Abstract
Background
The optimal surgical modality for appendiceal neuroendocrine tumors (ANETs) remains undefined. This study aimed to explore the optimal surgical approach for ANETs by comparing the outcomes between local resection (LR) and radical resection (RR).
Methods
Individuals diagnosed with ANETs during the period from 2000 to 2020 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was used to minimize selection bias. The Kaplan-Meier method and Cox proportional hazards models were used to assess overall survival (OS) and cancer-specific survival (CSS). Additionally, multivariate Cox analysis assessed risk factors linked to OS and CSS.
Results
The study enrolled 4,944 patients, comprising 3,804 in the LR group and 1,140 in the RR group. Patients receiving RR had higher tumor-node-metastasis (TNM) stages (P<0.001), higher age (P<0.001), and larger tumor sizes (P<0.001). Both the 5-year OS and CSS in the LR group were significantly better than those in the RR group (87.3% vs. 73.7%, P<0.001; 95.6% vs. 85.0%, P<0.001). After PSM, 896 patient pairs were matched and compared, showing no demographic and clinical characteristic differences. There was also no difference in long-term OS [hazard ratio (HR) =1.16; 95% confidence interval (CI): 0.86–1.54; P=0.33] and CSS (HR =1.61; 95% CI: 1.00–2.61; P=0.052) between the two groups. Furthermore, multivariate Cox analysis delineated age, diagnosis year, and chemotherapy as independent prognostic risk factors for both OS and CSS, while surgical modality was excluded.
Conclusions
This study indicated that, for patients with ANETs, there was no survival advantage observed for RR when compared to LR, implying that LR might suffice as a treatment for these patients.
Keywords: Appendiceal neuroendocrine tumors (ANETs); local resection (LR); radical resection (RR); survival; Surveillance, Epidemiology, and End Results (SEER)
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Key findings
• This population-based study compared survival outcomes between local resection (LR) and radical resection (RR) for appendiceal neuroendocrine tumors (ANETs), and found no significant difference in long-term overall survival (OS) and cancer-specific survival (CSS) between the two groups.
What is known and what is new?
• It is currently unclear which surgical modality—LR or RR—is optimal for ANETs. Previous studies have not definitively established the superiority of one approach over the other in terms of survival outcomes.
• The study found that, after adjusting for potential confounders through propensity score matching, there was no significant difference in long-term OS and CSS between the two groups.
What is the implication, and what should change now?
• The findings suggest that LR could be considered a viable and less invasive treatment option for ANETs, potentially reducing the morbidity associated with more extensive surgery.
Introduction
Appendiceal neuroendocrine tumors (ANETs) are rare neoplasms that arise from neuroendocrine cells in the appendix, with a reported incidence ranging from 0.15 to 0.6 cases per 100,000 individuals annually (1,2). Due to their nonspecific clinical symptoms and signs, preoperative diagnosis is challenging, and they are frequently incidentally detected through pathological examination following appendectomy (3,4). Common symptoms post-onset include abdominal pain, particularly in the right lower abdomen, abdominal distension, diarrhea, constipation, gastrointestinal bleeding, and weight loss (5,6). Some patients may experience carcinoid syndrome, characterized by flushing, sweating, emaciation, and hypoglycemia, in cases of liver metastases (7,8). Currently, surgical resection is the most prevalent treatment for ANETs (9). The surgical management of ANETs varies, ranging from radical resection (RR) such as hemicolectomy to local resection (LR), which includes appendectomy or partial colectomy (3,5,10).
Although several international medical associations, including the European Neuroendocrine Tumor Society (ENETS) (11), the North American Neuroendocrine Tumor Society (NANETS) (12), and the National Comprehensive Cancer Network (NCCN) (13), have provided recommendations for certain ANET cases—for instance, LR is advised for ANETs smaller than 1.0 cm, and right hemicolectomy in addition to appendectomy is recommended for ANETs larger than 2.0 cm—there remains controversy surrounding the surgical approach for ANETs sized between 1.0 and 2.0 cm. To resolve this controversy, Nesti et al. (14) analyzed the outcomes of 163 cases treated with appendectomy and 115 cases treated with hemicolectomy for ANETs of 1.0–2.0 cm in size and concluded that right-sided hemicolectomy is not necessary after complete resection of an appendiceal NET of 1.0–2.0 cm in size by appendectomy. However, no population-level studies have compared the long-term results of ANET patients treated with LR and RR so far. To address this knowledge gap, we undertook a study to compare the long-term outcomes of patients with ANETs treated with LR and RR using data from the Surveillance, Epidemiology, and End Results (SEER) database. We present this article in accordance with the STROBE reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-23/rc).
Methods
Patient selection
Focusing on ANET patients diagnosed during 2000–2020, the study drew data from the SEER database (http://seer.cancer.gov). Identification was based on the International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3), with code 8240/3 specifying carcinoid tumor, not otherwise specified (NOS). Figure 1 presents a flowchart of the research process. The study included patients who underwent surgical resection for ANETs, while excluding those based on specific criteria: (I) patients lacking a defined pathological histological diagnosis; (II) patients with absent survival information; and (III) patients who were not treated surgically or had undocumented surgical interventions. The investigation encompassed various factors, including age, race, gender, tumor grade, marital status, year of diagnosis, tumor-node-metastasis (TNM) stage, tumor size, chemotherapy status, cancer-specific mortality rate, overall survival (OS) status, and duration of follow-up. Per the SEER Program Coding and Staging Manual, ANETs’ treatment is categorized into the LR and RR groups. LR is local tumor excision or partial/simple removal of the primary site (codes 20–30); RR, in contrast, is total primary site removal or primary site removal with partial/total excision of other organs (codes 40–80). Two age groups were formed: those <60 years (the young group) and those ≥60 years (the elderly group). As for race, people were grouped into white, black, or other races (like American Indian, Alaska Native, and Asian/Pacific Islander). The TNM staging of the cancer was determined in line with the 7th edition of the American Joint Committee on Cancer (AJCC) Cancer Staging Manual. Marital status fell into two groups: married and unmarried. The unmarried group consisted of divorced, separated, single, and widowed individuals. The study’s primary aim was to evaluate OS and cancer-specific survival (CSS) in ANET patients. OS and CSS were determined by counting the time from ANETs’ diagnosis to death (from any cause), cancer-related death, or the last follow-up, depending on which event came first. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Given that the SEER database offers anonymized public data, neither Institutional Review Board (IRB) approval nor explicit consent was mandatory.
