Prognostic Role of Preoperative Onodera's Prognostic Nutritional Index (OPNI) in Gastrointestinal Stromal Tumors: a Systematic Review and Meta-analysis.

PURPOSE

The inflammatory parameters of peripheral blood are related to the prognosis of various cancers. The aim of this meta-analysis is to explore the prognostic value of preoperative OPNI in gastrointestinal stromal tumors (GIST).

METHODS

The following search strategies were used to locate all literature published up to May 1, 2022: PubMed, Web of Science, CBM, EMBASE, and Cochrane, using the keywords "Prognosis," "survival," "Nutritional Assessment," "Nutrition Index," and "PNI," "OPNI," "Gastrointestinal stromal tumor," and "GIST." Studies that did not report an associated cumulative hazard ratio (HR) of recurrence-free survival (RFS) were excluded. The pooled hazard ratio (HR) and corresponding 95% confidence intervals (CI) were calculated by a fixed-effects model. Subgroups were analyzed for heterogeneity of studies, and Egger's test was applied to assess the risk of publication bias.

RESULTS

Through the inclusion and exclusion criteria, 8 articles with a total of 2462 patients with gastrointestinal stromal tumors were selected for analysis. The HR summary of univariate analysis of RFS was 2.73 (95% CI: 2.17-3.43, P < 0.0001), and there was no heterogeneity, which indicated that the prognosis of gastrointestinal stromal tumors with low OPNI before operation was poor. Except for one article that did not give the HR of RFS under the condition of multi-factor analysis, the other 7 articles gave the HR of RFS and summarized it to 1.81 (95% CI: 1.40-3.83, P < 0.0001). Although there was slight heterogeneity in the multifactorial analysis, the publication bias risk and sensitivity assessment showed that the results were still reliable (p > 0.05).

CONCLUSION

The results of this systematic review and meta-analysis show that decreased preoperative OPNI is closely associated with poor long-term survival (RFS) in GIST patients. Monitoring OPNI in GIST patients may help with risk stratification and individualized treatment.