恶性肿瘤患者发生VTE的相关危险因素及风险评估模型的研究进展
Research Progress on Risk Factors and Risk Assessment Models for VTE in Malignant Tumor Patients
DOI: 10.12677/ACM.2024.141139, PDF, HTML, XML, 下载: 173  浏览: 296 
作者: 张长喜, 开维司尔克孜·开色尔, 罗 琴*:新疆医科大学附属肿瘤医院呼吸神经内科,新疆 乌鲁木齐
关键词: 恶性肿瘤静脉血栓栓塞风险评估模型综述Malignancy Venous Thromboembolism Risk Assessment Model Summarize
摘要: 总结恶性肿瘤并发静脉血栓栓塞症的危险因素以及相关静脉血栓风险评估模型,并对风险评估工具的基本特征、应用优缺点进行分析,旨在为今后开发符合中国国情及恶性肿瘤患者群体特征的静脉血栓风险评估模型与临床应用提供依据。
Abstract: Summarize the risk factors and related venous thromboembolism risk assessment models for ma-lignant tumors, and analyze the basic characteristics and advantages and disadvantages of risk as-sessment tools. The aim is to provide a basis for the future development of venous thromboembo-lism risk assessment models and clinical applications that are in line with China’s national condi-tions and the characteristics of malignant tumor patient populations.
文章引用:张长喜, 开维司尔克孜·开色尔, 罗琴. 恶性肿瘤患者发生VTE的相关危险因素及风险评估模型的研究进展[J]. 临床医学进展, 2024, 14(1): 971-978. https://doi.org/10.12677/ACM.2024.141139

1. 引言

静脉血栓栓塞(VTE)是恶性肿瘤患者的第二大死因,仅次于肿瘤本身,且发生率逐年上升,VTE主要分为肺栓塞和深静脉血栓形成。目前,关于中国癌症人群中对于VTE疾病的发生率、相关危险因素及常用风险评估模型验证的研究相对较少。本文旨在回顾肿瘤患者VTE的流行病学、危险因素、生物标志物以及相关风险评估模型的研究进展。

2. 肿瘤发生VTE的流行病学

恶性肿瘤患者中最常见的并发症之一是静脉血栓栓塞症。据统计约有20%的VTE与肿瘤相关 [1] [2] [3] [4] ,且发生率在逐年增加。随着医疗水平的发展,癌症治疗取得了重大进展,但近年来发生VTE的风险仍有所增加,是普通人群的9倍 [5] 。许多研究显示VTE可能导致肿瘤患者死亡的风险增加2至6倍 [6] [7] 。早期有研究显示亚洲人群中VTE的发生并不多见,而近期的研究证据显示亚洲地区发病率逐渐上升,且肿瘤被确定为最常见的风险因素之一 [8] 。VTE发生率的上升可能与生活方式的改变、更长的寿命、VTE筛查意识增强以及影像学和专业知识进步相关 [9] 。

3. 危险因素

3.1. 患者自身危险因素

癌症患者自身存在发展为VTE的危险因素包括以下几点:1) 年龄:在人口统计学变量中,发生静脉血栓栓塞的风险被证明与年龄密切相关,男性和女性的发病率和患病率均有所增加,据报道,从<15岁增加到>80岁VTE的发病率增加了近90倍 [10] 。在一项IA期非小细胞肺癌患者的研究中,发现年龄75岁以上患者发生VTE的风险是60岁以下患者的8.9倍 [11] 。2) 性别:关于VTE发病率的性别差异,存在相互矛盾的数据,在一项研究中显示,男性发病率低于45岁以下的女性,而高于45岁以上的女性 [12] ,而在Fletcher等研究结果显示男性较女性易发生静脉血栓 [13] ,目前关于性别的研究尚无统一结论。3) 种族:除骨髓瘤外,黑人/非裔美国人在所有肿瘤类型中CAT (癌症相关血栓形成)的发病率都较高,而亚洲/太平洋岛人在调整潜在混杂因素后,与非西班牙裔白人相比,CAT的发病率始终较低 [14] [15] 。4) 肥胖:根据国际血栓形成学会对静脉血栓栓塞的分类,肥胖属于发生静脉血栓栓塞的弱但同时具有短暂性和持续性的危险因素组 [16] 。5) 伴随症状:研究证实患有动脉血栓栓塞、肺部疾病、肾脏疾病、感染和贫血,这些都增加了静脉血栓形成的风险 [17] 。6) 体力活动和久坐时间:身体活动是动脉血栓形成的一个特征明确的保护性危险因素,它与静脉血栓栓塞的关联是复杂和不确定的 [18] 。有证据表明,静脉血栓栓塞风险可能因身体活动强度而异。轻度强度运动与静脉血栓栓塞风险之间没有关联(HR = 0.75, 95% CI: 0.49, 1.16),剧烈运动与静脉血栓栓塞风险高于无体力活动(HR = 1.75, 95% CI: 1.08, 2.83) [19] 。7) VTE病史:与无VTE病史的癌症患者相比,有VTE史的癌症患者VTE复发风险增加6~7倍 [20] 。

