AC). The limit of quantification (LOQ) results from both the limit of detection and the total Tf concentration. A normal Tf concentration (2.5 g/L) gives a total area of 140,000–160,000 (AC); consequently, the LOQ is closed to 0.4%. This value is significantly higher than that from the candidate reference method (Helander et al., 2003). This can be attributed to the lower sample volume of the %CDT by the HPLC test, 17 µL versus 28.6 µL of neat serum injected in the column and to a possible superior optical quality of the detection system used for the reference technique (Agilent 1100 LC).
Tf concentration The relationship between serum Tf concentration and CDT measurement was evaluated in 40 samples (Tf range 0.43–4.58 g/L). CDT levels could not be quantified in eight of these samples; in seven samples (Tf range 0.61– 1.45 g/L), the DiST peak area was under the integration threshold, and the uneven baseline of one sample (Tf 1.65 g/L) did not allow DiST quantification. The seven samples with no quantifiable CDT had a low Tf concentration and an AC for the sum of all glycoforms below 100,000. Therefore, this value of the total area peak can be considered as a limit for CDT quantification. In the 32 other samples, all CDT values were <1.90%, no significant correlation was observed between Tf and CDT values (r2 = 0.098), and the slope of the regression line was not significantly different from zero.
Lipaemic, icteric and haemolysed samples Among the 30 lipaemic samples analysed by the %CDT by the HPLC test before and after de-lipidation by ultracentrifugation, the results of untreated and de-lipidated samples were highly correlated (r2 = 0.971). CDT values showed no difference as attested by the absence of a significant slope (0.944) of the regression equation and by a non-significant paired t-test (P = 0.445). %CDT in the analysed samples was from 0.7% to 11.9%; only two results could be considered as erroneous (difference >10% between both determinations) and were obtained from two samples with high concentrations of triglycerides and chylomicrons, with severely lactescent aspect.
Addition of unconjugated bilirubin to non-lipaemic, non-haemolysed samples had no interfering effect on the %CDT by the HPLC test. The results of supplemented and original samples were highly correlated (r2 = 0.985), the regression equation showed no significant slope (0.967) and the paired t-test did not reveal any difference (P = 0.439).
By contrast, addition of haemoglobin to normal samples resulted in a progressive increase in the baseline of the chromatogram (Fig. 1D), and did not allow a correct integration of the DiST peak for haemoglobin concentrations >2 g/L. In addition, mean values were slightly increased after haemoglobin addition (3.68% versus 3.30%, P = 0.049).
High trisialotransferrin Thirty samples with elevated TriST (6.2–19.1%) were analysed with the %CDT by the HPLC test. In 16 samples, DiST appeared as a shoulder on the TriST peak (Fig. 1B). A low Tf concentration (<1.5 g/L) in 13 of these samples was an additional factor that made quantification of the minor peak difficult, and 9 of these could not be properly quantified. Six samples were obtained from AUD patients and CDT results were increased in these patients by Capillarys CDT and %CDT by HPLC techniques.
Correlation study
A total of 302 samples were included in the study. Two were rejected because their chromatogram revealed a BC phenotype for Tf. The CDT concentrations of 17 samples were particularly low and could not be quantified by the %CDT by the HPLC method. The remaining 283 samples covered a wide range of Tf (0.61–3.03 g/L) and %CDT (0.61–21.36%) concentrations.
We used the paired t-test to compare the overall bias of the results obtained with the different methods. The t values were 8.471 and 7.822, when the %CDT by the HPLC test was compared with %CDT TIA and Capillarys CDT methods, respectively. These differences were highly significant (P < 0.0001), indicating a gap between the results of the compared methods. Fig. 2 (A and B) shows comparisons of the %CDT by the HPLC test with the %CDT TIA and Capillarys CDT methods. The Pearson's correlation coefficients were 0.955 [95% confidence interval (CI) 0.943–0.964] for the %CDT TIA comparison and 0.969 (95% CI 0.961–0.976) for the Capillarys CDT comparison, indicating high concordance between the new %CDT by the HPLC test and the two other methods. Using the Passing and Bablock regression analysis, the slopes of the linear regression lines were calculated as 1.190 (95% CI 1.088–1.281) for the %CDT TIA comparison and 0.989 (95% CI 0.958–1.023) for the Capillarys CDT comparison. This indicated that the difference between %CDT by the HPLC test and %CDT TIA increases with CDT concentration, whereas the difference between %CDT by the HPLC test and the Capillarys CDT method remains approximately constant. The intercepts calculated by the same regression equation were –1.187 (95% CI –1.419 to –0.960) for %CDT TIA and 0.460 (95% CI 0.425 to 0.503) for Capillarys CDT, both being significantly different from zero. The linearity of the relationship between paired CDT measurements was checked using the Cusum test, which assesses the fit of the data to a linear model. As expected from the Bland and Altman diagrams in Fig. 2 (A and B), the test revealed a non-linear regression between %CDT by the HPLC test and %CDT TIA, and a linear regression between %CDT by the HPLC test and Capillarys CDT.
