Abstract
Background:
Well-differentiated Grade 3 neuroendocrine tumors (G3 NETs) represent a heterogeneous entity with limited therapeutic standards. Surufatinib, a small-molecule inhibitor, has shown efficacy in G1/G2 NETs, but its specific role in the G3 subpopulation and optimal patient selection strategies remain to be elucidated.
Objectives:
This study aimed to evaluate the real-world efficacy of surufatinib in G3 NETs and identify the factors that influenced progression-free survival (PFS).
Design:
A national, multicenter, retrospective observational study.
Methods:
We analyzed data from 77 patients with unresectable or metastatic G3 NETs (Ki-67 > 20%) treated with surufatinib across 15 centers in China between January 2021 and April 2024. The reporting of this study conforms to the STROBE statement. The primary endpoint was PFS. A multivariable Cox proportional hazards model was used to explore prognostic factors.
Results:
The median Ki-67 index was 30% (range: 22%−70%), and 49 patients were of pancreatic origin. A total of 11 patients were treatment-naïve, and 27 patients received surufatinib-based combination therapy. The overall median PFS was 9.4 months (95% confidence interval: 8.5–13.0), and the objective response rate (ORR) was 22.1%. Patients with a Ki-67 index ⩽ 30% had longer PFS than the Ki-67 > 30% group (12.6 vs 9.0 months, hazard ratio = 0.270, p = 0.003). Combined treatment showed a numerical trend toward improved ORR (33.3% vs 16.0%, p = 0.08), but did not significantly prolong PFS compared to surufatinib monotherapy (9.7 vs 9.4 months, p = 0.64).
Conclusion:
Surufatinib was a promising therapeutic option for G3 NETs. Prospective, larger-scale cohorts are warranted to confirm the efficacy and address the predictive markers for better patient selection.
Keywords: Grade 3 neuroendocrine tumors, Ki-67 index, multicenter, real-world, surufatinib
Plain language summary
Could surufatinib benefit patients with Grade 3 neuroendocrine tumor?
What was studied: Grade 3 neuroendocrine tumor (G3 NET) is a rare, well-differentiated, but aggressive type of cancer with limited treatment options. Surufatinib is a targeted therapy that blocks the growth of blood vessels that feed tumors. While it has been already approved in China for patients with G1 and G2 neuroendocrine tumors, it is unclear whether G3 NET patients could also benefit, and if so, what factors influence how long patients can live on surufatinib before their cancer progresses.
What we did: We analyzed data from 77 patients with G3 NET who were treated with surufatinib from 15 hospitals across China between 2021 and 2024.
What we found: About 22% of patients saw their tumors shrink (more than 30%). On average, patients went 9.4 months without their cancer getting worse. Patients with lower Ki-67 levels (30% or below), which is a marker of how quickly tumor cells grow, lived a median of 12.6 months without progression compared to 9.0 months for those with higher Ki-67 levels. In addition, combining surufatinib with other treatments led to more tumor shrinkage, but did not significantly extend the time before the cancer started growing again.
What did these results mean: Surufatinib is a promising therapeutic option for G3 NET patients. We need larger studies to confirm how well surufatinib works and figure out which patients benefit the most.
Introduction
Grade 3 neuroendocrine tumor (G3 NET) is a distinct pathologic entity recognized by the World Health Organization (WHO) classification, characterized by well-differentiated morphology but high proliferation (Ki-67 index > 20%).1,2 Unlike neuroendocrine carcinomas (NECs), in which platinum/etoposide has been an established first-line standard of care, the management of G3 NETs represents a significant “gray zone” in clinical practice.3–8 The prognosis and optimal therapeutic sequence for this population remain ill-defined, largely due to the biological heterogeneity within the G3 entity.9–11
Current guidelines often extrapolate treatments from G2 NETs or NECs, including somatostatin analogs (SSAs),12,13 targeted therapies,14–19 peptide receptor radionuclide therapy,13,20 cytotoxic chemotherapy,21–24 and immunotherapy.21–24 However, clinical outcomes are highly variable. Recent reviews emphasize the urgent need for precision medicine approaches to better characterize these neoplasms. 25 For instance, in unresectable advanced G3 NETs, patients with Ki-67 ⩾ 55% had a survival time of only 8.0 months, whereas those with Ki-67 < 55% survived for 23.7 months.14–19 This variability underscores a critical translational gap: the lack of validated biomarkers to stratify G3 NET patients and guide treatment selection.
