Correlation between malignant tumors and serum N-terminal pro-brain natriuretic peptide: a cross-sectional study
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摘要:目的
探讨恶性肿瘤与血清氨基末端脑钠肽前体（N-terminal pro-brain natriuretic peptide, NT-proBNP）的相关性。
方法选择2009年1月1日至2020年12月31日在中国人民解放军总医院第一医学中心心内科住院并行冠脉造影的患者，新近诊断且尚未接受任何抗肿瘤治疗的恶性肿瘤患者共336例（肿瘤组），采用倾向性评分，以性别、年龄为匹配因素，按1∶3的比例匹配1 008例患者（非肿瘤组）。收集患者临床资料，包括年龄、性别、血清NT-proBNP、左心室射血分数（left ventricular ejection fraction, LVEF）、SYNTAX评分、血清肌酐以及肿瘤诊断信息等。根据纳入患者的NT-proBNP四分位数分为4组：低水平组（NT-proBNP≤61.80 pg/mL）、中水平组（61.80 pg/mL＜NT-proBNP≤152.95 pg/mL）、高水平组（152.95 pg/mL＜NT-proBNP≤470.10 pg/mL）以及很高水平组（NT-proBNP＞470.10 pg/mL）。采用有序logistic回归分析患恶性肿瘤与血清NT-proBNP的相关性。
结果共纳入1 344例患者，平均年龄（65.78±9.18）岁，男性1 003例（74.63%），LVEF 60.00%（55.00%, 64.00%），SYNTAX评分（13.84±11.63）分，肌酐 76.60（66.50, 88.88）μmol/L。336例肿瘤患者中，患病人数前3位的肿瘤分别为肺癌（84例, 25.00%）、肠道肿瘤（58例, 17.26%）和胃癌（52例, 15.48%）。肿瘤组患者的NT-proBNP水平显著高于非肿瘤组[208.45（85.75, 601.83）pg/mL vs 134.35（57.18, 430.23）pg/mL, P＜0.001]。有序logistic 回归分析显示，在未经调整的模型中，患恶性肿瘤与NT-proBNP水平较高相关（OR＝1.561, 95%CI 1.538～1.584, P＜0.001）；在校正相关影响因素后，患恶性肿瘤仍与血清NT-proBNP水平较高显著相关（OR = 1.384，95%CI 1.070~1.791, P＝0.013）。
结论恶性肿瘤患者的NT-proBNP水平高于非恶性肿瘤患者，患恶性肿瘤与血清NT-proBNP水平显著相关。
Abstract:ObjectiveTo explore the correlation between malignant tumors and serum N-terminal pro-brain natriuretic peptide (NT-proBNP) levels.
MethodsA total of 336 patients with malignant tumors (cancer group) who were admitted to the Department of Cardiology, Chinese PLA General Hospital and underwent coronary angiography from January 1, 2009 to December 31, 2020, and were newly diagnosed and had not received any anti-tumor treatment were selected. They were matched with 1 008 patients (non-cancer group) in a 1∶3 ratio using propensity score matching based on gender and age. Clinical data of the patients were collected, including age, gender, serum NT-proBNP, left ventricular ejection fraction (LVEF), SYNTAX score, serum creatinine, and tumor diagnosis information. The patients were divided into 4 groups based on the quartiles of NT-proBNP levels: low-level group (NT-proBNP≤61.80 pg/mL), medium-level group (61.80 pg/mL＜NT-proBNP≤152.95 pg/mL), high-level group (152.95 pg/mL＜NT-proBNP≤470.10 pg/mL), and very high-level group (NT-proBNP＞470.10 pg/mL). Ordered logistic regression analysis was used to analyze the correlation between malignant tumors and serum NT-proBNP.