Figure 1.
Flow chart of the study. LR, local resection; PSM, propensity score matching; RR, radical resection.
Statistical analysis
Categorical data were presented using counts and percentages, and Chi-squared tests were used for comparisons between groups. For continuous variables that did not follow a normal distribution, medians and interquartile ranges (IQRs) were reported, and comparisons were conducted using the Mann-Whitney U test. To ensure comparability between the LR and RR groups, a 1:1 propensity score matching (PSM) technique was applied, incorporating factors such as age, race, gender, grade, marital status, year of diagnosis, TNM stage, tumor size, and chemotherapy status, with a caliper width of 0.01. Furthermore, subgroup analyses based on these variables were conducted between the LR and RR groups. The Kaplan-Meier method was utilized to assess OS and CSS, and survival curves were compared using the log-rank test. Cox proportional hazards models were used for both univariate and multivariate analyses, with hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) being calculated. Variables with a P value less than 0.05 in the univariate Cox regression analysis were included in the multivariate analysis. To enhance the statistical analysis of this study regarding missing data in the SEER database, a combination of multiple imputation (MI) and the random forest method was employed. All statistical computations were performed using R software (version 4.1.0), and statistical significance was defined as a P value of less than 0.05.
Categorical variables were depicted by means of frequency counts and their corresponding proportions. Group-wise comparisons were carried out utilizing the Chi-squared test. In the case of continuous variables that deviated from a normal distribution, we reported the median values along with the IQRs. The Mann-Whitney U test was employed for inter-group comparisons of these non-normally distributed continuous variables. To enhance the comparability between the LR and RR groups, a 1:1 PSM approach was implemented. A comprehensive set of factors, including age, race, gender, histological grade, marital status, year of diagnosis, TNM staging, tumor dimensions, and chemotherapy status, were incorporated into the PSM model. A caliper width of 0.01 was specified to ensure precise matching. Subgroup analyses were conducted, stratifying the LR and RR groups based on the aforementioned matching factors. OS and CSS were estimated using the Kaplan-Meier method. The log-rank test was applied to compare the survival curves between the two groups. For both univariate and multivariate analyses, Cox proportional hazards models were constructed. HRs and their associated 95% CIs were calculated. Variables that demonstrated a statistically significant association (P<0.05) in the univariate Cox regression analysis were retained for the multivariate analysis. To address the challenge of missing data in the SEER database and strengthen the statistical robustness of this study, a hybrid approach combining MI and the random forest algorithm was adopted. All statistical computations were performed using the R software (version 4.1.0). A P value of less than 0.05 was considered to indicate statistical significance.
Results
Patients’ characteristics
The study encompassed 4,944 patients, comprising 3,804 in the LR group and 1,140 in the RR group. Before PSM, significant differences were observed between the groups in terms of age, race, tumor grade, marital status, year of diagnosis, TNM stage, tumor size, and chemotherapy status (P<0.001). Following 1:1 PSM, the LR and RR groups each comprised 896 patients. Baseline data evaluation revealed no statistically significant disparities between the two groups (P>0.05; Table 1). Table 1 offers a comprehensive depiction of the patients’ demographic and clinical attributes. Missing data were observed in multiple variables within the study. Specifically, the proportion of missing values was 2.0% for race, 15.7% for grade, and 6.0% each for T, N, and M stages, along with 6.2% for tumor size. A detailed comparison of these factors between the two groups prior to MI is provided in Table S1.
Table 1. Demographic and clinical characteristics of patients before and after PSM.
