Most eligible candidates for primary tumor resection among metastatic colorectal cancer patients: a SEER-based population analysis

Introduction

Radical resection of the primary tumor with curative intention represents the standard of care for early colorectal cancer (CRC). However, radical primary tumor resection (PTR) in metastatic colorectal cancer (mCRC) does not cure the condition. Currently, modern combinate radiation and chemotherapy including targeted therapy as well as immune checkpoint inhibitors are used to improve the prognosis and survival of such patients (1-3). Radiotherapy in particular has been shown to be a good option for patients with rectal cancer (4). Since PTR alone cannot cure metastatic patients, surgical in such a setting is usually palliative to manage complications like obstruction, perforation or intractable bleeding, fistula, etc. (5). Nevertheless, PTR can still reduce patient mortality in selected cases (6,7).

The role of surgery in mCRC patients may have been a matter of controversy. Several studies have shown a significant improvement in survival of mCRC patients following PTR (8-11). When the number and size of metastatic lesions are limited, 5-year overall survival (OS) rates of approximately 20% may be reached following PTR (12,13). In a recently published meta-analysis, the 3-year OS rate and the 5-year OS rate were higher in the surgical group than in the non-surgical group (14). In addition, PTR can restore partial immunocompetence (15), offering hope for subsequent immunotherapy. Unfortunately, surgery may also increase the risk of other complications, including those related to anesthesia, blood transfusions, anastomotic leak, and postoperative infections, which can lead to death. Studies have shown that not all mCRC patients would benefit from surgery. However, it remains unclear which patients may benefit from PTR (16,17).

Thus, this study sought to develop and validate a predictive model using big data to assist clinicians to identify the most eligible candidates for PTR in the setting of mCRC and quantify the likelihood that they will benefit from PTR. We present this article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1084/rc).

Methods

Patients

The Surveillance, Epidemiology, and End Results (SEER) Program (https://seer.cancer.gov/) is the largest and most authoritative database of tumor-related information in the United States (U.S). From 2011 to 2018, the SEER database covers approximately 28% of the U.S. population, and up to 97% of cancer incidence rates (18). It collects data on the demographics, clinicopathological characteristics, treatment modalities, and survival of cancer patients. As the data in this study were obtained from the SEER database using SEER*Stat version 8.3.9 (Registration No. 17070-Nov2020), there was no need for an ethical review. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments (19).

Patients with mCRC treated between 2010 and 2018 (tumor site codes: C18.2–C18.9 and C19.9–C20.9) were included in the study. Patients were excluded from the study if they met any of the following exclusion criteria: (I) had undergone an unknown operation at the primary or distant sites; (II) had multiple primary tumors; (III) had unknown T and N stages, and an unknown differentiation degree; (IV) had incomplete ethnic and survival information; (V) had a non-pathological diagnosis or autopsy source; and/or (VI) were under 18 years of age. The surgical group comprised patients treated with PTR. OS was defined as the period between the cancer diagnosis and the last follow-up date or death from any cause. Cancer-specific survival (CSS) was defined as the period between cancer diagnosis and death from CRC.

Variables

The patients’ demographic data collected and included in the study from the SEER Program included: age, gender, ethnicity, clinicopathological features, including tumor, node, and metastasis (TNM) staging, histology and differentiation degree, bone, liver, lung, and brain metastasis, carcinoembryonic antigen (CEA), primary tumor site, and surgical and adjuvant therapies (radiotherapy and chemotherapy). The age of the patients ranged from 18 to 100 years. The ethnicities of the patients were white, black, and others. TNM staging was based on the 7^th American Joint Commission on Cancer (20). Histology was divided into adenocarcinoma and others. Tumor sites included the right colon (from the cecum to the transverse colon), left colon (from the splenic flexure to the rectosigmoid junction), and rectum.