ResultsA total of 1 344 patients were included, with an average age of (65.78±9.18) years old, 1 003 males (74.63%), LVEF of 60.00% (55.00%, 64.00%) , SYNTAX score of (13.84±11.63) points, and creatinine level of 76.60 (66.50, 88.88) μmol/L. Among the 336 cancer patients, the top 3 types of cancer were lung cancer (84 cases, 25.00%), colorectal cancer (58 cases, 17.26%), and gastric cancer (52 cases, 15.48%). The NT-proBNP levels in the cancer group were significantly higher than those in the non-cancer group (208.45[85.75, 601.83] pg/mL vs 134.35[57.18, 430.23] pg/mL, P＜0.001). Ordered logistic regression analysis showed that in the unadjusted model, malignant tumors were significantly associated with higher NT-proBNP levels (OR＝1.561, 95% CI 1.538-1.584, P＜0.001); after adjusting for relevant factors, malignant tumors remained significantly associated with higher serum NT-proBNP levels (OR＝1.384, 95% CI 1.070-1.791, P＝0.013).
ConclusionsNT-proBNP in malignant tumor patients is higher than that in non-malignant tumor patients, and there is a significant correlation between malignant tumors and serum NT-proBNP levels.
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心血管疾病和恶性肿瘤是影响人类健康的两大类疾病。随着世界人口的老龄化，心血管疾病以及恶性肿瘤患者数量不断增加[1-2]。既往观点认为，心血管疾病与肿瘤是两种独立的疾病，其发病机制、临床表现以及预后都存在较大差异。然而，越来越多的研究[3-4]表明，心血管疾病与肿瘤之间存在相关性，且常在同一个体中并存。冠心病患者的恶性肿瘤风险显著高于无冠心病的患者[5]；与非肿瘤人群相比，恶性肿瘤患者发生心血管疾病的风险也明显更高[6]。目前，关于心血管疾病与恶性肿瘤的相关性及其机制的研究较少，但二者并存的情况会给患者带来更多的健康风险和更复杂的临床管理问题。基于此，课题组前期进行了系列研究[7-8]，发现肿瘤与冠脉病变的严重程度显著相关，而且机体炎症水平是影响二者相关性的重要因素。
B型钠尿肽（brain natriuretic peptide, BNP）和氨基末端脑钠肽前体（N-terminal pro-brain natriuretic peptide, NT-proBNP）主要由心室肌细胞合成和分泌。其中，NT-proBNP更稳定，半衰期更长，作为心力衰竭及预后标志物优于BNP[9]。既往研究[10-12]表明，NT-proBNP水平与患者年龄、心功能、肾功能等有关，但关于恶性肿瘤与NT-proBNP的相关性，目前的研究相对较少。本横断面研究观察恶性肿瘤患者与非恶性肿瘤患者血清NT-proBNP水平的差异，并采用有序logistic回归校正年龄、心功能、肾功能等NT-proBNP相关的影响因素，探讨患恶性肿瘤与血清NT-proBNP水平的相关性，进一步为恶性肿瘤与心血管疾病的关联研究提供新的依据。
1. 资料与方法
1.1 研究对象
收集2009年1月1日至2020年12月31日在中国人民解放军总医院第一医学中心心内科因心血管疾病或疑似心血管疾病住院的患者51 928例，肿瘤组纳入新发且尚未经抗肿瘤治疗（如手术治疗、放疗、化疗、靶向治疗、免疫治疗等）的恶性肿瘤患者（n=336）。根据患者的年龄和性别，采用倾向性评分匹配以1∶3的比例随机选择1 008例非肿瘤患者为非肿瘤组。排除标准：（1）严重心律失常；（2）显著结构性心脏病；（3）严重肾功能不全；（4）缺少NT-proBNP等关键信息。研究对象入组流程详见图1。
1.2 临床资料收集
所有住院患者数据均来自中国人民解放军总医院第一医学中心病历系统，收集以下临床资料：（1）患者年龄、性别、体质量指数（body mass index, BMI）、吸烟史、饮酒史等；（2）合并疾病，包括高血压史、糖尿病史、高脂血症史、心律失常病史等；（3）肿瘤的病理诊断信息；（4）实验室检查，包括血红蛋白、血小板计数（PLT）、肌酐、NT-proBNP等，NT-proBNP数据采用患者入院时第1次检测的结果；（5）超声心动图，包括是否存在显著结构性心脏病，以及左心室射血分数（left ventricular ejection fraction, LVEF）。根据患者冠脉造影图像计算SYNTAX评分[13]，由2名经验丰富的介入心脏病专家共同计算与SYNTAX评分相关的所有血管造影变量。
