Premium
Individualized prediction of risk of metachronous peritoneal carcinomatosis from colorectal cancer
Author(s) -
Segelman J.,
Akre O.,
Gustafsson U. O.,
Bottai M.,
Martling A.
Publication year - 2014
Publication title -
colorectal disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.029
H-Index - 89
eISSN - 1463-1318
pISSN - 1462-8910
DOI - 10.1111/codi.12552
Subject(s) - medicine , colorectal cancer , stage (stratigraphy) , oncology , concordance , proportional hazards model , nomogram , hazard ratio , peritoneal carcinomatosis , generalizability theory , population , lymphovascular invasion , cancer , surgery , confidence interval , metastasis , paleontology , statistics , mathematics , environmental health , biology
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.