European Journal of Biomedical and Pharmaceutical Sciences

PREDICTIVE FACTORS OF POSTOPERATIVE OUTCOMES IN A JORDANIAN POPULATION OF COLORECTAL CANCER PATIENTS WHO UNDERWENT SURGICAL RESECTION USING A CLINICAL PREDICTION MODEL

Ghaseb Ahmad Abu Alghawai*, Mu'ayyad Mohammad Khair Falah Mugdadi, Ali Hussein Talab Alkhazaleh,
Ahmad Sameer Odeh Al Abbadi, Saif Yousef Hussein Al-Alwan, Muhanad Mohammad Ismail Al Rabee, Doaa
Nasri Ali Alsyoof and Ahmad Uraiqat

ABSTRACT

Background: Surgical resection is the mainstay treatment approach for colorectal cancer (CRC). However, it is
associated with high mortality and morbidity rates. Mortality risk estimation and prediction is on the rise for a
personalized treatment approach and can lead to better post-operative outcomes. Purpose: In this study, we aim to
develop and validate a post-operative mortality and complications risk model using preoperative and clinical
characteristics for Jordanian CRC patients. Methods: We retrospectively retrieved data for CRC patients from
2016 to 2024 who underwent surgical resection from King Hussein Medical Center (KHMC), Amman, Jordan.
Target outcomes were post-operative complications, postoperative pain, and postoperative wound infection.
Demographic and preoperative clinical variables were used as predictors including age, sex, body-mass index
(BMI), smoking, type of surgery (laparoscopic or open(. Logistic regression was built to predict the postoperative
outcomes. All models will be evaluated for accuracy accuracy score, area under the receiver operating
characteristics curve (AUC/ROC), sensitivity, and specificity. Results: Postoperative complications occurred in
10% of patients, with 4.2% experiencing pain and 3.0% developing wound infections. Higher preoperative BMI
was significantly associated with postoperative pain (OR: 1.47, 95% CI: 1.27-1.70, p<0.001), and longer hospital
stays were associated with overall complications. The model predicted postoperative pain with 96.7% accuracy
and an AUC of 0.93. Wound infection prediction had 97.5% accuracy with an AUC of 0.79. Conclusion:
Preoperative BMI and hospital stay duration are key factors influencing postoperative outcomes in CRC surgeries.
The developed model provides a useful tool for preoperative risk stratification, though further prospective studies
are necessary for broader validation.

Keywords: Colorectal cancer, mortality risk, postoperative complications, prediction model, Jordan.