Surufatinib, a novel small-molecule inhibitor targeting VEGFR-1/2/3, FGFR1, and CSF-1R, 26 has demonstrated efficacy in G1/G2 NETs in the pivotal SANET-p and SANET-ep trials.27,28 However, evidence for the use of anti-angiogenic tyrosine kinase inhibitors (TKIs) in the G3 population was limited to small subgroups,16–19 and the prognostic factors for response in this entity remain unknown. Given the distinct vascular and proliferative characteristics of G3 tumors, which exhibit greater proliferative activity than G1/G2 NETs, 29 understanding which subgroup benefits the most from anti-angiogenic therapy is crucial.
In this national multicenter study, we aimed not only to evaluate the efficacy of surufatinib in advanced G3 NETs but also to investigate the factors that influenced progression-free survival (PFS).
Materials and methods
Study design and patients
We conducted a retrospective study of 77 patients with unresectable or metastatic G3 NETs treated with surufatinib across 15 centers in China between January 2021 and April 2024. The reporting of this study conforms to the STROBE statement guidelines 30 for observational studies (Supplemental File 1).
Eligible patients were required to meet the following criteria: aged ⩾18 years; histologically confirmed G3 NET according to the 2021 WHO classification; lung/thymic atypical carcinoids with a relatively high Ki-67 proliferation index (>20%) were also included, as recommended in the CABONEN trial (NCT04524208) and one retrospective European study 31 ; locally advanced or metastatic G3 NET patients who had received surufatinib monotherapy or combination therapy at any line; and at least one measurable target lesion identified on the basis of the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria. The key exclusion criteria included NECs and G1/G2 NETs. Data were retrospectively collected, including basic clinicopathological characteristics, treatment modalities, safety, and outcome.
Treatments and assessments
Patients received oral surufatinib once daily at an initial dose of 200–300 mg. Treatment was continued until disease progression, death, unacceptable toxicity, or decision by the investigator or patients. Combination therapies that included SSAs, transcatheter arterial embolization (TAE), transcatheter arterial chemoembolization (TACE), immune checkpoint inhibitors (ICIs), targeted therapy, and cytotoxic agents were allowed.
Primary endpoint was PFS. Secondary endpoints included objective response rate (ORR), disease control rate (DCR), overall survival (OS), and safety. The tumor response was evaluated by magnetic resonance imaging or computed tomography in accordance with the RECIST 1.1. Image evaluations were performed at baseline and were repeated every 6–12 weeks at the discretion of the clinician or patient. Adverse events were recorded according to the Common Terminology Criteria for Adverse Events (version 5.0).
Statistical analysis
Baseline characteristics and toxicities were summarized using descriptive statistics. Efficacy analyses were restricted to patients who had at least one response evaluation. The Clopper–Pearson method was used to calculate 95% confidence intervals (CIs) for the ORR and DCR. Fisher’s exact test was used to compare differences in ORR and DCR between subgroups. PFS and OS curves were estimated using the Kaplan–Meier method and reported with two-sided 95% CIs.
Continuous variables, such as age and Ki-67 index, were transformed into categorical variables based on median values or clinical relevance prior to survival analysis. Univariate Cox proportional hazards regression was utilized to assess individual parameters. For multivariate analysis, a stepwise Cox regression model was applied to calculate hazard ratios (HRs) and 95% CIs, with entry and removal criteria both set at p < 0.05. Variables evaluated for the multivariate model included sex, age, Ki-67 classification, primary site, metastatic sites, functional status, treatment modality (monotherapy vs combination), line of therapy, hepatic tumor burden (HTB), prior immunotherapy, prior chemotherapy, prior SSAs, prior targeted therapy, and prior interventional therapy.
