Nutritional risk score drives postoperative morbidity in colorectal cancer: findings from a LASSO-selected multivariable model in 1013 consecutive patients
This LASSO-derived nomogram provides transparent, bedside-applicable risk stratification for postoperative composite complications in CRC surgery, identifying nutritional status as the dominant modifiable predictor and supporting targeted perioperative optimization.
Abstract
Background Postoperative complications afflict approximately 40% of patients undergoing colorectal cancer (CRC) surgery and adversely affect long-term oncological outcomes. Reliable perioperative risk stratification tools that are both clinically interpretable and actionable remain limited. Methods This retrospective cohort study enrolled 1,013 consecutive patients undergoing elective radical resection for histopathologically confirmed CRC at a single tertiary center. A nine-system composite complication endpoint was defined. Missing data were handled via multiple imputation by chained equations (MICE; m = 5). Candidate predictors were screened by univariable logistic regression and LASSO regularization; final predictors were entered into multivariable logistic regression with Rubin’s rules pooling. Model performance was assessed by AUC, bootstrap internal validation (1,000 iterations), Hosmer–Lemeshow calibration, and decision curve analysis (DCA). A nomogram was constructed for individualized risk estimation. Results Of 1,013 patients, 372 (36.7%) experienced ≥1 postoperative complication. LASSO selected eight independent predictors: NRS-2002 nutritional risk score (aOR 1.502, 95% CI 1.312–1.720), laparoscopic approach (aOR 0.457, 95% CI 0.297–0.702), intraoperative blood loss (aOR 1.002/mL), right colon tumor location (aOR 1.502), NLR (aOR 1.080/unit), operative time (aOR 1.002/min), hemoglobin, and total bilirubin. The model achieved an apparent AUC of 0.689 (bootstrap-corrected 0.680), satisfactory calibration (Hosmer–Lemeshow p = 0.709), and net clinical benefit across threshold probabilities of 10–90% on DCA. Sensitivity analyses confirmed robustness across four pre-specified scenarios (AUC range 0.666–0.715). Conclusion This LASSO-derived nomogram provides transparent, bedside-applicable risk stratification for postoperative composite complications in CRC surgery, identifying nutritional status as the dominant modifiable predictor and supporting targeted perioperative optimization.
Combining frailty with an objective inflammation–nutrition risk composite modestly improved internal model performance for 30-day severe complications and 90-day readmission in older EC patients, and 1-year non-EC death analysis remains exploratory.
This interpretable 11-variable model enables early POP risk stratification after brain tumor surgery and may support timely preventive intervention in neurosurgical care.
H. Mao, Fengchun Mu, Xinyu Wang et al.· Frontiers in Cellular and In...· 0 citations
Background Urinary dysfunction is a relatively common functional complication after laparoscopic radical surgery for rectal cancer and may affect postoperative recovery and quality of life. This study aimed to identify risk factors for urinary dysfunction after laparoscopic radical rectal cancer surgery and to develop a nomogram prediction model to facilitate early identification of high-risk patients. Methods A total of 392 patients who underwent laparoscopic radical surgery for rectal cancer between January 2021 and December 2025 were retrospectively included. Patients were grouped according to the occurrence of postoperative urinary dysfunction and randomly divided into a training cohort and a validation cohort at a ratio of 7:3. Demographic, tumor-related, and perioperative variables were collected. Univariable and multivariable logistic regression analyses were performed to identify independent predictors, and a nomogram model was constructed. Model performance was evaluated using receiver operating characteristic curves, calibration curves, the Hosmer-Lemeshow test, and decision curve analysis. Results Among the 392 patients, 84 developed postoperative urinary dysfunction, with an incidence of 21.4%. Multivariable logistic regression analysis showed that age ≥65 years, male sex, tumor distance from the anal verge ≤5 cm, intraoperative fluid rate ≥10 mL/kg/h, neoadjuvant chemoradiotherapy, documented incomplete pelvic autonomic nerve preservation, and postoperative urinary tract infection were independent factors associated with postoperative urinary dysfunction. A nomogram was constructed based on these predictors. The area under the curve was 0.864 (95% CI: 0.803–0.926) in the training cohort and 0.856 (95% CI: 0.774–0.938) in the validation cohort. Calibration curves and the Hosmer-Lemeshow test indicated good model fit, and decision curve analysis showed favorable clinical net benefit. Conclusion Age, sex, tumor distance from the anal verge, intraoperative fluid rate, neoadjuvant chemoradiotherapy, pelvic autonomic nerve preservation, and postoperative urinary tract infection were closely associated with urinary dysfunction after laparoscopic radical surgery for rectal cancer. The nomogram based on these factors showed good predictive performance and may help identify high-risk patients, guide urinary catheter management, and support postoperative follow-up.