| Variables | Before PSM | After PSM | ||||||
|---|---|---|---|---|---|---|---|---|
| Total (n=4,944) | LR group (n=3,804) | RR group (n=1,140) | P value | LR group (n=896) | RR group (n=896) | P value | ||
| Age (years) | <0.001 | 0.44 | ||||||
| <60 | 3,862 (78.1) | 3,144 (82.6) | 718 (63.0) | 534 (59.6) | 550 (61.4) | |||
| ≥60 | 1,082 (21.9) | 660 (17.4) | 422 (37.0) | 362 (40.4) | 346 (38.6) | |||
| Race | <0.001 | 0.88 | ||||||
| White | 4,281 (86.6) | 3,303 (86.8) | 978 (85.8) | 769 (85.8) | 776 (86.6) | |||
| Black | 367 (7.4) | 250 (6.6) | 117 (10.3) | 90 (10.0) | 86 (9.6) | |||
| Others† | 296 (6.0) | 251 (6.6) | 45 (3.9) | 37 (4.1) | 34 (3.8) | |||
| Gender | 0.36 | 0.41 | ||||||
| Male | 1,909 (38.6) | 1,482 (39.0) | 427 (37.5) | 362 (40.4) | 345 (38.5) | |||
| Female | 3,035 (61.4) | 2,322 (61.0) | 713 (62.5) | 534 (59.6) | 551 (61.5) | |||
| Grade | <0.001 | 0.053 | ||||||
| Well | 4,428 (89.6) | 3,393 (89.2) | 1,035 (90.8) | 849 (94.8) | 830 (92.6) | |||
| Moderately | 455 (9.2) | 365 (9.6) | 90 (7.9) | 47 (5.2) | 62 (6.9) | |||
| Poorly | 23 (0.5) | 10 (0.3) | 13 (1.1) | 0 (0.0) | 3 (0.3) | |||
| Undifferentiated | 38 (0.8) | 36 (0.9) | 2 (0.2) | 0 (0.0) | 1 (0.1) | |||
| Marital status | <0.001 | 0.74 | ||||||
| Married | 2,226 (45.0) | 1,638 (43.1) | 588 (51.6) | 451 (50.3) | 444 (49.6) | |||
| Unmarried | 2,718 (55.0) | 2,166 (56.9) | 552 (48.4) | 445 (49.7) | 452 (50.4) | |||
| Year of diagnosis | <0.001 | 0.47 | ||||||
| 2000–2006 | 191 (3.9) | 107 (2.8) | 84 (7.4) | 23 (2.6) | 25 (2.8) | |||
| 2007–2013 | 450 (9.1) | 315 (8.3) | 135 (11.8) | 105 (11.7) | 89 (9.9) | |||
| 2014–2020 | 4,303 (87.0) | 3,382 (88.9) | 921 (80.8) | 768 (85.7) | 782 (87.3) | |||
| T stage | <0.001 | 0.64 | ||||||
| T1 | 4,234 (85.6) | 3,460 (91.0) | 774 (67.9) | 725 (80.9) | 729 (81.4) | |||
| T2 | 290 (5.9) | 130 (3.4) | 160 (14.0) | 97 (10.8) | 84 (9.4) | |||
| T3 | 112 (2.3) | 57 (1.5) | 55 (4.8) | 28 (3.1) | 25 (2.8) | |||
| T4 | 101 (2.0) | 51 (1.3) | 50 (4.4) | 24 (2.7) | 31 (3.5) | |||
| TX | 207 (4.2) | 106 (2.8) | 101 (8.9) | 22 (2.5) | 27 (3.0) | |||
| N stage | <0.001 | 0.16 | ||||||
| N0 | 3,987 (80.6) | 3,131 (82.3) | 856 (75.1) | 804 (89.7) | 778 (86.8) | |||
| N1 | 331 (6.7) | 85 (2.2) | 246 (21.6) | 64 (7.1) | 82 (9.2) | |||
| NX | 626 (12.7) | 588 (15.5) | 38 (3.3) | 28 (3.1) | 36 (4.0) | |||
| M stage | <0.001 | 0.22 | ||||||
| M0 | 4,898 (99.1) | 3,790 (99.6) | 1,108 (97.2) | 890 (99.3) | 885 (98.8) | |||
| M1 | 46 (0.9) | 14 (0.4) | 32 (2.8) | 6 (0.7) | 11 (1.2) | |||
| Tumor size (cm) | <0.001 | 0.65 | ||||||
| ≤1.0 | 3,525 (71.3) | 2,962 (77.9) | 563 (49.4) | 534 (59.6) | 532 (59.4) | |||
| 1.1–2.0 | 986 (19.9) | 644 (16.9) | 342 (30.0) | 234 (26.1) | 247 (27.6) | |||
| >2.0 | 433 (8.8) | 198 (5.2) | 235 (20.6) | 128 (14.3) | 117 (13.1) | |||
| Chemotherapy | <0.001* | 0.43 | ||||||
| No/unknown | 4,879 (98.7) | 3,786 (99.5) | 1,093 (95.9) | 885 (98.8) | 881 (98.3) | |||
| Yes | 65 (1.3) | 18 (0.5) | 47 (4.1) | 11 (1.2) | 15 (1.7) | |||
| Survival months | 37.0 (15.0, 61.0) | 37.0 (15.0, 60.0) | 38.0 (16.0, 67.0) | 0.007* | 26.0 (7.0, 61.0) | 35.0 (14.0, 61.0) | <0.001* | |
Data are presented as n (%) or median (IQR). †, others: American Indian, Alaska Native, Asian/Pacific Islander. *, P<0.05. IQR, interquartile range; LR, local resection; M, metastasis; N, node; PSM, propensity score matching; RR, radical resection; T, tumor.
Survival analysis of patients with ANETs
Prior to PSM, for patients with ANETs in the LR group, the 1-, 3-, and 5-year OS probabilities were 98.1%, 94.9%, and 87.3%, respectively. In contrast, their counterparts in the RR group exhibited OS rates of 93.1%, 85.0%, and 73.7% at the corresponding time points. Regarding CSS, the LR group demonstrated 1-, 3-, and 5-year CSS probabilities of 99.3%, 98.3%, and 95.6%, respectively. Conversely, the RR group had CSS rates of 96.3%, 91.9%, and 85.0% at the 1-, 3-, and 5-year marks. Notably, the LR group consistently outperformed the RR group in terms of 1-, 3-, and 5-year OS and CSS rates, with the differences reaching statistical significance (P<0.001). Following PSM, for the LR group, the 1-, 3-, and 5-year OS probabilities were 94.9%, 88.0%, and 78.2%, sequentially. In stark contrast, the RR group manifested OS rates of 93.1%, 85.2%, and 71.9% at the corresponding time intervals. In terms of CSS, the LR group presented 1-, 3-, and 5-year CSS probabilities of 97.3%, 94.5%, and 91.2%, respectively. Meanwhile, the RR group exhibited CSS rates of 96.7%, 92.8%, and 88.3% at the 1-, 3-, and 5-year junctures. Statistical analysis revealed no discernible disparities in the 1-, 3-, and 5-year OS and CSS rates between the LR and RR groups (P>0.05), as detailed in Table 2. Before PSM, the RR group presented a markedly poorer OS outcome than the LR group, as evidenced by a HR of 2.69 (95% CI: 2.16–3.37, P<0.001) (Figure 2A). Similarly, in terms of CSS, the RR group fared significantly worse, with an HR of 4.54 (95% CI: 3.16–6.53, P<0.001) (Figure 2B). However, post-PSM, the OS status between the RR and LR groups reached a comparable level, with an HR of 1.16 (95% CI: 0.86–1.54; P=0.33) (Figure 2C). Regarding CSS, although the RR group still showed a slightly elevated risk compared to the LR group, the difference was no longer statistically significant, with an HR of 1.61 (95% CI: 1.00–2.61; P=0.052) (Figure 2D).
