溃疡性结肠炎患者PNI与疾病活动性的相关性研究
A Study of the Correlation between PNI and Disease Activity in Patients with UC
DOI: 10.12677/acm.2025.152525, PDF, HTML, XML,   
作者: 苏 芮:河北省人民医院老年消化科,河北 石家庄;河北医科大学研究生学院,河北 石家庄;赵 洋:河北医科大学研究生学院,河北 石家庄;王宇博, 白 云*:河北省人民医院老年消化科,河北 石家庄
关键词: 溃疡性结肠炎预后营养指数疾病活动度Ulcerative Colitis Prognostic Nutritional Index Disease Activity
摘要: 目的:探讨预后营养指数(prognostic nutritional index, PNI)与溃疡性结肠炎(ulcerative colitis, UC)患者疾病活动度的相关性。方法:回顾性分析2016年9月至2024年5月期间于河北省人民医院首次明确诊断为UC的患者117例。收集患者的基本信息、临床症状、实验室检查及内镜检查等结果。根据改良Mayo评分系统评估患者的疾病活动性。比较不同严重程度UC患者之间PNI、中性粒细胞–淋巴细胞比值(neutrophil to lymphocyte ratio, NLR)、血小板–淋巴细胞比值(platelet to lymphocyte ratio, PLR)、淋巴细胞–单核细胞比值(lymphocyte to monocyte ratio, LMR)、全身免疫炎症指数(systemic immune-inflammation index, SII)的差异,并进行上述指标分别与Mayo评分的相关性分析,应用受试者工作特征(receiver operating characteristic, ROC)曲线评估上述指标对UC活动的预测价值。结果:UC不同严重程度分组之间的PNI存在差异(P < 0.001)。PNI与UC患者Mayo评分呈负相关(P < 0.001)。受试者工作特征曲线分析结果显示,PNI对预测UC严重程度有一定价值,预测中重度活动及重度活动时PNI的最佳截断值分别为47.22、42.00,敏感性分别为81.82%、90.91%,特异性分别为75.00%、82.11%。结论:PNI水平与UC疾病活动性密切相关,可能是用于预测UC疾病活动的潜在指标。
Abstract: Objective: To investigate the correlation between the Prognostic Nutritional Index (PNI) and disease activity in patients with Ulcerative Colitis (UC). Methods: A retrospective analysis was conducted on 117 patients who were first diagnosed with UC at Hebei General Hospital between September 2016 and May 2024. Data collected included patient demographics, clinical manifestations, laboratory tests, and endoscopic findings. Disease activity was assessed using the modified Mayo score. The Prognostic Nutritional Index (PNI), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and systemic immune inflammation index (SII) were compared across different severities of UC. Correlations between these biomarkers and Mayo scores were evaluated, and receiver operating characteristic (ROC) curves were generated to assess the predictive value of these indices for UC activity. Results: The differences in PNI across groups with varying disease severities were statistically significant (P < 0.001). Furthermore, PNI demonstrated a negative correlation with Mayo scores (P < 0.001). ROC curve analysis suggested that PNI is a useful predictor of UC severity, with optimal cutoffs of 47.22 and 42.00 for predicting moderate-to-severe and severe disease activity, respectively. The sensitivities at these thresholds were 81.82% and 90.91%, with specificities of 75.00% and 82.11%, respectively. Conclusion: PNI levels are closely related to UC disease activity and may serve as a potential indicator for predicting UC activity.
文章引用:苏芮, 赵洋, 王宇博, 白云. 溃疡性结肠炎患者PNI与疾病活动性的相关性研究[J]. 临床医学进展, 2025, 15(2): 1681-1689. https://doi.org/10.12677/acm.2025.152525

1. 引言

炎症性肠病(inflammatory bowel disease, IBD)是一种慢性非特异性肠道炎性疾病,包括克罗恩病(Crohn’s disease, CD)、溃疡性结肠炎(ulcerative colitis, UC)、未分类结肠炎和不确定性结肠炎。2023年全球溃疡性结肠炎的患病率估计为 500 万例,并且全球的发病率呈上升趋势[1],UC已成为全球公共卫生挑战。然而,确切的病因尚不清楚,被认为是遗传、环境、微生物和免疫因素之间复杂相互作用的结果。UC病程长,表现为腹泻、血便和腹痛,临床上常反复出现复发和缓解,严重影响患者的生活质量。UC患者预期寿命较低,患结肠切除术和结直肠癌的风险增加[2]。因此,早期发现UC的疾病活动性,及时治疗对改善预后和预防并发症至关重要。