To address the potential bias of the median-based Ki-67 cutoff, sensitivity analyses were performed using alternative cutoffs (25%, 40%, and 55%). In addition, sensitivity analysis was conducted in the pancreatic NET (pNET) cohort. Statistical significance was defined as a two-sided p < 0.05.
Results
Clinicopathological characteristics of G3 NET patients
Table 1 summarizes the clinicopathological characteristics of the 77 enrolled patients. The median age was 54 years (range: 21–80), with a male predominance (57.1%). Most tumors were non-functional (89.6%), and the primary sites were predominantly pancreatic (n = 49, 63.6%) or thoracic (n = 14, 18.2%). The median Ki-67 index was 30%, which was subsequently used as the cutoff to define the “low-G3” subgroup (Ki-67 ⩽30%) in our analysis; notably, only 7 patients (9.1%) had a Ki-67 > 55%. Liver metastases were present in 61 patients (79.2%). Among the 41 patients evaluable for HTB, 18 (43.9%) had an HTB > 25%.
Table 1.
Clinical characteristics of 77 patients with Grade 3 neuroendocrine tumor treated with surufatinib.
| Characteristics | Total (n = 77, %) | Ki-67 ⩽ 30% (n = 48, %) | Ki-67 > 30% (n = 29, %) | p Value | pNET (n = 49, %) | epNET (n = 28, %) | p Value |
|---|---|---|---|---|---|---|---|
| Median age, years | 54 (21–80) | 55 (21–80) | 54 (26–72) | 54 (26–80) | 56 (21–72) | ||
| Gender | 0.50 | 0.34 | |||||
| Male | 44 (57.1%) | 26 (54.2%) | 18 (62.1%) | 26 (53.1%) | 18 (64.3%) | ||
| Female | 33 (42.9%) | 22 (45.8%) | 11 (37.9%) | 23 (46.9%) | 10 (35.7%) | ||
| Median Ki-67 index (range) % | 30 (22–70) | 25 (22–30) | 50 (35–70) | 30 (22–70) | 30 (23–60) | ||
| Functional status | 1.00 | 0.65 | |||||
| Functional | 8 (10.4%) | 6 (12.5%) | 2 (10.5%) | 4 (8.2%) | 4 (14.3%) | ||
| Nonfunctional | 69 (89.6%) | 42 (87.5%) | 17 (89.5%) | 45 (91.8%) | 24 (85.7%) | ||
| Primary site | 0.34 | NA | |||||
| Pancreas | 49 (63.6%) | 28 (58.3%) | 21 (72.4%) | 49 (100%) | 0 | ||
| Lung/thymus | 14 (18.2%) | 9 (18.8%) | 5 (17.2%) | 0 | 14 (50%) | ||
| Gastrointestinal | 14 (18.2%) | 11 (22.9%) | 3 (10.4%) | 0 | 14 (50%) | ||
| Hepatic tumor burden | 0.84 | 0.002 | |||||
| None | 16 (20.8%) | 11 (22.9%) | 5 (17.2%) | 4 (8.2%) | 12 (42.9%) | ||
| ⩽25% | 23 (29.9%) | 15 (31.3%) | 8 (27.6%) | 19 (38.8%) | 4 (14.3%) | ||
| >25% | 18 (23.4%) | 11 (22.9%) | 7 (24.1%) | 11 (22.4%) | 7 (25.0%) | ||
| NA | 20 (25.9%) | 11 (22.9%) | 9 (31.1%) | 15 (30.6%) | 5 (17.8%) | ||
| Prior treatment line | 0.93 | 0.20 | |||||
| 0 | 11 (14.3%) | 7 (14.6%) | 4 (13.8%) | 8 (16.3%) | 3 (10.7%) | ||
| 1 | 31 (40.3%) | 20 (41.7%) | 11 (37.9%) | 16 (32.7%) | 15 (53.6%) | ||
| ⩾2 | 35 (45.4%) | 21 (43.7%) | 14 (48.3%) | 25 (51.0%) | 10 (35.7%) | ||
| Prior first-line treatment option | 0.43 | 0.10 | |||||
| SSA | 17 (25.8%) | 10 (24.4%) | 7 (28.0%) | 13 (31.7%) | 4 (16.0%) | ||