Statistical analysis

In this study, all the enrolled patients were divided into the surgical and non-surgical groups. To increase the credibility of the study, propensity score matching (PSM) was used to balance all the baseline characteristics of the patients in both groups, and the nearest neighbor principle was adopted for 1:1 matching. The categorical data are expressed as frequencies and percentages, and were tested using the Chi-squared test or Fisher’s precise test. The continuous data are expressed as the mean and standard deviation (SD), and were compared using the Mann-Whitney U test. The OS and CSS curves were plotted using the Kaplan-Meier (K-M) method, and were compared using the log-series test. The Cox proportional hazard regression model was used for the univariate and multivariate analyses of the cohort after PSM to identify the independent risk factors affecting the prognosis and survival of patients in the two groups. The hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were calculated, as well as the two-sided P values; a P value <0.05 was considered statistically significant.

Construction and validation of nomogram

In the surgical group, after PSM, patients with median overall survival (mOS: 16 months) longer than that of those in the non-surgical group were allocated to the surgical-benefit group and non-surgical benefit group. To strengthen the significance of the investigation, we excluded deceased patients whose survival time was equal to or less than 16 months at the end of the follow-up period. The remaining patients were then randomly assigned to either the training group or validation group on a 7:3 basis. Univariate and multivariate analyses were performed in the training group using logistic regression to identify the clinical and demographic characteristics of the mCRC patients who could benefit from surgery. Eventually, based on the factors related to surgical benefit, a nomograph was constructed to predict and visualize the likelihood of benefit for patients undergoing surgery. To validate the accuracy of this model, the concordance index (C-index), area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and calibration curves were used for assessment in the training group and validation group, and the fitness of the model was assessed by the Hosmer-Lemesshow test (21). Finally, a decision curve analysis (DCA) was used to assess the model clinical applicability and predictive ability.

In addition, according to the scores of each covariate in the nomograph, the total score of each patient in the surgical group after PSM was calculated to further confirm nomograph accuracy and practicability. If a patient’s total score exceeded a corresponding score for a 50% probability of benefit, that patient was assigned to the surgical-benefit group, and the others are in the non-surgical benefit group. A K-M analysis and the log-rank test were used to evaluate whether the model could identify patients who could benefit from PTR. All the statistical analyses in this study were performed using R 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria; http://www.r-project.org) and related software packages.

Results

Baseline characteristics of patients

The data of 280,790 CRC patients were recorded in the SEER database from 2010 to 2018, including 54,557 in stage IV. After screening according to the inclusion and exclusion criteria (Figure 1), 11,763 patients were included in the study, of whom 8,808 (74.88%) received PTR. As Table 1 shows, there was no significant difference (P=0.20) between the surgical and non-surgical groups in terms of ethnicity; however, there were significant differences in other demographic and clinical pathological characteristics between the two groups (P<0.05). To eliminate the effect of this bias, 3,476 patients were enrolled in both the surgical and non-surgical groups after 1:1 PSM, with all the baseline characteristics well balanced (P>0.1). A forest map of the subgroup analysis (Figure 2) showed that the prognosis of the patients in the surgical group was better than that of those in the non-surgical group at each stratum (HR >1; P<0.05).

Figure 1 Flow chart. mOS, median overall survival; PSM, propensity score matching; PTR, primary tumor resection; SEER, Surveillance, Epidemiology, and End Results.

Figure 2 Hazard ratios of cancer-specific survival for the surgery and non-surgery groups. (A) Before PSM; (B) After PSM. AC, adenocarcinoma; CEA, carcinoembryonic antigen; LC, left colon; M, metastasis; N, node; PSM, propensity score matching; RC, right colon; T, tumor.

Effects of PTR and metastasis on survival and prognosis in mCRC patients

Before PSM, the median OS was 27 and 15 months (P<0.001), and the median CSS was 29 and 16 months (P<0.001) of the surgical and non-surgical groups, respectively, and there were no significant differences in the mOS and median CSS before and after PSM after eliminating the effects of the baseline characteristics using PSM (Figure 3A-3D). In addition, after PSM, the 1-, 3-, and 5-year CSS rates were 75.6%, 41.1%, and 23.5% in the surgical group, and 60.0%, 20.7%, and 10.0% in the non-surgical group, respectively. The prognosis of patients in the surgical group was generally better than that of those in the non-surgical group (the specific survival rates are detailed in Table S1). Patients who received PTR combined with chemotherapy (mOS: 29 months) had a better prognosis than those who received chemotherapy alone (mOS: 18 months) (P<0.001) (Figure 3E,3F).

