南方医科大学学报 ›› 2025, Vol. 45 ›› Issue (2): 379-386.doi: 10.12122/j.issn.1673-4254.2025.02.19
• • 上一篇
唐天威1(), 李路安2, 陈源汉2, 张丽2, 徐丽霞2, 李志莲2, 冯仲林2, 张辉林3, 华瑞芳3, 叶智明2, 梁馨苓2, 李锐钊1(
)
收稿日期:
2024-08-17
出版日期:
2025-02-20
发布日期:
2025-03-03
通讯作者:
李锐钊
E-mail:tw122666@163.com;liruizhao1979@126.com
作者简介:
唐天威,在读硕士研究生,E-mail: tw122666@163.com
基金资助:
Tianwei TANG1(), Luan LI2, Yuanhan CHEN2, Li ZHANG2, Lixia XU2, Zhilian LI2, Zhonglin FENG2, Huilin ZHANG3, Ruifang HUA3, Zhiming YE2, Xinling LIANG2, Ruizhao LI1(
)
Received:
2024-08-17
Online:
2025-02-20
Published:
2025-03-03
Contact:
Ruizhao LI
E-mail:tw122666@163.com;liruizhao1979@126.com
摘要:
目的 探讨血清胱抑素C(CysC)水平评估IgA肾病(IgAN)患者肾脏预后的价值。 方法 回顾性收集2014年1月~2018年12月在广东省人民医院通过肾穿刺活检诊断为IgAN患者的临床资料。根据基线血清CysC值将患者分为高血清CysC组(CysC>1.03 mg/L)和正常血清CysC组(CysC≤1.03 mg/L)。估算肾小球滤过率(eGFR)下降≥50%,和/或进入终末期肾病(ESRD)作为肾脏不良预后的随访复合终点事件。采用lasso回归和多因素Cox回归筛选独立危险因素,并基于这些独立危险因素构建多因素Cox回归预测模型。采用Kaplan⁃Meier生存分析比较两组之间的肾脏生存率差异。平滑曲线拟合及阈值效应探究血清CysC水平与结局之间的关系。通过Bootstrap法内部验证预测模型并使用一致性指数、校正曲线、受试者工作特征(ROC)曲线及其曲线下面积(AUC)对模型预测效能进行评价,并通过列线图可视化。 结果 本研究共纳入356例IgAN患者,平均随访时间为(4.65±0.93)年,74例发生肾脏不良预后的复合终点事件。高血清CysC被筛选为IgAN肾脏不良预后的独立危险因素(HR=2.142,95% CI:1.222~3.755),且血清CysC水平高的患者肾脏生存率较低(Log-rank检验χ2=47.970,P<0.001)。阈值效应分析显示,当患者血清CysC≤2.12 mg/L时,血清CysC水平越高,肾脏不良预后风险越大(β=3.487,95% CI:2.561~4.413,P<0.001);当患者的血清CysC>2.12 mg/L时,肾脏不良预后的发生风险仍有上升但差异无统计学意义(β=0.676,95% CI:-0.642~1.995,P=0.315)。基于血清 CysC及其他3个独立危险因素构建的多因素Cox回归预测模型经内部验证表现良好,其一致性指数为0.873(95% CI:0.839~0.907),AUC为0.909(95% CI:0.873~0.945)。 结论 血清CysC水平与IgAN患者肾脏预后相关,高血清CysC是IgA肾病不良预后的独立危险因素。
唐天威, 李路安, 陈源汉, 张丽, 徐丽霞, 李志莲, 冯仲林, 张辉林, 华瑞芳, 叶智明, 梁馨苓, 李锐钊. 高血清胱抑素C水平是IgA肾病不良预后的独立危险因素[J]. 南方医科大学学报, 2025, 45(2): 379-386.
Tianwei TANG, Luan LI, Yuanhan CHEN, Li ZHANG, Lixia XU, Zhilian LI, Zhonglin FENG, Huilin ZHANG, Ruifang HUA, Zhiming YE, Xinling LIANG, Ruizhao LI. High serum cystatin C is an independent risk factor for poor renal prognosis in IgA nephropathy[J]. Journal of Southern Medical University, 2025, 45(2): 379-386.
