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得不到及时有效治疗的肺炎病人演变为重症肺炎的风险将会提高,可能会引起严重并发症,严重影响病人的生活质量甚至危及病人生命[1],因此评估肺炎的严重程度并提供适当的治疗具有重要的临床意义和社会经济效益。肺炎严重指数评分系统已被用来评估肺炎病人是否可以作为门诊病人或住院病人治疗,CURB-65评分系统亦是预测肺炎严重程度的重要工具[2],然而,这些评分系统需要费时耗力去收集病人的多项数据,因此各种生物标志物被研究以便于评估肺炎的严重程度。目前中性粒细胞(N)与淋巴细胞(L)比值(NLR)是肺炎中研究最多的标志物之一,已被证明是肺炎预后、风险分层的重要标志物[3-4],同时NLR亦被证明与肺炎严重程度相关[5],然而单项标志物诊断肺炎的ROC曲线下面积相对较小,因此组合多种标志物联合评估可能会提供更多的诊断信息。
肿瘤特异性生长因子(TSGF)在口腔癌、直肠癌、胃癌、乳腺癌中被证明是重要的预测指标[6-9]。然而TSGF并不是恶性肿瘤特异性标志物,在非恶性肿瘤疾病中也有较高的阳性率[10],有文献[11-12]报道炎症细胞分泌非特异性血管生长因子,可以使血清中TSGF升高,非恶性肿瘤病人的TSGF升高可能是由于炎症所致,炎症消失后TSGF逐渐下降。已有研究[13-14]证明TSGF升高在非恶性肿瘤疾病如机械性损伤及淋巴结反应性增生中与炎症反应相关,然而TSGF在肺炎严重程度评估中的应用鲜见国内外文献报道。因此,本研究拟探讨TSGF在肺炎严重程度评估中的应用并与其他已知标志物进行比较。现作报道。
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除年龄和性别外,其他指标2组差异均有统计学意义(P < 0.05),与正常对照组比较,TSGF、FIB、hs-CRP、N、NLR在肺炎病人中呈上升趋势,而L呈下降趋势(P < 0.01)(见表 1)。
分组 n 男 年龄/岁 TSGF/(U/mL) FIB/(g/L) hs-CRP/(mg/L) N/(109/L) L/(109/L) NLR 正常对照组 40 25 75.9±8.7 29.6±7.7 2.9±0.9 1.8±3.9 3.7±1.3 2.2±0.7 1.8±0.7 肺炎组 79 45 76.8±8.6 64.9±10.5 4.2±1.6 34.4±21.6 6.9±4.7 1.2±0.7 8.4±8.3 t — 0.34# 0.54 18.84 4.76 9.45 4.22 7.36 5.01 P — >0.05 >0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 #示χ2值 表 1 肺炎组病人与正常对照组特征及实验室指标结果比较(x±s)
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除性别和年龄外,其他参数在3组之间的差异均有统计学意义(P < 0.01),TSGF、FIB、hs-CRP、NLR、N在低危肺炎组和中高危肺炎组中呈上升趋势,而L呈下降趋势;TSGF、hs-CRP、N、L、NLR在低危肺炎组和中高危肺炎组之间的差异均有统计学意义(P < 0.05)(见表 2)。
分组 n 男 年龄/岁 TSGF/(U/mL) FIB/(g/L) hs-CRP/(mg/L) N/(109/L) L/(109/L) NLR 正常对照组 40 25 75.9±8.7 29.6±7.7 2.9±0.9 1.8±3.9 3.7±1.3 2.2±0.7 1.8±0.7 低危肺炎组 42 21 76.1±7.7 60.0±9.2* 4.0±1.6* 27.8±21.7* 5.2±3.9 1.4±0.6* 5.1±6.2* 中高危肺炎组 37 24 77.5±9.6 70.5±9.2*# 4.5±1.5* 42.0±19.1*# 8.8±4.9*# 1.0±0.6*# 12.2±8.9*# F — 2.13# 0.39 231.82 13.91 56.67 19.58 36.96 28.14 P — >0.05 >0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 MS组内 — — 75.005 76.117 1.875 284.766 13.396 0.404 38.333 #示χ2值;两两比较:与正常对照组比较*P < 0.05;与低危肺炎组比较#P < 0.05 表 2 低危肺炎组和中高危肺炎组病人及正常对照组临床资料及实验室指标结果比较(x±s)
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ROC曲线见图 1,TSGF的AUC大小依次为hs-CRP、NLR、FIB,且TSGF与hs-CRP、NLR、FIB的AUC之间差异均有统计学意义(P < 0.01)(见表 3)。
炎症标志物 AUC SE P 95%CI hs-CRP 0.924 0.023 < 0.01 0.861~0.965 TSGF 0.995 0.004 < 0.01 0.960~1.000 NLR 0.864 0.032 < 0.01 0.789~0.920 FIB 0.758 0.045 < 0.01 0.671~0.832 表 3 4项标志物诊断肺炎的ROC的AUC分析结果
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对实验室指标与肺炎病人CURB-65评分进行双变量Spearman相关性分析,除L与CURB-65评分呈负相关(P < 0.01),TSGF、FIB、hs-CRP、N、NLR与CURB-65评分呈正相关(P < 0.05~P < 0.01)(见表 4)。
指标 FIB TSGF N L NLR hs-CRP rs 0.234 0.543 0.460 -0.371 0.516 0.364 P < 0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 表 4 6项指标与肺炎病人CURB-65评分相关性分析(rs)
