Individualized prediction of risk of metachronous peritoneal carcinomatosis from colorectal cancer

• Published in: Colorectal disease Vol. 16; no. 5; pp. 359 - 367
• Main Authors: Segelman, J., Akre, O., Gustafsson, U. O., Bottai, M., Martling, A.
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.05.2014
• Subjects: Adult; Age Factors; Aged; Aged, 80 and over; Carcinoma - secondary; Carcinoma - therapy; Chemotherapy, Adjuvant; Colonic Neoplasms - pathology; Colonic Neoplasms - therapy; Colorectal cancer; Elective Surgical Procedures; Emergencies; Female; Humans; individual risk; Lymph Nodes - pathology; Male; Medicin och hälsovetenskap; Middle Aged; Neoadjuvant Therapy; Neoplasm Staging; Neoplasm, Residual; Nomograms; peritoneal carcinomatosis; Peritoneal Neoplasms - secondary; Peritoneal Neoplasms - surgery; Predictive Value of Tests; Proportional Hazards Models; Radiotherapy, Adjuvant; Rectal Neoplasms - pathology; Rectal Neoplasms - therapy; Risk Assessment - methods; Risk Factors; Second-Look Surgery; Young Adult; peritoneal carcinomatosis; individual risk; Colorectal cancer
• ISSN: 1462-8910; 1463-1318; 1463-1318
• DOI: 10.1111/codi.12552

Aim The purpose of the study was to develop a tool for predicting the individual risk of metachronous peritoneal carcinomatosis after surgery for non‐metastatic colorectal cancer. Method Independent predictors for metachronous colorectal carcinomatosis have previously been identified using a population‐based database. Predictive models for colon and rectal cancer were developed from these data. The predictive models were based on multivariable Cox proportional hazard regression and were internally validated with bootstrapping. Performance was assessed by the concordance index and calibration plots. Results In all, 8044 patients who underwent abdominal resection of colorectal cancer Stage I–III were included. The colon and rectal cancer risk score models predicted metachronous peritoneal carcinomatosis with a concordance index of 80% and 78%, respectively. Factors in the models included age, pathological pT stage, pN stage, number of examined lymph nodes (0–11, 12+), type of surgery (emergency/elective), completeness of cancer resection (R0/R1/R2), adjuvant chemotherapy (yes/no), preoperative radiotherapy and tumour location. Conclusion The proposed predictive models showed high internal validity and enabled individualized prediction of peritoneal recurrence of colorectal cancer. The models may help in the planning of treatment and follow‐up of patients. However, external validation is warranted to assess generalizability of the predicted absolute risks.