Figure 3 K-M survival analysis. (A) OS before PSM; (B) CSS before PSM; (C) OS after PSM; (D) CSS after PSM; (E) OS in the PTR + chemotherapy group and chemotherapy group after PSM; (F) CSS in the PTR + chemotherapy group and chemotherapy group after PSM. Before PSM [surgery group (N=8,808), non-surgery group (N=2,955)]. After PSM [surgery group (N=1,738), non-surgery group (N=1,738)]. CSS, cancer-specific survival; mCSS, median cancer-specific survival; mOS, median overall survival; K-M, Kaplan-Meier; OS, overall survival; PSM, propensity score matching; PTR, primary tumor resection.

In this study, we found that among the mCRC patients with liver metastasis only, the rectal cancer patients had the best prognosis (mOS: 27 months), followed by the left colon cancer patients (mOS: 20 months), and was the worst in the right colon cancer patients (mOS: 13 months), and the difference was statistically significant. Further, in the patients with lung metastasis, the right colon cancer patients (mOS: 14 months) had a worse prognosis than the rectal cancer (mOS: 35 months) and left colon cancer (mOS: 22 months) patients (P<0.001). Notably, the same conclusion that the prognosis of right colon cancer is worse than that of left colon and rectal cancer was reached for patients with both liver and lung metastases (P<0.001) (Figure 4A-4C). In addition, among the mCRC patients with single organ metastasis, the lung metastasis patients (mOS: 26 months) had the best prognosis, followed by the liver metastasis patients (mOS: 22 months), while the brain metastasis patients had the worst prognosis (mOS: 8 months) (P<0.001) (Figure 4D).

Figure 4 K-M survival analysis. (A) OS of different primary sites in patients with liver metastases; (B) OS of different primary sites in patients with lung metastases; (C) OS of different primary sites in patients with liver and lung metastases; (D) OS of mCRC patients with different metastatic sites. mCRC, metastatic colorectal cancer; mOS, median overall survival; K-M, Kaplan-Meier; OS, overall survival.

Cox survival analysis outcome

To explore the independent prognostic factors related to the prognosis of the mCRC patients, univariate and multivariate Cox analyses were used for the CSS analysis (Table 2). We found that surgery at the primary site was significantly correlated with patient prognosis. Further, age, ethnicity, negative or positive CEA, TNM staging, grade, bone metastasis, liver metastasis, histology, primary tumor site, distant metastasis surgery (or no surgery), and chemotherapy were all independent prognostic factors of CSS.

Construction of nomograph to identify most eligible candidates

Based on the survival analysis, the survival time of the surgical patients was significantly better than that of the non-surgical patients, but not all the surgical patients benefitted from PTR. Therefore, we established a surgical-benefit group of patients from the surgical group whose survival time exceeded the mOS (16 months) of the non-surgical group. To improve the accuracy of the study outcomes, 38 patients with a survival time equal to 16 months, and 145 patients with a survival time of less than 16 months, who were alive at the end of the follow-up, were excluded from the analysis. Ultimately, the surgical-benefit group comprised 1,029 patients (66.17%) and the non-surgical benefit group comprised 526 patients (33.83%). The patients were then randomized on a 7:3 basis, and the independent factors for the benefit of PTR for mCRC patients were identified in the training group using univariate and multivariate logistic analyses. The independent factors affecting primary surgical resection included age (P<0.001), CEA (P=0.002), N staging (P<0.05), M staging (P<0.001), histology (P<0.001), primary site (P<0.05), liver metastasis (P<0.001), lung metastasis (P<0.05), bone metastasis (P<0.05), and chemotherapy (P<0.001) (Table 3). Based on these 10 factors, a predictive model was developed to screen mCRC surgical candidates (Figure 5). Based on the patient-specific baseline characteristics, the scores for each independent prognostic factor were added to quantify their potential benefits (Tables S2,S3).