根据所有纳入患者的NT-proBNP四分位数，分为低水平组（NT-proBNP≤61.80 pg/mL）、中水平组（61.80 pg/mL＜NT-proBNP≤152.95 pg/mL）、高水平组（152.95 pg/mL＜NT-proBNP≤470.10 pg/mL）以及很高水平组（NT-proBNP＞470.10 pg/mL）。
1.3 统计学处理
采用SPSS 26.0软件进行统计学分析。符合正态分布的计量资料以$ \bar{x}\pm s $表示，其中2组资料比较采用独立样本t检验，4组比较采用单因素方差分析；不符合正态分布的计量资料以M（P25, P75）表示，2组资料比较采用Mann-Whitney U检验，4组资料比较采用Kruskal-Wallis H检验。计数资料以 n（%）表示，采用χ2检验。采用有序logistic回归分析恶性肿瘤患病与血清NT-proBNP水平的关系，并对已知的风险因素（包括单因素分析有统计学意义的变量）进行调整，包括年龄、BMI、高脂血症、LVEF、SYNTAX 评分、肌酐等，计算比值比（OR）与95%置信区间（95%CI）。检验水准（α）为0.05。
2. 结 果
2.1 研究对象临床特征
共纳入1 344例患者，包括336例肿瘤患者和1 008例非肿瘤患者。患者平均年龄（65.78±9.18）岁，男性1 003例（74.63%），LVEF[ 60.00%（55.00%，64.00%）]，SYNTAX评分（13.84±11.63）分，肌酐水平76.60（66.50，88.88）μmol/L。肿瘤组患者中，肺癌84例（25.00%）、胃癌52例（15.48%）、肠癌58例（17.26%）、食管癌20例（5.95%）、肝癌17例（5.06%）、肾癌16例（4.76%）、乳腺癌12例（3.57%）、前列腺癌11例（3.27%）、胆道系统肿瘤10例（2.98%）、其他肿瘤56例（16.67%）。两组患者临床特征比较（表1）显示：BMI、高脂血症、SYNTAX评分、丙氨酸氨基转移酶（alanine aminotransferase, ALT）、 天冬氨酸氨基转移酶（aspartate aminotransferase, AST）、肌酐、中性粒细胞/淋巴细胞比值（neutrophil-to-lymphocyte ratio, NLR）、血红蛋白含量、血小板计数在两组间的差异有统计学意义（P＜0.05）。
表 1 肿瘤组与非肿瘤组患者临床特征比较Table 1. Comparison of clinical characteristics of patients between cancer group and non-cancer groupCharacteristic Cancer group (n＝336) Non-cancer group (n＝1 008) P value Age/year 66.02±8.52 65.70±9.39 0.571 Male n(%) 256(76.2) 746(74.0) 0.470 BMI/(kg·m−2) 24.76±3.29 25.30±3.12 0.007 Smoking historya n(%) 166(49.4) 494(49.0) 0.900 Drinking history n(%) 137(41.1) 370(36.8) 0.171 Hypertension n(%) 198(58.9) 591(58.6) 0.949 Hyperlipidemia n(%) 26(7.7) 186(18.5) ＜0.001 Diabetes n(%) 112(33.3) 304(30.2) 0.276 LVEF/% 59.50(55.00,63.00) 60.00(55.00,64.00) 0.056 SYNTAX Score 20.60±12.01 11.58±10.59 ＜0.001 ALT/(U·L−1) 16.35(12.03,25.40) 19.05(13.80,29.53) ＜0.001 AST/(U·L−1) 17.60(13.40,23.76) 18.35(14.70,25.00) 0.008 Creatinine/(μmol·L−1) 79.30(68.60,91.38) 75.90(65.68,88.13) 0.004 NLR 3.38±3.53 2.89±3.17 0.016 Hb/(g·L−1) 128.47±21.51 136.17±17.67 ＜0.001 PLT/(×109·L−1) 217.23±73.05 207.92±60.50 0.022 WBC/(×109·L−1) 6.40(5.27,7.85) 6.43(5.36,7.59) 0.950 BMI: body mass index; LVEF: left ventricular ejection fraction; ALT: alanine aminotransferase; AST: aspartate aminotransferase; Hb: hemoglobin; NLR: neutrophil-to-lymphocyte ratio; PLT: platelet; WBC: white blood cell. aParticipants were grouped according to whether they smoked more than 100 cigarettes. If so, they were former smokers; otherwise, they were never smokers. 以NT-proBNP四分位数分组的患者临床特征比较（表2）显示：4组患者的年龄、BMI、高脂血症史、肿瘤患病率、LVEF、血红蛋白含量、血小板计数的差异有统计学意义（P＜0.05）；而性别、吸烟史、饮酒史、高血压病史、糖尿病病史、SYNTAX 评分、肌酐等差异无统计学意义。
