Abstract
Background:
This study evaluated the clinical value of a new American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging prediction model based on lymph node ratio (LNR) in rectosigmoid cancer (RSC).
Methods:
The analysis included 1444 patients with nonmetastatic RSC diagnosed pathologically between 2010 and 2016 who were collected from the National Cancer Institute Surveillance, Epidemiology, and Results database. The AJCC N-stage was redefined according to the LNR cutoff point, and the ability of the new staging system to predict prognosis was compared with that of the AJCC TNM staging system. Data from 739 patients from our hospital were used for external validation.
Results:
According to the number of examined lymph nodes and LNR, the N stage was divided into five groups (LNR0–5). The 5-year OS of patients divided according to the new T lymph node ratio M (TLNRM) staging into stage I (T1LNR1, T1LNR2), IIA (T1LNR3, T2LNR1, T2LNR2, T2LNR3, T1LNR4, T3LNR1), IIB (T2LNR4), IIC (T3LNR2, T4a LNR1, T1LNR5), IIIA (T3LNR3, T2LNR5, T4b LNR1, T4a LNR2, T3LNR4), IIIB (T3LNR5, T4a LNR3, T4a LNR4, T4b LNR2), and IIIC (T4b LNR3, T4a LNR5, T4b LNR4, T4b LNR5) was significantly different (P<0.05). Decision curve analysis showed that the net income of the new TLNRM staging system for different decision thresholds was higher than the prediction line of the traditional eighth TNM staging system. The smaller Akaike information criterion and Bayesian information suggested that the new staging system had a higher sensitivity for predicting prognosis than the traditional staging system. TLNRM II and III patients benefited from adjuvant chemotherapy, while adjuvant chemotherapy did not improve the prognosis of TNM II patients. These findings were confirmed by the external validation data.
Conclusion:
The new TLNRM staging system was superior to the eighth edition AJCC staging system for staging and predicting the prognosis of patients with RSC and may become an effective tool in clinical practice.
Keywords: lymph node ratio, lymph node, OS, rectosigmoid cancer, stage
Background
Highlights
This study established the clinical value of a new American Joint Committee on Cancer tumor node metastasis staging prediction model.
The new T lymph node ratio M staging system was superior to the traditional eighth tumor node metastasis staging system.
T lymph node ratio M II and III rectosigmoid cancer patients benefited from adjuvant chemotherapy.
According to the 2020 global cancer statistics, rectal cancer ranks 8th in incidence and 9th in mortality1. There is no unified definition of rectosigmoid cancer (RSC), and the current theory defines it as surgical rectum2. Therefore, the staging and treatment of RSC are based on the established protocols for rectal cancer, underscoring the need to develop specific staging and treatment methods for RSC to provide more accurate treatments for patients with this disease. At present, the most commonly used clinical staging prediction model for rectal cancer is the eighth version of the tumor node metastasis (TNM) classification system proposed by the American Joint Committee on Cancer (AJCC)3–5. However, the N stage, according to AJCC staging is based solely on the number of positive lymph nodes (PLN). The number of examined lymph nodes (ELN) by surgery is positively correlated with the number of PLN, and the number of ELN during surgery is a key factor for evaluating the efficacy of radical resection of rectal cancer.
Considering the specificity of the location of RSC and the shortcomings of N staging, we propose a new staging method based on the positive lymph node ratio (LNR) to improve the traditional staging6–8. LNR is the ratio of the number of PLN to the total number of ELN. Its ability to predict the prognosis of patients is not affected by the number of ELN. The independent predictive ability of LNR in colorectal cancer has been demonstrated. The establishment of new LNR grouping variables will improve the prognostic stratification of RSC patients9–11.
In this study, RSC data from the Surveillance, Epidemiology, and End Results (SEER) Database were used to divide N stage patients into five groups according to LNR. The sensitivity of the new T lymph node ratio M (TLNRM) staging system was compared with that of traditional staging, and the accuracy of the patient’s prognostic evaluation was assessed, which selected the population that could most benefit from adjuvant chemotherapy (ACT). The advantages of the new TLNRM staging were verified using external data.
Methods
Patient cohort
SEER * Stat (version 8.4.0) software was used to search 1444 cases of nonmetastatic RSC diagnosed between 2010 and 2016. The inclusion criteria were as follows: patients with RSC diagnosed by pathology (ICD-O-3: C19.9), complete follow-up and survival data, no neoadjuvant radiotherapy and chemotherapy, underwent radical laparoscopic surgery, and primary RSC. The variables included in this study included age, sex, race, grade, size, T stage, ELN, PLN, and survival information. Patients with missing information were excluded. The external validation data were obtained from 739 patients with nonmetastatic RSC who underwent surgery in our department between 2010 and 2017. Advanced patients received ACT with the XELOX regimen. The staging of all patients was adjusted to the TNM staging, eighth edition. The work has been reported in line with the strengthening the reporting of cohort, cross-sectional and case–control studies in surgery (STROCSS) criteria.