Figure 5 A nomogram for selecting the most eligible candidates for PTR among mCRC patients. AC, adenocarcinoma; CEA, carcinoembryonic antigen; LC, left colon; M, metastasis; mCRC, metastatic colorectal cancer; N, node; PTR, primary tumor resection; RC, right colon.

Validation and clinical applicability of the predictive model

A calibration graph was used to validate the stability of the nomograph in the training and validation groups. As Figure 6A,6B show, the predicted survival results were in good agreement with the actual results. The calculated C-index values were 0.727 and 0.742 in the validation and training groups, respectively, and the resulting ROC curves are presented in Figure 6C,6D. In the training and validation groups, the AUC and C-index values were highly consistent at 0.727 (95% CI: 0.697–0.757) and 0.742 (95% CI: 0.696–0.788), respectively, indicating good consistency between the predicted and actual survival results.

Figure 6 Verify the accuracy and stability of the nomogram. (A) The calibration plots of the training group. (B) The calibration plots of the validation group. (C) Receiver operating characteristic curve of the training group. (D) Receiver operating characteristic curve of the validation group. (E) Decision curve analyses of the training group. (F) Decision curve analyses of the validation group. AUC, area under the curve; ROC, receiver operating characteristic.

A DCA was conducted to assess the net clinical benefit of the predictive model, with threshold probability on the horizontal axis and net gain rate on the vertical axis. As Figure 6E,6F show, this model had a good clinical application value. Finally, to further examine its applicability, the patients with a probability of benefit higher than 0.5 were allocated to the surgical-benefit group, and the rest were allocated to the non-surgical benefit group based on the total score of each patient (in the cohort after PSM) in the predictive model. The K-M survival curve was then used to analyze the differentiation ability of this model. As Figure 7A,7B show, the OS and CSS of the surgical-benefit group after surgery were significantly higher compared to those of the non-surgical benefit group and non-surgical group (P<0.001), while the OS of the non-surgical benefit group was significantly lower than that of the non-surgical group (P<0.001). Therefore, not all surgical patients benefitted from surgery, and our model had high accuracy in patient selection.

Figure 7 Validation of nomograms in the PSM cohort. K-M survival analysis of patients in the surgical-benefit group, non-surgical benefit group, and non-surgical group. (A) OS; (B) CSS. CSS, cancer-specific survival; K-M, Kaplan-Meier; mCSS, median cancer-specific survival; mOS, median overall survival; OS, overall survival; PSM, propensity score matching.

Discussion

In this study, we used data from the SEER public database to investigate the prognosis of patients with mCRC, comparing the outcomes of those undergoing resection of the primary cancer to those not managed surgically. Using PSM information we identified independent risk factors for the survival and prognosis of mCRC patients. Based on these risk factors, we were able to generate a prediction model to help clinical physicians select suitable surgical patients that may benefit for resection of the primary cancer, and quantify their benefit probabilities. The model was found to have high accuracy, and thus has practical potential in daily practice.

It is estimated that about 25% of CRC patients have liver metastasis at the time of initial diagnosis (22), and about half are reported to have liver metastasis after death (23). Similar to reports from a previous study (24), in this study, about 70% of the patients had liver metastasis, and about 22.3% had lung metastasis. The location of the metastasis was correlated with the prognosis of patients, and patients with brain metastasis have the worst prognosis (25). We found that the mOS of patients with brain metastasis in this investigation was only 8 months. Surgical resection of distant intrahepatic metastases in patients with colorectal cancer liver metastases can improve survival when surgery is tolerated, but surgery distant is not an independent prognostic risk factor in this article, which may be related to limitations and lack of data (26). Different primary tumor sites have different prognoses. This study confirmed that the prognosis of patients with left colon and rectal cancer was better than that of patients with right colon cancer, which as previously reported may be related to molecular and pathological features (27,28).