内镜检查被认为是诊断和评估UC患者疾病活动的金标准,然而内镜检查属于侵入性检查,常使患者感到不适,且费用昂贵,可能会增加UC活动复发的风险,并发生肠穿孔等不良事件。许多患者不愿接受频繁的内镜检查,特别是当症状较轻时,使得内镜检查不适合用于频繁、长期监测UC。因此,需要更多的研究来寻找一种高效、经济且易于获得的生物标志物用于临床实践。粪便钙卫蛋白是一种源自结肠粘膜中性粒细胞的钙结合蛋白,是评价UC活动性的关键生物标志物。据报道,粪便钙卫蛋白可用于各种情况,如IBD诊断、与内镜严重程度的相关性、治疗效果评估和复发预测[3]。然而,对于一些患者来说,基于粪便的测试可能不是他们的首选,可能与不愿意收集和处理粪便样本或成本高有关。因此,快速、方便、廉价、标准化和可重复的血液检测可能是大多数需要长期监测的患者的首选。常用于测量UC疾病活动度的临床标志物包括WBC、CRP和ESR,然而这些标志物并没有表现出足够的特异性和敏感性[4]

研究表明炎症和营养状况与IBD的起始和进展阶段密切相关[5]。预后营养指数(prognostic nutritional index, PNI)是由Onodera等人开发的简单指数[6],根据外周血中的白蛋白水平和总淋巴细胞计数计算,反映免疫、炎症和营养状况。据报道,PNI与各种疾病的不良结局显著相关,PNI是癌症、卒中、心脏病、失代偿期肝硬化、慢性肾病、慢性阻塞性肺病急性加重、脓毒症、COVID-19和自身免疫性疾病患者的独立预后预测因子[7]。本研究旨在探索PNI在活动期UC患者及缓解期UC患者之间的差异,评估PNI与疾病活动性之间的关系,探索PNI对疾病活动的预测价值,并与目前研究较多的其他血清学指标进行比较,希望可以为临床判断UC患者病情提供经济实用的参考依据。

2. 资料与方法

2.1. 研究对象

收集2016年9月至2024年5月期间于河北省人民医院首次明确诊断为UC的117例患者作为研究对象,诊断均符合《中国溃疡性结肠炎诊治指南(2023年,西安)》,根据改良Mayo评分系统评估疾病临床活动度,依据蒙特利尔分型判定病变范围。纳入标准:1. 符合以上中国溃疡性结肠炎诊治指南且诊断明确;2. 年龄 ≥ 14周岁;3. 与本次研究相关的临床资料完整:如病史、实验室检查、内镜检查资料。排除标准:1. 年龄 < 14周岁;2. 临床资料不完整;3. 合并恶性肿瘤、血液系统疾病、感染性疾病、急慢性肝肾疾病及其他自身免疫性疾病。

2.2. 研究方法

收集患者的一般资料(性别、年龄、BMI),既往病史,临床表现,内镜检查等。收集患者的血清学指标,包括白细胞计数(WBC)、中性粒细胞计数(NEU)、淋巴细胞(LYM)、单核细胞(MON)、血红蛋白(HBG)、血小板计数(PLT)、白蛋白(Albumin, ALB)、C反应蛋白(C-reactiveprotein, CRP)、血沉(Erythrocyte sedimentation rate, ESR)等。计算PNI、NLR、PLR、LMR、SII。计算公式为:1. PNI = ALB (g/L) + 5 × 总淋巴细胞计数(109/L);2. NLR = 中性粒细胞计数/淋巴细胞计数;3. PLR = 血小板计数/淋巴细胞计数;4. LMR = 淋巴细胞计数/单核细胞计数;5. SII = 血小板计数*中性粒细胞计数/淋巴细胞计数。

