Efficacy of three ELISA measurements of anti-cyclic citrullinated peptide antibodies in the early diagnosis of rheumatoid arthritis
Department of Biotechnology, Empresa Pública Hospital de Poniente de Almería, El Ejido, Almería, Spain.Clinical Chemistry and Laboratory Medicine (Impact Factor: 2.71). 02/2005; 43(11):1234-9. DOI: 10.1515/CCLM.2005.214
The objective of the present study was to determine the efficacy of anti-cyclic citrullinated peptide (anti-CCP) antibody detection in the early diagnosis of rheumatoid arthritis (RA), as well as to compare three commercially available enzyme-linked immunosorbent assay (ELISA) kits used to detect such antibodies. We analysed the presence of anti-CCP antibodies in the sera of 78 patients who had been newly referred from primary healthcare centres to the Early Polyarthritis Unit. We also included in the study a group of 50 healthy controls. None of the patients had previously received treatment for the disease. After 1-year follow-up, the diagnosis of RA was confirmed in 53 of these patients. The ELISA kits under study were IMMUNOSCAN RA (Euro-Diagnostica AB), QUANTA Lite CCP IgG ELISA (INOVA Diagnostic) and DIA-STAT Anti-CCP (Axis-Shield Diagnostics); the sensitivity obtained was 52.8%, 58.5% and 52.8%, respectively, with 100% specificity for all three kits. Anti-CCP antibodies detected the presence of RA in 26% of patients without positive rheumatoid factor (RF). The sum of anti-CCP antibodies or the presence of RF gave a sensitivity of up to 67%, with specificity ranging between 94 and 97%. Anti-CCP antibodies show high specificity for the diagnosis of RA. The three ELISAs analysed offer the same degree of diagnostic accuracy.
Conference Paper: Object detection and tracking using the particle filtering[Show abstract] [Hide abstract]
ABSTRACT: In this paper, we present a method for detecting and tracking rigid moving objects in a monocular image sequence. The originality of this method lies in a state modelling of this estimation problem which is solved in an unified way. This hybrid estimation problem leads to nonlinear state equations that are solved by the particle filtering. A particle filter is set for each shape model (modes). It estimates the motion and position parameters, tracks the object in the sequence and also computes at each time the probability of all modes.Signals, Systems and Computers, 2003. Conference Record of the Thirty-Seventh Asilomar Conference on; 12/2003
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ABSTRACT: To evaluate the two generations of anti-cyclic citrullinated protein (CCP) antibodies as a diagnostic marker of rheumatoid arthritis (RA) and as a predictor of future development of RA in healthy subjects and in patients with early undifferentiated arthritis. A systematic analysis of the literature published between 1999 and February 2006 was conducted. Data were collected on the sensitivity and specificity of the two generations of anti-CCP antibodies for diagnosing RA and predicting future development of the disease. Among 107 studies initially identified, 68 had interpretable data and were analysed. Diagnostic properties were assessed in 58 studies: mean (SD) sensitivity was 53 (10)% (range 41-68) and 68 (15)% (range 39-94) for anti-CCP1 and anti-CCP2, respectively; mean (SD) specificity was 96 (3)% (range 90-99) and 95 (5)% (range 81-100) for anti-CCP1 and anti-CCP2, respectively. Predictive properties were assessed in 14 studies; odds ratio (95% confidence interval) of anti-CCP1 and anti-CCP2 for the future development of RA were 20 (14 to 31) and 25 (18 to 35), respectively, among patients with early undifferentiated arthritis and 64.5 (8.5 to 489) and 28 (8 to 95), respectively, among healthy subjects. Sensitivity of the second generation of anti-CCP is close to that of rheumatoid factor, with a higher specificity, for distinguishing RA from other rheumatic diseases. Moreover, anti-CCP antibodies appear to be highly predictive of the future development of RA in both healthy subjects and patients with undifferentiated arthritis.Annals of the Rheumatic Diseases 08/2006; 65(7):845-51. DOI:10.1136/ard.2006.051391 · 10.38 Impact Factor
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ABSTRACT: To identify baseline variables that predict remission at 1 year in patients with recent onset inflammatory polyarthritis (IP). We prospectively studied 167 patients aged >or=16 years with a 4-week to 12-month history of swelling of >or=2 joints. At baseline, no patient had previously received corticosteroids or disease-modifying anti-rheumatic drugs (DMARDs). To adjust for differences in baseline variables associated with the type of treatment given (a surrogate marker of disease severity), we used regression analysis. The classification probability of treatment thus obtained was entered, along with other significant baseline variables, in a second separate regression analysis to identify variables that predicted remission (no swollen joints). Frequency of remission was 50.9% at 1 year. In the first regression analysis, variables associated with treatment with DMARDs or DMARDs and corticosteroids versus corticosteroids alone included age, morning stiffness, swollen joint count (SJC), disease severity according to the patient, and rheumatoid factor (RF) level; the strongest association was for higher SJC. In the second regression analysis, the model that best predicted remission (correct in 70.1% of cases) included age, tender joint count (TJC), erythrocyte sedimentation rate (ESR), RF, total Sharp score, disease severity according to the physician, and the 1987 American Rheumatism Association (ARA) criteria for rheumatoid arthritis (RA); the strongest association was for failure to meet these criteria. The model's sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve were 70.6%, 70.9%, and 75.4%, respectively. Although we identified some predictors of remission, no model accurately predicted remission at 1 year in this cohort.Scandinavian Journal of Rheumatology 01/2007; 36(5):378-85. DOI:10.1080/03009740701286748 · 2.53 Impact Factor
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