Abstract 4304
Background
Despite multimodality treatment, in the Western world > 50% of GC patients relapse following curative-intent surgery and succumb to their disease. The absolute survival benefit of perioperative or adjuvant chemotherapy ranges from 6 to 15% at 5 years and must be balanced against treatment-related toxicities. Reliable tools to risk-stratify patients are lacking. The aim of this study was to build a practical tool to guide daily decision-making and clinical trial design.
Methods
Data of patients undergoing curative-intent surgery for T2-4 and N-positive GC between 2008 and 2018 at the Modena Cancer Centre were retrieved. Clinicopathologic and biochemical parameters deemed of potential interest were collected. The cut-off value for continuos variables was assessed at 75° percentile. Univariate and multivariate Cox proportional-hazard models were used to assess the prognostic value of covariates. Based on the multivariate model, a nomogram to predict 2- and 3-year RFS was developed with a corresponding number of points assigned to a given magnitude of the variable.
Results
A total of 157 patients were eligible for the analysis. 51% (n = 80) were female and 88% (n = 139) had an ECOG PS of 0-1. Only 6% of cases were gastroesophageal junction cancers. 13% (n = 20), 25% (n = 40), 62% (n = 97) presented at diagnosis with stage I, II and III, respectively. Adjuvant chemotherapy was administered to 49% of patients. Out of 15 covariates tested, the following were independent predictors of outcome in the multivariate analysis and therefore included in the nomogram: ECOG PS (HR 2.51; p = 0.006), nodal status (HR 3.04; p = 0.078), angioinvasion (HR 2.62; p = 0.005) and logNeutrophil/Lymphocyte ratio (HR 3.50; p < 0.001).
Conclusions
We built an easy-to-use nomogram to estimate 2- and 3-year individual RFS probability in resected GC. Interestingly, this tool incorporates variables reflecting patients characteristics (ECOG PS), tumour aggressiveness (nodal status and angioinvasion) and immune-inflammation status (NLR). This nomogram could assist clinicians in discussing with patients prognosis and the risk-to-benefit ratio of systemic treatment as well as the design of future trials.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Massimiliano Salati.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
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