Pathological parameters and score | Content |
---|---|
Mesangial hypercellularity (M) | |
M0 | Mesangial score ≤0.5 |
M1 | Mesangial score >0.5 |
Endocapillary hypercellularity (E) | |
E0 | Absent |
E1 | Present |
Segmental glomerulosclerosis (S) | |
S0 | Absent |
S1 | Present |
Tubular atrophy/interstitial fibrosis (T) | |
T0 | 0-25% |
T1 | 26%-50% |
T2 | >50% |
Cellular/fibrocellular crescents (C) | |
C0 | Absent |
C1 | Crescents in a least 1 glomerulus and <25% of glomeruli |
C2 | Crescents in ≥25% of glomeruli |
表1 IgAN牛津分型(MEST-C评分)
Tab.1 Oxford Classification of IgA nephropathy (MEST-C score)
Pathological parameters and score | Content |
---|---|
Mesangial hypercellularity (M) | |
M0 | Mesangial score ≤0.5 |
M1 | Mesangial score >0.5 |
Endocapillary hypercellularity (E) | |
E0 | Absent |
E1 | Present |
Segmental glomerulosclerosis (S) | |
S0 | Absent |
S1 | Present |
Tubular atrophy/interstitial fibrosis (T) | |
T0 | 0-25% |
T1 | 26%-50% |
T2 | >50% |
Cellular/fibrocellular crescents (C) | |
C0 | Absent |
C1 | Crescents in a least 1 glomerulus and <25% of glomeruli |
C2 | Crescents in ≥25% of glomeruli |
Variables | Overall (n=356) | Normal serum CysC group (n=130) | High serum CysC group (n=226) | t/Z/χ2 | P |
---|---|---|---|---|---|
Age (year) | 36 (29, 45) | 32 (26, 39) | 39 (32, 47) | -5.245 | <0.001 |
Male [n (%)] | 149 (41.9) | 33(25.4) | 116 (51.3) | 21.770 | <0.001 |
Hypertension [n (%)] | 139 (39.0) | 28 (21.5) | 111 (49.1) | 25.224 | <0.001 |
Hyperuricaemia [n (%)] | 31 ( 8.7) | 5 (3.8) | 26 (11.5) | 5.163 | 0.023 |
Mean arterial pressure (mmHg) | 100.34 (91, 112.34) | 94.67 (87.33, 104.33) | 105 (94.67, 115.25) | -5.989 | <0.001 |
Weight (kg) | 59.8 (52.39, 68) | 58 (51, 65.81) | 61.48 (53.78, 69.48) | -2.766 | 0.006 |
Serum uric acid (μmol/L) | 423.5 (342, 517.5) | 345 (293, 409) | 470.1 (392.25, 565) | -9.559 | <0.001 |
Serum sodium (mmol/L) | 139 (137.7, 140.5) | 138.9 (137.7, 140.2) | 139.1 (137.8, 140.7) | -0.794 | 0.427 |
Serum potassium (mmol/L) | 3.72 (3.49, 3.95) | 3.58 (3.4, 3.77) | 3.84 (3.58, 4.07) | -6.489 | <0.001 |
Serum albumin (g/L) | 36.7 (33.78, 39.8) | 37.35 (34.53, 40.78) | 36.3 (32.4, 39.1) | 3.049 | 0.002 |
Triglyceride (mmol/L) | 1.59 (1.11, 2.49) | 1.38 (0.98, 2.02) | 1.78 (1.25, 2.57) | -3.577 | <0.001 |
Cholesterol (mmol/L) | 5.3 (4.4, 6.04) | 5.15 (4.25, 5.68) | 5.36 (4.56, 6.29) | -2.544 | 0.011 |
Low density lipoprotein cholesterol (mmol/L) | 3.19 (2.62, 3.89) | 3.1 (2.49, 3.53) | 3.27 (2.65, 4.04) | -2.777 | 0.005 |
High density lipoprotein cholesterol (mmol/L) | 1.15 (0.96, 1.41) | 1.23 (1.01, 1.48) | 1.13 (0.93, 1.38) | 2.306 | 0.021 |
Transferrin (g/L) | 1.96 (1.76, 2.25) | 2.11 (1.85, 2.36) | 1.91 (1.73, 2.17) | 4.300 | <0.001 |
Serum IgA (g/L) | 3.4 (2.5, 4.09) | 3.23 (2.49, 3.79) | 3.47 (2.55, 4.45) | -1.908 | 0.056 |
Serum IgM (g/L) | 1.16 (0.83, 1.68) | 1.21 (0.88, 1.67) | 1.14 (0.8, 1.68) | 1.154 | 0.249 |