| Interventional therapy a | 7 (10.6%) | 3 (7.3%) | 4 (16.0%) | 6 (14.6%) | 1 (4.0%) | ||
| Etoposide plus cisplatin | 13 (19.7%) | 7 (17.1%) | 6 (24.0%) | 7 (17.1%) | 6 (24.0%) | ||
| Temozolomide-based chemotherapy | 30 (45.5%) | 22 (53.7%) | 8 (32.0%) | 21 (51.2%) | 9 (36.0%) | ||
| Oxaliplatin-based chemotherapy | 5 (7.6%) | 4 (9.8%) | 1 (4.0%) | 1 (2.4%) | 4 (16.0%) | ||
| Treatment strategy | 0.16 | 0.06 | |||||
| Monotherapy | 50 (64.9%) | 34 (70.8%) | 16 (55.2%) | 28 (57.1%) | 22 (78.6%) | ||
| Combined therapy | 27 (35.1%) | 14 (29.2%) | 13 (44.8%) | 21 (42.9%) | 6 (21.4%) | ||
| SSA | 3 (3.9%) | 3 (6.3%) | 0 | 2 (4.1%) | 1 (3.6%) | ||
| Interventional therapy a | 8 (10.4%) | 7 (14.6%) | 1 (3.4%) | 6 (12.2%) | 2 (7.1%) | ||
| Checkpoint inhibitor | 9 (11.7%) | 4 (8.3%) | 5 (17.2%) | 6 (12.2%) | 3 (10.7%) | ||
| Temozolomide-based chemotherapy | 2 (2.6%) | 1 (2.1%) | 1 (3.4%) | 2 (4.1%) | 0 | ||
| Oxaliplatin-based chemotherapy | 9 (11.7%) | 3 (6.3%) | 6 (20.7%) | 9 (18.4%) | 0 | ||
Interventional therapy: TAE, TACE.
epNET, extra-pancreatic NETs; pNET, pancreatic NETs; TACE, transcatheter arterial chemoembolization; NA, not applicable.
Surufatinib was primarily administered as a second-line or later therapy (85.7%). Among the 66 pretreated patients, prior first-line treatments were predominantly systemic chemotherapy (72.7%), most notably temozolomide-based regimens (45.5%). Surufatinib was used as monotherapy in 50 patients (64.9%) and in combination regimens for 27 patients (35.1%), typically with ICIs (33.3%), oxaliplatin-based chemotherapy (33.3%), or interventional therapy (29.6%).
Subgroup analyses revealed that patients with Ki-67 > 30% showed a trend toward receiving more combination therapies than those with Ki-67 ⩽30% (44.8% vs 29.2%, p = 0.16). Furthermore, compared to extra-pancreatic G3 NETs, pNETs were significantly more likely to present with liver metastases (91.8% vs 57.1%, p = 0.002) and had a higher tendency to receive combination treatments (42.9% vs 21.4%, p = 0.06).
Response evaluation of surufatinib monotherapy or combination therapy in advanced G3 NETs
Overall, 17 patients achieved a partial response (22.1%, 95% CI: 13.4%–33.0%), 49 had stable disease (63.6%), and 11 experienced progressive disease (14.3%), yielding a DCR of 85.7% (95% CI: 75.9%–92.6%; Figure 1).
Figure 1.
Response evaluation to surufatinib in advanced G3 NETs.
G3 NETs, Grade 3 neuroendocrine tumors.
Subgroup analyses (Figure 1) indicated a numerically higher ORR in pNETs compared to epNETs (28.6% vs 10.7%, p = 0.069), though DCRs were identical (85.7%). Within the epNET cohort, the ORRs for the lung/thymus (n = 14) and gastrointestinal (n = 14) subgroups were 14.3% and 7.1%, respectively. In addition, patients with a lower HTB (⩽25%) trended toward a higher ORR than those with HTB > 25% (34.8% vs 11.1%, p = 0.143).