表 2 不同NT-proBNP水平患者的临床特征Table 2. Clinical characteristics of study patients stratified by NT-proBNPCharacteristic NT-proBNP P value Low (n＝336) Middle (n＝336) High (n＝336) Very high (n＝336) Age/year 62.19±9.24 66.09±8.33 66.63±8.77 65.78±9.18 ＜0.001 Male n(%) 257(76.5) 247(73.5) 255(75.9) 243(72.3) 0.561 BMI/(kg·m−2) 25.61±3.07 25.20±3.11 25.19±3.09 24.65±3.36 0.002 Smoking historya n(%) 166(49.4) 158(47.0) 161(47.9) 175(52.1) 0.577 Drinking history n(%) 139(41.5) 128(38.3) 133(39.8) 107(31.8) 0.055 Hypertension n(%) 180(53.6) 203(60.4) 211(62.8) 195(58.0) 0.092 Hyperlipidemia n(%) 71(21.1) 55(16.4) 47(14.0) 39(11.6) 0.006 Diabetes n(%) 102(30.4) 104(31.0) 107(31.8) 103(30.7) 0.978 Cancer n(%) 64(19.0) 67(19.9) 104(31.0) 101(30.1) ＜0.001 LVEF/% 61.00(56.00,65.00) 60.00(56.00,64.00) 59.00(54.00,64.00) 59.00(53.00,63.00) ＜0.001 SYNTAX score 12.83±11.19 13.24±11.19 14.42±11.51 14.85±12.52 0.078 ALT/(U·L−1) 19.80(13.80,23.38) 17.60(13.30,28.60) 18.10(13.40,28.70) 18.30(13.10,27.70) 0.640 AST/(U·L−1) 18.20 (14.40,22.68) 17.70 (14.30,25.00) 18.10(13.40,28.70) 18.30(14.60,25.60) 0.572 Creatinine/(μmol·L−1) 76.75 (66.90,87.95) 75.65 (66.95,87.53) 77.50(66.53,89.80) 77.60(65.90,90.93) 0.564 NLR 2.82±2.63 3.11±3.42 2.80±2.50 3.32±4.21 0.127 Hb/(g·L−1) 138.26±17.20 133.35±19.66 134.22±16.97 131.03±21.23 ＜0.001 PLT/(×109·L−1) 215.65±64.43 213.76±65.31 209.39±60.98 202.41±64.71 0.039 WBC/(×109·L−1) 6.47 (5.34,7.47) 6.32 (5.36,7.56) 6.29(5.16,7.83) 6.40 (5.42,7.65) 0.937 BMI: body mass index; LVEF: left ventricular ejection fraction; ALT: alanine aminotransferase; AST: aspartate aminotransferase; NLR: neutrophil-to-lymphocyte ratio; Hb: hemoglobin; PLT: platelet; WBC: white blood cell. aParticipants were grouped according to whether they smoked more than 100 cigarettes. If so, they were former smokers; otherwise, they were never smokers. 2.2 肿瘤组与非肿瘤组患者NT-proBNP水平比较结果
（图2A）显示：肿瘤组患者的NT-proBNP水平明显高于非肿瘤组[208.450（85.750，601.825）pg/mL vs 134.350（57.175，430.225）pg/mL，P＜0.001]。两组患者NT-proBNP趋势检验结果（图2B）显示：肿瘤组患者NT-proBNP低、中、高、很高水平的患者占比分别为19.0%、19.9%、31.0%和30.1%；非肿瘤组分别为27.0%、 26.7%、23.0%和23.3%，肿瘤组患者中较高NT-proBNP水平的比例高于非肿瘤组（P＜0.001）。
