Published online Nov 7, 2019. doi: 10.3748/wjg.v25.i41.6258
Peer-review started: July 12, 2019
First decision: August 18, 2019
Revised: September 6, 2019
Accepted: September 11, 2019
Article in press: September 11, 2019
Published online: November 7, 2019
Processing time: 118 Days and 12.8 Hours
Increasing numbers of laboratory blood parameters (BPM) have been reported to greatly affect the long-term outcomes of gastric cancer (GC) patients. However, the existing prognostic models, including the prognostic nutritional index, the modified Glasgow prognostic score, and the controlling nutritional status score, contain limited BPM and provide inadequate prognostic information.
We hypothesized that a new scoring system, based on all available BPM, would provide more accurate prognostic information in patients with GC.
The present study aimed to construct a new prognostic tool, based on all the prognostic BPM, to achieve more accurate prognosis prediction for GC.
We retrospectively assessed 850 consecutive patients who underwent curative resection for stage II-III GC from January 2010 to April 2013. The patients were classified into developing (n = 567) and validation (n = 283) cohorts using computer-generated random numbers. A scoring system, namely BPM score, was then constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression model. A nomogram consisting of the BPM score and tumor-lymph node-metastasis (TNM) stage was created. The discrimination and calibration of the nomogram were evaluated via Harrell’s C-statistic and the Hosmer-Lemeshow test.
Using the LASSO model, we established the BPM score based on five BPM: Albumin, lymphocyte-to-monocyte ratio, neutrophil-to-lymphocyte ratio, carcinoembryonic antigen, and carbohydrate antigen 19-9. The BPM scores were divided into high-BPM and low-BPM groups based on a cut-off value of -0.93. High-BPM patients were significantly older and had more advanced, larger tumors. In the developing cohort, significant differences were found in 5-year overall survival (OS) and 5-year disease-specific survival between the high-BPM and low-BPM patients. Similar results were found in the validation group. Multivariable analysis showed that the BPM score was an independent predictor of OS. High-BPM patients had a poorer 5-year OS for each subgroup. Furthermore, a nomogram that combined the BPM score and TNM stage had significantly better prognostic value compared with TNM stage alone.
The BPM score provides more accurate prognosis prediction in stage II-III GC patients and is an effective complement to the TNM staging system. Therefore, we recommend the use of the BPM score for multimodality treatment planning and risk stratification in the future clinical work.
Although we confirmed that the BPM score can accurately predict the outcomes in stage II-III GC patients, the efficiency of this novel scoring system need to be investigated in a prospective multicenter trial.