Serum IgG (g/L) | 11.5 (9.74, 13.1) | 11.4 (10.1, 12.6) | 11.55 (9.6, 13.5) | -0.551 | 0.582 |
Complement C3 (mg/L) | 878 (773.75, 1010) | 889 (769.25, 1010) | 868 (776.5, 1000) | 0.592 | 0.555 |
Complement C4 (mg/L) | 226 (178, 275) | 215.5 (166.25, 250.5) | 233 (184.5, 284) | -2.971 | 0.003 |
Hemoglobin (g/L) | 124.56±18.02 | 126.68±16.16 | 123.34±18.92 | 1.765 | 0.079 |
White blood cell (×109/L) | 7.48 (6.41, 8.69) | 7.37 (6.31, 8.59) | 7.59 (6.51, 8.75) | -1.049 | 0.295 |
Platelet (×109/L) | 251 (209, 289.25) | 256.5 (218, 296) | 249 (204, 285.75) | 1.685 | 0.092 |
Fibrinogen (g/L) | 3.56 (3.08, 4.31) | 3.31 (2.91, 3.85) | 3.73 (3.16, 4.54) | -4.052 | <0.001 |
D-Dimer(ng/mL) | 330 (270, 472.5) | 290 (270, 390) | 350 (270, 520) | -3.168 | 0.001 |
Hematuria [n (%)] | 151 (42.4) | 78 (60.0) | 73 (32.3) | 24.802 | <0.001 |
24 h urine protein (g) | 1.14 (0.51, 2.16) | 0.70 (0.33, 1.40) | 1.38 (0.69, 2.67) | -5.977 | <0.001 |
eGFR[mL·min-1·(1.73 m2)-1] | 65.62 (39.43, 100.51) | 106.39 (88.53, 119.9) | 44.84 (31.57, 64.36) | 13.664 | <0.001 |
Serum IgA/Complement C3 | 3.68 (2.83, 4.76) | 3.61 (2.75, 4.34) | 3.8 (2.86, 5.09) | -1.785 | 0.074 |
RAAS-inhibitor [n (%)] | 294 (82.6) | 125 (96.2) | 169 (74.8) | 24.752 | <0.001 |
Immunosuppressive agents [n (%)] | 217 (61.0) | 64 (49.2) | 153 (67.7) | 11.064 | 0.001 |
Percentage of global glomerulosclerosis | 0.23 (0.09, 0.46) | 0.1 (0.03, 0.18) | 0.36 (0.17, 0.55) | -9.405 | <0.001 |
M1 [n (%)] | 291 (81.7) | 110 (84.6) | 181 (80.1) | 0.850 | 0.357 |
E1 [n (%)] | 54 (15.2) | 22 (16.9) | 32 (14.2) | 0.299 | 0.585 |
S1 [n (%)] | 167 (46.9) | 49 (37.7) | 118 (52.2) | 6.416 | 0.011 |
T [n (%)] | 92.316 | <0.001 | |||
0 | 209 (58.7) | 119 (91.5) | 90 (39.8) | ||
1 | 91 (25.6) | 10 (7.7) | 81 (35.8) | ||
2 | 56 (15.7) | 1 (0.8) | 55 (24.3) | ||
C [n (%)] | 7.860 | 0.020 | |||
0 | 152 (42.7) | 49 (37.7) | 103 (45.6) | ||
1 | 168 (47.2) | 73 (56.2) | 95 (42.0) | ||
2 | 36 (10.1) | 8 (6.2) | 28 (12.4) |
表2 两组患者的基线资料
Tab.2 Baseline data of the patients with normal and high serum CysC levels
Variables | Overall (n=356) | Normal serum CysC group (n=130) | High serum CysC group (n=226) | t/Z/χ2 | P |
---|---|---|---|---|---|
Age (year) | 36 (29, 45) | 32 (26, 39) | 39 (32, 47) | -5.245 | <0.001 |
Male [n (%)] | 149 (41.9) | 33(25.4) | 116 (51.3) | 21.770 | <0.001 |
Hypertension [n (%)] | 139 (39.0) | 28 (21.5) | 111 (49.1) | 25.224 | <0.001 |
Hyperuricaemia [n (%)] | 31 ( 8.7) | 5 (3.8) | 26 (11.5) | 5.163 | 0.023 |
Mean arterial pressure (mmHg) | 100.34 (91, 112.34) | 94.67 (87.33, 104.33) | 105 (94.67, 115.25) | -5.989 | <0.001 |
Weight (kg) | 59.8 (52.39, 68) | 58 (51, 65.81) | 61.48 (53.78, 69.48) | -2.766 | 0.006 |
Serum uric acid (μmol/L) | 423.5 (342, 517.5) | 345 (293, 409) | 470.1 (392.25, 565) | -9.559 | <0.001 |
Serum sodium (mmol/L) | 139 (137.7, 140.5) | 138.9 (137.7, 140.2) | 139.1 (137.8, 140.7) | -0.794 | 0.427 |
Serum potassium (mmol/L) | 3.72 (3.49, 3.95) | 3.58 (3.4, 3.77) | 3.84 (3.58, 4.07) | -6.489 | <0.001 |