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Case control study
Among the 350 subjects studied, 13 had a CDT concentration below the LOQ of the %CDT by the HPLC technique. Two control subjects had a Tf BC phenotype, and their results were not considered in the study. One sample had an uneven baseline that made DiST peak integration not possible. One additional sample from an AUD patient was rejected owing to an abnormally high TriST, resulting in one single peak for TriST and DiST (15.1%).
For the remaining 333 subjects included, 165 control subjects (107 males, 58 females) and 168 AUD patients (136 males, 32 females), CDT was between 0.61% and 47.64%. There were no differences in age between the four subgroups of subjects, whereas there was a difference between mean CDT values for male and female subjects in both the control and the AUD patients groups (Table 3). CDT values ranged from 0.61% to 2.66% in the control group and from 0.65% to 47.64% in the AUD group. CDT results in this latter group showed a tailed distribution towards low values, which could be attributed to ‘non-responding’ patients for CDT, or to an erroneous report of the time since the last alcohol consumption.
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When calculating the diagnostic values using the cut-off proposed by the manufacturer (1.70%), the sensitivity was 0.74 and the specificity was 0.87. Another ‘optimized’ cut-off at 2.0% was proposed by the statistical software from the results of the case-control study reported on the ROC curve (Fig. 3). We next calculated the global predictive value (GPV) of the test, which represents the fraction of subjects correctly classified by the test in the studied sample. We used four different cut-off values (1.7%, 1.8%, 1.9% and 2.0%) and nine levels of prevalence (10% to 90%), to check the possible consequences of low or high cut-off levels on the diagnostic value of the test. As indicated in Fig. 4, there is a linear negative relationship between prevalence and GPV, with different slopes according to the cut-off level.
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Discussion |
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TOPABSTRACTIntroductionMaterials and MethodsStudy DesignResultsDiscussionConclusionsReferences |
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The present study was aimed at evaluating the new %CDT by the HPLC method focusing on the analytical aspects and to compare its diagnostic value to two established methods.
Our results suggest that the precision of the test is dependent on the signal, the peak area and thus on CDT concentration. The lack of precision of the %CDT by the HPLC test in low pools does not hamper the clinical interpretation of the results, for no individual result was above the cut-off (1.70%). On the other hand, in the medium pool, CDT was above the cut-off in 7 of the 30 determinations, leading to possible misinterpretation of the result. Optical characteristics of the system probably contribute to this imprecision, since a greater precision was observed (Helander and Bergström, 2006) using the same kit on a high performance HPLC system (Agilent 1100 LC). Our results confirm the better precision of CDT measurement when exclusively quantifying the DiST, the recently proposed (Jeppsson et al., 2007) target analyte.
The absence of significant slope of the regression line between Tf and CDT clearly indicates that the total Tf concentration does not by itself introduce a bias in CDT measurement. Nevertheless, this technique does not allow CDT quantification in some samples with Tf <1 g/L while in the 333 samples with Tf >1.5 g/L, only 4 had DiST peak area <500 AC. So, when Tf is in the normal range, the number of samples with no technically relevant result is acceptable (1.5%).
In 14 patients with high TriST and well-separated TriST and DiST peaks, the %CDT by the HPLC technique gave increased CDT values in 6 AUD patients and below the cut-off in the 8 remaining samples, while the %CDT TIA method gave high CDT in all samples. This discrepancy can probably be attributed to the partial co-elution of TriST in the CDT fraction in the %CDT TIA method (Aldén et al., 2005) that leads to false-positive CDT results in patients with high TriST. In this study, we confirm the findings of a recent study (Arndt et al., 2008) for atypical Tf glycoform distribution. Among the 16 samples with high TriST and poor TriST–DiST separation (di-tribridge), 9 of them had low serum Tf (AC< 120,000) and retrospective investigation of their clinical history revealed a liver disease and a suspicion of cirrhosis for 7 out 9 patients. Therefore, high TriST is not by itself a source of inappropriate results, except in patients with low Tf and di-tribridging phenomenon.
The high correlation between the %CDT by the HPLC test and the two other techniques is in agreement with previous results (Helander et al., 2001; Schwarz et al., 2003). We observed a linear correlation between the two methods based on Tf glycoforms pattern determination (%CDT by HPLC and Capillarys CDT), and a non-linear correlation of these techniques with the %CDT TIA method. This lack of linearity could be attributed either to a non-linear calibration of the immunoassay or to the incomplete separation between TriST and DiST in the %CDT TIA test.