Statistical analysis
The distribution of clinical and pathological factors was assessed. When LNR=0, X-tile software was used to divide the patients into two groups: LNR1 (n=133) (ELN 0–4) and LNR2 (n=327) (ELN 5–12). When LNR greater than 0, X-tile software was used to select two cutoff values to divide the patients into three groups: LNR3 (n=427; ratio 0.08–0.22), LNR4 (n=198; ratio 0.25–0.45), and LNR5 (n=359; ratio 0.50–1.00). An improved TLNRM staging system was established by replacing N staging from the eighth version of AJCC staging with the corresponding LNR staging.
The patients were divided into 25 groups (T1-4bLNR1-5M0). The hazard ratio (HR) of T1LNR1M0 was defined as 1, which was sorted from low to high. The two adjacent groups were tested by the log-rank of OS. Six groups with large differences were selected from 24 χ 2 values, and the 25 groups were divided into 7 stages.
The effectiveness of the TLNRM staging system was compared with that of the eighth edition AJCC staging system in terms of prognosis discrimination. The discrimination ability of the two staging systems was quantified using the Akaike information criterion (AIC) and Bayesian information (BIC)12. The clinical net benefits were evaluated by decision curve analysis (DCA) and compared with those of the eighth edition of the AJCC staging system13. The χ 2-test was used to evaluate the prognostic homogeneity of the two staging systems (the greater the likelihood ratio, the better the prognostic homogeneity of the staging system), and survival curves and COX analysis were used to analyze the prognosis of patients in different stages. SPSS 24.0 and R language (version 4.0.0) were used for all statistical analyses, and P<0.05 was considered as statistically significant.
Results
Patient demographics
A total of 1444 patients with RSC were included according to the inclusion criteria (Fig. 1). There were 846 patients (58.6%) greater than or equal to 65-year-old and 719 patients (49.8%) with T3-4b. The median number of ELN was 9, and the median number of PLN was 2 (Table 1). The median survival of patients was 85 months (0–191) and the number of deaths was 764 (52.9%).
Figure 1.
Flowchart of the selection process of included patients. AIC, Akaike information criterion; BIC, Bayesian information; DCA, decision curve analysis; SEER, Surveillance, Epidemiology, and End Results.
Table 1.
Characteristics of patients.
| Variable | Total [n (%)] | Training [n (%)] | External [n (%)] | P |
|---|---|---|---|---|
| Age | 1444 | 739 | <0.001 | |
| <65 | 598 (41.4) | 506 (68.5) | ||
| ≥65 | 846 (58.6) | 233 (31.5) | ||
| Sex | <0.001 | |||
| Male | 784 (54.3) | 527 (71.3) | ||
| Female | 660 (45.7) | 212 (28.7) | ||
| Race | <0.001 | |||
| White | 1108 (76.7) | 0 (0.0) | ||
| Black | 99 (6.9) | 0 (0.0) | ||
| API | 217 (15.0) | 0 (0.0) | ||
| Other | 20 (1.4) | 739 (100.0) | ||
| Grade | <0.001 | |||
| Well/moderately | 1200 (83.1) | 314 (42.5) | ||
| Poorly/undifferentiated | 166 (11.5) | 363 (49.1) | ||
| Unknown | 78 (5.4) | 62 (8.4) | ||
| Size (cm) | <0.001 | |||
| <3 | 458 (31.7) | 133 (18.0) | ||
| ≥3 | 781 (54.1) | 606 (82.0) | ||
| Unknown | 205 (14.2) | 0 (0.0) | ||
| T stage | <0.001 | |||
| T1 | 400 (27.7) | 128 (17.3) | ||
| T2 | 325 (22.5) | 98 (13.3) | ||
| T3 | 616 (42.7) | 233 (31.5) | ||
| T4a | 68 (4.7) | 189 (25.6) | ||
| T4b | 35 (2.4) | 91 (12.3) | ||
| ELN count, median | 9 | 10 | <0.001 | |
| Positive ELN count, median | 2 | 1 | <0.001 |
API, Asian/Pacific Islander; ELN, examined lymph nodes.