Table 2. Survival rate of patients with ANETs in the LR and RR groups.
| Survival rate | LR group | RR group | P value |
|---|---|---|---|
| Before PSM | |||
| OS rate (%) | |||
| 1-year | 98.1 | 93.1 | <0.001* |
| 3-year | 94.9 | 85.0 | <0.001* |
| 5-year | 87.3 | 73.7 | <0.001* |
| CSS rate (%) | |||
| 1-year | 99.3 | 96.3 | <0.001* |
| 3-year | 98.3 | 91.9 | <0.001* |
| 5-year | 95.6 | 85.0 | <0.001* |
| After PSM | |||
| OS rate (%) | |||
| 1-year | 94.9 | 93.1 | 0.17 |
| 3-year | 88.0 | 85.2 | 0.21 |
| 5-year | 78.2 | 71.9 | 0.07 |
| CSS rate (%) | |||
| 1-year | 97.3 | 96.7 | 0.53 |
| 3-year | 94.5 | 92.8 | 0.32 |
| 5-year | 91.2 | 88.3 | 0.08 |
*, P<0.05. ANETs, appendiceal neuroendocrine tumors; CSS, cancer-specific survival; LR, local resection; OS, overall survival; PSM, propensity score matching; RR, radical resection.
Figure 2.
OS and CSS were compared between the LR and RR groups before and after PSM. (A) OS before PSM; (B) CSS before PSM; (C) OS after PSM; (D) CSS after PSM. CSS, cancer-specific survival; LR, local resection; OS, overall survival; PSM, propensity score matching; RR, radical resection.
Univariate and multivariate Cox regression
Prior to PSM, the univariate Cox proportional hazards model was employed to assess the influence of various factors on the OS of patients with ANETs. The findings indicated that variables such as surgical approach, patient age, gender, tumor histological grade, T stage, M stage, tumor dimensions, and receipt of chemotherapy exerted an autonomous effect on OS. Subsequently, a multivariate Cox regression analysis was conducted to discern the most pivotal independent factors for OS prediction in this patient cohort. The results unequivocally demonstrated that surgical modality, age, gender, M stage, and the administration of chemotherapy were the dominant independent determinants of OS in patients with ANETs (Table 3). In parallel, the univariate Cox proportional hazards model was utilized to evaluate the independent impact of multiple factors on the CSS of ANET patients. The analysis revealed that surgical modality, age, gender, tumor grade, the year of diagnosis, T stage, N stage, M stage, and chemotherapy were all significant independent influencers of CSS. To further refine the understanding of the key predictors of CSS, a multivariate Cox regression analysis was performed. This analysis solidified the notion that surgical modality, age, gender, M stage, and chemotherapy were the cardinal independent factors that could accurately forecast CSS in this specific patient population (Table 4).
Table 3. Univariate and multivariate Cox regression for analyzing the OS for patients with ANETs before PSM.
| Variables | Univariate | Multivariate | |||||
|---|---|---|---|---|---|---|---|
| HR | 95% CI | P value | HR | 95% CI | P value | ||
| Surgical modality | |||||||
| LR | 1 | Reference | 1 | Reference | |||
| RR | 2.69 | 2.16, 3.37 | <0.001* | 1.63 | 1.29, 2.07 | <0.001* | |
| Age (years) | |||||||
| <60 | 1 | Reference | 1 | Reference | |||
| ≥60 | 10.37 | 8.11, 13.24 | <0.001* | 9.34 | 7.25, 12.02 | <0.001* | |
| Race | |||||||
| White | 1 | Reference | – | – | – | ||
| Black | 1.06 | 0.71, 1.60 | 0.77 | – | – | – | |
| Others† | 1.17 | 0.72, 1.92 | 0.52 | – | – | – | |
| Gender | |||||||
| Male | 1 | Reference | 1 | Reference | |||
| Female | 0.69 | 0.55, 0.86 | <0.001* | 0.65 | 0.52, 0.82 | <0.001* | |
| Grade | |||||||
| Well | 1 | Reference | 1 | Reference | |||
| Moderately | 0.67 | 0.45, 0.98 | 0.041* | 0.73 | 0.49, 1.08 | 0.12 | |
| Poorly | 3.02 | 1.34, 6.81 | 0.008* | 0.47 | 0.19, 1.16 | 0.10 | |
| Undifferentiated | 0.52 | 0.21, 1.31 | 0.17 | 0.57 | 0.22, 1.49 | 0.25 | |
| Marital status | |||||||
| Married | 1 | Reference | – | – | – | ||
| Unmarried | 0.81 | 0.65, 1.01 | 0.06 | – | – | – | |
| Year of diagnosis | |||||||
| 2000–2006 | 1 | Reference | – | – | – | ||
| 2007–2013 | 0.66 | 0.43, 1.02 | 0.06 | – | – | – | |
| 2014–2020 | 0.71 | 0.48, 1.05 | 0.09 | – | – | – | |
