Abstract
Although combination therapy is not recommended in patients with gastro–entero–pancreatic (GEP) neuroendocrine tumors (NETs), this strategy is widely used in clinical practice. This network meta-analysis of randomized trials evaluates targeted therapies and somatostatin analogues in GEP-advanced NETs, either alone or in combination, comparing the efficacy of different, single or combined treatment strategies in terms of progression-free survival (PFS). Interventions were grouped as analogs, everolimus, everolimus plus SSAs, sunitinib and placebo. In a secondary analysis, we also assessed the efficacy of individual-specific pharmacological treatments vs placebo or each other. From 83 studies identified, 8 randomized controlled trials were selected, with a total of 1849 patients with either functioning or non-functioning NETs. The analysis confirmed the superiority of all treatments over placebo (HR ranging from 0.34, 95% CI: 0.24–0.37 with the combination of everolimus plus SSAs to 0.42, 0.31–0.57 with the analogs; moderate quality of evidence). On ranking analysis, the combination of everolimus plus SSA (P score = 0.86) and then everolimus alone (P score = 0.65) ranked highest in increasing PFS. On comparative evaluation of different interventions, pasireotide (P score = 0.96) and everolimus + octreotide (P score = 0.82) ranked as the best pharmacological treatment options. Our findings support the use of combination therapy in the treatment of functioning and non-functioning GEP NETs. The role of pasireotide should be explored in selected subgroups of patients. Lastly, the combination of everolimus and octreotide appears promising and should be more widely considered in clinical practice.
Introduction
Neuroendocrine tumors (NETs) of the gastro–entero–pancreatic (GEP) system are rare neoplasms that originate from the diffused endocrine system in the gastrointestinal tract and the pancreas, with extremely varying clinical presentation (Partelli et al. 2014).
GEP NETs are classified considering both tumor morphology (well- or poorly differentiated) and proliferation rate (assessed by Ki67 and mitotic count), according to the World Health Organization (WHO) and European Neuroendocrine Tumor Society (ENETS) guidelines (Bosman et al. 2017, Nagtegaal et al. 2020). Well-differentiated NETs are associated with a relatively favorable prognosis (Milione et al. 2018, Pusceddu et al. 2018), although they present a marked heterogeneity in their clinical behavior (Pusceddu et al. 2017).
Surgery is the only curative treatment for localized and metastatic GEP NETs (Ishida & Lam 2020, Palmieri et al. 2020). However, if the patient has a metastatic disease without the possibility of curative surgical treatment or locoregional or ablative therapy, or if there is a high surgical risk, medical treatment remains the cornerstone for improving survival and preserving the quality of life (Kiesewetter & Raderer 2020).
Pharmacological treatment of GEP NETs comprises somatostatin analogs (SSAs; octreotide (OCT) long-acting release and lanreotide (LAN) autogel), chemotherapy, peptide receptor radiotherapy and targeted therapy with everolimus or sunitinib (Oronsky et al. 2017, Prinzi et al. 2019, Kiesewetter & Raderer 2020).
The above-mentioned target therapies can be administered alone or in combination (Tsoli et al. 2018), thus expanding the therapeutic armamentarium. Despite current guidelines not recommending combination therapy due to the disappointing results of some phase III clinical trials (Delle Fave et al. 2016, Falconi et al. 2016, Pavel et al. 2020), this strategy is widely used for GEP NETs in clinical practice, especially in patients with functioning tumors and in those with a high expression of somatostatin receptors (Pusceddu et al. 2016, Kulke et al. 2017, Pusceddu 2018).This meta-analysis aims to evaluate the use of targeted therapies and SSAs in GEP advanced NETs, used either alone or in combination, comparing the efficacy in terms of progression-free survival (PFS) of different single or combined treatment strategies.
Methods
This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and was conducted following an a priori established protocol (Moher et al. 2009).
Selection criteria
Studies included in this meta-analysis were parallel group, randomized controlled trials (RCTs), which met the following inclusion criteria: (a) patients: adult patients with NETs treated with systemic therapies; (b) intervention: analogs (OCT, pasireotide, LAN), combination of everolimus plus SSAs, everolimus alone, sunitinib); (c) comparator: placebo or active treatment and (d) outcome: PFS.
We excluded observational or non-randomized studies and trials not including any of the aforementioned treatments in the comparator group.
Search strategy, data abstraction and risk of bias assessment
A comprehensive search of several electronic databases from inception to September 2020 was conducted, without any language restrictions. The databases included Ovid Epub, MEDLINE, In-Process and other non-indexed citations, Ovid MEDLINE, Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Scopus and Web of Science. The search strategy was designed and conducted by one of the authors with input from the other studys’ investigators. In addition, conference proceedings from main oncological meetings from 2015 to 2017 were searched to identify studies published only as abstracts. We used the following general search strategy, then repeated according to the specific syntax for the query of each database: 'neuroendocrine tumors' AND ([octreotide OR lanreotide OR pasireotide OR somatostatin analogues] OR [sunitinib OR everolimus OR pazopanib OR axitinib OR bevacizumab]).
Data on study, participant and intervention characteristics were abstracted onto a standardized form, by two investigators independently and discrepancies were resolved by consensus, referring back to the original article, in consultation with a third reviewer. Two study investigators independently rated the quality of included trials using the Cochrane Risk of Bias Tool, with disagreements addressed by re-evaluation, in conjunction with a third reviewer.
Outcomes assessed
The primary outcome of interest was PFS, defined as the time from random assignment in a clinical trial to disease progression or death from any cause, reported as hazard ratio (HR) with 95% CIs. Adverse events were inconsistently reported and hence, were described only qualitatively. We decided not to analyze overall survival (OS), since most of the included trials did not reach the OS median due to the indolent course of GEP NETs.
For the purposes of primary analysis, interventions were grouped as noted above (analogs, everolimus, everolimus plus SSAs, sunitinib and placebo). In a secondary analysis, we also assessed the overall and comparative efficacy of individual specific pharmacological treatments vs placebo or each other, for increasing PFS.
Statistical analysis
We conducted a network meta-analysis using a multivariate random-effects meta-regression, using consistency model, as described by Ian White (White et al. 2012). We used a frequentist approach and provided a point estimate from the network along with 95% CI from the frequency distribution of the estimate. Network consistency was evaluated by comparing the direct estimates to the indirect estimates for each comparison, using a node-splitting technique. All network meta-analyses were performed using R software (netmeta package).