A new LNR staging system
A higher LNR was associated with a worse prognosis (Fig. 2A). Patients were divided into five groups according to the LNR value. When LNR=0, X-tile software divided the patients into two groups: LNR1 (n=133) (ELN 0–4) and LNR2 (n=327) (ELN 5–12) (ELN 0–4) (Fig. 2C, D), and when LNR greater than 0, X-tile software selected two optimal cutoff values to divide the patients into three groups LNR3 (n=427; ratio 0.08–0.22), LNR4 (n=198; ratio 0.25–0.45), and LNR5 (n=359; ratio 0.50–1.00) (Fig. 2E, F), the 5-year survival rates of the LNR1–5 were 81.67, 76.16, 70.03, 64.39, and 59.62%, respectively (Fig. 3). According to the eighth edition of staging, patients in the traditional N staging corresponding to LNR1–5 were divided into 25 groups. The HR of T1LNR1M0 was defined as 1, and the HR value was calculated from low to high, with the highest being T4b LNR5M0 (HR=11.976; 95% CI: 4.669–30.721; P<0.001; Table 2). Survival analysis was performed for two adjacent stages, and χ 2 values were calculated. Six high values were selected as cutoff points (0.180, 0.870, 0.374, 0.142, 0.260, and 0.207). Patients were divided into seven stages, stage I (T1LNR1, T1LNR2), IIA (T1LNR3, T2LNR1, T2LNR2, T2LNR3, T1LNR4, T3LNR1), IIB (T2LNR4), IIC (T3LNR2, T4a LNR1, T1LNR5), IIIA (T3LNR3, T2LNR5, T4b LNR1, T4a LNR2, T3LNR4), IIIB (T3LNR5, T4a LNR3, T4a LNR4, T4b LNR2), and IIIC (T4b LNR3, T4a LNR5, T4b LNR4, T4b LNR5) (Fig. 4), and the 5-year survival rates of the seven stages were 88.58, 84.96, 70.57, 61.89, 54.17, 44.29, and 31.82%, respectively, with a statistically significant difference (P<0.05; Fig. 5A). The 5-year survival rates from stage I to IIIC of traditional TNM staging were 83.31, 59.93, 45.30, 14.29, 81.58, 55.26, and 58.13%, respectively, and the difference was not statistically significant (P>0.05; Fig. 5B).
Figure 2.
(A) hazard estimates of death from training set; (B) hazard estimates of death from external set; (C) the optimal cutoff value for lymph node ratio =0; (D) overall survival for patients in two subgroups; (E) the optimal cutoff value for lymph node ratio >0; (F) overall survival for patients in three subgroups. LNR, lymph node ratio.
Figure 3.
The new lymph node ratio staging system. ELN, examined lymph nodes; LNR, lymph node ratio.
Table 2.
The COX analyses of factors associated with overall survival in the training set.
| Cox regression | Log-rank (Mantel–Cox) | |||
|---|---|---|---|---|
| Variable | HR (95% CI) | P | χ 2 | P |
| Stage I | ||||
| T1LNR1 | 1 | |||
| T1LNR2 | 1.052 (0.450–2.459) | 0.906 | 0.010 | 0.921 |
| Stage IIA | ||||
| T1LNR3 | 1.273 (0.752–2.155) | 0.369 | 0.180 | 0.671 |
| T2LNR1 | 1.326 (0.639–2.758) | 0.449 | 0.011 | 0.917 |
| T2LNR2 | 1.443 (0.736–2.829) | 0.286 | 0.050 | 0.823 |
| T2LNR3 | 1.587 (0.462–5.448) | 0.463 | 0.050 | 0.823 |
| T1LNR4 | 1.935 (0.757–4.945) | 0.168 | 0.069 | 0.792 |
| T3LNR1 | 1.979 (0.952–4.115) | 0.068 | 0.001 | 0.978 |
| Stage IIB | ||||
| T2LNR4 | 2.573 (1.529–4.330) | <0.001 | 0.870 | 0.351 |
| Stage IIC | ||||
| T3LNR2 | 2.798 (1.623–4.823) | <0.001 | 0.374 | 0.541 |
| T4a LNR1 | 2.847 (1.639–4.948) | <0.001 | 0.023 | 0.880 |
| T1LNR5 | 2.949 (1.764–4.930) | <0.001 | 0.056 | 0.813 |
| Stage IIIA | ||||
| T3LNR3 | 3.057 (1.733–5.392) | <0.001 | 0.142 | 0.706 |
| T2LNR5 | 3.111 (0.906–10.680) | 0.071 | 0.005 | 0.943 |
| T4b LNR1 | 3.252 (1.437–7.361) | 0.005 | 0.008 | 0.930 |
| T4a LNR2 | 3.464 (1.571–7.635) | 0.002 | 0.021 | 0.884 |
| T3LNR4 | 3.807 (1.273–11.391) | 0.017 | 0.015 | 0.902 |
| Stage IIIB | ||||
| T3LNR5 | 5.166 (2.886–9.248) | <0.001 | 0.260 | 0.610 |
| T4a LNR3 | 5.874 (1.962–17.589) | 0.002 | 0.014 | 0.907 |
| T4a LNR4 | 6.381 (2.334–17.442) | <0.001 | 0.012 | 0.912 |
| T4b LNR2 | 6.617 (2.719–16.102) | <0.001 | 0.005 | 0.943 |
| Stage IIIC | ||||
| T4b LNR3 | 7.307 (3.951–13.514) | <0.001 | 0.207 | 0.649 |
| T4a LNR5 | 8.792 (2.559–30.202) | 0.001 | 0.092 | 0.762 |
| T4b LNR4 | 9.773 (3.573–26.727) | <0.001 | 0.099 | 0.753 |
| T4b LNR5 | 11.967 (4.669–30.721) | <0.001 | 0.331 | 0.565 |
LNR, lymph node ratio.
