| Literature DB >> 35872782 |
Isaac T Cheng1, Huan Meng1, Martin Li1, Edmund K Li1, Priscilla C Wong1, Jack Lee2, Bryan P Yan1, Alex P W Lee1, Ho So1, Lai-Shan Tam1.
Abstract
Background: Whether calprotectin could play a role in augmenting cardiovascular (CV) risk in patients with psoriatic arthritis (PsA) remains uncertain. The aim of this study is to elucidate the association between serum calprotectin level and subclinical atherosclerosis in patient with PsA. Method: Seventy-eight PsA patients (age: 52 ± 10 years, 41 [52.6%] male) without CV disease were recruited into this cross-sectional study. Carotid intima-media thickness (cIMT) and the presence of plaque were determined by high-resolution ultrasound. Calprotectin levels in serum were quantified by enzyme-linked immunosorbent assay. The variables associated with the presence of carotid plaque (CP) were selected from the least absolute shrinkage and selection operator (LASSO) regression analysis.Entities:
Keywords: LASSO regression; carotid ultrasound; psoriatic arthritis; serum calprotectin; subclinical atherosclerosis
Year: 2022 PMID: 35872782 PMCID: PMC9305068 DOI: 10.3389/fmed.2022.932696
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
Anthropometric and clinical characteristics of PsA patients with or without carotid plaque.
| Carotid plaque | ||||||
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| ||||||
| All ( | No ( | Yes ( | ||||
| Male gender, n (%) | 41 (52.6%) | 22 (44.9%) | 19 (65.5%) | 0.078 | ||
| Age, (years) | 52 ± 10 | 50 ± 11 | 56 ± 8 | 0.024 | ||
| | ||||||
| PsA disease duration, (years) | 14.1 ± 7.0 | 12.4 ± 7.0 | 17.0 ± 6.3 | 0.005 | ||
| Tender joint count, (0–68) | 0.5 (0, 3) | 1 (0, 3) | 0 (0, 3) | 0.825 | ||
| Swollen joint count, (0–66) | 0 (0, 2) | 0 (0, 1) | 1 (0, 2) | 0.044 | ||
| Damaged joint count, (0–68) | 2 (0, 6) | 0 (0, 5) | 1 (0, 8) | 0.437 | ||
| Dactylitis (0–20) | 0 (0, 1) | 0 (0, 0) | 0 (0, 0) | 0.091 | ||
| MASES enthesitis, (0–13) | 0 (0, 11) | 0 (0, 1) | 0 (0, 0) | 0.467 | ||
| VAS Pain, (0–100) | 30 (14, 50) | 30 (20, 50) | 30 (10, 60) | 0.654 | ||
| PtGA, (0–100) | 40 (20, 60) | 35 (20, 55) | 50 (30, 60) | 0.129 | ||
| PGA, (0–100) | 20 (6, 40) | 15 (6, 35) | 20 (10, 40) | 0.427 | ||
| PASI, (0–72) | 2 (0.5, 5.9) | 2 (0.7, 5.8) | 1.8 (0.5, 5.4) | 0.922 | ||
| HAQ, (0–3) | 0.5 (0.0, 0.6) | 0.1 (0.0, 0.4) | 0.4 (0.0, 0.9) | 0.149 | ||
| MDA, n (%) | 13 (16.7%) | 10 (20.4%) | 3 (10.3%) | 0.249 | ||
| DAPSA, (0–64) | 2.5 (1.0, 6.0) | 2.2 (0.9, 6.8) | 2.8 (1.2, 5.1) | 0.722 | ||
| ESR, (mm/1st hr) | 16 (7.0, 30.5) | 14.5 (7.0, 29.0) | 21.0 (7.0, 32.0) | 0.991 | ||
| CRP, (mg/l) | 3.0 (1.0, 6.0) | 2.8 (1.0, 5.3) | 3.3 (1.1, 8.3) | 0.506 | ||
| | ||||||
| Body weight, (kg) | 67.2 ± 13.1 | 67.9 ± 13.7 | 66.1 ± 12.4 | 0.562 | ||
| BMI, (kg/m2) | 25.2 ± 4.1 | 25.6 ± 4.2 | 24.6 ± 3.9 | 0.314 | ||
| Waist-to-hip ratio | 0.9 ± 0.1 | 0.9 ± 0.1 | 0.9 ± 0.1 | 0.544 | ||
| Current smoker, n (%) | 8 (10.2%) | 5 (10.2%) | 3 (10.3%) | 0.248 | ||
| Current drinker, n (%) | 24 (30.8%) | 16 (32.6%) | 8 (27.6%) | 0.622 | ||
| Systolic BP, (mmHg) | 127 ± 15 | 126 ± 15 | 128 ± 15 | 0.765 | ||
| Diastolic BP, (mmHg) | 82 ± 11 | 81 ± 10 | 83 ± 12 | 0.483 | ||
| Total cholesterol, (mmol/l) | 5.0 ± 0.8 | 4.9 ± 0.8 | 5.1 ± 0.8 | 0.350 | ||
| HDL cholesterol, (mmol/l) | 1.4 ± 0.4 | 1.4 ± 0.3 | 1.5 ± 0.5 | 0.481 | ||
| LDL cholesterol, (mmol/l) | 3.0 ± 0.7 | 2.9 ± 0.7 | 3.1 ± 0.7 | 0.206 | ||
| Triglycerides, (mmol/l) | 1.4 ± 0.9 | 1.5 ± 1.0 | 1.3 ± 0.5 | 0.196 | ||
| Fasting plasma glucose, (mmol/l) | 5.5 ± 1.5 | 5.7 ± 1.8 | 5.1 ± 0.7 | 0.155 | ||
| Hypertension, n (%) | 42 (53.8%) | 27 (55.1%) | 15 (51.7%) | 0.772 | ||
| Hyperlipidemia, n (%) | 19 (24.3%) | 9 (18.4%) | 10 (34.5%) | 0.109 | ||
| Diabetes, n (%) | 14 (17.9%) | 9 (18.4%) | 5 (17.2%) | 0.900 | ||
