Abstract

BackgroundRectal adenocarcinoma is one of major public health problems, severely threatening people’s health and life. Cox proportional hazard models have been applied in previous studies widely to analyze survival data. However, such models ignore competing risks and treat them as censored, resulting in excessive statistical errors. Therefore, a competing-risk model was applied with the aim of decreasing risk of bias and thereby obtaining more-accurate results and establishing a competing-risk nomogram for better guiding clinical practice.MethodsA total of 22,879 rectal adenocarcinoma cases who underwent primary-site surgical resection were collected from the SEER (Surveillance, Epidemiology, and End Results) database. Death due to rectal adenocarcinoma (DRA) and death due to other causes (DOC) were two competing endpoint events in the competing-risk regression analysis. The cumulative incidence function for DRA and DOC at each time point was calculated. Gray’s test was applied in the univariate analysis and Gray’s proportional subdistribution hazard model was adopted in the multivariable analysis to recognize significant differences among groups and obtain significant factors that could affect patients’ prognosis. Next, A competing-risk nomogram was established predicting the cause-specific outcome of rectal adenocarcinoma cases. Finally, we plotted calibration curve and calculated concordance indexes (c-index) to evaluate the model performance.Results22,879 patients were included finally. The results showed that age, race, marital status, chemotherapy, AJCC stage, tumor size, and number of metastasis lymph nodes were significant prognostic factors for postoperative rectal adenocarcinoma patients. We further successfully constructed a competing-risk nomogram to predict the 1-year, 3-year, and 5-year cause-specific mortality of rectal adenocarcinoma patients. The calibration curve and C-index indicated that the competing-risk nomogram model had satisfactory prognostic ability.ConclusionCompeting-risk analysis could help us obtain more-accurate results for rectal adenocarcinoma patients who had undergone surgery, which could definitely help clinicians obtain accurate prediction of the prognosis of patients and make better clinical decisions.

Highlights

  • Rectal adenocarcinoma is one of major public health problems, severely threatening people’s health and life

  • Patient characteristics 22,879 patients were included of whom 5,735 (25.07%) died due to rectal adenocarcinoma and 2529 (11.05%) were due to other causes (DOC) patients. 9345 (40.85%) of all patients were older than 65 years old

  • The competing-risk model utilized in the present study greatly decreased the bias, and so moreaccurate results were obtained for rectal adenocarcinoma that will allow better guidance of clinical practice

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Summary

Introduction

Rectal adenocarcinoma is one of major public health problems, severely threatening people’s health and life. Cox proportional hazard models have been applied in previous studies widely to analyze survival data. Such models ignore competing risks and treat them as censored, resulting in excessive statistical errors. Rectal adenocarcinoma has been a fairly common malignant tumor in the USA, which is diagnosed in nearly 50,000 patients annually [6]. The nomogram is regarded as an effective analytical and statistical tool to predict the outcomes of patients accurately. Because rectal adenocarcinoma undergoing surgical resection varies largely in prognosis, in this research, we sought to construct nomograms for predicting survival outcomes in postoperative patients with rectal adenocarcinoma

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