| T stage | |||||||
| T1 | 1 | Reference | 1 | Reference | |||
| T2 | 0.80 | 0.48, 1.33 | 0.39 | 0.39 | 0.17, 1.90 | 0.13 | |
| T3 | 3.35 | 2.15, 5.24 | <0.001* | 1.42 | 0.67, 2.99 | 0.36 | |
| T4 | 3.39 | 2.01, 5.71 | <0.001* | 2.23 | 0.91, 4.48 | 0.12 | |
| TX | 0.98 | 0.61, 1.58 | 0.93 | 1.09 | 0.66, 1.80 | 0.74 | |
| N stage | |||||||
| N0 | 1 | Reference | – | – | – | ||
| N1 | 1.35 | 0.97, 1.87 | 0.08 | – | – | – | |
| NX | 0.88 | 0.60, 1.30 | 0.53 | – | – | – | |
| M stage | |||||||
| M0 | 1 | Reference | 1 | Reference | |||
| M1 | 8.64 | 5.49, 13.61 | <0.001* | 3.06 | 1.82, 5.15 | <0.001* | |
| Tumor size (cm) | |||||||
| ≤1.0 | 1 | Reference | 1 | Reference | |||
| 1.1–2.0 | 0.87 | 0.66, 1.17 | 0.36 | 0.98 | 0.73, 1.32 | 0.91 | |
| >2.0 | 1.60 | 1.16, 2.20 | 0.004* | 1.27 | 0.62, 2.60 | 0.51 | |
| Chemotherapy | |||||||
| Yes | 1 | Reference | 1 | Reference | |||
| No/unknown | 6.79 | 4.51, 10.22 | <0.001* | 3.71 | 2.36, 5.83 | <0.001* | |
†, others: American Indian, Alaska Native, Asian/Pacific Islander. *, P<0.05. ANETs, appendiceal neuroendocrine tumors; CI, confidence interval; HR, hazard ratio; LR, local resection; M, metastasis; N, node; OS, overall survival; PSM, propensity score matching; RR, radical resection; T, tumor.
Table 4. Univariate and multivariate Cox regression for analyzing the CSS for patients with ANETs before PSM.
| Variables | Univariate | Multivariate | |||||
|---|---|---|---|---|---|---|---|
| HR | 95% CI | P value | HR | 95% CI | P value | ||
| Surgical modality | |||||||
| LR | 1 | Reference | 1 | Reference | |||
| RR | 4.54 | 3.16, 6.53 | <0.001* | 2.54 | 1.68, 3.84 | <0.001* | |
| Age (years) | |||||||
| <60 | 1 | Reference | 1 | Reference | |||
| ≥60 | 8.74 | 5.97, 12.81 | <0.001* | 7.82 | 5.19, 11.78 | <0.001* | |
| Race | |||||||
| White | 1 | Reference | – | – | – | ||
| Black | 1.24 | 0.67, 2.32 | 0.49 | – | – | – | |
| Others† | 1.43 | 0.70, 2.94 | 0.33 | – | – | – | |
| Gender | |||||||
| Male | 1 | Reference | 1 | Reference | |||
| Female | 0.55 | 0.38, 0.78 | <0.001* | 0.46 | 0.32, 0.66 | <0.001* | |
| Grade | |||||||
| Well | 1 | Reference | 1 | Reference | |||
| Moderately | 0.63 | 0.33, 1.21 | 0.16 | 0.73 | 0.38, 1.41 | 0.35 | |
| Poorly | 8.43 | 3.67, 19.35 | <0.001* | 0.76 | 0.26, 2.22 | 0.62 | |
| Undifferentiated | 0.34 | 0.05, 2.54 | 0.30 | 0.40 | 0.05, 3.07 | 0.38 | |
| Marital status | |||||||
| Married | 1 | Reference | – | – | – | ||
| Unmarried | 0.79 | 0.56, 1.13 | 0.21 | – | – | – | |
| Year of diagnosis | |||||||
| 2000–2006 | 1 | Reference | 1 | Reference | |||
| 2007–2013 | 0.34 | 0.18, 0.67 | 0.002* | 0.51 | 0.25, 1.04 | 0.06 | |
| 2014–2020 | 0.43 | 0.25, 0.74 | 0.002* | 0.69 | 0.38, 1.24 | 0.21 | |
| T stage | |||||||
| T1 | 1 | Reference | 1 | Reference | |||
| T2 | 0.83 | 0.36, 1.89 | 0.65 | 0.60 | 0.16, 2.17 | 0.43 | |
| T3 | 3.89 | 1.96, 7.73 | <0.001* | 1.45 | 0.46, 4.54 | 0.52 | |
| T4 | 5.41 | 2.72, 10.77 | <0.001* | 3.90 | 0.97, 9.68 | 0.21 | |
| TX | 1.38 | 0.68, 2.79 | 0.37 | 0.97 | 0.43, 2.17 | 0.94 | |
| N stage | |||||||
| N0 | 1 | Reference | 1 | Reference | |||
| N1 | 2.68 | 1.71, 4.18 | <0.001* | 1.78 | 0.94, 3.35 | 0.08 | |
| NX | 1.04 | 0.57, 1.92 | 0.90 | 2.03 | 0.97, 3.86 | 0.06 | |
| M stage | |||||||
| M0 | 1 | Reference | 1 | Reference | |||
| M1 | 15.04 | 8.45, 26.79 | <0.001* | 3.44 | 1.61, 7.37 | 0.001* | |
| Tumor size (cm) | |||||||
| ≤1.0 | 1 | Reference | 1 | Reference | |||
| 1.1–2.0 | 0.92 | 0.58, 1.45 | 0.72 | 0.86 | 0.50, 1.46 | 0.57 | |
| >2.0 | 1.73 | 1.05, 2.85 | 0.03 | 0.61 | 0.21, 1.77 | 0.36 | |
| Chemotherapy | |||||||
| Yes | 1 | Reference | 1 | Reference | |||
| No/unknown | 15.24 | 9.42, 24.64 | <0.001* | 6.55 | 3.74, 11.48 | <0.001* | |
†, others: American Indian, Alaska Native, Asian/Pacific Islander. *, P<0.05. ANETs, appendiceal neuroendocrine tumors; CI, confidence interval; CSS, cancer-specific survival; HR, hazard ratio; LR, local resection; M, metastasis; N, node; PSM, propensity score matching; RR, radical resection; T, tumor.