Chemotherapeutic and targeted therapeutic drugs have led to great improvements in the prognosis of metastatic CRC patients; however, the 5-year OS of such patients is only 8–20% (29,30). Thus, the significance of surgery needs to be reconsidered. PTR treatment for mCRC is controversial (7,31-33). According to the National Comprehensive Cancer Network (NCCN) guidelines and European Society for Medical Oncology (ESMO) recommendations (34,35), mCRC patients who have been definitively diagnosed with resectable tumors can receive direct surgical treatment, while those with unresectable tumors tend to receive systematic treatments, such as multiple cytotoxic agents and targeted therapy (36). However, studies have shown that palliative PTR improves the prognosis of patients (37-39). Our study also confirmed that PTR is an independent prognostic factor for patients, and the survival of the patients in the surgical group was significantly prolonged compared with that of the patients in non-surgical group (29 vs. 16 months). Even after PSM, this finding remained valid, Some patients who undergo surgery, even palliative surgery, can still benefit some patients, so we advocate aggressive surgical treatment (40).

We also compared the survival of patients undergoing PTR combined with chemotherapy with those who received only chemotherapy, and found that PTR combined with chemotherapy greatly improved the survival of patients, an observation that have been reported previously (33,41). The reasons why PTR prolongs the survival time of patients are unknown, but the reduction of circulating tumor cells (CTCs) may be a factor. Studies (42,43) have shown that high CTC levels lead to micrometastasis, which will eventually develop into distant metastasis, such as liver metastasis and lung metastasis, and PTR can reverse tumor-induced immunosuppression (15). The resection of distant metastasis has also been shown to significantly improve the prognosis of patients (37,44), especially those with solitary metastasis of the liver and lung. As mentioned earlier, surgery for distant metastasis was another important prognostic factor in the Cox analysis of this study.

The initial types of tumors (e.g., resectable, potentially resectable, and unresectable) are not recorded in the SEER database, which is one of the limitations of this study. The latest randomized trial (45) reported that PTR did not improve the survival rate of patients with unresectable mCRC, which is contrary to the conclusions from previous retrospective analysis (44,45). Another randomized trial found that PTR improved the CSS rate (46), which shows that not all patients benefit from surgical treatment. Thus, a prediction model needs to be established to select surgical patients, and more prospective studies (47-49). A study has shown that modern chemotherapy combination and age have the greatest influence on the prognosis of PTR patients—the older the patient, the worse the prognosis (50). Notably, the morbidity and mortality of elderly patients are decreasing year by year, which might be related to the continuous improvement of cancer screening, treatment methods, and early diagnosis (51). However, the incidence of CRC is increasing in younger adults, which may be related to the different genes and clinical pathologies of young and elderly patients (51,52); thus, corresponding strategies should be developed (53). Modern chemotherapy combination plays an important role in metastatic CRC, as it can significantly prolong the survival time of patients (2,36,54-56), and transform potentially resectable patients into resectable patients, thereby increasing the probability of surgery. However, not all patients benefit from systemic chemotherapy (28). One meta-analysis (6) showed that when unresectable stage IV patients initially receive chemotherapy, about 22% experience tumor-related complications, of whom, about 87% require surgical treatment, which shows the importance of PTR. However, another meta-analysis (10) showed that not all patients are suited to PTR; thus, it is particularly important to select suitable patients. In this regard, our prediction model has high practical value, and our results showed that its accuracy is satisfactory.

Inevitably, our study had a number of limitations. First, the study used the data from the SEER database, so there may be some sort of selection bias. Second, data on the initial states of tumors (i.e., resectable, potentially resectable, or unresectable) are not recorded in the SEER database. Third, the data of the SEER database are imperfect, as they lack detailed information on the surgical method, short-term surgical outcomes, chemotherapy regimen, immunological and targeted therapies, general situation of patients, and complications (e.g., intestinal obstruction, bleeding, and perforation). Fourth, the data of CEA and N stages are not recorded in detail in the database. Fourth, the data of CEA and N stages are not recorded in detail in the database. Sixth, this was a retrospective study and lacks external data validation. As a result, in the future, prospective studies need to be conducted to validate the results.

Conclusions

This study showed that not all mCRC patients benefit from surgery. Thus, we established and verified a prediction model to help surgeons select the most eligible candidates, provide more refined treatment to patients, and improve patient prognosis.

Acknowledgments

The authors would like to thank the SEER Project Registry and the entire staff for their efforts in creating the database.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1084/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1084/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1084/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: L. Huleatt)