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对TSGF与NLR、hs-CRP、FIB线性相关性分析采用双变量Pearson相关性分析,TSGF与NLR、hs-CRP、FIB均成正相关(P < 0.05)(见图 2)。
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以是肺炎是否严重为因变量,定义低危肺炎状态变量为0,中高危肺炎状态变量为1,以TSGF、NLR、hs-CRP、FIB、N、L、年龄、性别等指标为自变量进行多因素logistic回归模型分析,结果显示高TSGF为肺炎严重独立危险因素(P < 0.01)(见表 5)。
指标 B Waldχ2 OR 95%CI P TSGF 0.192 10.393 1.211 1.078~1.361 < 0.01 NLR -0.005 0.004 0.995 0.838~1.181 >0.05 hs-CRP -0.021 0.690 0.979 0.931~1.029 >0.05 FIB 0.073 0.071 1.076 0.629~1.838 >0.05 N 0.260 3.633 1.297 0.993~1.694 >0.05 L -0.894 1.556 0.409 0.100~1.666 >0.05 年龄 -0.692 2.935 0.912 0.820~1.013 >0.05 性别 -0.081 0.014 0.922 0.243~3.503 >0.05 表 5 肺炎严重危险因素多因素logistic回归模型分析
肿瘤特异性生长因子在肺炎严重程度评估中的应用
Application value of the tumor-specific growth factor in evaluating the severity of pneumonia
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摘要:
目的探讨肿瘤特异性生长因子(TSGF)在肺炎严重程度评估中的应用,并与其他已知标志物中性粒细胞(N)与淋巴细胞(L)比值(NLR)、超敏C反应蛋白(hs-CRP)、纤维蛋白原(FIB)比较。 方法分析79例肺炎病人(肺炎组)及40名健康体检者(正常对照组)的临床资料和实验室指标,根据CURB-65评分系统将79例肺炎又分为低危肺炎组42例(CURB-65评分≤ 1)和中高危肺炎组37例(CURB-65评分≥ 2)。检测血清TSGF、hs-CRP、NLR、FIB,Pearson相关分析TSGF与NLR、hs-CRP、FIB之间的相关性,Spearman相关分析TSGF与CURB-65评分之间的相关性,logistic回归分析TSGF、NLR、hs-CRP、FIB、N、L、年龄、性别与肺炎是否严重的相关性,比较TSGF与NLR、hs-CRP、FIB的曲线下面积(AUC),评估其在肺炎诊断中的预测效能。 结果肺炎病人的TSGF高于正常对照组(P < 0.05);低危肺炎病人的TSGF高于正常对照组(P < 0.05),与低危肺炎病人相比,中高危肺炎病人的TSGF进一步升高(P < 0.05);TSGF与hs-CRP、FIB、NLR及CURB-65评分呈正相关(P < 0.05);诊断肺炎的ROC曲线中,TSGF的AUC大于NLR、hs-CRP、FIB(P < 0.05);TSGF与肺炎严重风险提高相关(P < 0.01)。 结论TSGF可能是评估肺炎严重程度的一种新的生物标志物,其快速、诊断效能高、易于分析检测,值得临床推广应用。 -
关键词:
- 肺炎 /
- 肿瘤特异性生长因子 /
- 纤维蛋白原 /
- 超敏C反应蛋白 /
- 中性粒细胞与淋巴细胞比值
Abstract:ObjectiveTo investigate the application value of tumor specific growth factor (TSGF) in evaluating the severity of pneumonia, and compare it with the neutrophil (N) -lymphocyte (L) ratio (NLR), hypersensitive C-reactive protein (hs-CRP) and fibrinogen (FIB). MethodsThe clinical data and laboratory index of 79 pneumonia patients from department of respiratory medicine (pneumonia group) and 40 physical examination people from the physical examination center (control group).According to the scoring system of CURB-65, 79 patients with pneumonia were subdivided into the low-risk pneumonia group (42 cases, CRUB-65 score ≤ 1) and medium-high risk pneumonia group (37 cases, CRUB-65 score ≥ 2).The serum levels of TSGF, hs-CRP, NLR and FIB were detected.The Pearson correlation analysis was used to analyze the correlations between TSGF, and NLR, hs-CRP and FIB, the Spearman correlation analysis was used to analyze the correlation between TSGF and CURB-65 score, and the logistic regression analysis was used to analyze the correlations between TSGF, NLR, hs-CRP, FIB, N, L, age and sex, and severity of pneumonia.The