After selection of original articles from literature we recognized four parameters that more commonly were investigated as potential predictors of response to PRRT: primary, PET-uptake, tumor burden and grade (ki67 index). Some authors evaluated even performance status, that seems to have some degree of influence, however there are few data about this point, hence we decided to focus our attention on the four above stated criteria.
Primary
In 26 papers (2007–2019), 8 prospective, 17 retrospective and one prospective/retrospective – German registry, primary tumor site was evaluated according to PRRT. Table 1 shows all selected original articles. The population comprised over 4050 patients with metastatic and almost all progressive NET, mainly gastroenteropancreatic. 177Lu was employed in 11 studies, 90Y in 2 and both in 13. Number of cycles ranged from 1 to 9 and cumulative dose varied usually between 14.7 and 30 GBq.
Table 1 Studies assessing role of Primary as predictor of different outcomes after PRRT. In light gray “Positive studies”, in gray “Negative Studies”, white for only descriptive studies In 20 studies the role of primary in PRRT was analyzed in detail [1, 4, 5, 12, 15, 21, 24, 27, 32, 35, 42, 46, 59, 60, 68, 70, 72, 78, 79], but primary showed an impact on response to PRRT only in 8 [4, 5, 12, 21, 24, 32, 42, 60]. No association was noted between positive and negative studies and patient populations, sample size, study design or radionuclide employed (177Lu or 90Y).
“Positive studies”
GEP NET showed higher PFS, ORR and DCR than other NET in the study by [4]. PFS in GEP was 30.3 months vs 17.4 months in the total NET population, ORR was 54.2% vs 40.6% and DCR was 100% vs 93.8%. Median OS was 34.7 months in both groups. Importantly, among patients with GEP NET undergoing >1 PRRT cycles, complete responders were 25%, the highest value reported and neither CR, nor PR in other NET were reported.
[12] reported longest median OS in panNET (71 months), and lowest in bronchial (52 months) and NET of unknown origin (53 months). Median PFS was 30 m in panNET, like NET of unknown origin (29 months) and 20 m in bronchial. Best time to progression (TTP) was reported in midgut NET (42 months), and worst in bronchial NET (25 months), while panNET had 31 m and NET of unknown origin 37 months .
Again, [5] in their retrospective analysis found that the site of origin of NENs was a predictor of median overall survival. Best OS was, in fact, observed in patients with NENs of small bowel (69 months, p = 0.01), which was statistically significant if compared with the other groups (pancreas, lung, other primaries, unknown origin). Even PFS was correlated with the site of primary tumor, having patients with small bowel NENs a longer PFS compared to patients with pancreatic NENs (p < 0.001); bronchial origin and unknown origin were associated with a significantly shorter PFS.
The site of primary influences OS, but not PFS in the study by [32], as patients with small bowel NET were significantly less likely to die (p 0.021).
Statistically significant difference in PFS and OS between large and small bowel NET was found by [42] (OS 82.5 vs 58.1 months; PFS 40.3 vs 29.5 months). [60] reported no significant difference in PFS among panNET (27 months), NET of unknown origin (30 months) and small intestinal NET (not reached at the time of analysis).
[21] show that ORR was significantly better (p 0.012) in panNET than in GI NET and in 2014 [24] reported worse outcome for NET of unknown origin than nonpancreatic GEP NET, having shorter PFS (P = 0.001) and OS (P = 0.003). PFS in panNET was 25 months vs nonpancreatic GEP NET (27 months) and OS was 57 vs 43 months.
In 2 studies, NET of unknown origin showed a trend of shorter survival [79] and the lowest PFS [18] without statistical significance.
“Negative studies”
Six studies [15, 17, 27, 35, 68, 79] reported no significant difference in survival according to primary. Comparable ORR between foregut carcinoids of bronchial, gastric or thymic origin (50%) and whole GEP NET (47%) was reported by [78], but time to progression (TTP) was shorter in foregut than in GEP NET.
[70] reported that TTP rates were not significantly different among pulmonary, small bowel NET and panNET (P = 0.093). The single result that achieved statistically significance was a longer OS in small bowel NET compared with other primary. In fact, OS after the first PRRT was 95.4, 37.3, and 20 months for small bowel, pancreatic, and NET of unknown origin, respectively (P = 0.009) [70].