2.3. 统计学方法

采用SPSS 25.0和GraphPadPrism 9进行数据分析。计数资料以例数(%)表示,组间比较使用χ2检验。计量资料进行正态性检验,符合正态分布的使用均数 ± 标准差(x ± s)表示,两组间比较使用独立样本t检验,多组间比较使用方差分析,多组数据再进行多重比较;不符合正态分布的使用中位数和四分位间距[M, (P25, P75)]表示,两组间的比较使用Mann-Whitney U检验,多组间比较使用Kruskal-Wallis H检验,多组数据再进行多重比较。采用Spearman相关性分析评估各指标与UC疾病活动性的相关性。使用ROC曲线来评估各指标预测UC严重程度的价值并计算最佳临界值。P < 0.05认为差异有统计学意义。

3. 结果

3.1. 一般资料

本研究共纳入117例UC患者。根据改良Mayo评分系统将UC患者分为活动期及缓解期患者,包括活动期患者104例和缓解期患者13例。患者临床特征见表1

Table 1. Baseline data

1. 基本资料

缓解期(n = 13)

活动期(n = 104)

P

性别(男/女)

8/5

62/42

0.894

年龄(岁)

59.00 (51.00, 65.00)

53.00 (34.25, 64.00)

0.190

BMI (kg/m2)

24.36 ± 3.36

22.67 ± 3.09

0.069

病变范围[n(%)]

直肠(E1)

5 (38.5)

13 (12.5)

0.062

左半结肠(E2)

3 (23.1)

27 (26.0)

全结肠(E3)

5 (38.5)

64 (61.5)

活动期分度[n(%)]

轻度

-

27 (26.0)

-

中度

-

55 (52.9)

-

重度

-

22 (21.2)

-

3.2. 不同严重程度的UC患者结果分析

将UC患者进行分组,各组之间的WBC、NEU、MON、HGB、PLT、ALB、HDL、LDL、CRP、ESR、PNI、NLR、PLR、LMR、SII差异具有统计学意义(P < 0.001)。各组间比较详见表2

Table 2. Comparison of clinical indicators in patients with UC of different severities

2. 不同严重程度的UC患者临床指标比较

缓解期

活动期

F/H

P

轻度

中度

重度

WBC (109/L)

5.96 (4.85, 6.68)

6.11 (4.90, 7.33)

7.66 (5.96, 10.28)*

9.76 (6.92, 13.18)*#

21.44

<0.001

NEU (109/L)

3.63 (2.65, 4.56)

4.02 (2.90, 4.86)

5.79 (3.72, 7.29)*#

7.47 (4.82, 10.63)*#

23.79

<0.001

LYM (109/L)

1.50 (1.40, 2.08)

1.69 (1.31, 2.15)

1.46 (1.24, 1.83)

1.52 (1.21, 1.72)

1.66

0.646

MON (109/L)

0.33 (0.23, 0.40)

0.31 (0.26, 0.39)

0.45 (0.31, 0.64)#

0.56 (0.39,0.76)*#

19.64

<0.001

HGB (g/L)

145.00

(129.00, 147.00)

135.00

(116.00, 145.00)

126.00

(112.00, 136.00)*

110.00

(90.00, 112.75)*#

23.46

<0.001

PLT (109/L)

236.00

(158.50, 253.50)

275.00

(239.00, 307.00)

310.00

(241.00, 368.00)*

362.00

(297.25, 420.00)*#

25.63

<0.001

ALB (g/L)

42.16 ± 3.68

41.15 ± 3.30

36.01 ± 4.28*#

28.01 ± 5.38*#

47.93

<0.001

HDL (mmol/L)

1.20 (1.10, 1.48)

1.14 (1.03, 1.26)

0.95 (0.81, 1.07)*#

0.84 (0.60, 0.96)*#

35.61

<0.001

LDL (mmol/L)

3.41 (2.73, 4.32)

3.29 (2.68, 3.75)

2.35 (2.01, 2.66)*#

1.79 (1.19, 2.71)*#

39.71

<0.001

CRP (mg/L)

0.92 (0.50, 1.53)

3.84 (0.91, 8.21)

19.82 (6.72, 52.20)*#

64.01 (39.72, 114.98)*#

40.72

<0.001

ESR (mm/h)

6.00 (2.50, 9.50)