We calculated the relative ranking of interventions for PFS as the P score, defined as the mean of all 1 – P[j] where P[j] denotes the one-sided P-value of accepting the alternative hypothesis that a specific treatment is better than one of the competing treatments j. Thus, if that treatment is better than many other treatments, many of these P-values will be small and the P score will be large. Vice versa, if the treatment is worse than most other treatments, the P score is small. Therefore, the P score of a treatment can be interpreted as the mean extent of certainty that that treatment is better than another treatment.
Quality of evidence
The quality of evidence derived from the pairwise and network meta-analysis was judged using the GRADE framework (Puhan et al. 2014). In this approach, direct evidence from RCTs starts at high quality and can be rated down based on risk of bias, indirectness, imprecision, inconsistency (or heterogeneity) and/or publication bias, to levels of moderate, low and very low quality. The rating of indirect estimates starts at the lowest rating of the two pairwise estimates that contribute as first-order loops to the indirect estimate but can be rated down further for imprecision or intransitivity (dissimilarity between studies in terms of clinical or methodological characteristics).
Results
Characteristics of included studies
From 83 unique studies identified using the search strategy, eight RCTs were identified and included in the network meta-analysis (Fig. 1). Study characteristics and main demographic data are depicted in Table 1. Overall, these eight two-arm trials included 1849 patients in total, who were well-balanced in terms of baseline characteristics.
Flow-chart of study selection.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Flow-chart of study selection.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Flow-chart of study selection.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Characteristics of patients enrolled in the considered studies.
| Study |
Patients (n) |
Median age (min–max); years |
Males, n (%) |
Primary tumor site, n (%) |
Tumor grade, n (%) |
Non-functioning tumor, n (%) |
Metastases, n (%) |
Previous treatment lines, n (%) |
|
|---|---|---|---|---|---|---|---|---|---|
| PROMID (Rinke et al. 2009) | Octreotide | 42 | 63.5 (38–79) | 20 (47.6) | Midgut | G1: 42 (100) | 25 (60) | NR | |
| Placebo | 43 | 61 (39–82) | 23 (53.5) | Midgut | G1: 43 (100) | 27 (63) | NR | ||
| CLARINET (Caplin et al. 2014) | Lanreotide | 101 | Mean ± s.d.: 63.3 ± 9.8 | 53 (52) | Pancreas: 42 (42) | G1: 69 (68) G2: 32 (32) |
101 (100) | NR | 16 (16) |
| Midgut: 33 (33) | |||||||||
| Hindgut: 11 (11) | |||||||||
| Unknown/other: 15 (15) | |||||||||
| Placebo | 103 | Mean ± s.d.: 62.2 ± 11.1 | 54 (52) | Pancreas: 49 (48) | G1: 72 (70) G2: 29 (28) |
103 (100) | NR | 16 (16) | |
| Midgut: 40 (39) | |||||||||
| Hindgut: 3 (3) | |||||||||
| Unknown/other: 11 (11) | |||||||||
| (Wolin et al. 2015) | Octreotide | 45 | 63 (28–86) | 34 (60) | Small intestine: 46 (81) | G1:48 (84) G2: 1 (2) |
0 | NR | Chemotherapy: 12 (21) |
| Colon: 1 (2) | Immunotherapy: 14 (25) | ||||||||
| Pancreas: 1 (2) | Targeted therapy: 8 (14) | ||||||||
| Lung: 1 (2) | Other: 10 (18) | ||||||||
| Stomach: 1 (2) | |||||||||
| Other: 7 (12) | |||||||||
| Pasireotide | 43 | 61 (40–80) | 29 (55) | Small intestine: 38 (72) | G1: 41 (77) G2: 2 (4) |
0 | NR | Chemotherapy: 10 (19) | |
| Colon: 3 (6) | Immunotherapy: 12 (23) | ||||||||
| Liver: 3 (6) | Targeted therapy: 7 (13) | ||||||||
| Pancreas: 1 (2) | Other: 14 (26) | ||||||||
| Other: 8 (15) | |||||||||
| RADIANT 2 (Pavel et al. 2011) | Everolimus + Octreotide | 216 | 60 (22–83) | 97 (45) | Small intestine: 111 (51) | G1: 166 (77) G2: 38 (18) |
0 | NR | SSA therapy: 173 (80) |
| Lung: 33 (15) | Octreotide therapy: 169 (78) | ||||||||
| Colon: 14 (6) | Other systemic antitumor drugs: 99 (46) | ||||||||
| Pancreas: 11 (5) | |||||||||
| Liver: 7 (3) | |||||||||
| Other: 40 (19) | |||||||||
| Octreotide | 213 | 60 (27–81) | 124 (58) | Small intestine: 113 (53) | G1: 175 (82) G2: 30 (14) |
0 | NR | SSA therapy: 166 (78) | |
| Lung: 11 (5) | Octreotide therapy: 152 (71) | ||||||||
| Colon: 14 (7) | Other systemic antitumor drugs: 82 (38) | ||||||||
| Pancreas: 15 (7) | |||||||||
| Liver: 11 (5) | |||||||||
| Other: 48 (23) | |||||||||
| RADIANT 3 (Yao et al. 2011) | Everolimus | 207 | 58 (23–87) | 110 (53) | Pancreas | G1: 170 (82) G2: 35(17) |
NR | Liver: 190 (92) | Radiotherapy:23; Chemotherapy:50; SSA therapy:49. |
| Pancreas: 92 (44) | |||||||||
| Lymph nodes: 68 (33) | |||||||||
| Lung: 28 (14) | |||||||||
| Bone: 13 (6) | |||||||||
| Placebo | 203 | 57 (20–82) | 117 (58) | Pancreas | G1: 171 (84) | NR | Liver: 87 (92) | Radiotherapy:20; Chemotherapy:50; SSA therapy:50. | |
| G2: 30 (15) | Pancreas: 84 (41) | ||||||||
| Lymph nodes: 73 (36) | |||||||||
| Lung: 30 (15) | |||||||||
| Bone: 29 (14) | |||||||||
| RADIANT 4 (Yao et al. 2016) | Everolimus | 205 | 65 (22–86) | 89 (43) | Lung: 63 (31) | G1:129 (63) | 65 (100) | Liver: 163 (80) | Surgery: 121 (59) |
| Ileum: 47 (23) | G2: 75(37) | Lymph nodes: 85 (42) | Chemotherapy: 54 (26) | ||||||
| Rectum: 25 (12) | Lung: 45 (22) | Radiotherapy including PRRT: 44 (22) | |||||||