A study by [1] showed conflicting results, founding difference in OS in the univariate analysis (small bowel NET had longer OS than pancreatic, lung and large intestine primaries) but not in the multivariate analysis. Reported median OS for non-functioning panNET was 25.7 months and for other NET was 46.7 months in the study of [72], but data were not statistically significant. A not significant trend towards a better PFS in panNETs was also reported by [59].
Regarding functionality, gastrinoma, insulinoma, VIPoma showed shorter response duration, and higher response rates were reported in gastrinoma, insulinoma, VIPoma, non-functioning NET than in carcinoid (p < 0.01), according to a sub-analysis conducted on a subgroup of patients from the study of Kwekkeboom et al. [46].
In 5 studies, no correlation was reported between primary and any outcome, [8, 25, 30, 67, 75].
Pet
Ga-68 labeled somatostatin analogs and 18F-FDG PET have been evaluated as potential predictors of response to PRRT in twenty-one studies conducted from 2009 to 2019. Table 2 and 3 show all selected original articles where Gallium/FDG PET were evaluated as a predictive factor of response to PRRT. Overall, more than one thousand patients with NET were evaluated. Eight studies are prospective non-randomized clinical trials while thirteen studies are retrospective.
Table 2 Studies assessing role of 68Ga-DOTA-peptides PETas predictor of different outcomes after PRRT. In light gray “Positive studies”, in gray “Negative Studies” Table 3 Studies assessing role of Tumor Burden as predictor of different outcomes after PRRT. In light gray “Positive studies”, in gray “Negative Studies”, white for only descriptive studies Concerning 68Ga-DOTA-peptide PET, all studies assessed tumor standardized uptake value (SUV) as a quantitative parameter, to predict response to PRRT (see Table 2). Among eleven papers that analyze 68Ga- PET, three papers did not find any significant result that attributes a predictive role to maximum SUV (SUVmax) during 68Ga-PET ([26, 27, 73]), two papers from the same group [80, 81] identified other parameters besides SUVmax, able to predict outcome of PRRT treatment, and six identified SUVmax as a predictor of response to therapy [25, 31, 38, 53, 54, 71]. All studies were performed on rather small NET series. Both negative and positive studies comprise retrospective and prospective experience and no particular features characterize a group relative to the other. No association was noted between positive and negative studies and patient populations or radionuclide employed (177Lu or 90Y).
“Positive studies”
In detail, pre therapeutic SUVmax was identified as a predictor of TTP in a population of 33 patients [31]. However, the SUVmax was identified as a predictor of TTP in univariate analysis only (p = 0.04), while, according to the Cox proportional hazards model, authors identified another parameter (the change in SUV of the tumors relative to the maximal splenic uptake – Delta SUV T/S) as the only predictor of TTP in both univariate (p = 0.006) and multivariate analyses (p = 0.03) [31]. Öksüz et al. [54] showed that 68Ga-DOTATOC tumor uptake was strongly associated with the response to PRRT (p < 0.001). Furthermore, the authors identified a SUV cut-off of 17.9 to predict treatment response to PRRT. Similarly, [38], observed significant differences in the mean SUVmax for non-responding vs responding liver metastases in 30 NET patients, proposing a SUVmax cut-off of 16.4 to select patients for PRRT. Sharma et al. also investigated SUVmax and SUVmean of 68Ga-PET/CT as possible predictor of PRRT response. Single lesion SUVmax was, in fact, predictive of both response to PRRT (p = 0.031) and PFS, and SUVmean correlated with PRRT response (P = 0.039) as well. The authors also indicated a cut-off of 13.0, when considering single lesion SUVmax, to give high sensitivity and specificity in prognosticating a favorable treatment response. Tumor to liver SUV ratio (SUVT/H) and tumor to spleen SUV ratio SUVT/S were investigated as well, but neither SUVT/S or SUVT/H were predictive of response to PRRT [71]. A significant correlation between the ORR to PRRT and the 68Ga-DOTANOC PET baseline SUVmax was also found in the prospective trial conducted from [53], but p value was not reported. Similarly, [25] showed that the SUVmax in the main lesion at baseline was predictive of response as indicated by functional evaluation.