| FRS, (%) | 10.7 ± 8.4 | 9.2 ± 8.5 | 12.7 ± 7.8 | 0.094 | ||
| | ||||||
| Anti-hypertensive | 39 (50.0%) | 26 (53.1%) | 13 (44.8%) | 0.482 | ||
| Statins | 12 (15.4%) | 5 (10.2%) | 7 (24.1%) | 0.099 | ||
| NASIDs | 35 (44.9%) | 23 (36.9%) | 12 (41.4%) | 0.633 | ||
| csDMARDs | 45 (57.7%) | 30 (61.2%) | 15 (51.7%) | 0.412 | ||
| bDMARDs | 13 (16.7%) | 8 (16.3%) | 5 (17.2%) | 0.917 | ||
| | ||||||
| Serum calprotectin, (ng/ml) | 665.4 (415.0, 947.0) | 564.6 (329.3, 910.5) | 721.3 (574.1, 1268.4) | 0.005 | ||
*P value < 0.05. VAS, visual analog scale; PtGA, patients’ global assessment of disease activity; PGA, physicians’ global assessment of disease activity; PASI, psoriasis area and severity index; HAQ, health assessment questionnaire; DAPSA, disease activity in psoriatic arthritis; MDA, minimal disease activity; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; BMI, body mass index; BP, blood pressure; FRS, Framingham risk score; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NSAID, non-steroidal anti-inflammatory drugs; csDMARDs, conventional synthetic disease-modifying antirheumatic drugs. bDMARDs, biologics disease-modifying antirheumatic drugs. Values are the number (percentage) or median (interquartile range) or mean ± SD.
FIGURE 1Serum calprotectin levels between CP+ groups and CP– groups. CP, carotid plaque. *P value < 0.05.
The logistic regression analysis of variables selected by LASSO regression for predicting the presence of carotid plaque.
| Predictive model | ||||
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| Intercept and variables | Estimate | OR (95%) | ||
| Intercept | −9.713 | −2.981 | 0.00 (0.00, 0.02) | 0.003 |
| Ln-calprotectin | 0.086 | 2.222 | 3.38 (1.37, 9.47) | 0.026 |
| PsA disease duration (years) | 1.218 | 2.495 | 1.09 (1.01, 1.18) | 0.013 |
*P value < 0.05.
FIGURE 2(A) Nomogram for predicting the probability of CP+ including the risk factors of PsA disease duration and Ln-calprotectin. To estimate the risk for the CP+ (shown as “Risk” in the figure) among patients with PsA, each individual patient’s values were plotted on each variable axis. A verticle line was drawn from that value to the top “Points” scale to determine the number of points that were assigned by that variable value. Then, the points from each variable value were summed. The sum on the “Points” scale was located and vertically projected onto the bottom “Total points” axis, and then a personalized risk of CP for PsA was obtained. CP+, the presence of carotid plaque (B). The dynamic nomogram was used as an example (one patient in our sample).
FIGURE 3The receiver operator characteristic (ROC) curve and Calibration curve of the nomogram for predicting in patients with PsA. (A) ROC curve of the predictive model for CP+. (B) Calibration curves of the predictive model for CP+. The black line represents a great fit between the nomogram predicted probability (x-axis) and the observed probability of actual diagnosed cases of CP+ (y-axis). The dotted line represents performance of the present nomogram. Closer fit between the two lines indicates a higher prediction accuracy. CP+, the presence of carotid plaque.
Discrimination and calibration assessment of CP+ nomogram model selected by multivariate and LASSO regression.
| Value (95% CI) | ||
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| ||
| AIC | 94.0 | – |
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| AUC | 0.744 (0.59, 0.80) | 0.037 |
| Sensitivity (%) | 65.3 | – |
| Specificity (%) | 79.3 | – |
| Accuracy (%) | 75.6 | – |
| PPV (%) | 84.2 | – |
| NPV (%) | 57.5 | – |
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| HL | 0.061 | |
*P value < 0.05. CP+, carotid plaque; AUC, area under the curve; PPV, positive predicted value; NPV, negative predicted value; HL, Hosmer-Lemeshow chi-square statistical test.