3.2. 癌症相关危险因素

癌症特定发生机制与VTE形成有关,主要包括4种。1) 癌症类型:静脉血栓栓塞的患病率因癌症类型而异,在一项多中心前瞻性癌症–静脉血栓栓塞登记处的基线数据报告中表明在胰腺癌中观察到的静脉血栓栓塞发生率最高,其次是胃癌,结直肠癌,妇科癌和肺癌,乳腺癌静脉血栓栓塞发生率最低 [21] 。2) 癌症分期:当考虑癌症分期时,发现VTE患病率随分期增加。VTE的患病率在IV期胃癌、肺癌和胰腺癌患者中急剧增加。这些结果与其他种族的癌症患者的分析数据一致,其中胰肠栓塞的频率在胰腺癌和较高阶段的肿瘤中也最高,由此推断转移是晚期癌症阶段的关键特征,是静脉血栓栓塞的重要危险因素 [22] 。3) 病理类型:在一项单中心前瞻性队列研究中,发现IA期常见的病理类型为腺癌,鳞状细胞癌患者较少。进一步分析显示,腺癌和鳞状细胞癌患者的VTE发生率无显著差异 [23] ,而肺腺癌表皮生长因子受体(EGFR)突变患者中,浸润性肺腺癌不同病理亚型中VTE发生率存在差异,其中腺泡型肺腺癌VTE发生率高于非腺泡型肺腺癌,与其他亚型比较差异有统计学意义 [24] 。4) 诊断后时间:癌症诊断后的初期与较高的VTE风险相关,在诊断后的前3个月中风险最大 [25] 。

3.3. 癌症治疗相关的危险因素

癌症的治疗与VTE风险有关,VTE是术后常见的并发症,化疗已被确定为静脉血栓栓塞的独立危险因素,根据癌症治疗的进展,在多项研究中发现,接受新辅助化疗的晚期卵巢癌患者中,VTE事件的发生率很高,约21.4%, [26] [27] [28] ;使用血管生成抑制剂可增加动脉血栓的发生风险;中心静脉导管置入对癌症治疗有至关重要的作用,CVC (中央静脉导管)相关VTE发生率在5%~30%之间,发生VTE可导致治疗中断,并引起肺栓塞和静脉血栓后综合征 [29] 。

4. 生物标志物及临床意义

4.1. 细胞外囊泡

在一项前瞻性队列研究表明,纤维蛋白生成试验测定的高EV-TF (细胞外小泡暴露组织因子)促凝血活性与癌症患者,尤其是胰腺癌患者VTE风险增加相关 [30] 。虽然将EV作为生物标记物的研究已经迅速发展,但EV的可重复性和可靠性测试受到分析前和分析障碍的阻碍。分析前步骤的差异,如采血、样本处理、处理和储存,会严重影响检测结果。例如,创伤采血会激活血小板并虚假增加EV数量,而不同的离心速度会影响EV的提取效率 [31] 。

4.2. 组织因子/组织因子细胞外囊泡

TF是一种促凝蛋白,可启动外源性凝血途径,导致凝血酶和纤维蛋白凝块的形成。对癌症患者的荟萃分析显示,随着TF+EV数量或功能的增加,VTE的风险增加76% (95% CI 1.21~2.56)。就TF分析而言,存在抗体特异性和选择性较差,耗时且分析间变异性高,因此不适合临床使用 [32] 。

