Establishment and Validation of Predictive Model of Tophus in Gout Patients
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.1.1. Subjects
2.1.2. Inclusion Criteria
2.1.3. Exclusion Standards
2.2. Methods
2.2.1. Grouping Methods and Diagnosis of Tophi
2.2.2. Study Indicators
2.2.3. Construction and Evaluation of Predictive Models
3. Statistical Analysis
4. Results
4.1. Comparison of Baseline Data
4.2. Screening of Characteristic Factors for Risk of Tophi in Gout Patients
4.3. Comprehensive Analysis of Classified Multi-Model
4.4. The Best Model Building and Evaluation
4.5. The SHAP to Model Interpretation
5. Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variable | Training Set (n = 491) | Testing Set (n = 211) | Z | P |
---|---|---|---|---|
annual attack frequency (times), n (%) | ||||
<6 | 319 (64.969) | 136 (64.455) | 1.089 | 0.58 |
6–12 | 74 (15.071) | 27 (12.796) | ||
>12 | 98 (19.959) | 48 (22.749) | ||
history of smoking, n (%) | ||||
no | 224 (45.621) | 96 (45.498) | 0.001 | 0.976 |
yes | 267 (54.379) | 115 (54.502) | ||
history of drinking, n (%) | ||||
no | 92 (18.737) | 46 (21.801) | 1.219 | 0.544 |
drinking every week < 70 g | 269 (54.786) | 107 (50.711) | ||
drinking every week ≥ 70 g/ years of drinking ≥ 10 years | 130 (26.477) | 58 (27.488) | ||
history of sugary diet, n (%) | ||||
no | 326 (66.395) | 151 (71.564) | 1.81 | 0.178 |
yes | 165 (33.605) | 60 (28.436) | ||
history of high purine diet, n (%) | ||||
no | 218 (44.399) | 80 (37.915) | 2.54 | 0.111 |
yes | 273 (55.601) | 131 (62.085) | ||
history of high altitude residence, n (%) | ||||
no | 404 (82.281) | 177 (83.886) | 0.267 | 0.606 |
yes | 87 (17.719) | 34 (16.114) | ||
history of hypertension, n (%) | ||||
no | 400 (81.466) | 159 (75.355) | 3.398 | 0.065 |
yes | 91 (18.534) | 52 (24.645) | ||
history of diabetes, n (%) | ||||
no | 474 (96.538) | 202 (95.735) | 0.267 | 0.605 |
yes | 17 (3.462) | 9 (4.265) | ||
history of hyperlipidemia, n (%) | ||||
no | 311 (63.469) | 131 (62.085) | 0.121 | 0.728 |
yes | 179 (36.531) | 80 (37.915) | ||
history of kidney stones, n (%) | ||||
no | 376 (76.578) | 156 (73.934) | 0.562 | 0.453 |
yes | 115 (23.422) | 55 (26.066) | ||
history of kidney crystallization, n (%) | ||||
no | 441 (89.817) | 182 (86.256) | 1.874 | 0.171 |
yes | 50 (10.183) | 29 (13.744) | ||
family history of gout, n (%) | ||||
no | 404 (82.281) | 181 (85.782) | 1.302 | 0.254 |
yes | 87 (17.719) | 30 (14.218) | ||
polyjoint involvement (joints), n (%) | ||||
<3 | 275 (56.008) | 114 (54.028) | 0.234 | 0.628 |
≥3 | 216 (43.992) | 97 (45.972) | ||
tophus, n (%) | ||||
no | 387 (78.819) | 157 (74.408) | 1.646 | 0.199 |
yes | 104 (21.181) | 54 (25.592) | ||
sex, n (%) | ||||
no | 8 (1.629) | 2 (0.948) | 0.488 | 0.485 |
yes | 483 (98.371) | 209 (99.052) | ||
compliance of ULT, n (%) | ||||
MPR < 60% | 230 (46.843) | 96 (45.498) | 0.107 | 0.743 |
MPR ≥ 60% | 261 (53.157) | 115 (54.502) | ||
urine specific gravity, median [IQR] | 1.014 [1.011, 1.018] | 1.015 [1.011, 1.020] | −1.577 | 0.114 |
Urine Ph, median [IQR] | 6.000 [5.500, 6.000] | 5.500 [5.500, 6.000] | 0.998 | 0.304 |
CysC, median [IQR] | 1.010 [0.870, 1.210] | 1.020 [0.890, 1.210] | −1.031 | 0.303 |
GLOB, median [IQR] | 32.400 [29.500, 35.100] | 31.500 [29.000, 35.000] | 1.293 | 0.196 |
ALB, median [IQR] | 46.100 [43.600, 48.600] | 45.600 [43.500, 48.300] | 0.594 | 0.552 |
AST, median [IQR] | 27.000 [22.000, 35.000] | 26.000 [20.000, 34.100] | 1.579 | 0.114 |
ALT, median [IQR] | 32.000 [21.000, 49.600] | 31.000 [20.000, 47.000] | 0.961 | 0.337 |
Crea, median [IQR] | 82.500 [73.700, 92.900] | 83.500 [74.700, 95.000] | −0.855 | 0.393 |
