The prognostic nutritional index is a predictive indicator of prognosis and postoperative complications in gastric cancer: A meta-analysis

https://doi.org/10.1016/j.ejso.2016.05.029Get rights and content

Abstract

Background

The clinical value of the prognostic nutritional index (PNI) in gastric cancer (GC) remains controversial. Therefore, we performed the meta-analysis to determine the prognostic and clinicopathological values of PNI in patients with GC.

Methods

A literature search was performed in the PubMed, Embase, and Web of Science databases. Hazard ratios (HRs) and odds ratios (ORs) were extracted to estimate the association of PNI with survival and clinicopathological characteristics, respectively.

Results

Ten studies involving 3396 patients with GC were analyzed. The pooled results indicated that a low PNI was a significant predictor of poor overall survival (OS) (HR = 1.89, 95% confidence interval [CI] = 1.67–2.13, P < 0.01) and postoperative complications (OR = 1.74, 95% CI = 1.41–2.16, P < 0.01). In the subgroup analysis, a low PNI was significantly associated with poor OS in patients with GC at stage I, II and III, but not at stage IV (HR = 1.14, 95% CI = 0.84–1.55, P = 0.40). Moreover, a low PNI was significantly associated with more advanced tumor features, such as older age, deeper depth of tumor, positive lymph node metastasis, more advanced TNM stages, and positive vessel and lymphatic invasion.

Conclusion

PNI was a predictive indicator of survival and postoperative complications, and was associated with clinicopathological features in GC patients. However, a low PNI was not significantly associated with poor OS in patients with GC at stage IV.

Introduction

Gastric cancer (GC) is one of the most frequent causes of cancer death worldwide, with an estimated occurrence of 951,600 new cases and 723,100 deaths in 2012.1 Despite developments in early diagnosis, surgery, adjuvant chemotherapy, and targeted therapies, the long-term survival is still unsatisfactory,2 perhaps owing to local recurrence and distant metastasis. Curative resection is still the most effective treatment for GC. On the other hand, some studies reported that postoperative complications, such as anastomotic leakage, can lead to poor prognosis in patients with GC.3, 4 It is valuable to identify patients who are likely to have unfavorable postoperative outcomes. Therefore, a method for the accurate prediction of postoperative complications and prognosis is needed to guide clinical decisions and improve the survival of patients.

The immune and nutritional status of patients was reported to be associated with the postoperative outcomes in malignant tumors.5, 6 The prognostic nutritional index (PNI), which was first designed by Buzby et al.,7 was calculated based on the serum albumin concentration and lymphocyte count in the peripheral blood.8 Recently, emerging evidence has demonstrated the prognostic value of PNI in different types of malignant tumors, including hepatocellular carcinoma,9 nasopharyngeal carcinoma,10 and colorectal cancer.11 Moreover, Sun et al.12 have performed a pooled analysis to estimate the prognostic value of PNI in cancer. However, owing to limited number of studies and their small sample sizes, the clinical value of PNI in GC has not reached a consensus. Therefore, whether the PNI can be a supplementary index together with the current TNM staging system to predict prognosis remain unknown. For this reason, a quantitative pooled study on PNI needs to be performed.

The aim of this study was to perform a meta-analysis to assess the prognostic value of PNI and the correlation between PNI and clinicopathological features in patients with GC.

Section snippets

Literature search strategy

A comprehensive literature search was performed using the PubMed, Embase, and Web of Science databases up to November 30, 2015. The main search terms were “prognostic nutritional index” and “gastric cancer/stomach cancer/gastrointestinal cancer.” In addition, potentially relevant searches were performed by screening the references of the relevant articles.

Inclusion and exclusion criteria

The eligible studies were selected on the basis of the following criteria: (1) diagnosis of GC was based on pathological examination; (2)

Search results and study characteristics

A total of 639 potentially relevant studies were initially identified via database searches. After the initial review, 596 articles were excluded. Then, 33 studies were excluded after a full text review. Finally, 10 cohort studies involving 3396 patients were included in this meta-analysis18, 19, 20, 21, 22, 23, 24, 25, 26, 27 (Fig. 1).

These 10 studies were published between 2010 and 2015, and investigated the prognosis or clinicopathological features of GC, and their sample sizes ranged

Discussion

The prognostic and clinicopathological value of PNI has recently been studied in patients with many malignancies. However, the prognostic and clinicopathological role of PNI in GC patients is still not unclear. To the best of our knowledge, this is the first meta-analysis to systematically explore the prognostic role of PNI and the relationship between PNI and clinicopathological characteristics in patients with GC.

Our results indicated that a low preoperative PNI was a poor prognostic factor

Conclusions

PNI was significantly associated with patients survival, postoperative complications, and clinicopathological features in GC. However, a low PNI was not a significant predictor of poor OS in patients with stage IV GC.

Conflict of interest

The authors declare that they have no conflict of interest.

Acknowledgments

This work was supported by Natural Science Foundation of Liaoning Province (No. 2014029201), Program of Education Department of Liaoning Province (L2014307) and the Key Laboratory Programme of Education Department of Liaoning Province (LZ2015076).

References (33)

  • G.P. Buzby et al.

    Prognostic nutritional index in gastrointestinal surgery

    Am J Surg

    (1980)
  • D. Takeuchi et al.

    Postoperative complications in elderly patients with gastric cancer

    J Surg Res

    (2015)
  • L.A. Torre et al.

    Global cancer statistics, 2012

    CA Cancer J Clin

    (2015)
  • L. Shen et al.

    Management of gastric cancer in Asia: resource-stratified guidelines

    Lancet Oncol

    (2013)
  • H.M. Yoo et al.

    Negative impact of leakage on survival of patients undergoing curative resection for advanced gastric cancer

    J Surg Oncol

    (2011)
  • M. Sierzega et al.

    Impact of anastomotic leakage on long-term survival after total gastrectomy for carcinoma of the stomach

    Br J Surg

    (2010)
  • I. Schwegler et al.

    Nutritional risk is a clinical predictor of postoperative mortality and morbidity in surgery for colorectal cancer

    Br J Surg

    (2010)
  • I. Ray-Coquard et al.

    Lymphopenia as a prognostic factor for overall survival in advanced carcinomas, sarcomas, and lymphomas

    Cancer Res

    (2009)
  • T. Onodera et al.

    [Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients]

    Nihon Geka Gakkai zasshi

    (1984)
  • A.W. Chan et al.

    Prognostic Nutritional Index (PNI) predicts tumor recurrence of very early/early stage hepatocellular carcinoma after surgical resection

    Ann Surg Oncol

    (2015)
  • X.J. Du et al.

    Value of the prognostic nutritional index and weight loss in predicting metastasis and long-term mortality in nasopharyngeal carcinoma

    J Transl Med

    (2015)
  • R. Tokunaga et al.

    Prognostic nutritional index predicts severe complications, recurrence, and poor prognosis in patients with colorectal cancer undergoing primary tumor resection

    Dis Colon Rectum

    (2015)
  • K. Sun et al.

    The prognostic significance of the prognostic nutritional index in cancer: a systematic review and meta-analysis

    J Cancer Res Clin Oncol

    (2014)
  • A. Stang

    Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses

    Eur J Epidemiol

    (2010)
  • J.F. Tierney et al.

    Practical methods for incorporating summary time-to-event data into meta-analysis

    Trials

    (2007)
  • J.P. Higgins et al.

    Measuring inconsistency in meta-analyses

    BMJ

    (2003)
  • Cited by (0)

    a

    Yuchong Yang and Peng Gao contributed equally to this work.

    View full text