Serum albumin (g/L) | 36.7 (33.78, 39.8) | 37.35 (34.53, 40.78) | 36.3 (32.4, 39.1) | 3.049 | 0.002 |
Triglyceride (mmol/L) | 1.59 (1.11, 2.49) | 1.38 (0.98, 2.02) | 1.78 (1.25, 2.57) | -3.577 | <0.001 |
Cholesterol (mmol/L) | 5.3 (4.4, 6.04) | 5.15 (4.25, 5.68) | 5.36 (4.56, 6.29) | -2.544 | 0.011 |
Low density lipoprotein cholesterol (mmol/L) | 3.19 (2.62, 3.89) | 3.1 (2.49, 3.53) | 3.27 (2.65, 4.04) | -2.777 | 0.005 |
High density lipoprotein cholesterol (mmol/L) | 1.15 (0.96, 1.41) | 1.23 (1.01, 1.48) | 1.13 (0.93, 1.38) | 2.306 | 0.021 |
Transferrin (g/L) | 1.96 (1.76, 2.25) | 2.11 (1.85, 2.36) | 1.91 (1.73, 2.17) | 4.300 | <0.001 |
Serum IgA (g/L) | 3.4 (2.5, 4.09) | 3.23 (2.49, 3.79) | 3.47 (2.55, 4.45) | -1.908 | 0.056 |
Serum IgM (g/L) | 1.16 (0.83, 1.68) | 1.21 (0.88, 1.67) | 1.14 (0.8, 1.68) | 1.154 | 0.249 |
Serum IgG (g/L) | 11.5 (9.74, 13.1) | 11.4 (10.1, 12.6) | 11.55 (9.6, 13.5) | -0.551 | 0.582 |
Complement C3 (mg/L) | 878 (773.75, 1010) | 889 (769.25, 1010) | 868 (776.5, 1000) | 0.592 | 0.555 |
Complement C4 (mg/L) | 226 (178, 275) | 215.5 (166.25, 250.5) | 233 (184.5, 284) | -2.971 | 0.003 |
Hemoglobin (g/L) | 124.56±18.02 | 126.68±16.16 | 123.34±18.92 | 1.765 | 0.079 |
White blood cell (×109/L) | 7.48 (6.41, 8.69) | 7.37 (6.31, 8.59) | 7.59 (6.51, 8.75) | -1.049 | 0.295 |
Platelet (×109/L) | 251 (209, 289.25) | 256.5 (218, 296) | 249 (204, 285.75) | 1.685 | 0.092 |
Fibrinogen (g/L) | 3.56 (3.08, 4.31) | 3.31 (2.91, 3.85) | 3.73 (3.16, 4.54) | -4.052 | <0.001 |
D-Dimer(ng/mL) | 330 (270, 472.5) | 290 (270, 390) | 350 (270, 520) | -3.168 | 0.001 |
Hematuria [n (%)] | 151 (42.4) | 78 (60.0) | 73 (32.3) | 24.802 | <0.001 |
24 h urine protein (g) | 1.14 (0.51, 2.16) | 0.70 (0.33, 1.40) | 1.38 (0.69, 2.67) | -5.977 | <0.001 |
eGFR[mL·min-1·(1.73 m2)-1] | 65.62 (39.43, 100.51) | 106.39 (88.53, 119.9) | 44.84 (31.57, 64.36) | 13.664 | <0.001 |
Serum IgA/Complement C3 | 3.68 (2.83, 4.76) | 3.61 (2.75, 4.34) | 3.8 (2.86, 5.09) | -1.785 | 0.074 |
RAAS-inhibitor [n (%)] | 294 (82.6) | 125 (96.2) | 169 (74.8) | 24.752 | <0.001 |
Immunosuppressive agents [n (%)] | 217 (61.0) | 64 (49.2) | 153 (67.7) | 11.064 | 0.001 |
Percentage of global glomerulosclerosis | 0.23 (0.09, 0.46) | 0.1 (0.03, 0.18) | 0.36 (0.17, 0.55) | -9.405 | <0.001 |
M1 [n (%)] | 291 (81.7) | 110 (84.6) | 181 (80.1) | 0.850 | 0.357 |
E1 [n (%)] | 54 (15.2) | 22 (16.9) | 32 (14.2) | 0.299 | 0.585 |
S1 [n (%)] | 167 (46.9) | 49 (37.7) | 118 (52.2) | 6.416 | 0.011 |
T [n (%)] | 92.316 | <0.001 | |||
0 | 209 (58.7) | 119 (91.5) | 90 (39.8) | ||
1 | 91 (25.6) | 10 (7.7) | 81 (35.8) | ||
2 | 56 (15.7) | 1 (0.8) | 55 (24.3) | ||
C [n (%)] | 7.860 | 0.020 | |||
0 | 152 (42.7) | 49 (37.7) | 103 (45.6) | ||
1 | 168 (47.2) | 73 (56.2) | 95 (42.0) | ||
2 | 36 (10.1) | 8 (6.2) | 28 (12.4) |
图1 Lasso回归模型筛选变量
Fig.1 Variable selection by Lasso regression model. A: Log Lambda versus partial likelihood deviance. B: Log Lambda versus coefficients.