4.3. 中性粒细胞和中性粒细胞外陷阱

根据癌症类型进行的亚组分析显示,只有胰腺癌和肺癌的VTE风险显著增加,H3Cit水平升高。然而,这些结果应谨慎解释,因为该研究在亚组分析方面动力不足。对癌症患者中性粒细胞与淋巴细胞比率(NLR)的研究也进行了探索,但没有显示出意义 [33] 。血浆H3Cit可通过ELISA测定,但临床上尚未广泛使用该方法 [34] 。

4.4. 炎症分子

在同一研究中,未发现IL-1β、IL-4、IL-6、IL-8、IL-10、IL-11、TNF-α和VEGF与VTE显著相关 [35] 。然而,在一项对转移性结直肠癌患者的研究中,化疗前血清TNF-α水平较低(<6.6 pg/ml)可将VTE风险降低83% (95%可信区间0.04~0.75),但由于可信区间较宽,估计效果不准确 [36] 。炎症标记物是生物标记物的常见候选物,这些标记物是有利的,因为定量分析在临床实践中很容易获得,并且许多标记物可以通过多路复用一次进行分析。但是细胞因子半衰期短,昼夜变化,在多次冻融循环中容易降解。

4.5. 足蛋白和异柠檬酸脱氢酶1

由于研究没有报告VTE事件发生的时间与获取用于足蛋白表达和IDH1基因分型的肿瘤样本相关,因此无法得出足蛋白和IDH 1对VTE风险影响的因果结论。在一项新诊断的胶质瘤患者的单独研究中,足蛋白组织阳性(≥30%表达)和IDH1突变状态与随后VTE风险显著相关,且风险估计精度较低 [37] 。在对肿瘤组织进行免疫染色后,组织学上评估足蛋白和IDH1的表达。虽然这些检测可以在临床环境中完成,但组织采集的侵入性,特别是在脑癌环境中,可以延迟和限制风险模型的使用。

4.6. 细胞外微RNA

评估miRNA生物标记物对癌症VTE风险的研究有限。miR-363-3p在胶质瘤和肺癌患者的血浆以及VTE患者的结直肠肿瘤组织中上调的发现是有意义的,并暗示了miR-363-3p的因果作用 [38] 。在一项研究中,已经确定了诊断时的miRNA谱,能够预测胰腺导管腺癌(PDAC)和远端肝外胆管癌(DECC)患者在随访期间VTE事件的发生 [39] 。

4.7. 多磷酸盐和接触途径

目前对癌症患者接触途径功能的研究有限,但表明接触途径的激活会导致胃肠道、结直肠癌和肺癌患者消耗和减少因子XII [40] 。在这里,我们确定了polyP/FXII驱动的内在凝血途径在PC相关血栓形成中的一种新的和意想不到的作用。对转基因小鼠的患者血浆和PE模型的凝血分析表明,PC细胞和前列腺体在其表面上暴露出长链polyP。该聚合物激活FXII,触发PC患者血浆中的凝血,并导致小鼠血栓形成。干扰polyP/FXII通路可防止血栓形成,同时不会增加出血风险。这些数据确定了一种新的凝血机制,该机制有助于PC驱动的血栓形成,并表明干扰polyP/FXII轴构成了PC相关血栓形成中抗凝药物开发的新靶点,而不会影响止血。干扰polyP/FXII通路为PC相关血栓形成中的抗凝提供了一种新方法,该方法缺乏目前使用的抗凝剂的出血风险 [41] 。

4.8. 纤溶酶原激活物抑制剂-1

在本研究中,我们发现胰腺癌患者血浆中活性PAI-1水平与VTE之间存在相关性(PAI-1浓度每加倍增加40%),表明PAI-1是胰腺癌VTE的风险标志物 [42] 。与我们的结果相反,Kondo及其同事在胰腺癌患者中没有观察到PAI-1总量和VTE之间的关系 [43] 。有趣的是,用贝伐单抗治疗后,小鼠肺癌模型显示肿瘤组织和血浆中PAI-1的表达增加,贝伐单单抗是一种抗血管生成性VEGF抗体,与癌症患者VTE增加相关,这表明PAI-1可能在基于血管生成治疗的VTE中发挥更显著的促凝血作用 [44] 。

4.9. 血小板活化剂

最近,对脑癌患者的研究表明,高PDPN水平通过激活血小板与VTE的发生相关,并且在多种癌症患者中发现血小板活化标记物的表达增加,支持血小板在癌症相关VTE中发挥重要作用的观点 [45] 。