Figure 2 shows a lower dispersion of the results between the HPLC and CZE methods, as opposed to the HPLC and TIA methods. These differences can be attributed to, at least, three factors influencing the TIA method: (i) a poor precision level at low values (CDT < 1.8%), (ii) the partial co-elution of TriST in the CDT fraction and (iii) the cumulative imprecision of the immunoassays used for the separate quantification of Tf and CDT. By contrast, in the HPLC and CZE methods, CDT is a ratio between areas obtained in a unique glycoform separation.
Independent of the correlation coefficients, the three compared methods give significantly different CDT results, as shown by the calculated regression equations. Obviously, a common international standard is needed to obtain a linear correlation between the techniques and to allow comparison of results (Oberrauch et al., 2008).
In the control group, we observed a moderate, but significant, difference in the CDT values among genders. This result appears in contradiction with a recent work (Bergström and Helander, 2008) that concluded to an absence of sex difference for CDT values. This might result from differences in the control group definition and from a possible increased alcohol intake in males as compared to women, within the limit of World Health Organization (WHO) recommendations assessed through a questionnaire.
Concerning the diagnostic value of CDT measured by HPLC methods, two studies (Simonsson et al., 1996; Werle et al., 1997) reported higher specificity (>0.95), and one study (Werle et al., 1997) reported better sensitivity (0.80). It is, however, hard to determine the respective contributions of the technical features and of the population study selection criteria to explain these differences. To compare the analytical performance of a test, it is crucial to base the population selection on the sole WHO definition of alcohol abuse. The cut-off setting is also a major point as it controls the diagnostic values. The cut-off can be defined from the distribution of values in the control group or as the value that gives the best discrimination between cases and controls in the study population. In this case, the cut-off can be determined using an ROC curve analysis. In our study (Fig. 3), cut-off determination from the ROC curve suggested a value of 2.0%. Selection of this cut-off resulted in a sensitivity of 0.66 with a specificity of 0.96. Because they are calculated from an established diagnosis, sensitivity and specificity values are nevertheless not highly informative for the physicians. Conversely, the global predictive value (GPV) measures the probability for a subject to be properly classified by the test, independent of his clinical status. With the exception of a test with equal sensitivity and specificity values, GPV fluctuates with the prevalence of the disease (AUD) in the population sample. As indicated in Fig. 4, the higher (2.0% and 1.9%) cut-off values yielded higher GPVs for prevalence values below 50%. Considering a population sample representative of the AUD prevalence in the general population (10%), GPVs were 0.93 for a cut-off at 2.0% or 0.92 for a cut-off at 1.9%. Although the higher cut-off value gives a slightly higher GPV, the heavy social and medical consequences of erroneous interpretations of false-positive CDT value led us to propose 1.9% as cut-off. With the same technique, Helander proposed a cut-off at 1.70% (Helander et al., 2006). Similarly, cut-off values ranging from 1% to 1.75% were selected using other HPLC techniques (Simonsson et al., 1996; Werle et al., 1997; Arndt and Keller, 2004; Helander et al., 2005). These discrepancies might be due to several methodological factors, including the basis for cut-off definition (CDT value distribution in the control group or discrimination between control and AUD groups) and the criteria for inclusion in the control group.
The various cut-off values proposed in these studies, as well as in this study, should be considered as interim values in the absence of a value obtained from a study based on the determination of CDT using the candidate reference method (Jeppsson et al., 2007) applied to a population strictly selected upon the WHO definition of alcohol abuse.
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Conclusions |
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TOPABSTRACTIntroductionMaterials and MethodsStudy DesignResultsDiscussionConclusionsReferences |
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The data from this study indicate a good validity of results obtained with the %CDT by the HPLC method on the VariantTM system. The precision level is acceptable for routine use and the results are not affected by lipaemic or icteric samples. High trisialotransferrin concentrations are not by themselves a cause of false-positive values. The serum Tf concentration does not affect CDT measurement for concentrations >1 g/L. Furthermore, the results correlate well with those obtained with other routine methods based on other analytical processes. This assay provides accurate clinical information, conjugated to the high throughput allowed by the VariantTM HPLC system.
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ACKNOWLEDGEMENTS |
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The authors are grateful to Mrs Annie Détruit, Nadine Puche and Geneviève Wattelet for their technical contribution. They thank Bio-Rad for supporting this study by lending the VariantTM system and providing the reagents. They thank Sebia for providing kits for CZE determinations of CDT. The case-control study was partly supported by INSERM grant ‘ATC Alcool’ no. ALC0205.
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References |
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