Survival outcomes of stage I colorectal cancer: development and validation of the ACEPLY model using two prospective cohorts

Author:

Wu Qingbin,Chen Pengju,Shu Chi,Chen Lin,Jin Zechuan,Huang Jun,Wang Xin,Li Xue,Wei Mingtian,Yang Tinghan,Deng Xiangbing,Wu Aiwen,He Yazhou,Wang Ziqiang

Abstract

AbstractBackgroundApproximately 10% of stage I colorectal cancer (CRC) patients experience unfavorable clinical outcomes after surgery. However, little is known about the subset of stage I patients who are predisposed to high risk of recurrence or death. Previous evidence was limited by small sample sizes and lack of validation.MethodsWe aimed to identify early indicators and develop a risk stratification model to inform prognosis of stage I patients by employing two large prospective cohorts. Prognostic factors for stage II tumors, including T stage, number of nodes examined, preoperative carcinoma embryonic antigen (CEA), lymphovascular invasion, perineural invasion (PNI), and tumor grade were investigated in the discovery cohort, and significant findings were further validated in the other cohort. We adopted disease-free survival (DFS) as the primary outcome for maximum statistical power and recurrence rate and overall survival (OS) as secondary outcomes. Hazard ratios (HRs) were estimated from Cox proportional hazard models, which were subsequently utilized to develop a multivariable model to predict DFS. Predictive performance was assessed in relation to discrimination, calibration and net benefit.ResultsA total of 728 and 413 patients were included for discovery and validation. Overall, 6.7% and 4.1% of the patients developed recurrences during follow-up. We identified consistent significant effects of PNI and higher preoperative CEA on inferior DFS in both the discovery (PNI: HR = 4.26, 95% CI: 1.70–10.67,p = 0.002; CEA: HR = 1.46, 95% CI: 1.13–1.87,p = 0.003) and the validation analysis (PNI: HR = 3.31, 95% CI: 1.01–10.89,p = 0.049; CEA: HR = 1.58, 95% CI: 1.10–2.28,p = 0.014). They were also significantly associated with recurrence rate. Age at diagnosis was a prominent determinant of OS. A prediction model on DFS usingAge at diagnosis,CEA,PNI, and number ofLYmph nodes examined (ACEPLY) showed significant discriminative performance (C-index: 0.69, 95% CI:0.60–0.77) in the external validation cohort. Decision curve analysis demonstrated added clinical benefit of applying the model for risk stratification.ConclusionsPNI and preoperative CEA are useful indicators for inferior survival outcomes of stage I CRC. Identification of stage I patients at high risk of recurrence is feasible using the ACEPLY model, although the predictive performance is yet to be improved.

Funder

National Natural Science Foundation of China

Sichuan Provincial Postdoctoral Science Foundation

Sichuan Province Science and Technology Support Program

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

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