A Novel Hematological Inflammation-Nutrition Score (HINS) and Its Related Nomogram Model to Predict Survival Outcome in Advanced Gastric Cancer Patients Receiving First-Line Palliative Chemotherapy

• Main Authors: Chen C (Author), Wang Z (Author), Qin Y (Author)
• Format: Book
• Published: Dove Medical Press, 2023-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Summary

Chen Chen,&ast; Zehua Wang,&ast; Yanru Qin Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China&ast;These authors contributed equally to this workCorrespondence: Yanru Qin, Department of Oncology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Erqi District, Zhengzhou, Henan, 450052, People's Republic of China, Tel [phone], Email [e-mail]: This study aims to construct a novel hematological inflammation-nutrition score (HINS) and investigate its prognostic value in patients with advanced gastric cancer (AGC). We investigated the risk stratification performance of HINS and developed a HINS-based nomogram model to predict overall survival by combining traditional predictors.Patients and Methods: We conducted a retrospective study on 812 AGC patients who received first-line platinum- or fluoropyrimidine-containing chemotherapy at The First Affiliated Hospital of Zhengzhou University Hospital between 2014 and 2019. Patients were randomly divided into a training cohort (N=609) and a validation cohort (N=203). HINS (0- 2) was constructed based on a pre-chemotherapy systemic immune-inflammation index (SII) and albumin (ALB). Prognostic factors were screened by univariate and multivariate COX proportional regression models. Significant factors were used to construct a nomogram model. Internal validation was performed by calibration curves, time-dependent receiver operating characteristics (ROC) curves, and decision curve analysis (DCA), evaluating its prediction consistency, discrimination ability, and clinical net benefit.Results: HINS was constructed based on SII and ALB. HINS showed a better stratification ability than JCOG prognostic index, with significant differences between groups. Multivariate analysis showed that ECOG ≥ 1 (HR: 1.379; P=0.005), Stage IV (HR: 1.581; P < 0.001), diffuse-type histology (HR: 1.586; P < 0.001), number of metastases ≥ 2 (HR: 1.274; P=0.038), without prior gastrectomy (HR: 1.830; P < 0.001), ALP ≥ULN (HR: 1.335; P=0.034), HINS (P < 0.001) were independent factors of OS. We successfully established a HINS-based nomogram model that showed a strong discriminative ability, accuracy, and clinical utility in training and validation cohorts.Conclusion: HINS shows a superior risk stratification ability, which might be a potential prognostic biomarker for AGC patients receiving palliative first-line palliative chemotherapy. The HINS-based nomogram model is a convenient and efficient tool for managing prognosis and follow-up treatments.Keywords: hematological inflammation-nutrition score, nomogram model, advanced gastric cancer, prognosis

Item Description

1178-7031