4.10. 血液计数

白细胞和血小板计数等血液计数作为原发性VTE的生物标志物已被广泛研究,并在许多风险模型中广泛应用。在癌症患者的前瞻性研究中,白细胞升高(>11 × 109/l)和血小板升高(≥350 × 109/l)计数增加了初始VTE的风险 [46] 。

4.11. D-二聚体

二聚体是纤溶酶诱导纤溶的降解产物,是癌症患者原发性VTE最常见的生物标志物之一。有研究表明血浆中高D-二聚体与卵巢癌发生VTE风险有关,但没有足够的证据支持D-二聚体升高与卵巢癌患者预后较差之间存在显着关联,仍需要多变量模型来探索D-二聚体对预后分析的独立影响 [47] [48] 。

4.12. P选择素

P-选择素是一种存在活化内皮细胞和血小板上的细胞粘附分子,可释放到血浆和EV中。来自维也纳CA TS队列的多个前瞻性研究表明,可溶性P-选择素水平的增加与VTE风险相关,然而,在另一项基于维也纳CATS队列的研究中,可溶性P-选择素水平与风险增加没有显著相关性。可溶性P-选择素是通过ELISA测定的,虽然检测可用于研究目的,但临床检测并不广泛。尽管维也纳CATS风险模型可以改善VTE预测,但缺乏可溶性P-选择素分析限制了其拟定的临床功能 [49] 。

5. 风险预测模型评估

癌症相关VTE的风险是多因素的,没有单一的风险因素或生物标记物可以用来最好地理解或预测风险。

在一项回顾性病例对照研究中比较住院癌症患者的两种风险评估模型,发现KS评分和Caprini评分与癌症住院患者VTE风险密切相关。然而,Caprini风险评估模型在识别VTE高危住院癌症患者方面比KS更有效 [50] 。美国临床肿瘤学会指南建议使用KS评估癌症门诊患者VTE的风险。KS ≥ 2的患者应考虑预防性抗凝治疗 [51] 。此外,Khorana等人 [52] 发现KS在住院癌症患者中具有令人满意的预测价值,识别VTE高危患者的最佳临界值为2分。尽管Caprini量表的计算有点复杂,因为它包含的项目很多,但如果对所有未经选择的住院患者(包括VTE高风险癌症住院患者)使用一个风险评估模型(我们建议使用Caprini风险评估模型),VTE风险评估过程将在临床实践中大大简化。文献回顾一致地确定了评估门诊癌症患者静脉血栓栓塞风险的三种常用风险预测模型:1) Khorana风险评分;2) 维也纳CATS评分;和3) Protecht评分 [53] 。目前的指南建议使用Khorana评分来确定癌症患者开始全身治疗时发生癌症相关VTE的风险。这一风险评估工具是十多年前开发和验证的,自概念提出以来,已经进行了多次验证研究 [54] 。然而,总体而言,生物标记物的数据是相互矛盾的,目前不建议在临床实践中单独使用单个生物标记物 [55] 。COMPASS-CAT评分是一个更复杂的模型,包括癌症相关因素和患者相关因素,和其他一些已开发的风险模型对比,可能很有前景,但仍需要进一步验证。目前,共识指南和临床实践之间仍存在差距。虽然风险评估工具的实施可以识别门诊患者中血栓预防获益最大的高危患者,但仍存在许多争议性问题。还需要进行其他研究,以探讨DOAC在癌症患者中的安全性和有效性。此外,个别临床医生对于偶发性静脉血栓栓塞的理念和治疗方式仍存在很大差异,尤其是对于SSPE。此外,癌症患者血栓前表型的确切机制仍有待阐明。随着这些机制变得越来越清晰,未来的研究应将重点放在操纵这些机制,以帮助预测静脉血栓栓塞风险最高的门诊患者。

6. 展望

关于中国恶性肿瘤患者发生VTE的相关风险因素及风险评估模型验证的研究较少。目前的指南不仅推荐风险评估模型,还根据是否进行血栓预防或治疗对风险进行分层。然而,由于当前风险评估模型仍保留着十多年前的数据和风险因素,临床应用时可能会低估或高估部分患者的血栓风险,这可能会导致疾病诊断不足的患者停止治疗和较差的预后,或增加不需要抗凝治疗的患者经济负担和出血风险。尽管目前已有许多风险评估模型,其中包含各种风险因素,但它们对不同人群的预测能力各不相同。因此,改进后的模型应该包括新的高价值临床特征或生物标志物,通过去除相对无用的标志物可显著提高模型的预测能力,并且应根据不同人群的特征调整阈值或改进亚组,从而将模型应用于具有不同人群特征的患者。