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图 2 肿瘤组和非肿瘤组血清NT-proBNP水平比较Figure 2. Comparison of serum levels of NT-proBNP between cancer group and non-cancer groupA: Comparison of serum NT-proBNP levels between patients in cancer group and non-cancer group by Mann-Whitney U test; B: Comparison of serum NT-proBNP levels between patients in cancer group and non-cancer group by trend analysis.2.3 恶性肿瘤与血清NT-proBNP水平的相关性
单因素有序logistic回归结果（表3）显示：年龄增长、低BMI、无高脂血症史、患恶性肿瘤、血红蛋白降低与患者NT-proBNP升高有关。与非肿瘤组相比，肿瘤患者NT-proBNP升高的概率增加56.1%（OR＝1.561，95%CI 1.538～1.584，P＜0.001）。在校正了年龄、BMI、高脂血症、LVEF、SYNTAX评分、肌酐、Hb后，结果（表4）显示：患恶性肿瘤与NT-proBNP水平升高有显著相关性（OR＝1.384，95%CI 1.070～1.791, P＝0.013）。
表 3 单因素有序回归分析血清NT-proBNP的影响因素Table 3. Univariate ordinal regression analysis of influencing factors of serum NT-proBNPVariate OR 95% CI P value Age 1.046 1.033-1.059 ＜0.001 Male 0.891 0.694-1.143 0.363 BMI 0.940 0.908-0.974 0.001 Smoking history 1.188 0.954-1.480 0.124 Drinking history 0.836 0.667-1.046 0.118 Hypertension 1.127 0.900-1.411 0.299 Hyperlipidemia 0.612 0.450-0.833 0.002 Diabetes 1.022 0.806-1.297 0.854 Cancer 1.561 1.538-1.584 ＜0.001 LVEF 0.972 0.960-0.984 ＜0.001 SYNTAX score 1.009 1.000-1.019 0.056 ALT 0.999 0.994-1.004 0.751 AST 1.001 0.998-1.004 0.539 Creatinine 1.000 0.998-1.002 0.849 NLR 1.011 0.977-1.045 0.534 Hb 0.989 0.983-0.995 ＜0.001 PLT 0.997 0.995-0.999 0.052 WBC 0.981 0.939-1.025 0.387 BMI: body mass index; LVEF: left ventricular ejection fraction; ALT: alanine aminotransferase; AST: aspartate aminotransferase; NLR: neutrophil-to-lymphocyte ratio; Hb: hemoglobin; PLT: platelet; WBC: white blood cell. 表 4 有序logistic回归分析肿瘤与血清NT-proBNP的相关性Table 4. Association between cancer and serum NT-proBNP by ordinal logistic regressionModel OR 95% CI P value Model 1 1.561 1.538-1.584 ＜0.001 Model 2 1.533 1.221-1.924 ＜0.001 Model 3 1.463 1.134-1.888 0.003 Model 4 1.460 1.131-1.884 0.004 Model 5 1.384 1.070-1.791 0.013 Model 1: crude model; Model 2: adjusted for age, BMI, hyperlipidemia; Model 3: adjusted for age, BMI, hyperlipidemia, LVEF, SYNTAX Score; Model 4: adjusted for age, BMI, hyperlipidemia, LVEF, SYNTAX Score, creatinine; Model 5: adjusted for age, BMI, hyperlipidemia, LVEF, SYNTAX score, creatinine, Hb. 3. 讨 论
本研究收集和分析单中心1 344例患者的数据，探讨恶性肿瘤与血清NT-proBNP水平的相关性。结果显示，肿瘤患者的血清NT-proBNP显著高于非肿瘤患者，在校正年龄、心功能（LVEF为指标）、肾功能（血清肌酐为指标）等传统影响因素，以及单因素分析中有统计学意义的因素后，恶性肿瘤与血清高NT-proBNP仍存在显著关联，提示患恶性肿瘤是NT-proBNP升高的独立相关因素。
