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Multicenter Study
. 2016 Nov 1;7(44):72076-72083.
doi: 10.18632/oncotarget.12271.

Preoperative combined hemoglobin, albumin, lymphocyte and platelet levels predict survival in patients with locally advanced colorectal cancer

Huihong Jiang  1 , Huaguang Li  2 , Ajian Li  3 , Erjiang Tang  2 , Dan Xu  2 , Yin Chen  2 , Yong Zhang  3 , Min Tang  3 , Zhiyong Zhang  4 , Xiaxing Deng  1 , Moubin Lin  2   3
Affiliations
Multicenter Study

Preoperative combined hemoglobin, albumin, lymphocyte and platelet levels predict survival in patients with locally advanced colorectal cancer

Huihong Jiang et al. Oncotarget. .

Abstract

More than 50% of patients with colorectal cancer (CRC) are initially diagnosed with locally advanced CRC (LACRC), and half of those patients develop recurrence or metastasis after resection. Here, we investigated whether the novel index HALP, which is a combination of preoperative hemoglobin, albumin, lymphocyte and platelet levels, correlates with survival in LACRC patients. A total of 820 patients with LACRC from two independent hospitals were included in our study. The correlations between HALP and overall and cancer-specific survival were calculated using training and validation sets. Lower HALP values correlated with an increased risk of death and cancer-related death in both sets. Moreover, the risk score based on HALP allowed stratification of patients into distinct prognostic groups with greater accuracy than previously proposed indexes. These results suggest that HALP may be useful as a clinical prognostic factor for patients with LACRC.

Keywords: HALP; colorectal cancer; prognostic; risk; survival.

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Conflict of interest statement

CONFLICTS OF INTEREST

The authors declare no potential conflicts of interest.

Figures

Figure 1
Figure 1. Kaplan-Meier curves for OS and CSS according to HALP in the A-C. training set and B-D. validation set
Figure 2
Figure 2. Kaplan-Meier curves for OS and CSS according to risk score in the A-C. training set and B-D. validation set
Figure 3
Figure 3. ROC analyses for A. OS and B. CSS, based on prognostic models in the training set
See this image and copyright information in PMC

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