| Unknown: 23 (11) | Bone: 45 (21) | Locoregional and ablative therapies: 23 (11) | |||||||
| Jejunum: 16 (8) | Peritoneum: 25 (12) | SSA: 109 (53) | |||||||
| Stomach: 7 (3) | |||||||||
| Duodenum: 8 (4) | |||||||||
| Colon: 5 (2) | |||||||||
| Other: 6 (3) | |||||||||
| Caecum: 4 (2) | |||||||||
| Placebo | 97 | 65 (22–86) | 53 (55) | Appendix: 1 (1) | G1: 65 (67) | 97 (100) | Liver: 76 (78) | Surgery: 70 (72) | |
| G2: 32 (33) | Lymph nodes: 45 (46) | Chemotherapy: 23 (24) | |||||||
| Lung: 20 (21) | Radiotherapy including PRRT: 19 (20) | ||||||||
| Bone: 15 (16) | Locoregional and ablative therapies: 10 (10) | ||||||||
| Peritoneum: 8 (8) | SSA: 54 (56) | ||||||||
| (Raymond et al. 2011) | Sunitinib | 86 | 56 (25–84) | 42 (49) | Pancreas | G1: 86 (100) | 42 (49) | Any, including hepatic: 82 (95) | Surgery: 76 (88) |
| Extrahepatic: 21 (24) | Chemotherapy: 57 (66) | ||||||||
| Radiation therapy: 9 (10) | |||||||||
| Chemoembolization: 7 (8) | |||||||||
| Radiofrequency ablation: 3 (3) | |||||||||
| Percutaneous ethanol injection: 1 (1) | |||||||||
| SSA: 30 (35) | |||||||||
| Placebo | 85 | 57 (26–78) | 40 (47) | Pancreas | G1: 85 (100) | 44 (52) | Any, including hepatic: 80 (94) | Surgery: 77 (91) | |
| Extrahepatic: 34 (40) | Chemotherapy: 61 (72) | ||||||||
| Radiation therapy: 12 (14) | |||||||||
| Chemoembolization: 14 (16) | |||||||||
| Radiofrequency ablation: 6 (7) | |||||||||
| Percutaneous ethanol injection: 2 (2) | |||||||||
| SSA: 32 (38) | |||||||||
| COOPERATE 2 (Kulke et al. 2017) | Everolimus + Pasireotide | 79 | 57 (22–79) | 39 (49.4) | Pancreas | G1 or G2: 77 (97) | NR | NR | 51 (65) |
| Everolimus | 81 | 59 (26–82) | 47 (58.0) | Pancreas | G1 or G2: 79 (97) | NR | NR | 50 (62) | |
Furthermore, the PROMID and the CLARINET trials compared OCT and LAN with placebo, respectively (Rinke et al. 2009, Caplin et al. 2014); the trial by Wolin et al. compared OCT with pasireotide (Wolin et al. 2015); the RADIANT-2 trial compared the association of everolimus and OCT with OCT alone (Pavel et al. 2011); the RADIANT-3 and -4 trials compared everolimus with placebo (Yao et al. 2011, 2016); the trial by Raymond et al. compared sunitinib with placebo (Raymond et al. 2011) and the COOPERATE 2 trial compared the association of everolimus and pasireotide with everolimus monotherapy (Kulke et al. 2017).
Risk of bias assessment was performed in the context of the primary outcome and, overall, the studies were felt to be at low risk of bias.
Overall and study-level quality assessments are summarized in Supplementary Fig. 1A and B(see section on supplementary materials given at the end of this article), respectively.
PFS of groups of interventions (primary analysis)
On network meta-analysis, no inconsistency was observed between results of direct and indirect comparison. Figure 2 shows the networks of trials, considering treatments grouped as described above. Main results of the network meta-analysis are reported in Table 2.
Networks of trials. A full colour version of this figure is available at https://doi.org/10.1530/ERC-20-0492.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Networks of trials. A full colour version of this figure is available at https://doi.org/10.1530/ERC-20-0492.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Networks of trials. A full colour version of this figure is available at https://doi.org/10.1530/ERC-20-0492.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Results of the network meta-analysis.
| Analog | Everolimus | Everolimus + analogue | Placebo | Sunitinib | |
|---|---|---|---|---|---|
| Analogue | 1.10 (0.8–1.51) | 1.24 (0.97–1.58) | 0.42 (0.31–0.57) | 1.01 (0.58–1.76) | |
| Everolimus | 0.90 (0.66–1.23) | 1.12 (0.81–1.55) | 0.38 (0.31–0.46) | 0.92 (0.55–1.52) | |
| Everolimus + analog | 0.80 (0.63–1.02) | 0.88 (0.64–1.23) | 0.34 (0.24–0.47) | 0.81 (0.46–1.44) | |
| Placebo | 2.34 (1.75–3.12) | 2.58 (2.13–3.13) | 2.90 (2.1–4.01) | 2.38 (1.49–3.79) | |
| Sunitinib | 0.98 (0.56–1.7) | 1.08 (0.65–1.79) | 1.22 (0.69–2.15) | 0.42 (0.26–0.66) |
All data are expressed as hazard ratio (95% CI).
The analysis confirmed the superiority of all treatments over placebo (HR ranging from 0.34, 95% CI: 0.24–0.37 with the combination of everolimus plus SSAs to 0.42, 0.31–0.57 with the analogs). None of the other comparisons were significant although everolimus plus SSAs determined a consistent benefit over analogs alone, close to the significance threshold (HR 0.80, 95% CI: 0.63–1.02).
On ranking analysis, combination of everolimus plus SSAs (P score 0.86) and then everolimus alone (P score 0.65) were ranked highest in increasing PFS, with the former detected as the best treatment strategy in this setting (Supplementary Table 1).
We did not find any evidence of small study effects based on funnel plot asymmetry (Supplementary Fig. 1) and there was no significant difference between direct and indirect estimates in closed loops that allowed assessment of network coherence.
PFS of single interventions (secondary analysis)
Figure 3 shows the networks of trials, considering individual treatments. On comparative evaluation of different interventions, all the single treatments were confirmed to be superior to placebo (HR 0.14, 95% CI: 0.05–0.38 with pasireotide to HR 0.47, 95% CI: 0.30–0.73 with LAN; Table 3).