Figure 4.
(A) The Kaplan–Meier curves of overall survival for patients in our new lymph node ratio staging system; (B) the new TLNRM staging system. LNR, lymph node ratio.
Figure 5.
(A) The Kaplan–Meier curves of overall survival (OS) for TLNRM staging system; (B) the Kaplan–Meier curves of OS for traditional tumor node metastasis (TNM) staging system; (C) TLNRM stage were compared to the TNM stage in terms of 3-year OS in our decision curve analysis; (D) TLNRM stage were compared to the TNM stage in terms of 5-year OS in our decision curve analysis.
Comparison of the prognostic effectiveness of the two staging systems
The AIC (10354.11) and BIC (10358.75) of traditional TNM were higher than the AIC (10220.55) and BIC (10225.19) of TLNRM staging. The χ2-test of the likelihood ratio of traditional TNM (133.583) was lower than that of TLNRM staging (196.090) (Table 3). The DCA curve showed that the TLNRM staging system had higher net benefits than the traditional TNM staging system (Fig. 5C, D). These findings indicated that the TLNRM staging system was superior to the eighth version of the AJCC staging system.
Table 3.
Effectiveness of the two staging systems for predicting prognosis.
| Stage | Likelihood ratio (χ 2) | AIC | BIC | P |
|---|---|---|---|---|
| TNM (Training) | 133.583 | 10 354.11 | 10 358.75 | <0.001 |
| TLNRM (Training) | 196.090 | 10 220.55 | 10 225.19 | <0.001 |
| TNM (External) | 318.688 | 4314.199 | 4318.099 | <0.001 |
| TLNRM (External) | 390.910 | 4219.002 | 4222.901 | <0.001 |
AIC, Akaike information; BIC, Bayesian information criterion.
Testing the efficiency of ACT for patients in different stages
We further investigated the benefit of ACT in patients with different stages. The results showed that patients in the TLNRM I group did not benefit from ACT (HR: 0.75, 95% CI: 0.21–2.74, P>0.05; Fig. 6A). Patients in the TLNRM II (HR: 0.41, 95% CI: 0.34–0.49, P<0.001; Fig. 6B) and III (HR: 0.42, 95% CI: 0.30–0.58, P<0.001; Fig. 6C) group benefit from ACT. Patients in the TNM I (HR: 1.02, 95% CI: 0.61–1.72, P>0.05; Fig. 6D) and II (HR: 0.76, 95% CI: 0.55–1.06, P>0.05; Fig. 6E) group did not benefit from ACT. Patients in the TNM III (HR: 0.51, 95% CI: 0.43–0.62, P<0.001; Fig. 6F) group benefit from ACT.
Figure 6.
(A) Overall survival (OS) for patients with or without adjuvant chemotherapy (ACT) in TLNRM stage I group; (B) OS for patients with or without ACT in TLNRM stage II group; (C) OS for patients with or without ACT in TLNRM stage III group; (D) OS for patients with or without ACT in TNM stage I group; (E) OS for patients with or without ACT in TNM stage II group; (F) OS for patients with or without ACT in tumor node metastasis stage III group. ACT, adjuvant chemotherapy; TNM, tumor node metastasis.
TLNRM staging system in the external validation group
According to the same inclusion criteria, 739 postoperative patients with RSC were collected from our hospital; of these, 513 (69.4%) were T3-4b patients. The median number of ELN was 10, and the median number of PLN was 1. The median survival period of the patients was 56 months (0–80), and the number of deaths was 365 (49.4%). According to the grouping of the SEER database, the patients were divided into seven stages as follows: I, IIA, IIB, IIC, IIIA, IIIB, and IIIC, and the 5-year survival rates were 92.32, 84.07, 75.00, 65.14, 58.66, 33.66, and 0.0%, respectively. The difference was statistically significant, P<0.05 (Fig. 7A). The 5-year survival rates from stage I to III of traditional TNM staging were 87.79, 79.60, 63.06, 30.25, 77.36, 42.11, and 11.14%, and the difference was not statistically significant (P>0.05; Fig. 7B).
