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A Novel Nutrition-Based Nomogram to Predict Prognosis After Curative Resection of Gastric Cancer

ABSTRACT: Objective: We sought to investigate the prognostic significance of body composition and weight change during the first 6 months of adjuvant chemotherapy after R0 resection and develop novel nomograms to accurately predict relapse-free survival (RFS) and overall survival (OS). Methods: This retrospective study included 190 patients who underwent curative radical gastrectomy for gastric cancer and received adjuvant chemotherapy. The changes in weight and body composition including skeletal muscle index (SMI), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) were analyzed for 6 months. LASSO Cox regression and multivariate Cox regression were conducted to evaluate other clinical characteristics, which were used to construct a nomogram for the prediction of 3- and 5-year RFS and OS. The constructed nomogram was subjected to 1,000 resamples bootstrap for internal validation. The Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate and compare the discriminative abilities of the new nomograms, non-nutritional nomograms, and pTNM stage. Results: The median follow-up duration was 42.0 (25.2–55.1) months. Factors included in the newly-built nomogram for RFS were pT stage, pN stage, tumor site, tumor size, nerve invasion or not, surgery type, and change of L3SMI, while factors included in the nomogram for OS were pT stage, pN stage, tumor size, nerve invasion or not, surgery type, and change of L3SMI. The C-index and t-ROC indicated that our newly-built nomograms had greater potential to accurately predict prognosis than the non-nutritional nomograms and pTNM stage system. Besides, oral nutritional supplements can reduce the degree of weight and L3SMI loss. Conclusion: Change in skeletal muscle mass during adjuvant chemotherapy can be incorporated into predictive prognostic nomograms for RFS and OS in GC patients after radical resection. Dynamic changes in body composition and weight during adjuvant chemotherapy contribute to the early detection of poor outcomes.

SUBMITTER: Zheng H

PROVIDER: S-EPMC8572887 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWe sought to investigate the prognostic value of complete blood count (CBC)-based biomarkers for patients with resectable gastric cancer (GC).MethodsPatients with GC who underwent primary surgical resection between December 2008 and December 2013 were included. The estimated area under the curve (AUC) and multivariate Cox regression models were used to identify the best CBC-based biomarker. Time-dependent receiver operating characteristic (t-ROC) curve analysis was used to predict overall survival and compare the prognostic impact.ResultsIn the 1810 patients analyzed, the median follow-up period was 51.0 months (range 1-101 months). Based on multivariate analysis, the lymphocyte-monocyte ratio (LMR) and hemoglobin (Hb) level were independent prognostic factors (both P < 0.05). Based on the LMR and Hb level, we established the CBC-based inflammatory score (CBCS). A higher CBCS was associated with older age, female sex, higher American Society of Anesthesiologists (ASA) score, proximal tumor location, larger tumor size, later stage and vascular involvement (all P < 0.05). Univariate analyses showed that a higher CBCS was also associated with worse overall survival (OS), which was consistent in each stage (all P < 0.05). Multivariate analysis revealed that the CBCS was a significant independent biomarker (P < 0.05). The AUC for the CBCS (0.627) was significantly higher than the AUCs for the LMR (0.573) and Hb level (0.605) (both P < 0.05). Furthermore, the t-ROC curve of the CBCS was superior to that of the prognostic nutritional index (PNI), systemic immune-inflammation index (SII), modified Glasgow prognostic score (mGPS) and C-reactive protein/albumin ratio (CRP/Alb) throughout the observation period.ConclusionThe preoperative LMR and Hb level were optimal CBC-based biomarkers for predicting OS in GC patients after curative resection. Based on the LMR and Hb, we developed a novel and easily obtainable prognostic score called the CBCS, which may improve the prediction of clinical outcomes.

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A Novel Nutrition-Based Nomogram to Predict Prognosis After Curative Resection of Gastric Cancer

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