NOTES

*通讯作者。

参考文献

[1] Riva, N., Donadini, M.P. and Ageno, W. (2015) Epidemiology and Pathophysiology of Venous Thromboembolism: Similarities with Atherothrombosis and the Role of Inflammation. Thrombosis and Haemostasis, 113, 1176-1183.
https://doi.org/10.1160/TH14-06-0563
[2] Ay, C., Pabinger, I. and Cohen, A.T. (2017) Cancer-Associated ve-nous Thromboembolism: Burden, Mechanisms, and Management. Thrombosis and Haemostasis, 117, 219-230.
https://doi.org/10.1160/TH16-08-0615
[3] Riess, H., Habbel, P., Jühling, A., et al. (2016) Primary Prevention and Treatment of Venous Thromboembolic Events in Patients with Gastrointestinal Cancers—Review. World Journal of Gastrointestinal Oncology, 8, 258-270.
https://doi.org/10.4251/wjgo.v8.i3.258
[4] Hisada, Y. and Mackman, N. (2017) Cancer-Associated Pathways and Biomarkers of Venous Thrombosis. Blood, 130, 1499-1506.
https://doi.org/10.1182/blood-2017-03-743211
[5] Mulder, F., Horváth-Puhó, E., Van Es, N., et al. (2021) Ve-nous Thromboembolism in Cancer Patients: A Population-Based Cohort Study. Blood, 137, 1959-1969.
https://doi.org/10.1182/blood.2020007338
[6] Khalil, J., Bensaid, B., Elkacemi, H., et al. (2015) Venous Throm-boembolism in Cancer Patients: An Underestimated Major Health Problem. World Journal of Surgical Oncology, 13, Ar-ticle No. 204.
https://doi.org/10.1186/s12957-015-0592-8
[7] Chew, H.K., Wun, T., Harvey, D., et al. (2006) Incidence of Ve-nous Thromboembolism and Its Effect on Survival among Patients with Common Cancers. Archives of Internal Medicine, 166, 458-464.
https://doi.org/10.1001/archinte.166.4.458
[8] Mcliesh, P. and Wiechula, R. (2012) Identifying and Reducing the Incidence of Post Discharge Venous Thromboembolism (VTE) in Orthopaedic Patients: A Systematic Review. JBI Li-brary of Systematic Reviews, 10, 1-14.
https://doi.org/10.11124/jbisrir-2012-315
[9] Karande, G.Y., Hedgire, S.S., Sanchez, Y., et al. (2016) Advanced Imaging in Acute and Chronic Deep Vein Thrombosis. Cardiovascular Diagnosis and Therapy, 6, 493-507.
https://doi.org/10.21037/cdt.2016.12.06
[10] Heit, J.A. (2015) Epidemiology of Venous Thromboembolism. Na-ture Reviews Cardiology, 12, 464-474.
https://doi.org/10.1038/nrcardio.2015.83
[11] Stein, P.D., Hull, R.D., Kayali, F., et al. (2004) Venous Thrombo-embolism According to Age: The Impact of an Aging Population. Archives of Internal Medicine, 164, 2260-2265.
https://doi.org/10.1001/archinte.164.20.2260
[12] Montagnana, M., Favaloro, E.J., Franchini, M., et al. (2010) The Role of Ethnicity, Age and Gender in Venous Thromboembolism. Journal of Thrombosis and Thrombolysis, 29, 489-496.
https://doi.org/10.1007/s11239-009-0365-8
[13] Dong, H., Liang, X., Gao, Y., et al. (2022) Postoperative Venous Thromboembolism after Surgery for Stage IA Non-Small-Cell Lung Cancer: A Single-Center, Prospective Cohort Study. Thoracic Cancer, 13, 1258-1266.
https://doi.org/10.1111/1759-7714.14373
[14] Douketis, J., Tosetto, A., Marcucci, M., et al. (2011) Risk of Re-currence after Venous Thromboembolism in Men and Women: Patient Level Meta-Analysis. BMJ, 342, d813.
https://doi.org/10.1136/bmj.d813
[15] Faiz, A., Guo, S., Sridharan, A., et al. (2023) Venous Thromboembolism and Acute Myeloid Leukemia: Risk Factors and Mortality in Elderly White, Black and Asian Patients. Blood Coagulation & Fibrinolysis: An International Journal in Haemostasis and Thrombosis, 34, 345-352.