NT-proBNP是一种重要的心血管疾病标志物，主要受心功能影响。心力衰竭、冠心病等心脏疾病导致心脏负荷增加或心肌受损时，都会引起 NT-proBNP水平升高[14-16]。此外，年龄是影响NT-proBNP的重要因素之一，随着年龄的增长，NT-proBNP水平也会逐渐升高[17]。研究[18]显示，肾功能不全会影响 NT-proBNP 的清除速度，使其在血液中的浓度升高。本研究单因素有序logistic回归分析结果显示，年龄增长、低BMI、无高脂血症、患恶性肿瘤、LVEF降低、血红蛋白含量降低与NT-proBNP升高相关。多因素有序logistic回归分析校正了一系列混杂因素后，患恶性肿瘤与高NT-proBNP仍显著相关。
在肿瘤患者中，放疗、细胞毒性治疗、分子靶向抑制剂等治疗手段可引起心血管副作用，使得血清NT-proBNP水平升高。既往研究[19-20]发现，癌症患者的BNP水平升高，但这些研究没有排除年龄、性别、心功能、肾功能、抗肿瘤治疗等因素的影响。本研究纳入的肿瘤患者均为新发的、尚未接受任何抗肿瘤治疗的患者，排除了抗肿瘤治疗药物对于心脏的影响。
恶性肿瘤可能通过心、肾功能障碍之外的其他机制促进NT-proBNP分泌，例如肿瘤导致的心脏炎症、恶病质或代谢紊乱[21-22]。Ohsaki等[23]在9个小细胞肺癌细胞系中发现5个检测到BNP前体的mRNA表达，表明小细胞肺癌细胞可直接产生NT-proBNP。在间皮瘤患者中，胸腔积液中的BNP水平升高，甚至超过了血清水平[24]，提示恶性间皮细胞可能产生BNP。此外，肿瘤可能通过炎症机制来增加NT-proBNP的产生。C反应蛋白（C-reactive protein, CRP）已被证实是与各种疾病相关的炎症标志物[25]。在心肌细胞中，炎性胞质分裂在转录水平促进了利尿肽的合成[26]。动物模型实验[27]显示，注射癌症细胞可诱导小鼠BNP水平升高，且BNP与CRP、IL-6或TNF-α水平相关。影响血清NT-proBNP的另一个因素可能是肿瘤引起的恶病质。肿瘤患者常见的症状包括呼吸困难、疲劳、厌食，以及高代谢、高分解代谢和低合成代谢等代谢紊乱[28]。这些症状可能导致恶病质的发生。恶病质伴随着明显的营养不良、炎性细胞因子增加、免疫系统功能亢进和神经激素变化，这些均可导致心血管功能下降，心肌细胞产生更多NT-proBNP[29]。动物模型的研究[22]表明，在各种肿瘤诱导的恶病质模型中存在严重的心脏萎缩和心脏功能障碍。一项临床研究[30]表明，肿瘤患者的左心室重量低于健康对照组，这可能是心功能下降的原因。因此，肿瘤诱导的恶病质可能与多种心脏功能障碍有关，包括心肌萎缩和心功能下降。这些变化可能与NT-proBNP水平的升高有关。
与健康个体相比，心血管疾病患者患恶性肿瘤的风险更高[31-32]。Meijers等[33]发现心力衰竭加速了恶性肿瘤的生长，在心力衰竭患者中观察到较高的NT-proBNP水平与结直肠癌风险增加有关，但需要进一步的研究来阐明潜在的生物学机制。总之，损伤的心肌细胞可能通过心脏外分泌效应影响远处恶性肿瘤的生长。
本研究存在一定局限性：（1）作为一项单中心回顾性研究，研究对象可能存在选择偏倚，为了尽可能减少偏倚，采用倾向性匹配评分以1∶3的比例匹配肿瘤和非肿瘤患者。（2）由于肿瘤组患者的样本量受限，未分析肿瘤类型和分期与NT-proBNP的相关性。（3）血清NT-proBNP作为血清学指标，数值会不断变化，易受到血管紧张素转化酶抑制剂(ACEI)、血管紧张素Ⅱ受体拮抗剂（ARB）、β-受体阻滞剂等心血管用药的影响，本研究未将其纳入分析[34-35]。（4）本研究为横断面研究，尚不能明确恶性肿瘤与NT-proBNP之间的因果关系，也未探讨两者相关的具体机制。
综上所述，本研究显示，恶性肿瘤患者的NT-proBNP高于非肿瘤患者。在调整其他NT-proBNP的影响因素后，恶性肿瘤与血清高NT-proBNP显著相关。本研究对于进一步明确恶性肿瘤与心血管疾病相关性的机制，以及扩展NT-proBNP的临床应用具有启示作用。然而，仍需要前瞻性、多中心以及基础研究来进一步验证恶性肿瘤与NT-proBNP的相关性及作用机制，并验证此结论在患者群体中的适用性。
伦理声明 本研究获得中国人民解放军总医院伦理委员会批准（2020-255-01）。本研究中的所有程序均符合《赫尔辛基宣言》。
利益冲突 所有作者声明不存在利益冲突。
作者贡献 王溢豪：分析数据，撰写论文；朱绍宁：数据收集与统计；孙明壮：数据收集与录入；李小龙：核对数据；孙志军：研究设计指导；胡舜英：研究开展与论文撰写过程中的各项指导。
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图 2 肿瘤组和非肿瘤组血清NT-proBNP水平比较
Figure 2. Comparison of serum levels of NT-proBNP between cancer group and non-cancer group
A: Comparison of serum NT-proBNP levels between patients in cancer group and non-cancer group by Mann-Whitney U test; B: Comparison of serum NT-proBNP levels between patients in cancer group and non-cancer group by trend analysis.