While ORR did not differ significantly between Ki-67 subgroups (⩽30% vs >30%) in the overall population, combination therapy showed a trend toward improved ORR compared to monotherapy (33.3% vs 16.0%, p = 0.08). Crucially, cross-subgroup analysis revealed that the ORR benefit of combination therapy was significant in patients with Ki-67 ⩽30% (42.9% vs 8.8%, p = 0.006), and this improvement was particularly pronounced within the pNET subpopulation (50.0% vs 11.1%, p = 0.023; Supplemental Figure 1).
Survival outcomes of surufatinib in advanced G3 NETs and the prognostic factors
As shown in Figure 2(a), the overall median PFS was 9.4 months (95% CI: 8.5–13.0). Subgroup analyses revealed no significant PFS difference between pNETs and epNETs (9.7 months, 95% CI: 8.6–13.3 vs 8.6 months, 95% CI: 5.9–16.0, p = 0.414; Figure 2(c)). Within the epNET cohort, the median PFS for the lung/thymus and gastrointestinal subgroups was 8.6 months (95% CI: 5.0–NR) and 8.5 months (95% CI: 1.9–15.1), respectively (Figure 2(d)).
Figure 2.
PFS to surufatinib in advanced G3 NETs and subgroup analysis. (a) PFS in the total population. (b) PFS divided by Ki-67 index (⩽30% vs >30%). (c) PFS in pNET and epNET. (d) PFS in lung/thymus and gastrointestinal NETs.
epNET, extra-pancreatic NETs; G3 NET, Grade 3 neuroendocrine tumors; PFS, progression-free survival; pNET, pancreatic NETs.
In the univariate analysis (Table 2), no single clinical factor significantly predicted PFS, although patients with a Ki-67 ⩽30% showed a trend toward longer PFS compared to those with a Ki-67 > 30% (12.6 vs 9.0 months, p = 0.093; Figure 2(b)). Exploratory multivariate Cox regression analysis (n = 42, excluding patients with missing data, primarily in HTB) indicated that Ki-67 ⩽30% predicted a favorable prognosis (HR = 0.270, 95% CI: 0.115–0.633, p = 0.003).
Table 2.
Univariate and multivariate analysis of factors associated with PFS in 77 G3 NET patients.
| Variables | Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|---|
| HR | 95% CI | p Value | HR | 95% CI | p Value | |
| Sex (female vs male) | 1.171 | 0.680–2.016 | 0.569 | |||
| Age, years (⩾54 vs <54) | 1.022 | 0.603–1.731 | 0.936 | |||
| Ki-67 (⩽30% vs >30%) | 0.625 | 0.360–1.087 | 0.093 | 0.270 | 0.115–0.633 | 0.003 |
| Primary site (pNET vs epNET) | 0.794 | 0.461–1.372 | 0.414 | |||
| Primary site (lung/thymus vs extrathoracic) | 1.317 | 0.552–3.141 | 0.535 | |||
| Metastatic sites (⩾2 vs <2) | 1.103 | 0.629–1.933 | 0.732 | |||
| Bone metastasis (no vs yes) | 0.994 | 0.550–1.794 | 0.983 | |||
| Functional states (functional vs non-functional) | 1.450 | 0.651–3.234 | 0.363 | |||
| Combined therapy (no vs yes) | 1.142 | 0.652–1.999 | 0.643 | |||
| Treatment lines (>1 vs 1 L) | 0.977 | 0.489–1.949 | 0.951 | |||
| HTB (⩽25% vs >25%) | 0.543 | 0.283–1.159 | 0.116 | |||
| Prior checkpoint inhibitor (yes vs no) | 2.235 | 0.944–5.289 | 0.067 | |||
| Prior chemotherapy (yes vs no) | 1.091 | 0.572–2.081 | 0.792 | |||
| Prior SSA (yes vs no) | 0.723 | 0.385–1.357 | 0.313 | |||
| Prior targeted therapy (yes vs no) | 0.430 | 0.154–1.201 | 0.107 | |||
| Prior interventional therapy (yes vs no) | 0.749 | 0.394–1.423 | 0.378 | |||
CI, confidence interval; epNET, extra-pancreatic NETs; G3 NET, Grade 3 neuroendocrine tumors; HR, hazard ratio; HTB, hepatic tumor burden; PFS, progression-free survival; pNET, pancreatic NETs; SSA, somatostatin analogs; TACE, transcatheter arterial chemoembolization.
