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. 2015 Dec 1;6(38):41370-82.
doi: 10.18632/oncotarget.5629.

Prognostic significance of the combination of preoperative hemoglobin, albumin, lymphocyte and platelet in patients with gastric carcinoma: a retrospective cohort study

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Prognostic significance of the combination of preoperative hemoglobin, albumin, lymphocyte and platelet in patients with gastric carcinoma: a retrospective cohort study

Xiao-Long Chen et al. Oncotarget. .

Abstract

Nutritional and immune status is important to the prognosis of patients with gastric carcinoma (GC). Here, we evaluated the prognostic significance of the combination of preoperative hemoglobin, albumin, lymphocyte and platelet (HALP) in patients with GC. From January 2005 to December 2011, 1332 patients with GC who underwent gastrectomy were randomly divided into the training (n = 888) and the validation sets (n = 444) by X-tile according to the sample size ratio 2:1. The cut-point of HALP was 56.8 and the patients were subsequently subdivided into HALP < 56.8 and HALP ≥ 56.8 groups in both two sets. Multivariate analysis revealed that gender (p < 0.001, p < 0.001), tumor size (p = 0.003, p = 0.035) and T stage (p < 0.001, p = 0.044) were independently related to HALP both in the training and the validation sets. Kaplan-Meier (p < 0.001, p = 0.003) and Cox regression (p = 0.043, p = 0.042) showed that the prognosis of HALP ≥ 56.8 group was significantly better than that of HALP < 56.8 group both in two sets (p < 0.001, p < 0.001). Nomograms of these two sets based on HALP were more accurate in prognostic prediction than TNM stage alone. Our findings suggested that HALP was closely associated with clinicopathological features and was an independent prognostic factor in GC patients. Nomogram based on HALP could accurately predict the prognosis of GC patients.

Keywords: albumin; gastric carcinoma; hemoglobin; lymphocyte; platelet.

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Conflict of interest statement

CONFLICTS OF INTEREST

The authors indicate no potential conflicts of interest.

Figures

Figure 1
Figure 1. Survival analysis of HALP in the training and the validation sets
Figure 2
Figure 2. Survival analysis of HALP stratified by TNM stage in the training and the validation sets
Figure 3
Figure 3. Nomogram of the training set
Figure 4
Figure 4. Nomogram of the validation set
Figure 5
Figure 5. Calibration curve of the training set
Figure 6
Figure 6. Calibration curve of the validation set
Figure 7
Figure 7. Analysis of other indexes by X-tile software
Figure 8
Figure 8. The flow chart of patients in this study
Figure 9
Figure 9. Division of patients into the training and the validation sets based on HALP by X-tile software

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