Development and validation of a competitive risk model in patients with rectal cancer: based on SEER database

Rectal cancer (RC) is a type of cancer that occurs at the dentate line and colon-sigmoideum junctions [1]. Colorectal cancer is the fourth deadliest cancer in the world [2], and RC represents 40% of colorectal cancer cases. In the United States, there are 44,850 new RC cases (26,650 in men; 18,200 in women) in 2022 and 46,050 new RC cases (27,440 in men, 18,610 in women) in 2023, suggesting an increasing incidence [3]. Furthermore, the morbidity and mortality of RC are projected to rise dramatically by 2035 [4]. This cancer may be caused by several controllable risk factors, such as sedentary work [OR = 1.08 (95%CI: 1.00–1.16)] [5], male obesity [RR = 1.12 (95%CI: 1.09–1.16)] [6], red meat intake [RR = 1.22 (95% CI: 1.01–1.46)] [7], meat products [RR = 1.26 (95% CI = 1.09–1.45)] [7], and high alcohol intake [OR = 1.25 (95%CI: 1.11–1.40)] [8].

The distal third of the rectum is drained by systemic veins instead of the portal venous system, which increases the likelihood of direct lung metastases [9]. RC penetrates the pelvis more easily than colon cancer, with a higher risk of lymph node metastasis in each T stage, complex anatomical structures, difficult-to-operate surgery, and a high postoperative recurrence rate. Currently, treatments for RC include local or extensive surgery, preoperative radiotherapy and systemic therapy, local ablation of metastases, palliative chemotherapy, targeted therapy, and immunotherapy [10]. The selection of treatments is based on the tumor’s clinicopathological characteristics, such as the degree of differentiation and the site of metastasis [11, 12]. RC survival is closely related to clinical decisions based on staging information. The 5-year disease-free survival (DFS) and overall survival (OS) of patients with RC were 70.1% (95%CI: 60.7%–73.0%) and 76.2% (95%CI: 73.8%–78.5%) with open surgery, and 72.2% (95%CI: 69.4%–74.8%) and 72.7% (95%CI: 69.8%–75.3%) with laparoscopic surgery, respectively [13]. Compared with long-course chemoradiotherapy, both total neoadjuvant therapy with long-course chemoradiotherapy [OR = 1.78 (95%CI: 1.43–2.26)] and total neoadjuvant therapy with short-course radiotherapy [OR = 1.75(95%CI: 1.23–2.50)] improved the pathological complete response rate; neoadjuvant chemotherapy increased DFS, but did not significantly prolong OS [14]. At present, TNM staging is the primary reference in clinical practice. Other potential prognostic factors, such as age, sex, marriage, and region, are also strongly associated with prognosis [15]. Therefore, it is necessary to explore a more comprehensive prediction method. Clinical predictive models are more personalized approaches tailored to these factors.

The specific mortality risk is more valuable than the traditional mortality risk in clinical practice due to some unforeseeable mortality events. Specifically speaking, the causes of death in RC patients are diverse, and a large number of mortality events are not caused by RC, as RC patients are often in poor functional status or accompanied by co-morbidities [16]. These deaths are unforeseeable when patients die of other diseases, such as cardiovascular disease. In addition, as competing risks often occur among the diverse risk factors for death in patients with RC, traditional survival analysis methods may ignore the occurrence of main concern events, resulting in overestimated results [17]. Therefore, traditional survival analysis methods are unsuitable for processing data containing competing outcomes. A competing risk model is more suitable for dealing with data containing competing events and can produce more accurate results [17].

Since most patients with RC have a long survival period, identifying the risk of specific death early, in the case of competing events, is necessary to facilitate the development of specific prognostic rehabilitation programs and follow-up plans, thereby reducing the risk of specific death in patients. Although various prognostic models, especially based on radiomics, have been established in recent years, predictive models in clinical practice should be highly interpretable and applicable. Therefore, we conducted this study based on the SEER database to construct an interpretable nomogram for early predicting the risk of RC-specific mortality.

Based on univariate and multivariate analyses, we included the independent influencing factors of RC-specific death, including Age, Marriage, Race, Sex, ICD-O-3Hist/Behav, Grade, AJCC stage, T stage, N stage, Surgery, Examined LN, RX SUMM-SURG OTH, Chemotherapy, CEA, Deposits, Regional nodes positive, Brain, Bone, Liver, Lung, Tumor size, and Malignant. These variables were combined to construct a competing risk model for RC and a predictive nomogram, which have excellent accuracy. The overall C statistic was 0.821 (Se 0.001) in the model training cohort and 0.829 (Se 0.002) in the internal validation cohort.

