Predictors of Peritoneal Surface Recurrence and Quantitative Association with Time to Relapse After Complete CRS/HIPEC for Colorectal Peritoneal Metastasis.

BACKGROUND/

OBJECTIVES

Peritoneal surface metastases (PSMs) from colorectal cancer have high rates of peritoneal recurrence after cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC). Prior studies dichotomize peritoneal recurrence into "early" and "late," limiting insight into how clinicopathologic factors influence recurrence timing. This study aimed to identify predictors of peritoneal recurrence and quantify their continuous association with time to recurrence following CRS/HIPEC.

METHODS

Patients undergoing CC-0 CRS/HIPEC for colorectal PSM from 2018 to 2024 were identified from a prospectively maintained database. The primary outcome was peritoneal surface recurrence. Variables included peritoneal cancer index (PCI), tumor location, histology, HIPEC regimen, and KRAS/BRAF/SMAD4 status. Factors with p < 0.10 on univariable analysis were entered into multivariable logistic regression (recurrence: yes/no) and linear regression (time to recurrence).

RESULTS

Among 133 patients, 64 (48.1%) developed peritoneal recurrence. Median time to recurrence was 41.4 weeks (IQR 24.9-74.0), and PCI was higher among those who recurred (median 11.0 vs. 5.0, p < 0.01). Neither tumor stage, histology, intraperitoneal chemotherapy agent, nor molecular alterations were associated with increased risk of peritoneal recurrence. When controlling for PCI, right- and sigmoid-colon primaries independently predicted peritoneal recurrence compared to all other locations without influence on recurrence timing (right: OR 7.18; sigmoid: OR 6.54; p < 0.01). Among patients who recurred, each one-point increase in PCI corresponded to a 2.43-week earlier relapse (p < 0.01).

CONCLUSIONS

Nearly half of patients with colorectal PSM recurred despite complete CRS/HIPEC. Tumor location predicted peritoneal recurrence, while PCI independently shortened time to relapse. Modeling PCI as a continuous predictor refines postoperative risk stratification and may inform individualized surveillance strategies.