表 1 肿瘤组与非肿瘤组患者临床特征比较
Table 1 Comparison of clinical characteristics of patients between cancer group and non-cancer group
Characteristic Cancer group (n＝336) Non-cancer group (n＝1 008) P value Age/year 66.02±8.52 65.70±9.39 0.571 Male n(%) 256(76.2) 746(74.0) 0.470 BMI/(kg·m−2) 24.76±3.29 25.30±3.12 0.007 Smoking historya n(%) 166(49.4) 494(49.0) 0.900 Drinking history n(%) 137(41.1) 370(36.8) 0.171 Hypertension n(%) 198(58.9) 591(58.6) 0.949 Hyperlipidemia n(%) 26(7.7) 186(18.5) ＜0.001 Diabetes n(%) 112(33.3) 304(30.2) 0.276 LVEF/% 59.50(55.00,63.00) 60.00(55.00,64.00) 0.056 SYNTAX Score 20.60±12.01 11.58±10.59 ＜0.001 ALT/(U·L−1) 16.35(12.03,25.40) 19.05(13.80,29.53) ＜0.001 AST/(U·L−1) 17.60(13.40,23.76) 18.35(14.70,25.00) 0.008 Creatinine/(μmol·L−1) 79.30(68.60,91.38) 75.90(65.68,88.13) 0.004 NLR 3.38±3.53 2.89±3.17 0.016 Hb/(g·L−1) 128.47±21.51 136.17±17.67 ＜0.001 PLT/(×109·L−1) 217.23±73.05 207.92±60.50 0.022 WBC/(×109·L−1) 6.40(5.27,7.85) 6.43(5.36,7.59) 0.950 BMI: body mass index; LVEF: left ventricular ejection fraction; ALT: alanine aminotransferase; AST: aspartate aminotransferase; Hb: hemoglobin; NLR: neutrophil-to-lymphocyte ratio; PLT: platelet; WBC: white blood cell. aParticipants were grouped according to whether they smoked more than 100 cigarettes. If so, they were former smokers; otherwise, they were never smokers. 