“Negative studies”
On the contrary, in a multicenter study [80], both SUVmax and SUVmean of 68Ga-PET/CT failed in response prediction to PRRT. However, the authors identified other textural features representing intratumoral heterogeneity, such Tissue Receptor Expression (TRE), able to predict OS (p = 0.003) and PFS (p = 0.02). Similar results were found by the same group in 2019, in their retrospective study where only panNETs were evaluated: SUVmax/mean failed to predict PFS, whereas the intratumoral textural feature (TF) analysis, assessed by a baseline SSTR-PET, predicted response in terms of PFS [81]. The following studies also did not find any significant relationship between the response to PRRT and SUVmax of reference lesions [26] (p 0.12), [73] (p = 0.25), [27] (p = 0.59).
Regarding 18F-FDG PET, all studies tend to divide patients in PET-positive and PET-negative, depending on a value of SUVmax 2.5 or more, as an arbitrary cut off to consider a lesion positive for malignancy (see Table 3). Among eleven papers that analyze 18F-FDG PET, only one paper clearly defines that SUVmax FDG does not have a predictive role [33], while nine papers show that this criterion could have a predictive role [2, 18, 51, 52, 55, 58, 64, 69, 75]. Finally, one paper reported descriptive data only [53]. As for gallium PET, none of these studies is based on large study populations.
“Positive studies”
A retrospective study [69] showed the capacity of FDG PET to characterize the aggressiveness of NETs, both in terms of PFS (p = 0.033) and DCR (p = 0.02). [64] confirmed these data in a prospective study on pancreatic NETs. Median PFS in the PET-positive group was 21.2 months, while in the PET-negative group, it was 68.7 months (P < 0.0002). Median OS was not reached in the PET-negative group and was 63.8 months in the PET-positive group (p = 0.006). Similarly, PFS was significantly longer in PET-negative patients in the prospective study from [55] (p = 0.02). Accordingly, DCR was better, but no significantly different, in PET-negative cases (P = 0.16). Data from Adnan et al., in their retrospective study which considered only mediastinal NETs, are consistent with what reported thus far, where lower lesional FDG uptake was associated with longer PFS (p = 0.002) and OS (p = 0.043) [2]. FDG PET predicted survival also in patients with high Ki 67 proliferation index (15–35%) in the retrospective study by [52]: the PFS in FDG negative patients was 65.5 months versus 23.0 months in the FDG-positive patients (no p value is reported though).
Finally, [18] did not confirm data about PFS. Median PFS in PET-positive patients was lower but not statistically different from PET-negative patients (P = 0.058). However, a significant correlation between a positive 18F-FDG PET and patient death (P = 0.03) was found. Moreover, other studies reported the possible role of FDG PET in predicting response to PRRT, with only descriptive data. In particular, a high 18F-FDG SUVmax is associated with a poor outcome to PRRT and with disease progression [51, 53, 75]. This finding also emerged from a retrospective study [58] conducted on 22 patients with pulmonary NET.
“Negative studies”
In a prospective trial on progressive bronchial carcinoids [33] median PFS was lower in FDG PET-positive patients (15.3 months) than in PET-negative patients (26.4 months), but no significant differences were found (p = 0.201).
Tumor burden
Tumor burden (TB) has been evaluated as potential predictor of response to PRRT in sixteen studies conducted from 2003 to 2019. Table 4 shows all selected original articles where TB was evaluated as a predictive factor of response to PRRT. Overall, 1496 patients (807 males and 689 females) with NET were evaluated. One study is a prospective non-randomized phase II clinical trial, two papers are phase I dose escalation studies, while thirteen studies are retrospective. 177Lu was employed in nine studies, 90Y in two and both in five. The main parameter assessed as predictor of response to PRRT or associated with survival was the liver TB, however, authors considered even the presence of other metastatic sites, such as bone metastases, or resection of primary tumor. When liver TB was evaluated, different cut-off were applied, more frequently <25 or < 50% of liver involvement. Several studies did not identify a precise cut-off of liver involvement to stratify patients. The patient populations were affected by neuroendocrine neoplasia (NENs) of the GEP tract in the majority of cases. Only four studies were performed on bronchial NENs or on mixed case series of GEP and thoracic NENs. Almost all patients treated with PRRT were affected by a metastatic and mainly progressive NET. Tumor burden was assessed by CT or MRI in all studies except one and response to treatment was evaluated according to the RECIST criteria in most studies. Five out of sixteen studies consider also the SWOG criteria and only one study evaluated tumor response to treatment by the WHO criteria.