Regarding the pancreatic G3 NET cohort, the “low-G3” subgroup (Ki-67 ⩽30%) experienced a numerically longer PFS than those with a Ki-67 > 30% (13.0 vs 9.0 months, p = 0.262).
At a median follow-up of 17.8 months, the median OS was not reached.
Sensitivity analysis
Across all tested cutoffs, Ki-67 appeared to be prognostic for PFS (adjusted p < 0.05, Supplemental Table 2). Of note, when applying higher cutoffs (40% or 55%), the higher Ki-67 subgroups became markedly small (16 and 7 patients, respectively). Moreover, in the pNET cohort, lower Ki‑67 was consistently associated with a more favorable PFS trend (Supplemental Table 3).
Adverse effects
The safety profiles were evaluated in 68 patients, as 9 patients lacked complete medical records for accurate adverse event extraction. As detailed in Supplemental Table 1, the most common treatment-related adverse events (TRAEs) of any grade were hypertension (51.5%), proteinuria (26.5%), and diarrhea (20.6%). Grade 3 or 4 TRAEs occurred in 23.5% of patients, primarily driven by hypertension (16.2%) and proteinuria (7.4%). Dose reductions due to toxicity were required in 20.6% of patients. Notably, one patient with a mediastinal NET experienced an esophageal perforation that was deemed surufatinib-related. Although a higher proportion of patients receiving combination therapy experienced ⩾Grade 3 TRAEs compared to those on monotherapy (30.0% vs 20.8%), this difference was not statistically significant (p = 0.62).
Discussion
To our knowledge, this was the largest real-world multicenter study investigating surufatinib in G3 NETs, addressing a critical gap in the management of this heterogeneous entity. We demonstrated a promising ORR of 22.1% and a median PFS of 9.4 months.
A key challenge in treating G3 NETs lies in their biological heterogeneity, underscoring the urgent need for precision medicine approaches to better characterize these neoplasms. 25 A key strength of this study was its reflection of the real-world heterogeneity inherent to G3 NETs. Unlike RCTs, our cohort captured diverse populations, including functional/non-functional and pancreatic/extra-pancreatic tumors. Our outcomes compared similarly with other TKIs in G3 NETs, such as cabozantinib (PFS 6.7–7.9 months).16,17 Furthermore, patients with Ki-67 ⩽30% showed a numerically longer PFS than those with Ki-67 > 30%. Of note, given that the multivariate analysis was conducted in a reduced subset (n = 42) with high heterogeneity, the prognostic value of Ki-67 was only exploratory. Likewise, sunitinib exhibited the highest activity in neuroendocrine neoplasm (NEN) G3 with a Ki-67 cutoff value of 25%.18,19
The prognostic value of Ki-67 to treatments remains a subject of debate1,2 and the optimal Ki-67 cutoff may differ according to various treatments in G3 NETs. A Ki-67 index < 40% may identify G3 GEP-NET patients who benefit more from CAPTEM32–35 or oxaliplatin-based regimens (FOLFOX/XELOX).36,37 The low-G3 subgroup (Ki-67 ⩽30%) had a trend of improved ORR compared to G3 high subgroup (Ki-67 > 30%) in the NETTER-2 study. 38 The duration of response to everolimus did not seem to be related to the Ki-67 index, ranging between 20% and 55%. 15
In our study, to address the concern regarding the historic and our cohort data-driven nature of the 30% cutoff (median value), we performed sensitivity analyses using alternative cutoffs (25%, 40%, and 55%). Although informative of Ki67 as a prognostic factor across all cutoffs, the small number of patients substantially limits the reliability. More importantly, the evaluation of Ki‑67 as a continuous variable rather than dichotomization at any specific cutoff should be explored in future prospective large-scale studies. Specifically, patients with 20% < Ki-67 ⩽ 30% achieved a median PFS of 12.6 months, comparable to G2 NETs with 10% < Ki-67 ⩽ 20% treated with surufatinib in the SANET-p (11.1 months) and SANET-ep (8.3 months) trials.27,28 This implies that “low-G3” (Ki-67 ⩽30%) tumors biologically resemble aggressive G2 tumors, a concept reinforced by recent proposals of “G2b” sub-grading.