Networks of trials considering individual treatments. A full colour version of this figure is available at https://doi.org/10.1530/ERC-20-0492.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Networks of trials considering individual treatments. A full colour version of this figure is available at https://doi.org/10.1530/ERC-20-0492.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Networks of trials considering individual treatments. A full colour version of this figure is available at https://doi.org/10.1530/ERC-20-0492.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
Comparative evaluation of different interventions.
| Everolimus | Everolimus + octreotide | Everolimus + pasireotide | Lanreotide | Octreotide | Pasireotide | Placebo | Sunitinib | |
|---|---|---|---|---|---|---|---|---|
| Everolimus | 1.59 (0.85–2.97) | 1.01 (0.64–1.57) | 0.84 (0.51–1.36) | 1.23 (0.69–2.17) | 2.68 (1.01–7.12) | 0.39 (0.32–0.48) | 0.94 (0.56–1.56) | |
| Everolimus + octreotide | 0.62 (0.33–1.17) | 0.63 (0.29–1.36) | 0.52 (0.25–1.10) | 0.77 (0.59–1.00) | 1.68 (0.72–3.89) | 0.24 (0.13–0.44) | 0.59 (0.27–1.25) | |
| Everolimus + pasireotide | 0.99 (0.63–1.54) | 1.57 (0.73–3.39) | 0.83 (0.43–1.60) | 1.22 (0.59–2.51) | 2.65 (0.90–7.76) | 0.39 (0.24–0.63) | 0.93 (0.47–1.82) | |
| Lanreotide | 1.19 (0.73–1.93) | 1.89 (0.90–3.97) | 1.20 (0.62–2.32) | 1.46 (0.73–2.93) | 3.19 (1.11–9.16) | 0.47 (0.30–0.73) | 1.11 (0.58–2.13) | |
| Octreotide | 0.81 (0.45–1.43) | 1.29 (0.99–1.67) | 0.81 (0.39–1.68) | 0.68 (0.34–1.36) | 2.17 (0.98–4.81) | 0.32 (0.18–0.54) | 0.76 (0.37–1.54) | |
| Pasireotide | 0.37 (0.14–0.99) | 0.59 (0.25–1.37) | 0.37 (0.12–1.10) | 0.31 (0.10–0.89) | 0.46 (0.20–1.01) | 0.14 (0.05–0.38) | 0.35 (0.12–1.01) | |
| Placebo | 2.53 (2.07–3.09) | 4.03 (2.22–7.29) | 2.55 (1.57–4.16) | 2.12 (1.36–3.31) | 3.12 (1.83–5.31) | 6.79 (2.61–17.6) | 2.38 (1.49–3.79) | |
| Sunitinib | 1.06 (0.64–1.76) | 1.69 (0.79–3.59) | 1.07 (0.54–2.10) | 0.89 (0.46–1.70) | 1.31 (0.64–2.66) | 2.85 (0.98–8.26) | 0.42 (0.26–0.66) |
All data are expressed as hazard ratio (95% CI).
Moreover, pasireotide was significantly superior to everolimus (HR 0.37, 95% CI: 0.14–0.99), LAN (HR 0.31, 95% CI: 0.10–0.89), and it almost reached statistical significance over OCT (HR 0.46, 95% CI: 0.20–1.01) and sunitinib (HR 0.35, 95% CI: 0.12–1.01) (Fig. 4).
(A and B) Forest plots of progression-free survival.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
(A and B) Forest plots of progression-free survival.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
(A and B) Forest plots of progression-free survival.
Citation: Endocrine-Related Cancer 28, 7; 10.1530/ERC-20-0492
As a consequence, pasireotide (P score 0.96) and everolimus+octreotide (P score 0.82) ranked as the best pharmacological treatment options in patients with NETs (Table 4).
Ranking of treatments.
| Rank | P-score |
|---|---|
| Pasireotide | 0.9655 |
| Everolimus + octreotide | 0.8223 |
| Octreotide | 0.5951 |
| Everolimus + pasireotide | 0.4657 |
| Everolimus | 0.4521 |
| Sunitinib | 0.3993 |
| Lanreotide | 0.2999 |
| Placebo | 0.0001 |
Quality of evidence
The overall body of evidence was rated down due to imprecision and indirectness, whereas there was no inconsistency, risk of bias in the literature or publication bias for any of the comparisons.
Therefore, based on network meta-analysis, moderate quality of evidence supported the comparisons of the pharmacological treatments over placebo to increase PFS (quality of evidence rated down due to indirectness), and low-quality evidence supported the use of pasireotide over LAN and everolimus (quality of evidence rated down because of imprecision and indirectness).
Adverse events
Grade 3/4 adverse events (AEs) of those classified as serious reported in the considered studies are summarized in Table 5.
Grade 3–4 or serious adverse events.
| Adverse event | Lanreotide | Everolimus | Everolimus + pasireotide | Pasireotide | Everolimus + octreotide | Octreotide | Sunitinib | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| CLARINET (Caplin et al. 2014) | COOPERATE 2 (Kulke et al. 2017) | RADIANT 3 (Yao et al. 2011) | RADIANT 4 (Yao et al. 2016) | COOPERATE 2 (Kulke et al. 2017) | (Wolin et al. 2015) | RADIANT 2 (Pavelet al. 2011) | RADIANT 2 (Pavelet al. 2011) | (Wolinet al. 2015) | PROMID (Rinke et al. 2009) | (Raymond et al. 2011) | |
| Hyperglycemia | 3% | 11% | 5% | 4% | 37% | 10% | 5% | 2% | |||
| Diabete mellitus | 3% | 11% | |||||||||
| Stomatitis | 8% | 7% | 9% | 9% | 5% | 7% | |||||
| Diarrhea | 3% | 3% | 7% | 5% | 6% | 2% | 14% | ||||
| Nausea/vomiting | 3% | 4% | |||||||||
| Abdominal pain | 3% | 6% | 2% | 14% | |||||||
| Anemia | 5% | 6% | 4% | 5% | 12% | ||||||
| Thrombocytopenia | 4% | 5% | 12% | ||||||||
| Neutropenia | 12% | 12% | |||||||||
| Fatigue | 4% | 7% | 3% | 2% | 19% | ||||||
| Infections | 7% | 5% | |||||||||
| Cholelithiasis | 3% | 2% | |||||||||
| Hypertension | 10% | ||||||||||
| Erythrodysesthesia | 6% | ||||||||||
Proportion of patients at each event is reported.
Discussion
The best treatment regimen in patients with GEP NETs amenable to targeted therapies requires further investigation. Some mechanistic studies allow to speculate that the combination of SSAs with either everolimus or sunitinib can improve the clinical outcome of these kinds of tumors (Capdevila et al. 2015), even if data addressing whether this combination results in synergistic or additive efficacy compared to monotherapy are lacking (Krug et al. 2019). SSAs – OCT and LAN – can alleviate the symptoms associated with NETs through a strong inhibitory effect on hypersecretion of different hormones and growth factors (Bousquet et al. 2012). Pasireotide, another SSA, is able to target a wider range of somatostatin receptors than the other SSA (subtypes 1, 2, 3 and 5), and thus has a larger field of activity (Lesche et al. 2009).