Figure 7.
(A) The Kaplan–Meier curves of overall survival (OS) for TLNRM staging system in our external set; (B) the Kaplan–Meier curves of OS for traditional tumor node metastasis (TNM) staging system in our external set; (C) TLNRM stage were compared to the TNM stage in terms of 3-year OS in our decision curve analysis in our external set; (D) TLNRM stage were compared to the TNM stage in terms of 5-year OS in our decision curve analysis in our external set. TNM, tumor node metastasis.
The AIC (4314.199) and BIC (4318.099) of traditional TNM were higher than the AIC (4219.002) and BIC (4222.901) of TLNRM staging. The χ2-test of the likelihood ratio of traditional TNM (318.688) was lower than that of TLNRM staging (390.910) (Table 3). The DCA curve showed that the TLNRM staging system had higher net benefits than the traditional TNM staging system (Fig. 7C, D). The external validation data confirmed that the TLNRM staging system was superior to the eighth version of the AJCC staging system.
We further investigated the benefit of ACT in patients with different stages (in the external validation group. The results showed that patients in the TLNRM I group did not benefit from ACT (HR: 1.50, 95% CI: 0.12–18.41, P>0.05; Fig. 8A). Patients in the TLNRM II (HR: 0.60, 95% CI: 0.39–0.93, P<0.05; Fig. 8B) and III (HR: 0.49, 95% CI: 0.38–0.63, P<0.001; Fig. 8C) group benefit from ACT. Patients in the TNM I (HR: 0.86, 95% CI: 0.13–5.86, P>0.05; Fig. 8D) and II (HR: 1.65, 95% CI: 1.00–2.72, P<0.05; Fig. 8E) group did not benefit from ACT. Patients in the TNM III (HR: 0.48, 95% CI: 0.38–0.61, P<0.001; Fig. 8F) group benefit from ACT.
Figure 8.
(A) Overall survival (OS) for patients with or without adjuvant chemotherapy (ACT) in TLNRM stage I group in our external set; (B) OS for patients with or without ACT in TLNRM stage II group in our external set; (C) OS for patients with or without ACT in TLNRM stage III group in our external set; (D) OS for patients with or without ACT in tumor node metastasis (TNM) stage I group in our external set; (E) OS for patients with or without ACT in TNM stage II group in our external set; (F) OS for patients with or without ACT in TNM stage III group in our external set. ACT, adjuvant chemotherapy; TNM, tumor node metastasis.
Discussion
The AJCC system stages patients according to the invasion depth of the primary tumor (T), the regional ELN (N), and whether there is distant metastasis14–16. AJCC N staging is based solely on the number of PLN. In addition, the technological skills of the surgeon, the monitoring experience of the pathologist, and other unavoidable circumstances affect the number of ELN, which may lead to the stage migration of patients17,18. RSC occurs in the spiral mucosa of the sigmoid colon, which belongs to the colon anatomically. However, the rectum and RSC in the peritoneal retraction share a common vascular system19,20, which is similar to rectal cancer in prognosis. Some scholars believe that this tumor should be classified as rectal cancer, and its staging also mainly refers to rectal cancer21. Considering these issues, we attempted to develop a better staging index to replace the N staging from the AJCC TNM staging of RSC.
LNR is defined as the number of PLN divided by the total number of ELN. LNR is an important prognostic factor in lung cancer, oral cancer, esophageal cancer, and other malignant tumors. LNR-based staging may be more accurate than the traditional N staging system for evaluating prognosis22–27. The number of ELN in the right colon cancer was higher than that in the left. Shinto et al. 6 showed that the LNR of the right and left sides in stage III colon cancer was 0.16 and 0.22, respectively, and the survival of patients with low LNR was better than that of those with high LNR in both left and right colon cancers. Ceelen et al.28 analyzed 16 studies and found that LNR was an independent prognostic factor of OS (HR=2.36; 95% CI: 2.14–2.61; P<0.05) in patients with stage III colorectal cancer, and the stratification effect on prognosis is better than that of traditional N staging. In patients with stage III rectal cancer, the optimal cutoff value of LNR is 0.257, whereas the AUC of the traditional N stage is 0.669, with a sensitivity of 43% and a specificity of 86%29. Macedo et al. 30 found that LNR was an independent prognostic factor for colorectal cancer patients (HR=1.250; 95% CI: 1.077–1.450; P<0.01), and its prognostic value is higher than that of the traditional N stage. LNR can simultaneously evaluate the number of PLN and the number of ELN, thereby reducing the staging bias caused by insufficient ELN. However, the value of LNR in RSC has not been reported to date. Here, we evaluated the prognostic significance of LNR in RSC.