Regarding prognostic factors beyond Ki-67, we found that primary tumor location did not significantly influence PFS. Notably, our study included a rare subgroup of lung/thymus NETs (n = 14), achieving a promising median PFS of 8.6 months (Figure 2(d)). This finding was clinically encouraging, as evidence for TKI efficacy in thoracic G3 NETs was extremely scarce, suggesting potential efficacy extending beyond digestive origins. Other markers, such as CRP or ALP, were not included in this analysis, warranting future exploration.
Regarding combination therapy, adding chemotherapy or immunotherapy to surufatinib doubled the ORR (33.3% vs 16.0%), yet no significant PFS benefit was observed (median 9.7 vs 9.4 months). For the “low-G3” subgroup, surufatinib monotherapy appeared sufficient for long-term control with a manageable safety profile consistent with previous trials,27,28 avoiding the toxicity of combinations. Therefore, we proposed that combination strategies might be better reserved for patients with high tumor burden requiring rapid symptom relief, rather than as a standard maintenance approach for all G3 patients.
The safety profile in our study was consistent with previous reports,27,28 with hypertension and proteinuria being the most common adverse events. No new safety signals were identified.
Limitations of our study must be acknowledged. First, while the efficacy of surufatinib in this study was clinically noteworthy, the retrospective, single-arm, non-comparative design without a control group precludes any definitive conclusion that could serve as confirmatory evidence of treatment benefit. These findings should, therefore, be regarded as exploratory in nature and require prospective validation through randomized controlled trials. Second, the lack of central pathology review was a significant limitation, such as inter-observer variability in Ki-67 scoring and misclassification between NET G3 and NEC. It was worth noting that all participating centers were high-volume centers for neuroendocrine tumors, which helped to alleviate concerns regarding the accuracy of pathological grading. In future studies, we will use multicenter joint quality control or centralized review to reduce bias. Third, the sample size was still limited. Furthermore, epidemiological data have revealed racial disparities in NEN incidence, genomic landscape, treatment receipt, and even cancer-specific survival.39–42 Therefore, the findings derived exclusively from a Chinese population cannot be directly extrapolated to other ethnic or regional groups. Fourth, dichotomization of a continuous variable such as Ki-67 inevitably leads to loss of information, residual within-group heterogeneity, and potential misclassification near the cutoff. Finally, molecular profiling (e.g., DAXX/ATRX, MEN1, TP53) was not available, which could provide deeper biological insights.
Conclusion
Surufatinib was shown to be a promising therapeutic option for patients with advanced G3 NETs, although these findings remain exploratory and warrant prospective validation (Figure 3).
Figure 3.
Surufatinib in advanced G3 NETs.
G3 NET, Grade 3 neuroendocrine tumors.
Beyond pancreatic primaries, the therapeutic potential of TKIs in epNETs—including those of lung or thymic origin—merits further investigation. Combination strategies involving TKIs and other modalities represent a promising avenue for exploration and increase the chance of conversion surgery, particularly among patients with negative somatostatin receptor expression. Moving forward, prospective and randomized trials are needed to identify biomarkers for better treatment selection, such as the integration of molecular characterization into study designs, and to establish the optimal sequencing of therapies for G3 NETs.
Supplemental Material
Supplemental material, sj-docx-1-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-2-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-3-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-4-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-jpg-1-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Acknowledgments
We sincerely appreciate the valuable contribution of Taibao Zhang (PhD, Hanyang University, South Korea) for his expertise in creating the graphical abstract. We thank all the patients and their families for their participation in this study, as well as the investigators from the 15 participating centers.