After PSM, we used the univariate Cox regression analysis to figure out how different factors affected the OS of patients with ANETs, except for surgical modality. We found that things like the patient’s age, gender, tumor grade, the year they were diagnosed, T stage, M stage, tumor size, and whether they got chemotherapy all had an independent effect on OS. Then, we did a multivariate Cox regression analysis to find out which of these factors were the most important independent ones for predicting OS in these patients. The results clearly showed that age, the year of diagnosis, and receiving chemotherapy were the key independent factors for predicting OS in ANET patients (Table 5). We also used the univariate Cox regression analysis at the same time to look at how various factors independently influenced the CSS of ANET patients, not including surgical modality. We discovered that factors such as age, tumor grade, the year of diagnosis, M stage, tumor size, and chemotherapy all played an independent role in affecting CSS. To better understand the main factors that could predict CSS, we carried out a multivariate Cox regression analysis. This analysis made it clear that age, the year of diagnosis, and chemotherapy were the really important independent factors for predicting CSS in this group of patients (Table 6).
Table 5. Univariate and multivariate Cox regression for analyzing the OS for patients with ANETs after PSM.
| Variables | Univariate | Multivariate | |||||
|---|---|---|---|---|---|---|---|
| HR | 95% CI | P value | HR | 95% CI | P value | ||
| Surgical modality | |||||||
| LR | 1 | Reference | – | – | – | ||
| RR | 1.30 | 0.96, 1.77 | 0.09 | – | – | – | |
| Age (years) | |||||||
| <60 | 1 | Reference | 1 | Reference | |||
| ≥60 | 8.44 | 5.74, 12.42 | <0.001* | 9.42 | 6.17, 14.39 | <0.001* | |
| Race | |||||||
| White | 1 | Reference | – | – | – | ||
| Black | 0.72 | 0.41, 1.28 | 0.26 | – | – | – | |
| Others† | 0.91 | 0.41, 2.03 | 0.83 | – | – | – | |
| Gender | |||||||
| Male | 1 | Reference | 1 | Reference | |||
| Female | 0.70 | 0.51, 0.95 | 0.02* | 0.78 | 0.56, 1.09 | 0.15 | |
| Grade | |||||||
| Well | 1 | Reference | 1 | Reference | |||
| Moderately | 0.77 | 0.38, 1.56 | 0.47 | 1.09 | 0.49, 2.43 | 0.84 | |
| Poorly | 17.19 | 1.55, 190.53 | 0.02* | 2.64 | 0.16, 44.00 | 0.50 | |
| Undifferentiated | NA | NA | NA | NA | NA | NA | |
| Marital status | |||||||
| Married | 1 | Reference | – | – | – | ||
| Unmarried | 0.95 | 0.70, 1.29 | 0.75 | – | – | – | |
| Year of diagnosis | |||||||
| 2000–2006 | 1 | Reference | 1 | Reference | |||
| 2007–2013 | 0.24 | 0.12, 0.48 | <0.001* | 0.28 | 0.12, 0.66 | 0.004* | |
| 2014–2020 | 0.14 | 0.08, 0.25 | <0.001* | 0.11 | 0.05, 0.24 | <0.001* | |
| T stage | |||||||
| T1 | 1 | Reference | 1 | Reference | |||
| T2 | 0.43 | 0.21, 0.85 | 0.02* | 0.71 | 0.18, 2.75 | 0.62 | |
| T3 | 1.89 | 0.93, 3.84 | 0.08 | 3.84 | 0.95, 13.96 | 0.07 | |
| T4 | 0.31 | 0.07, 1.27 | 0.10 | 0.39 | 0.08, 1.89 | 0.24 | |
| TX | 1.14 | 0.48, 2.71 | 0.77 | 1.32 | 0.51, 3.43 | 0.57 | |
| N stage | |||||||
| N0 | 1 | Reference | – | – | – | ||
| N1 | 0.99 | 0.57, 1.73 | 0.97 | – | – | – | |
| NX | 1.06 | 0.48, 2.37 | 0.88 | – | – | – | |
| M stage | |||||||
| M0 | 1 | Reference | 1 | Reference | |||
| M1 | 3.67 | 1.28, 10.53 | 0.02* | 3.55 | 0.93, 13.52 | 0.06 | |
| Tumor size (cm) | |||||||
| ≤1.0 | 1 | Reference | 1 | Reference | |||
| 1.1–2.0 | 0.48 | 0.32, 0.72 | <0.001* | 0.83 | 0.53, 1.29 | 0.41 | |
| >2.0 | 0.51 | 0.30, 0.85 | 0.01* | 0.61 | 0.17, 2.16 | 0.44 | |
| Chemotherapy | |||||||
| Yes | 1 | Reference | 1 | Reference | |||
| No/unknown | 6.67 | 3.02, 14.74 | <0.001* | 6.79 | 2.57, 17.93 | <0.001* | |
†, others: American Indian, Alaska Native, Asian/Pacific Islander. *, P<0.05. ANETs, appendiceal neuroendocrine tumors; CI, confidence interval; HR, hazard ratio; LR, local resection; M, metastasis; N, node; NA, not available; OS, overall survival; PSM, propensity score matching; RR, radical resection; T, tumor.