An explanation that sustains the hypothesis of a synergistic anti-proliferative effect of SSAs and mTOR inhibitors (as everolimus) could be the simultaneous modulation of the PI3K/AKT/mTOR signaling pathway that results in the control of protein synthesis (Bousquet et al. 2012). Another explanation may derive from the complementary inhibitory action of everolimus and SSAs on the protein 4EBP1, a potent regulator of cellular protein synthesis and an essential factor that transduces oncogenic signals (She et al. 2010). Everolimus and somatostatin analogs could also synergistically decrease angiogenesis (Albini et al. 1999). With respect to sunitinib, this molecule can modulate the somatostatin receptor expression and thus affect the impact of SSAs (Krug et al. 2019).
Despite these encouraging mechanistic premises, phase III trials that evaluated combination treatments vs monotherapy failed to show the superiority of combination treatments. However, some critical issues may have affected the conclusions of these studies. For instance, in the phase III RADIANT-2 trial, the WHO performance status was not comparable between the everolimus plus octreotide and the octreotide arm, disadvantaging the treatment arm, which also presented a higher incidence of pulmonary primary tumors in the everolimus plus octreotide arm. Furthermore, patients assigned to the combination arm had a more frequent prior use of chemotherapy. Lastly, this study did not reach statistical significance with respect to PFS, but the significance threshold was set at 0.0246 and its actual value was 0.026 (Pavel et al. 2011, Pusceddu et al. 2016).
In the COOPERATE 2 trial, differences in baseline progression status between arms could be speculated since the RECIST-defined progression was not required and no central review to confirm the progression before study entry was carried out. Additionally, somatostatin receptor status was not known before enrollment and scintigraphy was not required (Kulke et al. 2017).
Therefore, additional studies to evaluate the effectiveness of the combination therapy are needed, considering its large-scale use in the 'real-world' setting.
Through the present network meta-analysis of eight RCTs, we made several key observations. First, a combination of everolimus plus SSAs ranked as the most valuable treatment regimen in prolonging PFS (P score 0.86), followed by everolimus alone (P score 0.65). Moreover, although not reaching the significance threshold, the combination regimen of everolimus plus SSAs appeared superior to SSAs alone. As expected, all treatments were found to be significantly superior over placebo (HR 0.34, 95 %CI 0.24–0.37). Remarkably, these results were observed in patients with either functioning or non-functioning tumors.
All single treatments were confirmed to be superior to placebo. This analysis suggests a very favorable efficacy of pasireotide, which resulted significantly superior to the other analog LAN (HR: 0.31; 95% CI: 0.10–0.89) and everolimus (HR: 0.37; 95% CI: 0.14–0.99) in terms of PFS, while almost reaching statistical significance over OCT and sunitinib. Of note, the evidence supporting pasireotide results was based on a single RCT. This requires a particular note of caution in interpreting this finding, also considering that the efficacy results of combination therapy with pasireotide plus everolimus in NETs are still controversial. Indeed, this combination therapy showed a higher response rate, in terms of tumor stabilization and tumor regression, but this was not associated to a statistically significant benefit in PFS compared to each drug alone (Vitale et al. 2018). In addition, in the studies analyzing this treatment of GEPs (Wolin et al. 2015, Kulke et al. 2017), pasireotide was associated with a low tolerability profile, due to the high risk of diabetes and hyperglycemia. The only prospective study in which pasireotide demonstrated a benefit was the LUNA study, which showed preliminary evidence of the anti-tumour activity and an acceptable safety profile that suggests the feasibility of combining the therapy with everolimus, but this study was a phase II study performed in the lung and thymus NETs (Ferolla et al. 2017).
As a consequence, up to now, pasireotide is not registered for the treatment of GEP NETs but the US FDA and EMA have approved this treatment only for the treatment of adult patients with Cushing's disease for whom pituitary surgery is not an option or has not been curative.
Nevertheless, a potential limitation in the majority of previous studies can be identified, as the heterogeneous cohort of enrolled patients with unknown SSTR profiles, which could be relevant for the responsiveness to pasireotide (Cives et al. 2015). Therefore, the antitumor activity of pasireotide in NETs needs to be further explored in prospective phase II–III studies with symptom control, PFS and additional tumor control metrics as predefined endpoints and after a complete characterization of SSTR subtypes, such as SSTR5.
Future trials should also investigate the potential effects of high-dose treatment with pasireotide in NETs, as suggested by the encouraging results of a phase I study with pasireotide used at 120 mg every 4 weeks (Yao et al. 2017) and also confirm the promising preliminary activity showed in phase II trial of everolimus in combination with pasireotide and SIRT in patients with pancreatic and intestinal NETs with unresectable liver metastasis (Kim et al. 2017).
Moreover, an association between pasireotide and other targeted therapies, such as lenvatinib, cabozantinib or sunitinib, should be explored. This treatment had a different toxicity profile from everolimus and the association could be better tolerated.
According to the abovementioned treatment, we speculate that pasireotide could find a niche of use in clinical practice in selected patients with a specific SSTR profile, or with low risk of development of hyperglycemia and diabetes, such as those with malignant insulinoma, thanks to its marked anti-secretive activity.
Of note, different trials are currently investigating the role of pasireotide, alone or in combination with everolimus, in particular categories of NETs as medullary thyroid cancer (NCT01270321, NCT01625520), Merkel cell carcinoma (NCT01652547), or in rare tumors of neuroendocrine origin, such as pancreatic NETs, pituitary adenoma, Nelson syndrome and ectopic ACTH syndrome (NCT00958841). The aim of these studies is to clarify the efficacy of pasireotide in terms of safety, symptomatic and biochemical control, and effects on tumor mass and survival.
Everolimus has demonstrated important benefits in terms of PFS over placebo in several clinical studies (Yao et al. 2011, 2016) and is currently approved as a monotherapy for the treatment of well-differentiated GEP and lung NETs. On the other hand, OCT is well-known to control symptoms of carcinoid syndrome and has an anti-proliferative effect in well-differentiated GEP NET (Stueven et al. 2019). Interestingly, at our secondary analysis, the combination of everolimus + octreotide ranked second in terms of efficacy in prolonging PFS. This finding supports the use of this combination in clinical practice for the control tumor progression, as previously suggested (Bajetta et al. 2014, 2018), also in non-functioning tumors. On this mechanistic and clinical rationale, and according to the findings of the present network meta-analysis, we believe that the combination of everolimus and OCT may be worth consideration in the treatment of well-differentiated GEP NETs expressing the somatostatin receptor or with aggressive behavior (e.g. grade 2–3 disease). Furthermore, this combination – although its burden on the NHS should be assessed – appears associated with a favorable tolerability profile in phase II and III studies (Pavel et al. 2011, Bajetta et al. 2014, 2018).