Because the cutoff values of LNR differ among colorectal cancer studies31–34, we divided patients into five groups using an X-tile according to an LNR ratio of 0 or greater than 0, which had good differentiation potential. Combined with the T stage, we divided patients into seven stages. A higher stage was associated with a worse prognosis. Stage II colon cancer patients with less than 12 ELN are high-risk patients, and chemotherapy is highly recommended for these patients. Stage bias may have occurred in these patients, and their prognosis is similar to that of stage IIIB patients35. In the present study, T4a LNR1 migrated to stage IIC, and T4b LNR1 migrated to stage IIIA, suggesting that the proposed N staging was an effective method for avoiding stage bias. Compared with the eighth edition of the AJCC staging system, the new TNM staging system was superior for determining the 5-year prognosis of patients (P<0.05). The higher accuracy of the new TNM staging system for predicting prognosis could be attributed to the additional prognostic value of LNR. We also observed that the heterogeneity between the new TNM staging systems was relatively low as indicated by AIC, BIC, and χ 2, which significantly improved patient stratification and the prognosis prediction efficiency. The new staging system thus provided a reliable, practical, standardized, and personalized method for oncologists, which will improve the design of treatments and the efficacy of follow-up evaluations. Finally, for patients with insufficient ELN detection, the new staging system reduced the risk of insufficient treatment or follow-up.
We further verified the patients who could really benefit from ACT in the new TLNRM stage. The results showed that patients in the TLNRM I group did not benefit from ACT, patients in the TLNRM II and III group benefit from ACT. Patients with advanced colorectal cancer could benefit from ACT, which is consistent with our results36–38. However, traditional TNM staging showed that patients with stage II RSC could not benefit from ACT. It showed that there might be leading to stage migration in the traditional TNM stage, and our TLNRM stage could correctly guide the ACT of postoperative RSC patients.
The present study had several limitations. First, a decreased number of ELN due to various reasons, such as a gap in technology, the inexperience of surgeons, or the small size of lymph nodes in the specimen, will have an impact on the total number of ELN, which is an unavoidable problem for the SEER database and our own database. Second, this was a retrospective study, and some patients were not included because of data loss, which may lead to bias. Third, the new staging system is not applicable to patients with stage IV RSC. Fourth, the definition of RSC in our center and the SEER database may have inconsistent standards. Fifth, there are certain differences between ELN, PLN, and median survival in our center and the SEER database, which may lead to certain bias. Sixth, our external validation is single center. The staging and treatment of RSC are controversial. Stratifying patients using LNR staging will help with the design of individualized treatments, which highlights the importance of this article39.
Conclusion
The new TNM staging system proposed can lead to improved staging and prognosis prediction in patients with RSC. It showed a superior predictive ability, which is important for the clinical management of patients with RSC.
Ethical approval
This study is a retrospective cohort study in SEER database. All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional and National Research Committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The SEER Program collects data from population-based cancer registries with anonymous information. The SEER is a publicly available database, thus no ethical approval is required.
Sources of funding
National Natural Science Foundation of China (No 82203801); Department of Science and Technology of Jilin Province (No YDZJ202202CXJD047; YDZJ202301ZYTS037). The Bethune Project (2023B12).
Author contribution
X.W.: conceptualization, methodology, software; C.Z.: data curation, writing – original draft preparation; D.W.: data curation, investigation; S.Z.: visualization, investigation, super-vision, and validation.
Conflicts of interest disclosure
The authors declare no conflicts of interest.
Research registration unique identifying number (UIN)
Name of the registry: Chinese Clinical Trial Registry.
Unique identifying number or registration ID: ChiCTR2100050554.
Hyperlink to your specific registration (must be publicly accessible and will be checked):http://www.chictr.org.cn/showprojen.aspx?proj=132614
Guarantor
Xudong Wang and Dacheng Wen accept full responsibility for the work. Chao Zhang had access to the data.
Data availability statement
The raw data of this study are derived from the SEER database, which is a publicly available database. All detailed data included in the study are available upon request by contact with the corresponding author.
Provenance and peer review
Not commissioned, externally peer-reviewed.
Footnotes
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
C.Z. and S.Z. contributed equally to this work.
Published online 19 July 2023
Contributor Information
Chao Zhang, Email: zhangchao10767@jlu.edu.cn.
Shutao Zhao, Email: zhaoshutao001@jlu.edu.cn.
Xudong Wang, Email: zhaojiu042@163.com.
Dacheng Wen, Email: wangxud@jlu.edu.cn.
