63
Views
3
CrossRef citations to date
0
Altmetric
Original Research

A clinical prognostic scoring system for resectable gastric cancer to predict survival and benefit from paclitaxel- or oxaliplatin-based adjuvant chemotherapy

, , , , , , , , , , , , , & show all
Pages 241-258 | Published online: 24 Feb 2016
 

Abstract

Background

Gastrectomy with D2 lymphadenectomy is a standard procedure of curative resection for gastric cancer (GC). The aim of this study was to develop a simple and reliable prognostic scoring system for GC treated with D2 gastrectomy combined with adjuvant chemotherapy.

Methods

A prognostic scoring system was established based on clinical and laboratory data from 579 patients with localized GC without distant metastasis treated with D2 gastrectomy and adjuvant chemotherapy.

Results

From the multivariate model for overall survival (OS), five factors were selected for the scoring system: ≥50% metastatic lymph node rate, positive lymphovascular invasion, pathologic TNM Stage II or III, ≥5 ng/mL preoperative carcinoembryonic antigen level, and <110 g/L preoperative hemoglobin. Two models were derived using different methods. Model A identified low- and high-risk patients for OS (P<0.001), while Model B differentiated low-, intermediate-, and high-risk patients for OS (P<0.001). Stage III patients in the low-risk group had higher survival probabilities than Stage II patients. Both Model A (area under the curve [AUC]: 0.74, 95% confidence interval [CI]: 0.69–0.78) and Model B (AUC: 0.79, 95% CI: 0.72–0.83) were better predictors compared with the pathologic TNM classification (AUC: 0.62, 95% CI: 0.59–0.71, P<0.001). Adjuvant paclitaxel- or oxaliplatin-based or triple chemotherapy showed significantly better outcomes in patients classified as high risk, but not in those with low and intermediate risk.

Conclusion

A clinical three-tier prognostic risk scoring system was established to predict OS of GC treated with D2 gastrectomy and adjuvant chemotherapy. The potential advantage of this scoring system is that it can identify high-risk patients in Stage II or III who may benefit from paclitaxel- or oxaliplatin-based regimens. Prospective studies are needed to confirm these results before they are applied clinically.

Supplementary materials

Method S1

Indications for adjuvant chemotherapy

Histologically confirmed gastric cancer of seventh UICC-TNM Stage II, III, or I (T1b/T2N0) with risk factors including poor differentiation; lymphovascular or neural invasion; adequate organ function (a leukocyte count of >4×109/L or the lower limit of the normal range; a platelet count of >100×109/L; a total bilirubin level of <1.5 mg/dL, aspartate aminotransferase and alanine aminotransferase levels not more than two times the upper limit of the normal range; and a serum creatinine level no greater than the upper limit of the normal range); and an age of 20–85 years.

Figure S1 Flow chart outlining patient selection.

Figure S1 Flow chart outlining patient selection.

Figure S2 Maximally selected log-rank statistics plot for optimal cutoff point identification in Model A.

Figure S2 Maximally selected log-rank statistics plot for optimal cutoff point identification in Model A.

Figure S3 ROC analysis of two prognostic models compared with TNM alone to predict patient probability for 5-year survival.

Abbreviation: ROC, Receiver Operating Characteristic curve.
Figure S3 ROC analysis of two prognostic models compared with TNM alone to predict patient probability for 5-year survival.

Figure S4 Kaplan–Meier curves of OS in gastric cancer patients according to adjuvant chemotherapy with or without taxol (AC), oxaliplatin (DF), and cisplatin (GI) stratified by Model B.

Abbreviation: OS, overall survival.
Figure S4 Kaplan–Meier curves of OS in gastric cancer patients according to adjuvant chemotherapy with or without taxol (A–C), oxaliplatin (D–F), and cisplatin (G–I) stratified by Model B.

Table S1 Adjuvant chemotherapy regimens

Table S2 Adjuvant chemotherapy regimens and dosing schedules

Acknowledgments

We would like to thank Dr Richard L Schilsky from the University of Chicago for revising an earlier version of this manuscript. This study was funded by the National Natural Science Foundation of China (81301896), Natural Science Foundation of the Colleges and Universities in Jiangsu Province (13KJB320011), Program for Development of Innovative Research Teams, Jiangsu Province Clinical Science and Technology Projects (Clinical Research Center, BL 2012008), Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), and Provincial Initiative Program for Excellency Disciplines, Jiangsu Province, People’s Republic of China.

Disclosure

The authors report no conflicts of interest in this work.