https://doi.org/10.1097/MBC.0000000000001226
[16] White, R.H., Zhou, H., Murin, S., et al. (2005) Effect of Ethnicity and Gender on the Incidence of Venous Thromboembolism in a Diverse Population in California in 1996. Thrombosis and Haemostasis, 93, 298-305.
https://doi.org/10.1160/TH04-08-0506
[17] Matsushita, K. (2016) Pathogenetic Pathways of Cardiorenal Syn-drome and Their Possible Therapeutic Implications. Current Pharmaceutical Design, 22, 4629-4637.
https://doi.org/10.2174/1381612822666160510125057
[18] Hu, M., Wang, X. and Yang, Y. (2023) Causal Rela-tionship between Moderate to Vigorous Physical Activity and Venous Thromboembolism. Journal of Thrombosis and Thrombolysis, 55, 576-583.
https://doi.org/10.1007/s11239-022-02754-x
[19] Datta, T., Brunson, A., Mahajan, A., et al. (2022) Racial Dispar-ities in Cancer-Associated Thrombosis. Blood Advances, 6, 3167-3177.
https://doi.org/10.1182/bloodadvances.2021006209
[20] Khan, F., Tritschler, T., Kahn, S.R., et al. (2021) Venous Thromboembolism. The Lancet, 398, 64-77.
https://doi.org/10.1016/S0140-6736(20)32658-1
[21] Kearon, C., Ageno, W., Cannegieter, S.C., et al. (2016) Cat-egorization of Patients as Having Provoked or Unprovoked Venous Thromboembolism: Guidance from the SSC of ISTH. Journal of Thrombosis and Haemostasis, 14, 1480-1483.
https://doi.org/10.1111/jth.13336
[22] Timp, J.F., Braekkan, S.K., Versteeg, H.H., et al. (2013) Epidemiology of Cancer-Associated Venous Thrombosis. Blood, 122, 1712-1723.
https://doi.org/10.1182/blood-2013-04-460121
[23] Van Stralen, K.J., Doggen, C.J., Lumley, T., et al. (2008) The Relationship between Exercise and Risk of Venous Thrombosis in Elderly People. Journal of the American Geriatrics Society, 56, 517-522.
https://doi.org/10.1111/j.1532-5415.2007.01588.x
[24] Connolly, G.C. and Khorana, A.A. (2010) Emerging Risk Stratification Approaches to Cancer-Associated Thrombosis: Risk Factors, Biomarkers and a Risk Score. Thrombosis Research, 125, S1-S7.
https://doi.org/10.1016/S0049-3848(10)00227-6
[25] Ohashi, Y., Ikeda, M., Kunitoh, H., et al. (2020) Venous Thromboembolism in Cancer Patients: Report of Baseline Data from the Multicentre, Prospective Cancer-VTE Registry. Japanese Journal of Clinical Oncology, 50, 1246-1253.
https://doi.org/10.1093/jjco/hyaa112
[26] Wang, J., Hu, B., Li, T., et al. (2019) The EGFR-Rearranged Adenocar-cinoma Is Associated with a High Rate of Venous Thromboembolism. Annals of Translational Medicine, 7, 724.
https://doi.org/10.21037/atm.2019.12.24
[27] Mclaughlin, H., Greco, P., Straubhar, A., et al. (2023) Implementa-tion of Routine Venous Thromboembolism Prophylaxis during Neoadjuvant Chemotherapy for Patients with Ovarian Cancer. Gynecologic Oncology, 178, 89-95.
https://doi.org/10.1016/j.ygyno.2023.10.001
[28] Shafa, A., Watkins, A., Mcgree, M., et al. (2023) Incidence of Venous Thromboembolism in Patients with Advanced Stage Ovarian Cancer Undergoing Neoadjuvant Chemotherapy: Is It Time for Thromboprophylaxis? Gynecologic Oncology, 176, 36-42.
https://doi.org/10.1016/j.ygyno.2023.06.577
[29] Ren, Y., Chang, L., Zhao, B., et al. (2020) Venous Thromboem-bolism after Peripherally Inserted Central Catheters Placement in Children with Acute Leukemia: A Single-Center Retro-spective Cohort Study. Journal of Pediatric Hematology/Oncology, 42, e407-e409.