In November 2020, the phase III SANET-p study was published. In this trial, surufatinib significantly improved PFS and had an acceptable safety profile in patients with progressive, advanced pancreatic NETs and is suggested as a potential treatment option in this patient population. Nevertheless, this study has not been included in our meta-analysis because it was published after our search in September 2020. In addition, an important statistical point stands against the inclusion of this trial. In network meta-analyses, both indirect and direct effects are available for closed loops only (Rouse et al. 2017). Adding another trial with a drug (surufatinib) not tested in any of the other included studies would open a further 'open loop'. Therefore, while a closed loop has been estimated between all pairs within a network of three or more nodes, an open loop has no direct effects for at least one of the pairs (in this case it would be surufatinib).
Quality of evidence
While the quality of evidence supporting the comparisons of several treatments with placebo was moderate, only low-quality evidence informed the comparison of individual treatments each other mainly due to imprecision (broad confidence intervals) and indirectness (related to different populations and treatment regimens tested across the included RCTs).
There are certain limitations, related to both the network meta-analysis, as well as individual studies, which merit further discussion. The studies had a short duration of follow-up, and the primary outcome of this network meta-analysis was focused only on PFS as a long-term assessment of OS in an indolent disease as NET was lacking. Therefore, limited post-treatment follow-up prevents the ability to understand long-term comparative efficacy between different therapies. There was also a paucity of direct head-to-head comparative trials, thus limiting the evidence supporting single comparisons between individual treatments. Furthermore, different populations recruited in the included RCTs have raised some concerns on the risk of indirectness, which in fact decreased the quality of evidence. Similarly, treatment-related AEs were poorly reported, and a thorough assessment of risk–benefit profile could not be performed. Finally, inherent to network meta-analyses is a risk of misinterpretation due to conceptual heterogeneity, related to differences in participants, interventions, co-interventions/background treatment and outcome assessment, which may limit comparability of trials; these cannot be adequately accounted for study-level synthesis, and individual participant level pooled analyses will be needed once further RCTs are published.
Conclusion
The results of our network meta-analysis, although with all the above-mentioned bias, support the use of combination therapy in the treatment of functioning and non-functioning GEP NETs in clinical practice. We believe that this therapeutic approach is particularly feasible in patients who progressed on somatostatin analog therapy after showing some clinical benefit or in those with high expression levels of somatostatin receptor. The combination of targeted therapy plus SSAs is currently being investigated in several other clinical studies, evaluating different combination schemes (SUNLAND (sunitinib + LAN vs placebo; NCT01731925), LOLA (cabozantinib + LAN; NCT04427787)).
Furthermore, our network meta-analysis suggests that given the potential activity of pasireotide and its antisecretory properties, its role probably should still be explored in selected subgroups of patients. Lastly, the combination of everolimus and OCT appears promising and should be more widely considered in clinical practice.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/ERC-20-0492.
Declaration of interest
SP received honoraria from Novartis, Ipsen, Italfarmaco, Pfizer, Advanced Accelerator Applications (AAA) and Mylan. LG has received honoraria for participating at Advisory Boards of Ipsen. All authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding
This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.
Acknowledgements
Graphical assistance was provided by Massimiliano Pianta (Polistudium SRL), Milan, Italy, on behalf of Eureka Informed SRL. This assistance was supported by Novartis Farma (Origgio, Italy).
References
Albini A, Florio T, Giunciuglio D, Masiello L, Carlone S, Corsaro A, Thellung S, Cai T, Noonan DM & Schettini G 1999 Somatostatin controls Kaposi’s sarcoma tumor growth through inhibition of angiogenesis. FASEB Journal 13 647–655. (https://doi.org/10.1096/fasebj.13.6.647)
Bajetta E, Catena L, Fazio N, Pusceddu S, Biondani P, Blanco G, Ricci S, Aieta M, Pucci F, Valente M, et al.2014 Everolimus in combination with octreotide long-acting repeatable in a first-line setting for patients with neuroendocrine tumors: an ITMO group study. Cancer 120 2457–2463. (https://doi.org/10.1002/cncr.28726)
Bajetta E, Catena L, Pusceddu S, Spada F, Iannacone C, Sarno I, Di Menna G, Dottorini L & Marte AM 2018 Everolimus in combination with octreotide long-acting repeatable in a first-line setting for patients with neuroendocrine tumors: a 5-year update. Neuroendocrinology 106 307–311. (https://doi.org/10.1159/000479587)
Basu B, Sirohi B & Corrie P 2010 Systemic therapy for neuroendocrine tumours of gastroenteropancreatic origin. Endocrine-Related Cancer 17 R75–R 90. (https://doi.org/10.1677/ERC-09-0108)