References
- 1.Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021;71:209–249. [DOI] [PubMed] [Google Scholar]
- 2.Li F, Wang B, Lu S, et al. Comparison of the sigmoid take-off with other definitions of the rectosigmoid junction: a retrospective comparative cohort analysis. Int J Surg 2020;80:168–174. [DOI] [PubMed] [Google Scholar]
- 3.Kawada H, Kurita N, Nakamura F, et al. Incorporation of apical lymph node status into the seventh edition of the TNM classification improves prediction of prognosis in stage III colonic cancer. Br J Surg 2014;101:1143–1152. [DOI] [PubMed] [Google Scholar]
- 4.Ng KS, Dent OF, Chan C, et al. Apical node involvement does not influence prognosis after potentially curative resection for stage iii colorectal cancer: a competing risks analysis. Ann Surg 2022;276:e24–e31. [DOI] [PubMed] [Google Scholar]
- 5.Lan YT, Chang SC, Lin PC, et al. Clinicopathological and molecular features of patients with early and late recurrence after curative surgery for colorectal cancer. Cancers 2021;13:1883. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Shinto E, Ike H, Hida JI, et al. Marked impact of tumor location on the appropriate cutoff values and the prognostic significance of the lymph node ratio in stage III colon cancer: a multi-institutional retrospective analysis. J Gastroenterol 2019;54:597–607. [DOI] [PubMed] [Google Scholar]
- 7.Parnaby CN, Scott NW, Ramsay G, et al. Prognostic value of lymph node ratio and extramural vascular invasion on survival for patients undergoing curative colon cancer resection. Br J Cancer 2015;113:212–219. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Arrichiello G, Pirozzi M, Facchini BA, et al. Beyond N staging in colorectal cancer: current approaches and future perspectives. Front Oncol 2022;12:937114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Li T, Yang Y, Wu W, et al. Prognostic implications of ENE and LODDS in relation to lymph node-positive colorectal cancer location. Transl Oncol 2021;14:101190. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Baqar AR, Wilkins S, Wang W, et al. Log odds of positive lymph nodes is prognostically equivalent to lymph node ratio in non-metastatic colon cancer. BMC Cancer 2020;20:762. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Pyo JS, Shin YM, Kang DW. Prognostic implication of metastatic lymph node ratio in colorectal cancers: comparison depending on tumor location. J Clin Med 2019;8:1812. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Gong Y, Pan S, Wang X, et al. A novel lymph node staging system for gastric cancer including modified Union for cancer Control/American Joint Committee on cancer and Japanese Gastric Cancer Association criteria. Eur J Surg Oncol 2020;46:e27–e32. [DOI] [PubMed] [Google Scholar]
- 13.Wei C, Chen X, Ji J, et al. Urinary exosomal prostate-specific antigen is a noninvasive biomarker to detect prostate cancer: not only old wine in new bottles. Int J Cancer 2023;152:1719–1727. [DOI] [PubMed] [Google Scholar]
- 14.Wang X, Cheng W, Dou X, et al. The new ‘coN’ staging system combining lymph node metastasis and tumour deposit provides a more accurate prognosis for TNM stage III colon cancer. Cancer Med 2023;12:2538–2550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Alese OB, Zhou W, Jiang R, et al. Predictive and prognostic effects of primary tumor size on colorectal cancer survival. Front Oncol 2021;11:728076. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Pei JP, Zhang R, Zhang NN, et al. Screening and validation of a novel T stage-lymph node ratio classification for operable colon cancer. Ann Transl Med 2021;9:1513. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Sekhar H, Zwahlen M, Trelle S, et al. Nodal stage migration and prognosis in anal cancer: a systematic review, meta-regression, and simulation study. Lancet Oncol 2017;18:1348–1359. [DOI] [PubMed] [Google Scholar]
- 18.Shi Q, Andre T, Grothey A, et al. Comparison of outcomes after fluorouracil-based adjuvant therapy for stages II and III colon cancer between 1978 to 1995 and 1996 to 2007: evidence of stage migration from the ACCENT database. J Clin Oncol 2013;31:3656–3663. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Sanford NN, Aguilera TA, Beg MS, et al. Patterns of care for stage II-III rectosigmoid cancers in the United States, 2004-2015. Am J Clin Oncol 2020;43:311–318. [DOI] [PubMed] [Google Scholar]
- 20.Popek S, Tsikitis VL, Hazard L, et al. Preoperative radiation therapy for upper rectal cancer T3,T4/Nx: selectivity essential. Clin Colorectal Cancer 2012;11:88–92. [DOI] [PubMed] [Google Scholar]