Footnotes
ORCID iD: Jian Wang 
https://orcid.org/0000-0001-7620-6740
Supplemental material: Supplemental material for this article is available online.
Contributor Information
Jian Wang, Department of Medical Oncology, Qilu Hospital of Shandong University, Jinan, China.
Ning Zhang, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Yun Liang, Fudan University Shanghai Cancer Center, Shanghai, China.
Jiang Long, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yihebali Chi, Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, China.
Suzhen Zhang, Shanxi Cancer Hospital, Taiyuan, China.
Chunmei Bai, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yu Wang, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Yinying Wu, Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China.
Hanguang Hu, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Weiyu Hu, The Affiliated Hospital of Qingdao University, Qingdao, China.
Li Huang, Zibo Central Hospital, Zibo, China.
Ying Liu, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Huifang Lv, Henan Cancer Hospital, Zhengzhou, China.
Shanai Song, The Affiliated Hospital of Qingdao University, Qingdao, China.
Aili Suo, Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China.
Xiangling Wang, Department of Medical Oncology, Qilu Hospital of Shandong University, Jinan, China.
Lin Zhang, Shandong Cancer Hospital, Jinan, China.
Liming Zhu, Zhejiang Cancer Hospital, Hangzhou, China.
Jie Chen, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Jing Hao, Department of Medical Oncology, Qilu Hospital of Shandong University, Jinan 250012, China.
Declarations
Ethics approval and consent to participate: This study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Qilu Hospital of Shandong University (approval No. KYLL-202210-028-1). The study was registered at ClinicalTrials.gov (NCT05973968; registered July 16, 2023). The requirement for informed consent was waived due to the retrospective nature of the study.
Consent for publication: Not applicable.
Author contributions: Jian Wang: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Validation; Writing – original draft; Writing – review & editing.
Ning Zhang: Data curation; Investigation; Methodology; Project administration; Resources; Visualization; Writing – original draft.
Yun Liang: Investigation; Writing – original draft.
Jiang Long: Investigation; Writing – original draft.
Yihebali Chi: Investigation; Writing – original draft.
Suzhen Zhang: Investigation; Writing – original draft.
Chunmei Bai: Investigation; Writing – original draft.
Yu Wang: Investigation; Writing – original draft.
Yinying Wu: Investigation; Writing – original draft.
Hanguang Hu: Investigation; Writing – original draft.
Weiyu Hu: Investigation; Writing – original draft.
Li Huang: Investigation; Writing – original draft.
Ying Liu: Investigation; Writing – original draft.
Huifang Lv: Investigation; Writing – original draft.
Shanai Song: Investigation; Writing – original draft.
Aili Suo: Investigation; Writing – original draft.
Xiangling Wang: Investigation; Writing – original draft.
Lin Zhang: Investigation; Writing – original draft.
Liming Zhu: Investigation; Writing – original draft.
Jie Chen: Conceptualization; Investigation; Resources; Supervision; Validation; Writing – review & editing.
Jing Hao: Conceptualization; Data curation; Investigation; Methodology; Project administration; Resources; Supervision; Validation; Writing – review & editing.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the China Health & Medical Development Foundation (Grant No. chmdf2024-xrzx07-14).
The authors declare that there is no conflict of interest.
Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.*
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Supplementary Materials
Supplemental material, sj-docx-1-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-2-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-3-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-docx-4-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology
Supplemental material, sj-jpg-1-tam-10.1177_17588359261464488 for Efficacy of surufatinib in advanced Grade 3 neuroendocrine tumors: a real-world, national, multicenter study by Jian Wang, Ning Zhang, Yun Liang, Jiang Long, Yihebali Chi, Suzhen Zhang, Chunmei Bai, Yu Wang, Yinying Wu, Hanguang Hu, Weiyu Hu, Li Huang, Ying Liu, Huifang Lv, Shanai Song, Aili Suo, Xiangling Wang, Lin Zhang, Liming Zhu, Jie Chen and Jing Hao in Therapeutic Advances in Medical Oncology