Background Elderly patients with colon cancer are at increased risk of major postoperative adverse events, but existing risk assessment tools often require detailed clinical or laboratory information. We developed and internally validated a rapid prediction nomogram using routinely available administrative variables. Methods This multicenter retrospective study included 4, 942 elderly patients with colon cancer from five hospitals. Major postoperative adverse events were identified using a predefined ICD-10 code-based algorithm adapted from the Healthgrades patient-safety framework. Given the low event rate, Firth penalized likelihood regression was used to develop the prediction model. Internal validation was performed using 1, 000 bootstrap resamples. Model performance was assessed by discrimination, calibration, Brier score, and decision curve analysis. Results Independent predictors included payment method (medical insurance: OR = 2.630), admission type (outpatient: OR = 0.501), surgical approach (minimally invasive: OR = 0.473), and comorbidity index (OR = 1.041). The full model showed moderate discrimination, with an apparent AUC of 0.724 and a bootstrap-corrected AUC of 0.709. The apparent and bootstrap-corrected Brier scores were 0.0244 and 0.0247, respectively. Decision curve analysis suggested potential net benefit across threshold probabilities of 1%–51%. Conclusion This nomogram may serve as a rapid, low-cost preliminary screening tool for estimating the risk of major postoperative adverse events in elderly patients with colon cancer. External validation and further refinement using more detailed clinical, nutritional, oncological, and functional variables are needed before broader clinical application.
Yixiang Huang, Xiaohui Yuan, Xiangbo Zhang et al.· Frontiers in Oncology· 0 citations
Standard preoperative variables are insufficient for individualized risk stratification of RLNP, anastomotic leak, or vocal cord palsy after esophagectomy, and improved prediction will require prospective integration of real-time intraoperative data.
Si-miao Lu, Yi Zhu, Yong-tao Han et al.· Diseases of the esophagus· 0 citations
Background Accurate preoperative risk stratification remains a major clinical challenge in patients with colorectal cancer (CRC) undergoing radical surgery. Simple and readily available biomarkers that reflect systemic inflammation and nutritional status may improve prognostic assessment in routine clinical practice. Methods This retrospective study included 581 patients with CRC who underwent radical surgery as the training cohort. Overall survival (OS) and disease-free survival (DFS) were the primary endpoints. NPAR was analyzed primarily as a continuous variable standardized per 1-SD increase. A pre-specified final model including NPAR, age, sex, tumor site, pathological stage, and log10-transformed CEA was used consistently across Cox regression, nomogram development, time-dependent ROC analysis, calibration, decision-curve analysis, and external validation. Dichotomized NPAR was retained only for descriptive and supplementary analyses. External validation was performed in 483 patients from an external clinical database. Results In the training cohort, higher preoperative NPAR was associated with adverse clinicopathological features. After adjustment for age, sex, tumor site, pathological stage, and log10-transformed CEA, each 1-SD increase in NPAR was associated with shorter OS (HR 2.19, 95% CI 1.90–2.53, p < 0.001) and DFS (HR 1.88, 95% CI 1.62–2.19, p < 0.001). The final model showed optimism-corrected C-indexes of 0.835 for OS and 0.752 for DFS in the training cohort. In the external cohort, the association between continuous NPAR and outcomes was directionally consistent but attenuated for both OS (HR 1.21, 95% CI 1.08–1.35, p < 0.001) and DFS (HR 1.24, 95% CI 1.12–1.37, p < 0.001). External C-indexes were 0.690 for OS and 0.705 for DFS. Adding NPAR to the baseline clinicopathological model did not improve external time-dependent discrimination for OS and showed only limited incremental value for DFS. Low external recalibration slopes suggested possible optimism in the training model. Conclusion Preoperative NPAR showed an adjusted association with OS and DFS, and the direction of this association was reproduced in the external cohort. However, its incremental predictive value beyond conventional clinicopathological factors was limited, particularly for OS. NPAR may be considered a simple adjunctive marker of inflammatory and nutritional status, but its clinical utility for individualized risk prediction requires further validation in larger prospective cohorts.
Alafate Yilamu, Aikeremu Yusufu, Saibihutula Ababek et al.· Frontiers in Oncology· 0 citations
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