Table 6. Univariate and multivariate Cox regression for analyzing the CSS for patients with ANETs after PSM.
| Variables | Univariate | Multivariate | |||||
|---|---|---|---|---|---|---|---|
| HR | 95% CI | P value | HR | 95% CI | P value | ||
| Surgical modality | |||||||
| LR | 1 | Reference | – | – | – | ||
| RR | 1.21 | 0.91, 1.66 | 0.12 | – | – | – | |
| Age (years) | |||||||
| <60 | 1 | Reference | 1 | Reference | |||
| ≥60 | 8.27 | 4.42, 15.49 | <0.001* | 8.68 | 4.37, 17.21 | <0.001* | |
| Race | |||||||
| White | 1 | Reference | – | – | – | ||
| Black | 0.99 | 0.45, 2.20 | 0.98 | – | – | – | |
| Others† | 1.06 | 0.32, 3.45 | 0.93 | – | – | – | |
| Gender | |||||||
| Male | 1 | Reference | – | – | – | ||
| Female | 0.64 | 0.40, 1.03 | 0.06 | – | – | – | |
| Grade | |||||||
| Well | 1 | Reference | 1 | Reference | |||
| Moderately | 0.93 | 0.33, 2.60 | 0.89 | 1.23 | 0.38, 3.91 | 0.73 | |
| Poorly | 48.88 | 4.38, 545.87 | 0.002* | 12.28 | 0.95, 159.45 | 0.06 | |
| Undifferentiated | NA | NA | NA | NA | NA | NA | |
| Marital status | |||||||
| Married | 1 | Reference | – | – | – | ||
| Unmarried | 1.26 | 0.78, 2.02 | 0.34 | – | – | – | |
| Year of diagnosis | |||||||
| 2000–2006 | 1 | Reference | 1 | Reference | |||
| 2007–2013 | 0.14 | 0.05, 0.40 | <0.001* | 0.24 | 0.07, 0.80 | 0.02* | |
| 2014–2020 | 0.14 | 0.07, 0.29 | <0.001* | 0.18 | 0.07, 0.44 | <0.001* | |
| T stage | |||||||
| T1 | 1 | Reference | – | – | – | ||
| T2 | 0.38 | 0.12, 1.24 | 0.11 | – | – | – | |
| T3 | 1.86 | 0.65, 5.33 | 0.25 | – | – | – | |
| T4 | 0.42 | 0.06, 3.11 | 0.40 | – | – | – | |
| TX | 1.49 | 0.45, 4.92 | 0.51 | – | – | – | |
| N stage | |||||||
| N0 | 1 | Reference | – | – | – | ||
| N1 | 1.70 | 0.82, 3.49 | 0.15 | – | – | – | |
| NX | 1.72 | 0.61, 4.89 | 0.31 | – | – | – | |
| M stage | |||||||
| M0 | 1 | Reference | 1 | Reference | |||
| M1 | 5.30 | 1.49, 18.87 | 0.01* | 4.77 | 0.92, 22.36 | 0.09 | |
| Tumor size (cm) | |||||||
| ≤1.0 | 1 | Reference | 1 | Reference | |||
| 1.1–2.0 | 0.47 | 0.25, 0.89 | 0.02* | 0.85 | 0.42, 1.70 | 0.65 | |
| >2.0 | 0.38 | 0.15, 0.97 | 0.04* | 0.40 | 0.13, 1.24 | 0.12 | |
| Chemotherapy | |||||||
| Yes | 1 | Reference | 1 | Reference | |||
| No/unknown | 14.31 | 6.14, 33.35 | <0.001* | 14.97 | 5.40, 41.50 | <0.001* | |
†, others: American Indian, Alaska Native, Asian/Pacific Islander. *, P<0.05. ANETs, appendiceal neuroendocrine tumors; CI, confidence interval; CSS, cancer-specific survival; HR, hazard ratio; LR, local resection; M, metastasis; N, node; NA, not available; PSM, propensity score matching; RR, radical resection; T, tumor.
Subgroup analysis
Before PSM, the OS of the LR group was significantly better than that of the RR group (P<0.001), and this trend was also observed across multiple subgroups, as indicated by the superior OS of the LR group compared to the RR group, as depicted in Figure S1. Similarly, the CSS of the LR group was significantly higher than that of the RR group (P<0.001), and this was also evident across multiple subgroups, where the CSS of the LR group exceeded that of the RR group, as detailed in Figure S2. After PSM, the OS of the LR group and the RR group became comparable (P=0.33), with all subgroups exhibiting similar OS between the two groups (P>0.05) (Figure 3). Likewise, the CSS of the LR group and the RR group was comparable (P>0.05). With the exception of the T1 stage group, where the CSS of the LR group was superior to that of the RR group, all other subgroups demonstrated similar CSS between the two groups (P>0.05) (Figure 4).
Figure 3.
Subgroup analysis of OS between the LR and RR groups after PSM. CI, confidence interval; HR, hazard ratio; LR, local resection; M, metastasis; N, node; OS, overall survival; PSM, propensity score matching; RR, radical resection; T, tumor.
Figure 4.
Subgroup analysis of CSS between the LR and RR groups after PSM. CI, confidence interval; CSS, cancer-specific survival; HR, hazard ratio; LR, local resection; M, metastasis; N, node; PSM, propensity score matching; RR, radical resection; T, tumor.