https://doi.org/10.1097/MPH.0000000000001832
[30] Fuentes, H.E., Tafur, A.J. and Caprini, J.A. (2016) Can-cer-Associated Thrombosis. Disease-a-Month, 62, 121-158.
https://doi.org/10.1016/j.disamonth.2016.03.003
[31] Marshall-Webb, M., Bright, T., Price, T., et al. (2017) Ve-nous Thromboembolism in Patients with Esophageal or Gastric Cancer Undergoing Neoadjuvant Chemotherapy. Dis-eases of the Esophagus, 30, 1-7.
https://doi.org/10.1111/dote.12516
[32] Basaran, D., Boerner, T., Suhner, J., et al. (2021) Risk of Venous Throm-boembolism in Ovarian Cancer Patients Receiving Neoadjuvant Chemotherapy. Gynecologic Oncology, 163, 36-40.
https://doi.org/10.1016/j.ygyno.2021.07.030
[33] Van Es, N., Hisada, Y., Di Nisio, M., et al. (2018) Extracellular Vesicles Exposing Tissue Factor for the Prediction of Venous Thromboembolism in Patients with Cancer: A Prospective Cohort Study. Thrombosis Research, 166, 54-59.
https://doi.org/10.1016/j.thromres.2018.04.009
[34] Mooberry, M.J. and Key, N.S. (2016) Microparticle Analysis in Disorders of Hemostasis and Thrombosis. Cytometry A, 89, 111-122.
https://doi.org/10.1002/cyto.a.22647
[35] Yuana, Y., Bertina, R.M. and Osanto, S. (2011) Pre-Analytical and An-alytical Issues in the Analysis of Blood Microparticles. Thrombosis and Haemostasis, 105, 396-408.
https://doi.org/10.1160/TH10-09-0595
[36] Cui, C.J., Wang, G.J., Yang, S., et al. (2018) Tissue Factor-Bearing MPs and the Risk of Venous Thrombosis in Cancer Patients: A Meta-Analysis. Scientific Reports, 8, Article No. 1675.
https://doi.org/10.1038/s41598-018-19889-8
[37] Grilz, E., Posch, F., Königsbrügge, O., et al. (2018) Association of Platelet-to-Lymphocyte Ratio and Neutrophil-to-Lymphocyte Ratio with the Risk of Thromboembolism and Mortality in Patients with Cancer. Thrombosis and Haemostasis, 118, 1875-1884.
https://doi.org/10.1055/s-0038-1673401
[38] Ferroni, P., Riondino, S., Formica, V., et al. (2015) Venous Throm-boembolism Risk Prediction in Ambulatory Cancer Patients: Clinical Significance of Neutrophil/Lymphocyte Ratio and Platelet/Lymphocyte Ratio. International Journal of Cancer, 136, 1234-1240.
https://doi.org/10.1002/ijc.29076
[39] Thålin, C., Daleskog, M., Göransson, S.P., et al. (2017) Validation of an Enzyme-Linked Immunosorbent Assay for the Quantification of Citrullinated Histone H3 as a Marker for Neutrophil Ex-tracellular Traps in Human Plasma. Immunologic Research, 65, 706-712.
https://doi.org/10.1007/s12026-017-8905-3
[40] Mir Seyed Nazari, P., Marosi, C., Moik, F., et al. (2019) Low Systemic Levels of Chemokine C-C Motif Ligand 3 (CCL3) Are Associated with a High Risk of Venous Thromboem-bolism in Patients with Glioma. Cancers (Basel), 11, Article No. 2020.
https://doi.org/10.3390/cancers11122020
[41] Awkar, N., Amireh, S., Rai, S., et al. (2018) Association between Level of Tumor Markers and Development of VTE in Patients with Pancreatic, Colorectal and Ovarian Ca: Retrospective Case-Control Study in Two Community Hospitals. Pathology and Oncology Research, 24, 283-287.
https://doi.org/10.1007/s12253-017-0239-x
[42] Watanabe, J., Natsumeda, M., Okada, M., et al. (2019) Podoplanin Expression and IDH-Wildtype Status Predict Venous Thromboembolism in Patients with High-Grade Glio-mas in the Early Postoperative Period. World Neurosurgery, 128, e982-e988.
https://doi.org/10.1016/j.wneu.2019.05.049
