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
Background The relationship between frailty and healthcare resource utilization in older patients with colorectal cancer (CRC) remains insufficiently quantified. We evaluated the associations of frailty with high inpatient costs, length of stay (LOS), and adverse events, and examined the explanatory roles of co-occurring comorbidity burden and postoperative complications. Methods This multicenter retrospective study analyzed 4,936 patients aged ≥60 years undergoing elective CRC surgery between 2014 and 2024. Hierarchical multivariable regression models evaluated associations between frailty and outcomes. Mediation-style decomposition was used to estimate the extent to which comorbidity burden and postoperative complications explained frailty-associated differences in high inpatient costs and LOS. A simulation-based sensitivity analysis was performed to assess the potential impact of ICD-10-based frailty misclassification. A Bonferroni-corrected threshold of p < 0.006 was applied. Results Frailty was significantly associated with high inpatient costs (OR = 1.274, 95% CI: 1.083–1.498, p = 0.003), prolonged LOS (log-transformed β = 0.082, 95% CI: 0.053–0.111, p < 0.001), and adverse events (OR = 3.317, 95% CI: 2.267–4.854, p < 0.001). Mediation-style decomposition showed that co-occurring comorbidity burden explained 28.6% of frailty-associated difference in high inpatient costs (p < 0.001). Postoperative complications did not significantly explain the frailty–LOS association (3.8%, p = 0.368). The estimated excess socioeconomic burden associated with frailty was CNY 657 million. In the sensitivity analysis, the direction of frailty associations with all three outcomes remained unchanged across simulated ICD-10 misclassification scenarios, although the association with high inpatient costs was attenuated under moderate and severe assumptions. Conclusion Frailty was associated with increased healthcare resource utilization and adverse outcomes in older CRC patients. Co-occurring comorbidity burden partly explained the frailty-associated difference in high inpatient costs, whereas prolonged LOS was not significantly explained by postoperative complications. These findings support routine frailty screening and dual-track perioperative optimization targeting both comorbidity burden and frailty-related physiological vulnerability.
Yixiang Huang, Jian-Chao Liu, Run-da Jiao et al.· Frontiers in Medicine· 0 citations
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