Bousquet C, Lasfargues C, Chalabi M, Billah SM, Susini C, Vezzosi D, Caron P & Pyronnet S 2012 Clinical review: current scientific rationale for the use of somatostatin analogs and mTOR inhibitors in neuroendocrine tumor therapy. Journal of Clinical Endocrinology and Metabolism 97 727–7 37. (https://doi.org/10.1210/jc.2011-2088)
Capdevila J, Sevilla I, Alonso V, Antón Aparicio L, Jiménez Fonseca P, Grande E, Reina JJ, Manzano JL, Alonso Lájara JD, Barriuso J, et al.2015 Evaluation of the efficacy and safety of lanreotide in combination with targeted therapies in patients with neuroendocrine tumours in clinical practice: a retrospective cross-sectional analysis. BMC Cancer 15 495. (https://doi.org/10.1186/s12885-015-1512-6)
Capdevila J, Teulé A, Barriuso J, Castellano D, Lopez C, Manzano JL, Alonso V, García-Carbonero R, Dotor E, Matos I, et al.2019 Phase II study of everolimus and octreotide lar in patients with nonfunctioning gastrointestinal neuroendocrine tumors: the GETNE1003_EVERLAR study. Oncologist 24 38–46. (https://doi.org/10.1634/theoncologist.2017-0622)
Caplin ME, Pavel M, Ćwikła JB, Phan AT, Raderer M, Sedláčková E, Cadiot G, Wolin EM, Capdevila J, Wall L, et al.2014 Lanreotide in metastatic enteropancreatic neuroendocrine tumors. New England Journal of Medicine 371 224–2 33. (https://doi.org/10.1056/NEJMoa1316158)
Cives M, Kunz PL, Morse B, Coppola D, Schell MJ, Campos T, Nguyen PT, Nandoskar P, Khandelwal V & Strosberg JR 2015 Phase II clinical trial of pasireotide long-acting repeatable in patients with metastatic neuroendocrine tumors. Endocrine-Related Cancer 22 1–9. (https://doi.org/10.1530/ERC-14-0360)
Delle Fave G, O'Toole D, Sundin A, Taal B, Ferolla P, Ramage JK, Ferone D, Ito T, Weber W, Zheng-Pei Z, et al.2016 Enets consensus guidelines update for gastroduodenal neuroendocrine neoplasms. Neuroendocrinology 103 119–1 24. (https://doi.org/10.1159/000443168)
Falconi M, Eriksson B, Kaltsas G, Bartsch DK, Capdevila J, Caplin M, Kos-Kudla B, Kwekkeboom D, Rindi G, Klöppel G, et al.2016 Enets Consensus guidelines update for the management of patients with functional pancreatic neuroendocrine tumors and non-functional pancreatic neuroendocrine tumors. Neuroendocrinology 103 153–1 71. (https://doi.org/10.1159/000443171)
Ferolla P, Brizzi MP, Meyer T, Mansoor W, Mazieres J, Do Cao C, Léna H, Berruti A, Damiano V, Buikhuisen W, et al.2017 Efficacy and safety of long-acting pasireotide or everolimus alone or in combination in patients with advanced carcinoids of the lung and thymus (LUNA): an open-label, multicentre, randomised, phase 2 trial. Lancet. Oncology 18 1652–1664. (https://doi.org/10.1016/S1470-2045(1730681-2)
Ishida H & Lam AK-Y 2020 Pancreatic neuroendocrine neoplasms: the latest surgical and medical treatment strategies based on the current World Health Organization classification. Critical Reviews in Oncology/Hematology 145 102835. (https://doi.org/10.1016/j.critrevonc.2019.102835)
Kiesewetter B & Raderer M 2020 How I treat neuroendocrine tumours. ESMO Open 5 E000811. (https://doi.org/10.1136/esmoopen-2020-000811)
Kim HS, Shaib WL, Zhang C, Nagaraju GP, Wu C, Alese OB, Chen Z, Brutcher E, Renfroe M & El-Rayes BF 2018 Phase 1b study of pasireotide, everolimus, and selective internal radioembolization therapy for unresectable neuroendocrine tumors with hepatic metastases. Cancer 124 1992–2000. (https://doi.org/10.1002/cncr.31192)
Krug S, Mordhorst JP, Moser F, Theuerkorn K, Ruffert C, Egidi M, Rinke A, Gress TM & Michl P 2019 Interaction between somatostatin analogues and targeted therapies in neuroendocrine tumor cells. PLoS ONE 14 e0218953. (https://doi.org/10.1371/journal.pone.0218953)
Kulke MH, Ruszniewski P, Van Cutsem E, Lombard-Bohas C, Valle JW, De Herder WW, Pavel M, Degtyarev E, Brase JC, Bubuteishvili-Pacaud L, et al.2017 A randomized, open-label, phase 2 study of everolimus in combination with pasireotide LAR or everolimus alone in advanced, well-differentiated, progressive pancreatic neuroendocrine tumors: COOPERATE-2 trial. Annals of Oncology 28 1309–1315. (https://doi.org/10.1093/annonc/mdx078)
Lesche S, Lehmann D, Nagel F, Schmid HA & Schulz S 2009 Differential effects of octreotide and pasireotide on somatostatin receptor internalization and trafficking in vitro. Journal of Clinical Endocrinology and Metabolism 94 654–661. (https://doi.org/10.1210/jc.2008-1919)
Milione M, Maisonneuve P, Pellegrinelli A, Grillo F, Albarello L, Spaggiari P, Vanoli A, Tagliabue G, Pisa E, Messerini L, et al.2018 Ki67 proliferative index of the neuroendocrine component drives MANEC prognosis. Endocrine-Related Cancer 25 583–593. (https://doi.org/10.1530/ERC-17-0557)
Mohamed A, Romano D, Saveanu A, Roche C, Albertelli M, Barbieri F, Brue T, Niccoli P, Delpero JR, Garcia S, et al.2017 Anti-proliferative and anti-secretory effects of everolimus on human pancreatic neuroendocrine tumors primary cultures: is there any benefit from combination with somatostatin analogs? Oncotarget 8 41044–41063. (https://doi.org/10.18632/oncotarget.17008)
Moher D, Liberati A, Tetzlaff J, Altman DG & PRISMA Group 2009 Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine 151 264–26 9. (https://doi.org/10.7326/0003-4819-151-4-200908180-00135)
Nagtegaal ID, Odze RD, Klimstra D, Paradis V, Rugge M, Schirmacher P, Washington KM, Carneiro F, Cree IA & WHO Classification of Tumours Editorial Board 2020 The 2019 WHO classification of tumours of the digestive system. Histopathology 76 182–188. (https://doi.org/10.1111/his.13975)
Oberg KE 2012 The management of neuroendocrine tumours: current and future medical therapy options. Clinical Oncology 24 282–293. (https://doi.org/10.1016/j.clon.2011.08.006).