11.00 (7.00, 19.00)

23.00 (10.00, 34.00)*

37.50 (28.50, 65.50)*#

56.70

<0.001

PNI

50.45 ± 3.85

49.87 ± 4.98

43.86 ± 4.50*#

35.84 ± 6.43*#

39.40

<0.001

NLR

2.22 (1.63, 3.04)

2.28 (1.95, 3.15)

3.64 (2.36, 6.02)*#

4.70 (2.95, 6.88)*#

20.86

<0.001

PLR

129.86

(113.45, 166.70)

168.09

(122.56, 213.19)

200.61

(158.82, 287.27)*

237.69

(199.40, 290.60)*#

22.19

<0.001

LMR

6.04 (3.94, 6.66)

5.19 (4.18, 6.39)

3.56 (2.39, 4.71)*#

3.03 (1.87, 4.26)*#

24.21

<0.001

SII

523.34

(287.70, 695.00)

623.74

(525.63, 753.79)

1177.41

(650.38, 1821.42)*#

1666.37

(1154.31, 2534.64)*#

34.02

<0.001

注:*代表与缓解期相比具有统计学差异,#代表与轻度相比具有统计学差异,代表与中度相比具有统计学差异。

3.3. UC患者临床指标与疾病活动度评分的相关性分析

Spearman相关性分析发现,WBC、NEU、MON、PLT、CRP、ESR、NLR、PLR、SII与UC活动性呈正相关(P < 0.001),HGB、ALB、HDL、LDL、PNI、LMR与UC活动性呈负相关(P < 0.001),详见表3

Table 3. Correlation analysis of UC patient indicators with Mayo score

3. UC患者指标与Mayo评分的相关性分析

Mayo评分

rs

P

WBC (109/L)

0.461

<0.001

NEU (109/L)

0.481

<0.001

LYM (109/L)

−0.095

0.309

MON (109/L)

0.430

<0.001

HGB (g/L)

−0.460

<0.001

PLT (109/L)

0.483

<0.001

ALB (g/L)

−0.752

<0.001

HDL (mmol/L)

−0.577

<0.001

LDL (mmol/L)

−0.586

<0.001

CRP (mg/L)

0.734

<0.001

ESR (mm/h)

0.609

<0.001

PNI

−0.721

<0.001

NLR

0.442

<0.001

PLR

0.448

<0.001

LMR

−0.469

<0.001

SII

0.561

<0.001

3.4. 不同指标对UC疾病活动的预测价值

无论以中重度为事件绘制ROC曲线(图1)还是以重度为事件绘制ROC曲线(图2),结果显示PNI、NLR、PLR、LMR、SII预测UC严重程度均具有统计学意义。PNI的曲线下面积(area under curve, AUC)最大,预测价值高于常用指标NLR、PLR、LMR、SII。预测中重度活动时,PNI临界值为47.22,敏感度及特异度分别为81.82%,75.00%。预测重度活动时,PNI临界值为42.00,敏感度及特异度分别为90.91%,82.11%。

Figure 1. ROC curves of PNI and CBC parameters for predicting moderate to severe UC

1. PNI及CBC参数预测中重度UC的ROC曲线

Figure 2. ROC curves of PNI and CBC parameters for predicting severe UC

2. PNI及CBC参数预测重度UC的ROC曲线

4. 讨论

溃疡性结肠炎(ulcerative colitis, UC)是一种病因不明的慢性炎症性肠病,及时地判断病情对UC的治疗及预后至关重要。血清学标记物相对内镜检查而言无创易获得,得到了广泛关注。血清白蛋白是外周血中众所周知的急性反应蛋白,与全身炎症呈负相关。此外,淋巴细胞减少症是多种自身免疫性疾病的常见表现。因此,可以假设基于血清白蛋白和淋巴细胞计数的PNI,可以预测UC患者的疾病活动性。

