Systemic inflammatory markers: Predictors of survival in mucinous appendix cancer patients treated with cytoreductive surgery and hyperthermic intraperitoneal chemotherapy

Abstract

Introduction

Inflammatory markers have been investigated as predictors of prognosis in various malignancies, but their role in mucinous appendix cancer (MAC) remains controversial. We evaluated the association between complete blood count-derived markers and survival in MAC patients undergoing cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS/HIPEC).

Methods

We conducted a retrospective analysis of a single-center database (1998–2023) including newly diagnosed MAC patients who underwent complete (CC-0/1) CRS/HIPEC. Preoperative values of neutrophil-to-lymphocyte ratio (NLR), derived NLR, platelets-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) were calculated. For markers strongly associated with survival, we used time-dependent ROC analysis to define cutoffs to predict 5-year overall survival (OS). The Kaplan-Meier method with and Cox regression were employed for survival analysis.

Results

Of 626 CRS/HIPEC cases, 211 were eligible. NLR (p=0.049), dNLR (p=0.049), and MLR (p<0.001) were significantly associated with OS, while PLR was not. MLR demonstrated the strongest prognostic power (AUC=0.682) with the optimal cut-off 0.29. There were no significant differences in age, grade, or peritoneal cancer index (PCI) between patients with MLR<0.29 and MLR≥0.29. Five-year progression-free (PFS) and OS were 72.2 % and 83.2 % for MLR<0.29 and 54.2 % and 66.6 % for MLR≥0.29, respectively. After adjusting for age, PCI, and grade, MLR≥0.29 was associated with worse 3-year PFS (hazard ratio [HR] 1.74, 95 % confidence interval [CI]:1.02–2.97, p=0.044) and 3-year and 5-year OS (HR 1.87, 95 %CI: 1.00–3.47, p=0.049).

Conclusion

MLR has emerged as an independent predictor of survival in MAC patients undergoing CRS/HIPEC. Along with other prognostic factors, MLR≥0.29 may be potentially used for preoperative risk stratification.