Currently, there are various RC prediction nomograms based on clinical data [18‐21]. However, they are based on Cox regression. For example, a previous study reported that the consistency index (C index) was 0.71 (95% CI: 0.64–0.79) in the training cohort and 0.69 (95% CI: 0.61–0.78) in the validation cohort [21]. According to another research that constructed an RC risk prediction model based on the SEER database, the C index of the RC model was 0.756 (95% CI, 0.726–0.786) for the internal validation and 0.729 (95% CI, 0.678–0.780) for the external validation [22]. In contrast, the overall C statistic for the model in the validation set in our study was 0.829 (Se = 0.002). The reason for the differences in C-index is that the former two do not consider the effects of other causes of death, which can result in a severe bias in the specific mortality and an overestimated specific mortality. In our study, deaths from other causes accounted for approximately 10%. If these deaths were ignored, the accuracy of the model would be reduced. We compared the results of the competing risk model for RC and the traditional Cox proportional hazards model, and found differences in their mortality estimates. Other studies also have reported similar results and proposed that the COX model may also misestimate the direction of independent risk factors and the correlation between outcomes [23]. According to another competing risk model for early-stage RC-specific mortality [24], the AUC for predicting the 3-, 5-, and 10-year cancer-specific mortality was 82.2, 78.4, and 75 in the training cohort, and 83.4, 75.9, and 76.8 in the validation cohort, respectively. The different results may be due to an early-stage population, a small number of included cases, and insufficient risk indicators in the study.

Currently, the most widely used tumor prognosis prediction tool is the TNM staging. However, the use of the TNM system for RC has been questioned in recent years [25]. In some studies, a series of oxidative stress indicators significantly correlated with the survival rate of colorectal cancer patients were included to establish a CIOSS score system. The CIOSS score was reported to outperform the TNM staging in terms of survival prediction in patients with colorectal cancer [26]. Furthermore, a recent analysis showed that the survival pattern of colorectal cancer was heterogeneous even within the TNM classification [27]. Furthermore, a study attempted to use molecular and biochemical markers to aid in colon cancer staging [28]. In our research, specificity factors were added. Carcinoembryonic antigen (CEA) is now the most widely adopted and readily available tumor marker [29]. Many clinical scientists have evaluated the kinetic patterns of tumor markers as predictors [30]. One study found that patients with elevated postoperative CEA had an increased risk of recurrence [31]. Another study found a direct relationship between tumor volume and overall survival in RC patients [32]. Furthermore, the ratio of serum CEA to maximum tumor diameter may be a more important indicator for assessing tumor bioactivity with higher predictive value in RC [33]. Tumor deposits (TDs), especially solitary tumor nodules (in the mesocolic and mesorectal adipose tissue) at the lymphatic drainage zone of the primary tumor, are a hallmark of RC aggressiveness. The clinical value of TDs in treating RC is severely underestimated [34]. TD-positive tumors are classified as N1c without lymph node metastasis (LNM) in the NCCN guidelines [35], whereas neither the presence of TD nor the number of TD is considered for cases with LNM in the pN staging system. Recently, a clinical study found that tumor deposits in locally advanced RC had great predictive value in RC patients. TDs combined with lymph node metastasis could improve the accuracy of TNM staging [35‐37]. In addition, CEA [38, 39] and tumor deposits [40] were strongly associated with RC-specific death based on meta-analyses and evidence-based evidence.

The number of indicators involved in this paper is limited. More indicators should be included in the future to further explore the relationship between the research mechanism, clinical indicators, and prognosis. The occurrence of RC is thought to be closely related to the inflammation and oxidative stress of the intestinal epithelium, damaging the integrity of the intestinal barrier. Exposure to environmental toxins in the intestine enhances intestinal inflammation and releases reactive oxygen species (ROS) [41]. The indicators mentioned in this study, including the primary site of cancer [42], the surgical method [43], and lymph node organ metastasis [44], are all related to oxidative stress. For example, it was found that RC patients with a right-sided primary site had higher mean malondialdehyde serum levels than those with a primary site elsewhere [42]. The serum 8-isoprostanes (8-epiPGF2α) could be used to judge the oxidative state, and the degree of oxidative stress was found to be lower in laparoscopic surgery than in open RC surgery [43]. Additionally, the urinary 8-hydroxydeoxyguanosine (8-OHdG) content in colorectal cancer patients gradually increased from stage I to stage IV, and the urinary 8-OHdG content in patients with tumor metastasis was significantly higher than that of patients without tumor metastasis [42]. More oxidative stress or other specific indicators will be incorporated in the future.

Our predictive nomogram constructed based on a competing risk model is highly accurate in predicting time-specific mortality in RC patients and can assist clinicians in making clinical decisions and developing follow-up strategies. Subsequent studies should incorporate some other key factors or use other radiomics methods to further enhance the predictive performance of the model.