PNI由Onodera等于1984首次提出,用于预测营养不良的胃肠道癌症患者的围手术期并发症和死亡率[6]。几十年来,PNI广泛用于评估各种癌症患者的预后。目前认为,PNI能有效反映患者的营养、炎症和免疫状况。在接受IBD手术的患者中,观察到低PNI与术后并发症风险增加之间的相关性。Zhang等[8]发现术前低PNI是接受肠切除术的CD患者术后并发症的预测因子。Bae等[9]评估了PNI在CD术后感染并发症(PIC)发生率方面的临床意义,发现与PNI > 40组相比,PNI ≤ 40组的感染并发症发生率显著更高(32.0%与10.4%,P = 0.001),术前PNI可作为CD患者行肠切除术后发生感染并发症的预测因子。根据Chohno等[10]的一项评价UC患者PNI与手术结局之间相关性的研究,较低的PNI可预测UC患者的预后,PNI可作为决定手术时机和手术方式的有用指标。Okita等[11]发现较低的PNI可能是UC患者行直肠结肠切除–回肠储袋肛门吻合术后感染并发症的重要预测因素。Kato等[12]发现关于UC术后并发症,PNI是晚发性UC组(50岁以后发病)中显示显著性的唯一标志物(OR = 0.872, 95% CI 0.77~0.99, P = 0.03),表明PNI不仅可用于预测早发性UC患者的术后并发症,还可用于预测晚发性UC患者的术后并发症。研究发现PNI可用于评估系统性红斑狼疮患者的疾病活动[13] [14]。Peng等[15]报道基线时的PNI可以作为确定英夫利昔单抗治疗CD患者有效性的预测因子。PNI可识别临床缓解(AUC = 0.633, P = 0.004),最佳临界值为39.2。PNI与CRP、ESR、PLT、CDAI呈显著负相关(P < 0.05),基线时较低的PNI、吸烟史和较高的CDAI是52周时疾病活动性的独立危险因素。Nassri等[16]研究结果表明,与无组织学炎症的患者相比,在活检中有组织学炎症证据的CD患者的PNI降低,ROC分析表明PNI可用于预测组织学活动(AUC = 0.7, P = 0.01),最佳临界值为48.0。然而,目前还没有关于PNI与UC疾病活动相关性的研究。本研究发现PNI在UC患者中缓解期较高(P < 0.001),随疾病活动度增加而降低(P < 0.001)。PNI与改良Mayo评分呈显著负相关(P < 0.001),是预测病情中重度活动及重度活动的良好指标。

血清白蛋白由肝细胞产生,是血浆的重要成分,其水平可反映机体的营养状况。ALB不仅是营养状态的标志物,也是炎症指标,在炎症状态下,白介素(interleukin, IL)-6及肿瘤坏死因子(tumor necrosis factor, TNF)会导致ALB降低[17]。ALB常与疾病炎症情况成反比,IBD处于活动期时,肠道炎症可能会损伤血管内皮,导致粘膜渗漏,并抑制肝脏白蛋白的合成。UC引起的营养不良和吸收不良也会导致低ALB水平[18]。据报道,ALB具有抗氧化作用,可以作为氧化应激/炎症相关疾病的血清生物标志物[19]。有证据表明UC患者的血清ALB与临床结局之间存在关联[20]-[22]。Khan等[21]指出,疾病诊断时低水平的ALB可以作为一个预后指标,在诊断时预测UC的临床病程。Wang等[23]的研究评价了ALB水平与IBD活动的关系,在症状严重程度较高的患者中观察到ALB浓度较低。Nakamura等[24]研究结果表明,ALB > 4.4 g/dL的UC患者的累积临床缓解率高于ALB ≤ 4.4 g/dL的患者,证实血清ALB水平是缓解患者复发的独立预测因素。Fasanmade等[25]报道ALB水平是接受英夫利昔单抗治疗的UC患者临床应答的预测因素。Ishida等[22]研究报告,血清ALB水平可预测他克莫司给药后UC的临床结局。PNI的另一个组成部分,总淋巴细胞计数,被认为是全身炎症状态的有用指标。其次,淋巴细胞计数表明患者的免疫功能,淋巴细胞低下表明机体免疫力不好或有紊乱,从而使患者预后变差。Gil-Borras等[26]发现CD患者的外周B1 a淋巴细胞缺乏与术后并发症有关。Selby等[27]报道UC患者淋巴细胞计数减少可能是由于粘膜浸润所致。Neubauer等[28]发现,UC患者淋巴细胞计数降低可能源于细胞凋亡,这表明免疫系统存在功能障碍。另一方面,UC患者淋巴细胞反应性受损,淋巴细胞功能障碍,无论外周或粘膜水平如何[29]。伴随着UC的发病或进展,淋巴细胞功能出现丧失。肠上皮细胞与周围免疫细胞之间信号转导的异常可能促进炎症性肠病(IBD)的免疫失调[30]。克罗恩病和溃疡性结肠炎的既往研究均检测到外周和粘膜水平存在淋巴细胞功能障碍(淋巴细胞对有丝分裂原植物血凝素的反应性降低) [31]。淋巴细胞向肠道的迁移也可能导致IBD,淋巴细胞亚群被认为是导致IBD溃疡的原因,异常的肠道归巢淋巴细胞通过表达特异性表面受体识别内皮配体,导致过度活跃的免疫应答和肠道损伤[32]

