A Nomogram Model Involving Preoperative Fibrinogen and Prognostic Nutritional Index Score for Predicting Postoperative Outcome in Patients with Gastric Cancer.

BACKGROUND: Inflammation and nutrition play vital roles in the development of gastric cancer (GC). We combined the preoperative fibrinogen with prognostic nutritional index (PNI) to create a novel scoring system named as the fibrinogen and prognostic nutritional index (FPNI) score and establish a more effective model. PATIENTS AND METHODS: A total of 689 patients with gastric adenocarcinoma who underwent gastrectomy from January 2012 to December 2016 were reviewed. We measured correlations between FPNI score and clinicopathological variables and overall survival (OS). A nomogram predicting OS was constructed. Its predictive performance was verified using the concordance index, calibration curves, receiver operating characteristic curves, decision curve analysis and time-dependent receiver operating characteristic analysis. RESULTS: We observed that the FPNI score was an independent predictor of OS in patients with gastric cancer (P < 0.05). A high FPNI score was significantly related to older age at surgery, tumor size ≥4.6 cm, high ASA score, advanced TNM stage and poor outcome (both P < 0.05). And the FPNI score remained an independent indicator at various TNM stages (P < 0.05). Ultimately, the nomogram based on FPNI score, age, tumor size, histological grade and TNM stage showed a better predictive ability than TNM alone. CONCLUSION: The preoperative FPNI score is a novel, simple, and effective predictor of OS in patients with GC. Furthermore, the nomogram involving FPNI score will help clinicians to optimize individualized treatment plans.

A nomogram combining plasma fibrinogen and systemic immune­inflammation index predicts survival in patients with resectable gastric cancer.

Hyperfibrinogenemia and cancer-associated systemic inflammatory response are strongly associated with cancer progression and prognosis. We aimed to develop a novel prognostic score (F-SII score) on the basis of preoperative fibrinogen (F) and systemic immunoinflammatory index (SII), and evaluate its predictive value in patients with resectable gastric cancer (GC). Patients diagnosed with GC between January 2012 and December 2016 were reviewed. The F-SII score was 2 for patients with a high fibrinogen level (≥ 3.37 g/L) and a high SII (≥ 372.8), whereas that for patients with one or neither was 1 or 0, respectively. A high F-SII score was significantly associated with older patient age, a high ASA score, large tumor size, large proportion of perineural invasion, and late TNM stage. Multivariate analysis indicated that the F-SII score, histological grade, and TNM stage were independent factors for overall survival (OS). The Harrell's concordance index (C-index) of a nomogram based on the F-SII score and several clinicopathological manifestations was 0.72, which showed a better predictive ability for OS than the TNM stage alone (0.68). In conclusion, preoperative F-SII may serve as a useful predictive factor for OS and refine outcome prediction for patients with resectable GC combined with traditional clinicopathological analysis.

[Comparison of nocturnal ecosystem respiration measured with eddy covariance and chamber system at two agricultural sites in Sanjiang plain].

Measurements of nocturnal ecosystem respiration were conducted in a rice paddy of Sanjiang from July to September in 2004 and in a soybean field from June to September in 2005, using eddy covariance (EC) and dark chamber-gas chromatography (DC-GC). The differences of simultaneous data measured by two methods were not significant when night turbulent mixing was well. The correlations between two methods can be improved under more large friction velocity. EC measurements were poorly correlated to night ecosystem respiration estimated by chamber models for the variability inherent to EC measurements (R2 = 0.06, 0.23 for rice and soybean, respectively). However, this correlation can be improved by aggregating measurements over longer time period (R2 = 0.16, 0.75 for rice and soybean field, respectively). In general, whatever comparison with simultaneous chamber measurements or modeled results, eddy covariance measurements were consistently lower 4% - 30% than chambers, and this bias varied with crop growing stage, which were maximum in middle and minimum in early and late growing stage.