Background

Colorectal cancer is an important disease to control. It is one of the most commonly diagnosed cancers in the world, causing ~ 700,000 deaths each year [1]. Many patients with colorectal cancer also experience clinically important events, such as recurrences or metastases after diagnosis. Assessing the characteristics of potential disease outcomes and identifying their predictors are critical for effective patient surveillance, and to treat and control this disease in both the short term and long term. Studies have reported that the majority of the recurrences, metastases, and deaths from colorectal cancer occur within the first few years following the diagnosis or surgery [2, 3]. The main clinical surveillance guidelines recommend up to 5 years of follow-up [4].

Clinical features (e.g., disease stage, tumor grade, histology, location), demographic variables (e.g., age at diagnosis, sex, and familial risk status), and tumor characteristics (e.g., the MSI tumor phenotype and somatic mutations, including BRAF Val600Glu mutation) are among the most commonly investigated variables in colorectal cancer [5,6,7,8,9,10]. Familial risk status may indicate familial clustering of the disease and is an interest for both the susceptibility and prognostic studies [10, 11]. Microsatellite instability (MSI) is a tumor phenotype that is characterized by defects in the DNA mismatch repair system that leads to genomic instability [12]. Generally, MSI-high tumors are associated with better patient survival [7]. BRAF Val600Glu mutation occurs in ~ 10% of the colorectal tumors, causes oncogenic BRAF activity, and promotes cellular transformation [9]. Literature reports also suggest a prognostic role for this BRAF mutation in colorectal cancer [13].

Many prognostic studies aim to identify the markers to help distinguish the patients with different outcome risks. Potential time-varying effects of markers on the patient outcomes, however, are not well-studied. Markers with time-varying effects are those whose effect direction (e.g., protective or detrimental) or size (i.e., magnitude) changes over the follow-up [14,15,16,17,18]. There are at least two important implications of assessing the time-varying effects of the markers in prognostic studies. First, such markers are important as they can distinguish the patients who are at increased risk of events only during specific time periods (e.g., in the short term [early event markers] or the long term [late event markers or markers with late effects]). Second, examining the time-varying effects of variables is not a standard or widely utilized research practice, which potentially leads to loss of information or inaccurate inference [14, 19, 20].

In colorectal cancer, a few studies examined the clinical, demographic, or molecular variables for time-varying effects using statistical methods. For example, disease location [21]; age, disease stage, time period of diagnosis, or tumor site [15, 16, 18]; regional cancer, age, and tumor location (pelvic/sigmoid colon) [22]; age (in two of our previous studies using subsets of the patients included in this study) [23, 24]; tumor site (left or right), grade, sex, and stage [69,70,71]. As these authors discussed [69,70,71], a variety of potential mechanisms can explain this effect, such as the appearance or development of radiation-resistant tumor cells, changes in the tumor microenvironment or immune system response over time, or suppression of the tumor progression by radiation treatment that initially delays the tumor metastasis. These previous and our findings emphasize the need for new research revenues and potentially prolonged surveillance for late-onset metastatic lesions in colorectal cancer patients who are treated with adjuvant radiotherapy.

Strengths and limitations

Limitations of this study include the missing information on the cause of death for a portion of the patients; assuming that the non-colorectal cancer-related deaths were independent of colorectal cancer; having a small number of recurrences in the dataset, which may have limited the study power in analysis of recurrence-related outcomes; and examining select clinico-demographic and tumor molecular markers, which leaves it to future studies to examine the potential effects of other markers. Additionally, characteristics of the patients who are included in this study may differ from the patients who were diagnosed during the recruitment phase, but declined to consent and participate in NFCCR. This may affect the generalizability of the findings. However, it should also be noted that in some cases, the consent to access the medical records and tissue specimen was obtained from the close relatives/proxies of the patients who had died. Thus, the bias that may be introduced by the exclusion of advanced stage patients is expected to be lower in our study compared to many other studies [35]. This study also has a number of unique advantages: the cohort examined in this study is one of the longest followed up cohorts that allowed the systematic examination of long-term survival characteristics in colorectal cancer; this is a prospective cohort study that reduces information bias compared to retrospective cohort studies [72]; a comprehensive set of outcome measures were examined, which provided detailed information on survival patterns and relationships; and finally, the PH assumption in Cox regression models was checked, and the effects of variables were properly assessed—this not only increased the reliability of the effect estimations, but also allowed us to identify promising early and late effect markers.

Conclusions

In conclusion, this study describes the long-term survival characteristics of a prospective cohort of colorectal cancer patients and the detailed relationships between baseline variables and patient outcomes over a long time. Overall, our results increase the depth of information on patient outcomes and the markers of short-term and long-term risks and provide new insights that may assist future research and clinical care strategies in colorectal cancer.