本研究存在一些局限性:首先,作为一项单中心回顾性研究,不同地区UC患者的临床特征和疾病进展可能存在差异,研究结论可能受到选择性偏倚的影响;其次,本研究的样本量较少,未来仍需大规模的随机对照研究进一步验证结论;最后,这项研究没有排除药物治疗对患者血清指标的影响,可能导致研究结果的偏差。

总之,我们的研究表明,UC患者的血清PNI与疾病活动相关,在UC病情评估中有一定的价值,且可作为预测中重度及重度UC的一个新指标,与全血细胞(complete blood count, CBC)参数衍生指标比较,PNI 有较高的预测价值。由于我们的研究存在一定的局限性,未来需要更多的前瞻性研究、更大的队列规模来进一步验证PNI与UC疾病活动的关系。

声 明

本研究通过河北省人民医院伦理委员会的审查,并严格按照伦理委员会标准执行,本研究已获得豁免知情同意许可。

NOTES

*通讯作者。

参考文献

[1] Le Berre, C., Honap, S. and Peyrin-Biroulet, L. (2023) Ulcerative Colitis. The Lancet, 402, 571-584.
https://doi.org/10.1016/s0140-6736(23)00966-2
[2] Gros, B. and Kaplan, G.G. (2023) Ulcerative Colitis in Adults. JAMA, 330, 951-965.
https://doi.org/10.1001/jama.2023.15389
[3] Caviglia, G.P., Ribaldone, D.G., Rosso, C., Saracco, G.M., Astegiano, M. and Pellicano, R. (2018) Fecal Calprotectin: Beyond Intestinal Organic Diseases. Panminerva Medica, 60, 29-34.
https://doi.org/10.23736/s0031-0808.18.03405-5
[4] Liu, T., Qin, Z., Yang, Z. and Feng, X. (2024) Predictive Value of MHR and NLR for Ulcerative Colitis Disease Activity. International Journal of General Medicine, 17, 685-692.
https://doi.org/10.2147/ijgm.s446723
[5] Mentella, M.C., Scaldaferri, F., Pizzoferrato, M., Gasbarrini, A. and Miggiano, G.A.D. (2020) Nutrition, IBD and Gut Microbiota: A Review. Nutrients, 12, Article No. 944.
https://doi.org/10.3390/nu12040944
[6] Onodera, T., Goseki, N. and Kosaki, G. (1984) Prognostic Nutritional Index in Gastrointestinal Surgery of Malnourished Cancer Patients. Nihon Geka Gakkai Zasshi, 85, 1001-1005
[7] Xie, Y., He, C. and Wang, W. (2023) Prognostic Nutritional Index: A Potential Biomarker for Predicting the Prognosis of Decompensated Liver Cirrhosis. Frontiers in Nutrition, 9, Article ID: 1092059.
https://doi.org/10.3389/fnut.2022.1092059
[8] Zhang, C., Zhang, T., Shen, Z., Zhong, J. and Wang, Z. (2023) Preoperative Prognostic Nutritional Index and Nomogram for Predicting the Risk of Postoperative Complications in Patients with Crohn’s Disease. Clinical and Translational Gastroenterology, 14, e00563.
https://doi.org/10.14309/ctg.0000000000000563
[9] Bae, H.W., Lee, Y.J., Park, M.Y., Yang, S.Y., Han, Y.D., Cho, M.S., et al. (2024) Clinical Significance of Prognostic Nutrition Index in Patients with Crohn’s Disease after Primary Bowel Resection. Yonsei Medical Journal, 65, 380-388.
https://doi.org/10.3349/ymj.2023.0279
[10] Chohno, T., Uchino, M., Sasaki, H., Bando, T., Takesue, Y. and Ikeuchi, H. (2017) Associations between the Prognostic Nutritional Index and Morbidity/mortality during Intestinal Resection in Patients with Ulcerative Colitis. World Journal of Surgery, 42, 1949-1959.
https://doi.org/10.1007/s00268-017-4411-y
[11] Okita, Y., Araki, T., Okugawa, Y., Kondo, S., Fujikawa, H., Hiro, J., et al. (2019) The Prognostic Nutritional Index for Postoperative Infectious Complication in Patients with Ulcerative Colitis Undergoing Proctectomy with Ileal Pouch-Anal Anastomosis Following Subtotal Colectomy. Journal of the Anus, Rectum and Colon, 3, 91-97.