Variables | Lasso regression coefficients | Multivariate Cox regression | |
---|---|---|---|
HR (95% CI) | P | ||
Mean arterial pressure (mmHg) | 4.23×10-3 | 1.015 (1.000-1.031) | 0.048 |
Serum CysC (mg/L) | 6.10×10-1 | 2.142 (1.222-3.755) | 0.008 |
Serum albumin (g/L) | -4.57×10-3 | 0.934 (0.892-0.977) | 0.003 |
24-hour urine protein (g) | 2.88×10-5 | 1.000 (0.999-1.000) | 0.638 |
eGFR[mL·min-1·(1.73 m2)-1] | -5.43×10-3 | 0.984 (0.965-1.003) | 0.107 |
Percentage of global glomerulosclerosis | 1.81×10-2 | 2.077 (0.518-8.327) | 0.302 |
T [n (%)] | 5.10×10-1 | 1.000 (Ref) | |
T1 | 3.416 (1.424-8.192) | 0.006 | |
T2 | 3.408 (1.144-10.150) | 0.028 |
表3 Lasso回归及多因素Cox回归分析IgAN肾脏不良预后的危险因素
Tab.3 Lasso regression and multivariate Cox regression analysis of the risk factors for poor renal prognosis in IgAN
Variables | Lasso regression coefficients | Multivariate Cox regression | |
---|---|---|---|
HR (95% CI) | P | ||
Mean arterial pressure (mmHg) | 4.23×10-3 | 1.015 (1.000-1.031) | 0.048 |
Serum CysC (mg/L) | 6.10×10-1 | 2.142 (1.222-3.755) | 0.008 |
Serum albumin (g/L) | -4.57×10-3 | 0.934 (0.892-0.977) | 0.003 |
24-hour urine protein (g) | 2.88×10-5 | 1.000 (0.999-1.000) | 0.638 |
eGFR[mL·min-1·(1.73 m2)-1] | -5.43×10-3 | 0.984 (0.965-1.003) | 0.107 |
Percentage of global glomerulosclerosis | 1.81×10-2 | 2.077 (0.518-8.327) | 0.302 |
T [n (%)] | 5.10×10-1 | 1.000 (Ref) | |
T1 | 3.416 (1.424-8.192) | 0.006 | |
T2 | 3.408 (1.144-10.150) | 0.028 |
图2 Kaplan⁃Meier生存曲线分析血清CysC对IgAN患者5年肾脏生存率的影响
Fig.2 Kaplan-Meier survival curves for analyzing the effect of serum CysC on 5-year renal survival rate of IgAN patients.
图3 广义加性模型描述血清CysC水平与IgAN肾脏不良预后之间的关系
Fig.3 Generalized additive models demonstrate the relationship between serum CysC level and poor renal prognosis of IgAN.
Threshold effect | β (95% CI) | P |
---|---|---|
Fitting by GAMs | ||
Serum CysC | 2.637 (2.034, 3.240) | <0.001 |
Fitting by two-piecewise GAMs | ||
Inflection point | 2.12 | |
Serum CysC≤2.12 | 3.487 (2.561, 4.413) | <0.001 |
Serum CysC>2.12 | 0.676 (-0.642, 1.995) | 0.315 |
Log likelihood ratio | 0.008 |
表4 血清CysC水平与IgAN肾脏不良预后的阈值效应分析
Tab.4 Threshold effect analysis of serum CysC level and poor renal prognosis of IgAN
Threshold effect | β (95% CI) | P |
---|---|---|
Fitting by GAMs | ||
Serum CysC | 2.637 (2.034, 3.240) | <0.001 |
Fitting by two-piecewise GAMs | ||
Inflection point | 2.12 | |
Serum CysC≤2.12 | 3.487 (2.561, 4.413) | <0.001 |
Serum CysC>2.12 | 0.676 (-0.642, 1.995) | 0.315 |
Log likelihood ratio | 0.008 |
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