- 21.Rosenberg R, Maak M, Schuster T, et al. Does a rectal cancer of the upper third behave more like a colon or a rectal cancer? Dis Colon Rectum 2010;53:761–770. [DOI] [PubMed] [Google Scholar]
- 22.Zhang Y, Cao Y, Zhang J, et al. Lymph node ratio improves prediction of overall survival in esophageal cancer patients receiving neoadjuvant chemoradiotherapy: a national cancer database analysis. Ann Surg 2022;277:E1239–E1246. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Shao Y, Geng Y, Gu W, et al. Assessment of lymph node ratio to replace the pn categories system of classification of the TNM system in esophageal squamous cell carcinoma. J Thorac Oncol 2016;11:1774–1784. [DOI] [PubMed] [Google Scholar]
- 24.Ding X, Hui Z, Dai H, et al. A proposal for combination of lymph node ratio and anatomic location of involved lymph nodes for nodal classification in non-small cell lung cancer. J Thorac Oncol 2016;11:1565–1573. [DOI] [PubMed] [Google Scholar]
- 25.Spolverato G, Ejaz A, Kim Y, et al. Prognostic performance of different lymph node staging systems after curative intent resection for gastric adenocarcinoma. Ann Surg 2015;262:991–998. [DOI] [PubMed] [Google Scholar]
- 26.Gartagani Z, Doumas S, Kyriakopoulou A, et al. Lymph node ratio as a prognostic factor in neck dissection in oral cancer patients: a systematic review and meta-analysis. Cancers 2022;14:4456. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Xu P, Wu D, Liu X. A proposed grading scheme for predicting recurrence in medullary thyroid cancer based on the Ki67 index and metastatic lymph node ratio. Endocrine 2023;81:107–115. [DOI] [PubMed] [Google Scholar]
- 28.Ceelen W, Van Nieuwenhove Y, Pattyn P. Prognostic value of the lymph node ratio in stage III colorectal cancer: a systematic review. Ann Surg Oncol 2010;17:2847–2855. [DOI] [PubMed] [Google Scholar]
- 29.Li Destri G, Barchitta M, Pesce A, et al. Predictive value of the number of harvested lymph nodes and cut-off for lymph node ratio in the prognosis of stage II and III colorectal cancer patients. J Invest Surg 2019;32:1–7. [DOI] [PubMed] [Google Scholar]
- 30.Macedo F, Sequeira H, Ladeira K, et al. Metastatic lymph node ratio as a better prognostic tool than the TNM system in colorectal cancer. Fut Oncol 2021;17:1519–1532. [DOI] [PubMed] [Google Scholar]
- 31.Hu X, Jiang L, Wu J, et al. Prognostic value of log odds of positive lymph nodes, lymph node ratio, and N stage in patients with colorectal signet ring cell carcinoma: a retrospective cohort study. Front Surg 2022;9:1019454. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Zhang CH, Li YY, Zhang QW, et al. The prognostic impact of the metastatic lymph nodes ratio in colorectal cancer. Front Oncol 2018;8:628. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Ahmed S, Leis A, Chandra-Kanthan S, et al. Regional lymph nodes status and ratio of metastatic to examined lymph nodes correlate with survival in stage IV colorectal cancer. Ann Surg Oncol 2016;23:2287–2294. [DOI] [PubMed] [Google Scholar]
- 34.Lykke J, Jess P, Roikjaer O. The prognostic value of lymph node ratio in a national cohort of rectal cancer patients. Eur J Surg Oncol 2016;42:504–512. [DOI] [PubMed] [Google Scholar]
- 35.Zhang C, Zhao S, Wang X. Analysis of the risk factor of insufficient examined lymph nodes in stage II colon cancer from the perspective of stage migration: a retrospective study combined with external validation. Int J Surg 2022;101:106628. [DOI] [PubMed] [Google Scholar]
- 36.Kim JH. Chemotherapy for colorectal cancer in the elderly. World J Gastroenterol 2015;21:5158–5166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Simillis C, Singh HKSI, Afxentiou T, et al. Chemotherapy improves survival in patients with resected high-risk Stage II colorectal cancer: results of a systematic review and meta-analysis. Colorectal Dis 2020;22:1231–1244. [DOI] [PubMed] [Google Scholar]
- 38.Hatlevoll I, Skolbekken JA, Oldervoll LM, et al. Colorectal cancer patients’ experiences with supervised exercise during adjuvant chemotherapy – a qualitative study. Scand J Med Sci Sports 2021;31:2300–2309. [DOI] [PubMed] [Google Scholar]
- 39.Mathew G, Agha R. for the STROCSS Group. STROCSS 2021: strengthening the reporting of cohort, cross-sectional and case-control studies in surgery. Int J Surg 2021;96:106165. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The raw data of this study are derived from the SEER database, which is a publicly available database. All detailed data included in the study are available upon request by contact with the corresponding author.