https://doi.org/10.23922/jarc.2018-032
[12] Kato, H. (2023) Correction: The Prognostic Nutritional Index Is a Predictive Marker for Postoperative Complications in Patients with Late‐Onset Ulcerative Colitis. World Journal of Surgery, 47, 2876-2876.
https://doi.org/10.1007/s00268-023-07125-y
[13] Zhao, H., Huang, Z., Wang, S., Fu, P., Fu, B., Guo, Y., et al. (2024) Using Combination of Albumin to Fibrinogen Ratio and Prognostic Nutritional Index Model for Predicting Disease Activity in Patients with Systemic Lupus Erythematosus. Lupus, 33, 490-501.
https://doi.org/10.1177/09612033241238505
[14] Correa-Rodríguez, M., Pocovi-Gerardino, G., Callejas-Rubio, J., Fernández, R.R., Martín-Amada, M., Cruz-Caparros, M., et al. (2019) The Prognostic Nutritional Index and Nutritional Risk Index Are Associated with Disease Activity in Patients with Systemic Lupus Erythematosus. Nutrients, 11, Article No. 638.
https://doi.org/10.3390/nu11030638
[15] Peng, Z., Xu, D., Li, Y., Liu, X., Li, F. and Peng, Y. (2023) A Novel Role of Prognostic Nutritional Index in Predicting the Effectiveness of Infliximab in Crohn’s Disease. Annals of Medicine, 55, Article ID: 2236011.
https://doi.org/10.1080/07853890.2023.2236011
[16] Nassri, A., Muftah, M., Nassri, R., Fialho, A., Fialho, A., Ribeiro, B., et al. (2020) Novel Inflammatory-Nutritional Biomarkers as Predictors of Histological Activity in Crohn’s Disease. Clinical Laboratory, 66, 7.
https://doi.org/10.7754/clin.lab.2019.190816
[17] Cabrerizo, S., Cuadras, D., Gomez-Busto, F., Artaza-Artabe, I., Marín-Ciancas, F. and Malafarina, V. (2015) Serum Albumin and Health in Older People: Review and Meta Analysis. Maturitas, 81, 17-27.
https://doi.org/10.1016/j.maturitas.2015.02.009
[18] 董莎莎. 血清CRP/ALB比值与溃疡性结肠炎疾病活动度的相关性研究[D]: [硕士学位论文]. 长春: 吉林大学, 2022.
[19] Das, S., Maras, J.S., Hussain, M.S., Sharma, S., David, P., Sukriti, S., et al. (2016) Hyperoxidized Albumin Modulates Neutrophils to Induce Oxidative Stress and Inflammation in Severe Alcoholic Hepatitis. Hepatology, 65, 631-646.
https://doi.org/10.1002/hep.28897
[20] Uchihara, M., Kato, J., Tsuda, S., Yoshida, T., Maekita, T., Iguchi, M., et al. (2017) Blood Biomarkers Reflect Integration of Severity and Extent of Endoscopic Inflammation in Ulcerative Colitis. JGH Open, 1, 98-104.
https://doi.org/10.1002/jgh3.12017
[21] Khan, N., Patel, D., Shah, Y., Trivedi, C. and Yang, Y. (2017) Albumin as a Prognostic Marker for Ulcerative Colitis. World Journal of Gastroenterology, 23, 8008-8016.
https://doi.org/10.3748/wjg.v23.i45.8008
[22] Ishida, N., Miyazu, T., Tamura, S., Tani, S., Yamade, M., Iwaizumi, M., et al. (2021) Early Serum Albumin Changes in Patients with Ulcerative Colitis Treated with Tacrolimus Will Predict Clinical Outcome. World Journal of Gastroenterology, 27, 3109-3120.