Oronsky B, Ma PC, Morgensztern D & Carter CA 2017 Nothing but NET: a review of neuroendocrine tumors and carcinomas. Neoplasia 19 991–1002. (https://doi.org/10.1016/j.neo.2017.09.002)
Palmieri LJ, Dermine S, Barré A, Dhooge M, Brezault C, Cottereau AS & Coriat R 2020 Medical treatment of advanced pancreatic neuroendocrine neoplasms. Journal of Clinical Medicine 9 1860. (https://doi.org/10.3390/jcm9061860)
Pavel ME, Hainsworth JD, Baudin E, Peeters M, Hörsch D, Winkler RE, Klimovsky J, Lebwohl D, Jehl V, Wolin EM, et al.2011 Everolimus plus octreotide long-acting repeatable for the treatment of advanced neuroendocrine tumours associated with carcinoid syndrome (RADIANT-2): a randomised, placebo-controlled, phase 3 study. Lancet 378 2005–2012. (https://doi.org/10.1016/S0140-6736(1161742-X)
Pavel M, Öberg K, Falconi M, Krenning EP, Sundin A, Perren A, Berruti A & ESMO Guidelines Committee 2020 Gastroenteropancreatic neuroendocrine neoplasms: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of Oncology 31 844–860. (https://doi.org/10.1016/j.annonc.2020.03.304)
Prinzi N, Raimondi A, Maccauro M, Milione M, Garanzini E, Torchio M, Corti F, Nichetti F, Russo GL, Giacomelli L, et al.2019 Somatostatin analogs in association with peptide receptor radionucleotide therapy in advanced well-differentiated NETs. Future Oncology 15 3015–3024. (https://doi.org/10.2217/fon-2019-0138)
Puhan MA, Schünemann HJ, Murad MH, Li T, Brignardello-Petersen R, Singh JA, Kessels AG, Guyatt GH & GRADE Working Group 2014 A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ 349 g5630. (https://doi.org/10.1136/bmj.g5630)
Pusceddu S, De Braud F, Lo Russo G, Concas L, Femia D, Vernieri C, Indini A, Formisano B & Buzzoni R 2016 How do the results of the RADIANT trials impact on the management of NET patients? A systematic review of published studies. Oncotarget 7 44841–44847. (https://doi.org/10.18632/oncotarget.8601)
Pusceddu S, Verzoni E, Prinzi N, Mennitto A, Femia D, Grassi P, Concas L, Vernieri C, Lo Russo G & Procopio G 2017 Everolimus treatment for neuroendocrine tumors: latest results and clinical potential. Therapeutic Advances in Medical Oncology 9 183–188. (https://doi.org/10.1177/1758834016683905)
Pusceddu S, Barretta F, Trama A, Botta L, Milione M, Buzzoni R, De Braud F, Mazzaferro V, Pastorino U, Seregni E, et al.2018 A classification prognostic score to predict OS in stage IV well-differentiated neuroendocrine tumors. Endocrine-Related Cancer 25 607–618. (https://doi.org/10.1530/ERC-17-0489)
Raymond E, Dahan L, Raoul JL, Bang YJ, Borbath I, Lombard-Bohas C, Valle J, Metrakos P, Smith D, Vinik A, et al.2011 Sunitinib malate for the treatment of pancreatic neuroendocrine tumors. New England Journal of Medicine 364 501–5 13. (https://doi.org/10.1056/NEJMoa1003825)
Rinke A, Müller HH, Schade-Brittinger C, Klose KJ, Barth P, Wied M, Mayer C, Aminossadati B, Pape UF, Bläker M, et al.2009 Placebo-controlled, double-blind, prospective, randomized study on the effect of octreotide LAR in the control of tumor growth in patients with metastatic neuroendocrine midgut tumors: a report from the PROMID Study Group. Journal of Clinical Oncology 27 4656–46 63. (https://doi.org/10.1200/JCO.2009.22.8510)
Rouse B, Chaimani A & Li T 2017 Network meta-analysis: an introduction for clinicians. Internal and Emergency Medicine 12 103–111. (https://doi.org/10.1007/s11739-016-1583-7)
She QB, Halilovic E, Ye Q, Zhen W, Shirasawa S, Sasazuki T, Solit DB & Rosen N 2010 2010.4E-BP1 is a key effector of the oncogenic activation of the AKT and ERK signaling pathways that integrates their function in tumors. Cancer Cell 18 39–51. (https://doi.org/10.1016/j.ccr.2010.05.023)
Stueven AK, Kayser A, Wetz C, Amthauer H, Wree A, Tacke F, Wiedenmann B, Roderburg C & Jann H 2019 Somatostatin analogues in the treatment of neuroendocrine tumors: past, present and future. International Journal of Molecular Sciences 20 3049. (https://doi.org/10.3390/ijms20123049)
Taal BG & Visser O 2004 Epidemiology of neuroendocrine tumours. Neuroendocrinology 80(Supplement 1) 3–7. (https://doi.org/10.1159/000080731)
Tsoli M, Chatzellis E, Koumarianou A, Kolomodi D & Kaltsas G 2018 Current best practice in the management of neuroendocrine tumors. Therapeutic Advances in Endocrinology and Metabolism 10 2042018818804698. (https://doi.org/10.1177/2042018818804698)
Vitale G, Dicitore A, Sciammarella C, Di Molfetta S, Rubino M, Faggiano A & Colao A 2018 Pasireotide in the treatment of neuroendocrine tumors: a review of the literature. Endocrine-Related Cancer 25 R351–R364. (https://doi.org/10.1530/ERC-18-0010)
White IR, Barrett JK, Jackson D & Higgins JP 2012 Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression. Research Synthesis Methods 3 111–1 25. (https://doi.org/10.1002/jrsm.1045)
Wolin EM, Jarzab B, Eriksson B, Walter T, Toumpanakis C, Morse MA, Tomassetti P, Weber MM, Fogelman DR, Ramage J, et al.2015 Phase III study of pasireotide long-acting release in patients with metastatic neuroendocrine tumors and carcinoid symptoms refractory to available somatostatin analogues. Drug Design, Development and Therapy 9 5075–50 86. (https://doi.org/10.2147/DDDT.S84177)
Yao JC, Hassan M, Phan A, Dagohoy C, Leary C, Mares JE, Abdalla EK, Fleming JB, Vauthey JN, Rashid A, et al.2008 One hundred years after “carcinoid”: epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. Journal of Clinical Oncology 26 3063–3072. (https://doi.org/10.1200/JCO.2007.15.4377)
Yao JC, Shah MH, Ito T, Bohas CL, Wolin EM, Van Cutsem E, Hobday TJ, Okusaka T, Capdevila J, de Vries EG, et al.2011 Everolimus for advanced pancreatic neuroendocrine tumors. New England Journal of Medicine 364 514–523. (https://doi.org/10.1056/NEJMoa1009290)
Yao JC, Fazio N, Singh S, Buzzoni R, Carnaghi C, Wolin E, Tomasek J, Raderer M, Lahner H, Voi M, et al.2016 Everolimus for the treatment of advanced, non-functional neuroendocrine tumours of the lung or gastrointestinal tract (RADIANT-4): a randomised, placebo-controlled, phase 3 study. Lancet 387 968–977. (https://doi.org/10.1016/S0140-6736(1500817-X)
Yao JC, Chan JA, Mita AC, Kundu MG, Hermosillo Reséndiz K, Hu K, Ravichandran S, Strosberg JR & Wolin EM 2017 Phase I dose escalation study of long-acting pasireotide in patients with neuroendocrine tumors. OncoTargets and Therapy 10 3177–3186. (https://doi.org/10.2147/OTT.S128547)