predictive efficacy of the comparison the area under the curve (AUC) of TSGF with NLR, hs-CRP and FIB in the diagnosis of pneumonia was evaluated. ResultsThe TSGF level in pneumonia patients was significantly higher than that in control group (P < 0.05), the TSGF in low-risk pneumonia patients was significantly higher than that in control group (P < 0.05), and the TSGF level in medium-high risk pneumonia group further increased compared with the low-risk pneumonia group (P < 0.05).The TSGF was positively correlated with the scores of hs-CRP, FIB, NLR and CRUB-65 score (P < 0.05).In the ROC curve for predict pneumonia, the AUC of TSGF was significantly greater than that of NLR, hs-CRP and FIB (P < 0.05).TSGF was significantly correlated with the risk of pneumonia severity increasing (P < 0.01). ConclusionsTSGF may be a new biomarker for evaluating the severity of pneumonia, which is rapid, with high diagnostic efficiency, easy to analyze, and worthy of clinical application. -
表 1 肺炎组病人与正常对照组特征及实验室指标结果比较(x±s)
分组 n 男 年龄/岁 TSGF/(U/mL) FIB/(g/L) hs-CRP/(mg/L) N/(109/L) L/(109/L) NLR 正常对照组 40 25 75.9±8.7 29.6±7.7 2.9±0.9 1.8±3.9 3.7±1.3 2.2±0.7 1.8±0.7 肺炎组 79 45 76.8±8.6 64.9±10.5 4.2±1.6 34.4±21.6 6.9±4.7 1.2±0.7 8.4±8.3 t — 0.34# 0.54 18.84 4.76 9.45 4.22 7.36 5.01 P — >0.05 >0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 #示χ2值 表 2 低危肺炎组和中高危肺炎组病人及正常对照组临床资料及实验室指标结果比较(x±s)
分组 n 男 年龄/岁 TSGF/(U/mL) FIB/(g/L) hs-CRP/(mg/L) N/(109/L) L/(109/L) NLR 正常对照组 40 25 75.9±8.7 29.6±7.7 2.9±0.9 1.8±3.9 3.7±1.3 2.2±0.7 1.8±0.7 低危肺炎组 42 21 76.1±7.7 60.0±9.2* 4.0±1.6* 27.8±21.7* 5.2±3.9 1.4±0.6* 5.1±6.2* 中高危肺炎组 37 24 77.5±9.6 70.5±9.2*# 4.5±1.5* 42.0±19.1*# 8.8±4.9*# 1.0±0.6*# 12.2±8.9*# F — 2.13# 0.39 231.82 13.91 56.67 19.58 36.96 28.14 P — >0.05 >0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 MS组内 — — 75.005 76.117 1.875 284.766 13.396 0.404 38.333 #示χ2值;两两比较:与正常对照组比较*P < 0.05;与低危肺炎组比较#P < 0.05 表 3 4项标志物诊断肺炎的ROC的AUC分析结果
炎症标志物 AUC SE P 95%CI hs-CRP 0.924 0.023 < 0.01 0.861~0.965 TSGF 0.995 0.004 < 0.01 0.960~1.000 NLR 0.864 0.032 < 0.01 0.789~0.920 FIB 0.758 0.045 < 0.01 0.671~0.832 表 4 6项指标与肺炎病人CURB-65评分相关性分析(rs)
指标 FIB TSGF N L NLR hs-CRP rs 0.234 0.543 0.460 -0.371 0.516 0.364 P < 0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 表 5 肺炎严重危险因素多因素logistic回归模型分析
指标 B Waldχ2 OR 95%CI P TSGF 0.192 10.393 1.211 1.078~1.361 < 0.01 NLR -0.005 0.004 0.995 0.838~1.181 >0.05 hs-CRP -0.021 0.690 0.979 0.931~1.029 >0.05 FIB 0.073 0.071 1.076 0.629~1.838 >0.05 N 0.260 3.633 1.297 0.993~1.694 >0.05 L -0.894 1.556 0.409 0.100~1.666 >0.05 年龄 -0.692 2.935 0.912 0.820~1.013 >0.05 性别 -0.081 0.014 0.922 0.243~3.503 >0.05 -
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