https://doi.org/10.3748/wjg.v27.i22.3109
[23] Wang, Y., Li, C., Wang, W., Wang, J., Li, J., Qian, S., et al. (2022) Serum Albumin to Globulin Ratio Is Associated with the Presence and Severity of Inflammatory Bowel Disease. Journal of Inflammation Research, 15, 1907-1920.
https://doi.org/10.2147/jir.s347161
[24] Nakamura, N., Honzawa, Y., Nishimon, S., Sano, Y., Tokutomi, Y., Ito, Y., et al. (2023) Combined Serum Albumin, Fecal Immunochemical Test, and Leucine-Rich Alpha-2 Glycoprotein Levels for Predicting Prognosis in Remitting Patients with Ulcerative Colitis. Scientific Reports, 13, Article No. 13863.
https://doi.org/10.1038/s41598-023-41137-x
[25] Fasanmade, A.A., Adedokun, O.J., Olson, A., Strauss, R. and Davis, H.M. (2010) Serum Albumin Concentration: A Predictive Factor of Infliximab Pharmacokinetics and Clinical Response in Patients with Ulcerative Colitis. Int. Journal of Clinical Pharmacology and Therapeutics, 48, 297-308.
https://doi.org/10.5414/cpp48297
[26] Gil-Borras, R., García-Ballesteros, C., Benet-Campos, C., Catalán-Serra, I., López-Chuliá, F., Cuéllar, C., et al. (2018) B1a Lymphocytes (CD19+CD5+) Deficiency in Patients with Crohn’s Disease and Its Relation with Disease Severity. Digestive Diseases, 36, 194-201.
https://doi.org/10.1159/000486893
[27] Selby, W.S. and Jewell, D.P. (1983) T Lymphocyte Subsets in Inflammatory Bowel Disease: Peripheral Blood. Gut, 24, 99-105.
https://doi.org/10.1136/gut.24.2.99
[28] Neubauer, K., Woźniak-Stolarska, B. and Krzystek-Korpacka, M. (2018) Peripheral Lymphocytes of Patients with Inflammatory Bowel Disease Have Altered Concentrations of Key Apoptosis Players: Preliminary Results. BioMed Research International, 2018, Article ID: 4961753.
https://doi.org/10.1155/2018/4961753
[29] Sachar, D.B., Taub, R.N., Brown, S.M., Present, D.H., Korelitz, B.I. and Janowitz, H.D. (1973) Impaired Lymphocyte Responsiveness in Inflammatory Bowel Disease. Gastroenterology, 64, 203-209.
https://doi.org/10.1016/s0016-5085(73)80030-7
[30] Martini, E., Krug, S.M., Siegmund, B., Neurath, M.F. and Becker, C. (2017) Mend Your Fences: The Epithelial Barrier and Its Relationship with Mucosal Immunity in Inflammatory Bowel Disease. Cellular and Molecular Gastroenterology and Hepatology, 4, 33-46.
https://doi.org/10.1016/j.jcmgh.2017.03.007
[31] Fu, W., Fu, H., Ye, W., Han, Y., Liu, X., Zhu, S., et al. (2021) Peripheral Blood Neutrophil-to-Lymphocyte Ratio in Inflammatory Bowel Disease and Disease Activity: A Meta-Analysis. International Immunopharmacology, 101, Article ID: 108235.
https://doi.org/10.1016/j.intimp.2021.108235
[32] Giuffrida, P., Corazza, G.R. and Di Sabatino, A. (2017) Old and New Lymphocyte Players in Inflammatory Bowel Disease. Digestive Diseases and Sciences, 63, 277-288.
https://doi.org/10.1007/s10620-017-4892-4