Urea, median [IQR] | 4.740 [3.780, 5.700] | 4.700 [3.750, 5.840] | 0.022 | 0.983 |
UA, median [IQR] | 527.100 [434.300, 595.900] | 507.000 [417.600, 593.300] | 1.053 | 0.293 |
PDW, median [IQR] | 16.500 [16.200, 16.800] | 16.500 [16.100, 16.700] | 1.882 | 0.059 |
PCT, median [IQR] | 0.231 [0.202, 0.272] | 0.238 [0.199, 0.273] | 0.107 | 0.915 |
MPV, median [IQR] | 11.200 [10.100, 12.600] | 11.300 [10.200, 12.700] | −0.446 | 0.656 |
PLT, median [IQR] | 204.000 [166.000, 249.000] | 206.000 [164.000, 245.000] | −0.027 | 0.978 |
MCHC, median [IQR] | 331.000 [323.000, 337.000] | 330.000 [322.000, 339.000] | 0.04 | 0.968 |
MCV, median [IQR] | 92.000 [89.700, 94.400] | 91.500 [89.300, 94.500] | 0.547 | 0.584 |
HCT, median [IQR] | 0.462 [0.435, 0.485] | 0.456 [0.428, 0.479] | 1.844 | 0.065 |
HGB, median [IQR] | 153.000 [143.000, 161.000] | 151.000 [139.000, 160.000] | 1.549 | 0.121 |
RBC, median [IQR] | 5.040 [4.710, 5.350] | 4.990 [4.660, 5.340] | 1.139 | 0.255 |
MO, median [IQR] | 0.440 [0.350, 0.580] | 0.450 [0.340, 0.580] | −0.138 | 0.891 |
LY, median [IQR] | 1.930 [1.570, 2.410] | 2.000 [1.590, 2.530] | −0.721 | 0.471 |
GR, median [IQR] | 4.550 [3.690, 6.230] | 4.600 [3.420, 6.420] | 0.135 | 0.893 |
WBC, median [IQR] | 7.380 [6.190, 9.090] | 7.710 [6.090, 9.260] | −0.371 | 0.711 |
ESR, median [IQR] | 13.000 [5.000, 26.000] | 13.000 [6.000, 29.000] | 0.159 | 0.874 |
eGFR, median [IQR] | 61.149 [49.171, 72.686] | 58.768 [47.969, 70.451] | 1.541 | 0.123 |
course of disease, median [IQR] | 48.000 [24.000, 96.000] | 60.000 [24.000, 108.000] | −1.171 | 0.241 |
BMI, median [IQR] | 25.687 [23.459, 27.682] | 25.712 [23.437, 27.682] | −0.205 | 0.838 |
Variable | R | SE | Z | p | OR (95% CI) |
---|---|---|---|---|---|
sex | 16.646 | 593.391 | 0.028 | 0.978 | 16,956,319.853 (-) |
compliance of ULT | −1.53 | 0.251 | −6.104 | <0.001 | 0.217 (0.131–0.35) |
annual attack frequency (>12 times) | 0.848 | 0.273 | 3.1 | 0.002 | 2.334 (1.365–3.996) |
annual attack frequency (6–12 times) | −0.156 | 0.339 | −0.461 | 0.644 | 0.855 (0.434–1.642) |
history of drinking (drinking ≥ 70 g per week/drinking years ≥ 10 years), | 0.819 | 0.33 | 2.481 | 0.013 | 2.268 (1.198–4.386) |
history of drinking (drinking < 70 g per week) | −0.632 | 0.328 | −1.929 | 0.054 | 0.532 (0.281–1.017) |
family history of gout | 0.824 | 0.291 | 2.83 | 0.005 | 2.279 (1.285–4.033) |
polyjoint involvement | 1.288 | 0.256 | 5.028 | <0.001 | 3.624 (2.209–6.041) |
course of disease | 0.009 | 0.002 | 4.858 | <0.001 | 1.009 (1.005–1.012) |
BMI | −0.084 | 0.038 | −2.242 | 0.025 | 0.919 (0.853–0.989) |
ESR | 0.013 | 0.006 | 2.371 | 0.018 | 1.013 (1.002–1.025) |
eGFR | −0.024 | 0.007 | −3.333 | 0.001 | 0.977 (0.963–0.99) |
UA | 0.001 | 0.001 | 1.515 | 0.13 | 1.001 (1–1.1003) |
(Intercept) | −16.443 | 593.392 | −0.028 | 0.978 | 0 (-) |
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Lei, T.; Guo, J.; Wang, P.; Zhang, Z.; Niu, S.; Zhang, Q.; Qing, Y. Establishment and Validation of Predictive Model of Tophus in Gout Patients. J. Clin. Med. 2023, 12, 1755. https://doi.org/10.3390/jcm12051755
Lei T, Guo J, Wang P, Zhang Z, Niu S, Zhang Q, Qing Y. Establishment and Validation of Predictive Model of Tophus in Gout Patients. Journal of Clinical Medicine. 2023; 12(5):1755. https://doi.org/10.3390/jcm12051755
Chicago/Turabian StyleLei, Tianyi, Jianwei Guo, Peng Wang, Zeng Zhang, Shaowei Niu, Quanbo Zhang, and Yufeng Qing. 2023. "Establishment and Validation of Predictive Model of Tophus in Gout Patients" Journal of Clinical Medicine 12, no. 5: 1755. https://doi.org/10.3390/jcm12051755