Prognostic value of preoperative platelet parameters in locally advanced renal cell carcinoma

  • Ruo-tao XIAO ,
  • Cheng LIU ,
  • Chu-xiao XU ,
  • Wei HE ,
  • Lu-lin MA
Expand
  • Department of Urology, Peking University Third Hospital, Beijing 100191, China

Received date: 2021-03-10

  Online published: 2021-08-25

Supported by

National Natural Science Foundation of China(81972381)

Abstract

Objective: To explore the prognostic value of preoperative platelet parameters in locally advanced renal cell carcinoma for the risk stratification of such patients. Methods: Clinical data of patients with locally advanced renal cell carcinoma in the Third Hospital of Peking University from January 2015 to December 2017 were collected. The patients were divided into progression group and progression-free group according to follow-up data, and preoperative platelet parameters and clinical data between the two groups were compared. The optimal cut-off value of platelet parameters was determined by receiver operating characteristic curve (ROC) and analyzed by Kaplan-Meier survival curve. Cox proportional hazards model was used to analyze the independent risk factors of PFS. Time dependent ROC curve, net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to evaluate the improvement of SSIGN model by incorporating platelet parameters. Results: Of the 215 patients, 192 (89.3%) were followed up for a median of 36 months. Sixty-four patients (29.8%) had disease progression during the follow-up, and the median PFS was 46 months. In progression group, the platelet count (PLT) was higher [(250.72 ± 88.59)×109/L vs. (227.27 ± 66.94)×109/L, P=0.042] and the platelet distribution width (PDW) was lower [(12.01 ± 2.27)% vs. (13.31 ± 2.74)%, P = 0.001] than that of progression-free groups. 285×109 /L and 12.65% as the best cut-off values of PLT and PDW, the median PFS of PLT≤285×109 /L group was significantly longer than that of PLT>285×109 /L group (53 months vs. 41 months, P=0.033), and the median PFS of PDW>12.65% group was also significantly longer than that of PDW≤12.65% group (56 months vs. 41 months, P<0.001). Multivariate analysis showed that preoperative PDW (HR=0.735, P<0.001), nuclear grade Ⅲ to Ⅳ (HR=2.425, P=0.001) and sarcomatoid differentiation (HR=3.101, P=0.008) were independent risk factors for PFS. The area under the curve of PDW combined with SSIGN model was larger than that with the original SSIGN model [0.748 (95%CI:0.662-0.833) vs. 0.678 (95%CI: 0.583-0.773), P=0.193], NRI was 0.262 (P=0.04), and IDI was 0.085 (P=0.01), indicating that the predictive ability of PDW combined with SSIGN model was improved. Conclusion: Preoperative high PLT and low PDW are associated with adverse prognosis of locally advanced renal cell carcinoma, and PDW is an independent risk factor. Therefore, preoperative PDW could serve as biomarker for risk stratification of locally advanced renal cell carcinoma.

Cite this article

Ruo-tao XIAO , Cheng LIU , Chu-xiao XU , Wei HE , Lu-lin MA . Prognostic value of preoperative platelet parameters in locally advanced renal cell carcinoma[J]. Journal of Peking University(Health Sciences), 2021 , 53(4) : 647 -652 . DOI: 10.19723/j.issn.1671-167X.2021.04.004