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表 2 不同NT-proBNP水平患者的临床特征
Table 2 Clinical characteristics of study patients stratified by NT-proBNP
Characteristic NT-proBNP P value Low (n＝336) Middle (n＝336) High (n＝336) Very high (n＝336) Age/year 62.19±9.24 66.09±8.33 66.63±8.77 65.78±9.18 ＜0.001 Male n(%) 257(76.5) 247(73.5) 255(75.9) 243(72.3) 0.561 BMI/(kg·m−2) 25.61±3.07 25.20±3.11 25.19±3.09 24.65±3.36 0.002 Smoking historya n(%) 166(49.4) 158(47.0) 161(47.9) 175(52.1) 0.577 Drinking history n(%) 139(41.5) 128(38.3) 133(39.8) 107(31.8) 0.055 Hypertension n(%) 180(53.6) 203(60.4) 211(62.8) 195(58.0) 0.092 Hyperlipidemia n(%) 71(21.1) 55(16.4) 47(14.0) 39(11.6) 0.006 Diabetes n(%) 102(30.4) 104(31.0) 107(31.8) 103(30.7) 0.978 Cancer n(%) 64(19.0) 67(19.9) 104(31.0) 101(30.1) ＜0.001 LVEF/% 61.00(56.00,65.00) 60.00(56.00,64.00) 59.00(54.00,64.00) 59.00(53.00,63.00) ＜0.001 SYNTAX score 12.83±11.19 13.24±11.19 14.42±11.51 14.85±12.52 0.078 ALT/(U·L−1) 19.80(13.80,23.38) 17.60(13.30,28.60) 18.10(13.40,28.70) 18.30(13.10,27.70) 0.640 AST/(U·L−1) 18.20 (14.40,22.68) 17.70 (14.30,25.00) 18.10(13.40,28.70) 18.30(14.60,25.60) 0.572 Creatinine/(μmol·L−1) 76.75 (66.90,87.95) 75.65 (66.95,87.53) 77.50(66.53,89.80) 77.60(65.90,90.93) 0.564 NLR 2.82±2.63 3.11±3.42 2.80±2.50 3.32±4.21 0.127 Hb/(g·L−1) 138.26±17.20 133.35±19.66 134.22±16.97 131.03±21.23 ＜0.001 PLT/(×109·L−1) 215.65±64.43 213.76±65.31 209.39±60.98 202.41±64.71 0.039 WBC/(×109·L−1) 6.47 (5.34,7.47) 6.32 (5.36,7.56) 6.29(5.16,7.83) 6.40 (5.42,7.65) 0.937 BMI: body mass index; LVEF: left ventricular ejection fraction; ALT: alanine aminotransferase; AST: aspartate aminotransferase; NLR: neutrophil-to-lymphocyte ratio; Hb: hemoglobin; PLT: platelet; WBC: white blood cell. aParticipants were grouped according to whether they smoked more than 100 cigarettes. If so, they were former smokers; otherwise, they were never smokers.
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表 3 单因素有序回归分析血清NT-proBNP的影响因素
Table 3 Univariate ordinal regression analysis of influencing factors of serum NT-proBNP
Variate OR 95% CI P value Age 1.046 1.033-1.059 ＜0.001 Male 0.891 0.694-1.143 0.363 BMI 0.940 0.908-0.974 0.001 Smoking history 1.188 0.954-1.480 0.124 Drinking history 0.836 0.667-1.046 0.118 Hypertension 1.127 0.900-1.411 0.299 Hyperlipidemia 0.612 0.450-0.833 0.002 Diabetes 1.022 0.806-1.297 0.854 Cancer 1.561 1.538-1.584 ＜0.001 LVEF 0.972 0.960-0.984 ＜0.001 SYNTAX score 1.009 1.000-1.019 0.056 ALT 0.999 0.994-1.004 0.751 AST 1.001 0.998-1.004 0.539 Creatinine 1.000 0.998-1.002 0.849 NLR 1.011 0.977-1.045 0.534 Hb 0.989 0.983-0.995 ＜0.001 PLT 0.997 0.995-0.999 0.052 WBC 0.981 0.939-1.025 0.387 BMI: body mass index; LVEF: left ventricular ejection fraction; ALT: alanine aminotransferase; AST: aspartate aminotransferase; NLR: neutrophil-to-lymphocyte ratio; Hb: hemoglobin; PLT: platelet; WBC: white blood cell.
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表 4 有序logistic回归分析肿瘤与血清NT-proBNP的相关性
Table 4 Association between cancer and serum NT-proBNP by ordinal logistic regression
Model OR 95% CI P value Model 1 1.561 1.538-1.584 ＜0.001 Model 2 1.533 1.221-1.924 ＜0.001 Model 3 1.463 1.134-1.888 0.003 Model 4 1.460 1.131-1.884 0.004 Model 5 1.384 1.070-1.791 0.013 Model 1: crude model; Model 2: adjusted for age, BMI, hyperlipidemia; Model 3: adjusted for age, BMI, hyperlipidemia, LVEF, SYNTAX Score; Model 4: adjusted for age, BMI, hyperlipidemia, LVEF, SYNTAX Score, creatinine; Model 5: adjusted for age, BMI, hyperlipidemia, LVEF, SYNTAX score, creatinine, Hb.
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