[43] Wang, X., Liu, B., Xu, M., et al. (2021) Blocking Podoplanin In-hibits Platelet Activation and Decreases Cancer-Associated Venous Thrombosis. Thrombosis Research, 200, 72-80.
https://doi.org/10.1016/j.thromres.2021.01.008
[44] Anijs, R.J.S., Laghmani, E.H., Ünlü, B., et al. (2022) Tu-mor-Expressed microRNAs Associated with Venous Thromboembolism in Colorectal Cancer. Research and Practice in Thrombosis and Haemostasis, 6, e12749.
https://doi.org/10.1002/rth2.12749
[45] Oto, J., Navarro, S., Larsen, A.C., et al. (2020) MicroRNAs and Neutro-phil Activation Markers Predict Venous Thrombosis in Pancreatic Ductal Adenocarcinoma and Distal Extrahepatic Cholangiocarcinoma. International Journal of Molecular Sciences, 21, Article No. 840.
https://doi.org/10.3390/ijms21030840
[46] Wang, Y., Zhang, Z., Tao, P., et al. (2020) The Abnormal Expression of miR-205-5p, miR-195-5p, and VEGF-A in Human Cervical Cancer Is Related to the Treatment of Venous Thrombo-embolism. BioMed Research International, 2020, Article ID: 3929435.
https://doi.org/10.1155/2020/3929435
[47] Pan, J., Qian, Y., Weiser, P., et al. (2010) Glycosaminoglycans and Activated Contact System in Cancer Patient Plasmas. Progress in Molecular Biology and Translational Science, 93, 473-495.
https://doi.org/10.1016/S1877-1173(10)93020-2
[48] Cosmi, B., Legnani, C., Libra, A., et al. (2023) D-Dimers in Diagnosis and Prevention of Venous Thrombosis: Recent Advances and Their Practical Implications. Polish Archives of Internal Medicine, 133, 16604.
https://doi.org/10.20452/pamw.16604
[49] Nickel, K.F., Ronquist, G., Langer, F., et al. (2015) The Polyphos-phate-Factor XII Pathway Drives Coagulation in Prostate Cancer-Associated Thrombosis. Blood, 126, 1379-1389.
https://doi.org/10.1182/blood-2015-01-622811
[50] Gerotziafas, G.T., Taher, A., Abdel-Razeq, H., et al. (2017) A Predictive Score for Thrombosis Associated with Breast, Colorectal, Lung, or Ovarian Cancer: The Prospective COMPASS-Cancer-Associated Thrombosis Study. Oncologist, 22, 1222-1231.
https://doi.org/10.1634/theoncologist.2016-0414
[51] Wu, J., Fu, Z., Liu, G., et al. (2017) Clinical Significance of Plasma D-Dimer in Ovarian Cancer: A Meta-Analysis. Medicine (Baltimore), 96, e7062.
https://doi.org/10.1097/MD.0000000000007062
[52] Mauracher, L.M., Posch, F., Martinod, K., et al. (2018) Cit-rullinated Histone H3, a Biomarker of Neutrophil Extracellular Trap Formation, Predicts the Risk of Venous Thrombo-embolism in Cancer Patients. Journal of Thrombosis and Haemostasis, 16, 508-518.
https://doi.org/10.1111/jth.13951
[53] Posch, F., Thaler, J., Zlabinger, G.J., et al. (2016) Soluble Vascular Endo-thelial Growth Factor (sVEGF) and the Risk of Venous Thromboembolism in Patients with Cancer: Results from the Vienna Cancer and Thrombosis Study (CATS). Clinical Cancer Research, 22, 200-206.
https://doi.org/10.1158/1078-0432.CCR-14-3358
[54] Reitter, E.M., Kaider, A., Ay, C., et al. (2016) Longitudinal Analysis of Hemostasis Biomarkers in Cancer Patients during Antitumor Treatment. Journal of Thrombosis and Hae-mostasis, 14, 294-305.
https://doi.org/10.1111/jth.13218
[55] Key, N.S., Khorana, A.A., Kuderer, N.M., et al. (2020) Venous Thromboembolism Prophylaxis and Treatment in Patients with Cancer: ASCO Clinical Practice Guideline Update. Journal of Clinical Oncology, 38, 496-520.
https://doi.org/10.1200/JCO.19.01461