Discussion
In this study, we utilized the SEER database to explore the optimal surgical approach for ANETs by comparing the outcomes between LR and RR. Notably, our findings indicate that there was no survival advantage observed for RR when compared to LR in patients with ANETs. Before PSM analysis, the LR group exhibited better 5-year OS and CSS rates compared to the RR group (P<0.001). However, after PSM, no differences in long-term OS and CSS were observed between the two groups. Furthermore, multivariate Cox analysis identified age, year of diagnosis, and chemotherapy as independent prognostic risk factors affecting both OS and CSS, but not surgical modality. This study implies that LR might suffice as a treatment for patients with ANETs.
Nussbaum et al. (15) analyzed data from the National Cancer Database (NCDB) to compare the outcomes of 916 cases involving appendectomy and right hemicolectomy for treating ANETs ranging from 1.0 to 2.0 cm in size. The findings indicated that the right hemicolectomy group did not show better outcomes, even in cases of higher-grade tumors. Another systematic review also disclosed that, even for high-risk ANETs, appendectomy alone results in better outcomes than right hemicolectomy (16). These observations align with our research findings. Our study revealed that, after PSM, for different size categories (≤1.0, 1.1–2.0, >2.0 cm), the LR group and the RR group exhibited similar OS and CSS rates (P>0.05). Likewise, for ANET patients with varying grades, the LR group and the RR group still demonstrated comparable OS and CSS rates (P>0.05) (Figures 3,4).
The NCCN guidelines (13) also recommend that appendectomy alone is adequate, even when one or more histopathological high-risk factors are present (such as unclear resection margins, lymphovascular invasion, high proliferation rate, or appendiceal mesenteric invasion exceeding 3 mm). However, the ENETS and NANETS guidelines (11,12) suggest that additional right colectomy should be performed when the aforementioned histopathological high-risk factors are present, primarily to achieve regional lymph node dissection. The research conducted by Mullen et al. (17) proposes that right colectomy should be performed for ANETs larger than 1.0 cm due to an increased risk of lymph node metastasis in these patients. In their study, among 27 ANETs smaller than 1.0 cm, 4 cases exhibited lymph node metastasis; among 34 ANETs ranging from 1.1 to 2.0 cm, 16 cases showed lymph node metastasis; and among 28 ANETs larger than 2.0 cm, 24 cases presented with lymph node metastasis. The percentage of lymph node metastasis in this study was notably high, reaching 49%, which may be attributed to the small sample size and the fact that all included cases were malignant ANETs.
A previous study has documented that the occurrence of lymph node metastasis in ANETs ranges from 6% to 9% (18), which is comparable to the 6.7% reported in our study (Table 1). Our findings indicate that, after PSM, for patients with lymph node metastasis, the LR group and the RR group still exhibited similar OS and CSS rates (P>0.05). Consequently, we postulate that even if ANET patients have lymph node metastasis, appendectomy alone might be adequate, with postoperative chemotherapy or radiotherapy being utilized to enhance patient outcomes. Nevertheless, further prospective randomized controlled (RCT) trials are necessary to confirm these findings.
In this study, we discovered that age, year of diagnosis, and chemotherapy are prognostic risk factors for ANET patients, whereas surgical procedures are not. Zheng et al. (19) similarly pinpointed older age as a prognostic determinant in their investigation of risk factors for colorectal neuroendocrine tumors. Another research highlighted age as a crucial prognostic factor for carcinoid tumors, a subtype of malignant neuroendocrine tumors (20). The inferior prognosis observed in older ANET patients may be ascribed to the gradual deterioration of physiological functions, diminished treatment tolerability with advancing age, and the likelihood of coexisting multiple chronic conditions, all of which elevate treatment risks and complexities (21). Moreover, elderly patients may encounter greater psychological stress and social challenges, which could further compromise their prognosis (22,23). Concurrently, tumor-specific factors such as malignancy and stage may also exacerbate with age, thereby exerting additional influence on patient prognosis. Additionally, our study revealed that patients diagnosed in later years exhibit better prognoses, aligning with the conclusions drawn by Quaedvlieg et al. (20). We postulate that the recent enhancement in patient prognosis may be attributable to the collective impact of ongoing medical technological advancements, evolving treatment paradigms, refined patient management strategies, and a deeper comprehension of the disease.
There are several limitations in this study. Firstly, our retrospective analysis depends on the SEER database, which inherently carries risks of data inconsistencies and biases. Secondly, the SEER database lacks comprehensive information on family history, postoperative complications, specific chemotherapy protocols, disease recurrence, and the criteria used to select surgical methods for individual patients. These factors have the potential to significantly influence the long-term prognosis of patients. Lastly, it is important to note that the SEER database primarily represents the American medical context, and healthcare practices can differ across various regions and cultures. Therefore, caution should be taken when applying our study’s findings to other geographical or cultural settings. Nonetheless, to our knowledge, this is currently the largest study comparing the long-term prognosis of ANETs treated with LR versus RR. Furthermore, we utilized PSM to minimize potential biases and conducted subgroup analyses to examine the impact of different factors on prognosis.
Conclusions
Our study revealed that LR demonstrates comparable survival outcomes to RR in patients with ANETs. Nonetheless, LR is associated with reduced invasiveness for patients. Consequently, LR can be safely executed without compromising oncological outcomes, and it should be regarded as a viable treatment option for appropriately selected patients with ANETs.
Supplementary
The article’s supplementary files as
Acknowledgments
None.
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.
Footnotes
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-23/rc
Funding: This study was supported by the Changshu Science and Technology Program (No. CY202339), the Suzhou Youth Science and Technology Project for the Advancement of Science, Education, and Health (No. KJXW2023067), and the Suzhou 23rd Batch of Science and Technology Development Plan (Clinical Trial Institution Capability Enhancement) Project (No. SLT 2023006).
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-23/coif). The authors have no conflicts of interest to declare.
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