Prognostic Role of Prothrombin Time Activity, Prothrombin Time, Albumin/Globulin Ratio, Platelets, Sex, and Fibrinogen in Predicting Recurrence-Free Survival Time of Renal Cancer
Authors Bian Z, Meng J, Niu Q, Jin X, Wang J, Feng X, Che H, Zhou J, Zhang L, Zhang M, Liang C
Received 2 June 2020
Accepted for publication 25 August 2020
Published 15 September 2020 Volume 2020:12 Pages 8481—8490
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Yong Teng
Zichen Bian,1,* Jialin Meng,1,* Qingsong Niu,1 Xiaoyan Jin,2 Jinian Wang,3 Xingliang Feng,1 Hong Che,4 Jun Zhou,1 Li Zhang,1 Meng Zhang,1,5 Chaozhao Liang1
1Department of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People’s Republic of China; 2The Second Clinical College of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 3Clinical Skills Training Center, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui, People’s Republic of China; 4Department of Cardiac Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China; 5Institute of Urology of Shenzhen University, The Third Affiliated Hospital of Shenzhen University, Shenzhen Luohu Hospital Group, Shenzhen 518000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Chaozhao Liang; Meng Zhang Email [email protected]; [email protected]
Background: To help with the clinical practice of renal cancer patients, prognostic models are urgently warranted. We hunted and identified prognostic variables associated with recurrence-free survival (RFS) for renal cancer patients.
Patients and Methods: In this retrospective study, 187 renal cancer patients who had received curative radical/partial nephrectomy between November 2011 and January 2017 were enrolled in the current study. These patients were randomly split into the training (n = 95) and validation sets (n = 92) by the ratio of 1:1. Univariate and multivariable Cox regression analyses were used to establish the nomogram, which was then evaluated by receiver operating characteristic (ROC) and Kaplan-Meier (K-M) analyses.
Results: Patient characteristics and outcomes were well balanced between the training and validation sets; the median RFS values were 54.1 months and 58.9 months for the training and validation cohorts, respectively. The final nomogram included six independent prognostic variables (prothrombin time (%), prothrombin time (second), albumin/globulin ratio, platelets, sex and fibrinogen). The mean values of RFS for the low- and high-risk groups defined by a prognostic formula were 56.22 ± 18.50 months and 49.54 ± 23.57 months, respectively, in the training cohort and were 59.00 ± 19.50 months and 53.32 ± 19.95 months, respectively, in the validation cohort. The significance and stability of the model were tested by the time-dependent K-M model and ROC curves, respectively.
Conclusion: Our validated prognostic model incorporates variables routinely collected from renal cancer patients, identifying subsets of patients with different survival outcomes, which provides useful information for patient care and clinical trial design.
Keywords: renal cancer, recurrence, nomogram
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