References

[1] Gay LJ, Felding-Habermann B. Contribution of platelets to tumour metastasis [J]. Nat Rev Cancer, 2011, 11(2):123-134.
[2] Labelle M, Begum S, Hynes RO. Direct signaling between platelets and cancer cells induces an epithelial-mesenchymal-like transition and promotes metastasis [J]. Cancer Cell, 2011, 20(5):576-590.
[3] Nieswandt B, Hafner M, Echtenacher B, et al. Lysis of tumor cells by natural killer cells in mice is impeded by platelets [J]. Cancer Res, 1999, 59(6):1295-1300.
[4] Zhu X, Cao Y, Lu P, et al. Evaluation of platelet indices as diagnostic biomarkers for colorectal cancer [J]. Sci Rep, 2018, 8(1):11814.
[5] Liu C, Zhang H, Qi Q, et al. The preoperative platelet distribution width: A predictive factor of the prognosis in patients with non-small cell lung cancer [J]. Thorac Cancer, 2020, 11(4):918-927.
[6] Liu S, Fang J, Jiao D, et al. Elevated platelet count predicts poor prognosis in breast cancer patients with supraclavicular lymph node metastasis [J]. Cancer Manag Res, 2020, 12(6):6069-6075.
[7] Heng DY, Xie W, Regan MM, et al. External validation and comparison with other models of the international metastatic renal-cell carcinoma database consortium prognostic model: a population-based study [J]. Lancet Oncol, 2013, 14(2):141-148.
[8] Choi JY, Ko YH, Song PH. Clinical significance of preoperative thrombocytosis in patients who underwent radical nephrectomy for nonmetastatic renal cell carcinoma [J]. Investig Clin Urol, 2016, 57(5):324-329.
[9] Seles M, Posch F, Pichler GP, et al. Blood platelet volume represents a novel prognostic factor in patients with nonmetastatic renal cell carcinoma and improves the predictive ability of established prognostic scores [J]. J Urol, 2017, 198(6):1247-1252.
[10] Karakiewicz PI, Trinh QD, Lam JS, et al. Platelet count and preoperative haemoglobin do not significantly increase the performance of established predictors of renal cell carcinoma-specific mortality [J]. Eur Urol, 2007, 52(5):1428-1436.
[11] Frank I, Blute ML, Cheville JC, et al. An outcome prediction model for patients with clear cell renal cell carcinoma treated with radical nephrectomy based on tumor stage, size, grade and necrosis: the SSIGN score [J]. J Urol, 2002, 168(6):2395-2400.
[12] Zisman A, Pantuck AJ, Dorey F, et al. Improved prognostication of renal cell carcinoma using an integrated staging system [J]. J Clin Oncol, 2001, 19(6):1649-1657.
[13] Amin MB, Edge SB, Greene FL, et al. AJCC cancer staging manual[M]. 8th ed. Chicago: Springer, 2017: 739-747.
[14] Ljungberg B, Bensalah K, Canfield S, et al. EAU guidelines on renal cell carcinoma: 2014 update [J]. Eur Urol, 2015, 67(5):913-924.
[15] Moch H, Cubilla AL, Humphrey PA, et al. The 2016 WHO classification of tumours of the urinary system and male genital organs-part A: renal, penile, and testicular tumours [J]. Eur Urol, 2016, 70(1):93-105.
[16] Siegel RL, Miller KD, Fuchs HE, et al. Cancer statistics, 2021 [J]. CA Cancer J Clin, 2021, 71(1):7-33.
[17] Haas NB, Manola J, Dutcher JP, et al. Adjuvant treatment for high-risk clear cell renal cancer: updated results of a high-risk subset of the ASSURE randomized trial [J]. JAMA Oncol, 2017, 3(9):1249-1252.
[18] Motzer RJ, Haas NB, Donskov F, et al. Randomized phase Ⅲ trial of adjuvant pazopanib versus placebo after nephrectomy in patients with localized or locally advanced renal cell carcinoma [J]. J Clin Oncol, 2017, 35(35):3916-3923.
[19] Motzer RJ, Ravaud A, Patard JJ, et al. Adjuvant sunitinib for high-risk renal cell carcinoma after nephrectomy: subgroup analyses and updated overall survival results [J]. Eur Urol, 2018, 73(1):62-68.
[20] Leibovich BC, Blute ML, Cheville JC, et al. Prediction of progression after radical nephrectomy for patients with clear cell renal cell carcinoma: a stratification tool for prospective clinical trials [J]. Cancer, 2003, 97(7):1663-1671.
[21] Karakiewicz PI, Briganti A, Chun FK, et al. Multi-institutional validation of a new renal cancer-specific survival nomogram [J]. J Clin Oncol, 2007, 25(11):1316-1322.
[22] Correa AF, Jegede O, Haas NB, et al. Predicting renal cancer recurrence: defining limitations of existing prognostic models with prospective trial-based validation [J]. J Clin Oncol, 2019, 37(23):2062-2071.
[23] Xiao R, Xu C, He W, et al. Preoperative anaemia and thrombocytosis predict adverse prognosis in non-metastatic renal cell carcinoma with tumour thrombus [J]. BMC Urol, 2021, 21(1):31.
[24] Yue CX, Liu YX, Yun ZY, et al. Decreased platelet distribution width predicts a worse prognosis in patients undergoing surgical resection for hepatocellular carcinoma [J]. Cancer Biomark, 2019, 26(3):361-366.
[25] Chen H, Wu Q, Zhang Y, et al. Nomograms based on the novel platelet index score predict postoperative prognosis in endometrial cancer [J]. Gynecol Oncol, 2020, 158(3):689-697.
[26] Kawakita Y, Motoyama S, Sato Y, et al. Prognostic significance of combined platelet distribution width and C-reactive protein score in esophageal cancer [J]. Anticancer Res, 2020, 40(10):5715-5725.
[27] 蒋慧云, 李小毛, 王佳, 等. 术前血小板分布宽度在子宫内膜癌诊断预测中的价值 [J]. 实用医学杂志, 2018, 34(7):1188-1190.
[28] Vagdatli E, Gounari E, Lazaridou E, et al. Platelet distribution width: a simple, practical and specific marker of activation of coagulation [J]. Hippokratia, 2010, 14(1):28-32.
[29] 张翔, 庄瑞. 血小板分布宽度对鼻咽癌患者预后的影响 [J]. 国际肿瘤学杂志, 2018, 45(5):257-261.
[30] Huang Y, Cui MM, Huang YX, et al. Preoperative platelet distribution width predicts breast cancer survival [J]. Cancer Biomark, 2018, 23(2):205-211.
[31] 张林楠, 刘玉峰, 苏淑芳, 等. 血小板分布宽度对神经母细胞瘤预后的预测价值 [J]. 中华实用儿科临床杂志, 2020, 35(6):440-444.
Outlines

/