Among sixteen papers that analyze liver TB, four papers [35, 59, 62, 63] did not find any significant result that attributes a predictive role to liver TB, one paper [12] describes the presence of liver metastases as a predictor of overall survival, and eleven identified liver TB as a predictor of response to therapy [6, 14, 18, 23, 24, 43, 46, 49, 50, 77, 82]. Both negative and positive studies comprise retrospective and prospective experiences and no particular features characterize a group relative to the other, nor regarding patient populations or radionuclide employed (177Lu or 90Y).
For instance, some article evaluated the impact of liver TB on ORR after PRRT. [43] observed that after PRRT DCR was achieved in 6 (54.5%) out of 11 patients with diffuse liver metastases and in 21 (91.3%) out of 23 patients without diffuse liver metastases (p = 0.01). Similarly, [82] observed that PR and SD at 1 year after PRRT were more frequent in patients with liver TB ≤50% (70.8%) with respect to patients with liver tumor load >50% (38.6%; p < 0.001). Authors concluded that hepatic TB is a strong predictor of response to PRRT, of PFS and OS. However, two other studies [23, 63] failed to demonstrate a higher DCR in patients with a low liver TB. Additional reports evaluated the impact of liver TB on disease free survival (DFS) after PRRT. Most of these studies [18, 24, 43, 46, 62, 63, 82] reported in patients with low liver TB (<25% or < 50%, according to the different criteria considered to define the liver tumor load in each study) a statistically significant longer DFS, which ranged from 21 to 49 months after PRRT, relative to patients with a high liver TB where DFS was shorter (ranging from 8 to 28 months). A similar difference was also noted when comparing patients without and with bone metastases: OS was N.R. vs. 25.0 months (p = 0.03) and PFS was N.R. vs. 12.0 months (p = 0.003). Conversely, these findings were not confirmed by other studies [35, 49, 59] that reported a not significant different DFS when patients were stratified according to the liver TB.
Grade
Grade (G) has been evaluated as potential predictor of response to PRRT in seventeen papers (2 prospective, 14 retrospective, and 1 retrospective/prospective study -German registry) conducted from 2010 to 2019. Another three retrospective studies stratified the population on the percentage of Ki67 antigen expression [1, 15, 52] and one of them distinguished well-differentiate from poorly differentiated [15]. The population comprised 3561 patients with metastatic and almost all progressive NET, mainly gastroenteropancreatic. 177Lu was employed in 11 studies, and both 90Y and/or 177Lu in 9. Number of cycles ranged from 1 to 8 and cumulative dose was usually between 18.5 and 31.6 GBq. Table 4 shows all selected original articles.
Table 4 Studies assessing role of ki67 index as predictor of different outcomes after PRRT. In light gray “Positive studies”, in gray “Negative Studies” In 20 studies the role of grade in PRRT was analyzed in detail ([14, 17, 21,22,23, 32, 49, 59, 60] [24], [1, 5, 9, 15, 19, 35, 52, 61, 62, 82]), and this criterion showed an impact on response to PRRT in 14 ([14, 21, 23, 24], Horsch et al 2016, [1, 5, 9, 15, 19, 35, 52, 59, 61]). No association was noted between positive and negative studies and patient populations, sample size, study design or radionuclide employed (177Lu or 90Y).
“Positive studies”
In particular six papers defined grade as a predictor of PD [5, 14, 21, 35, 52, 59]. Campana et al. showed that higher grade in NETs is a risk factor for tumor progression after PRRT both at univariate and multivariate analysis (G2 vs G1, p 0.003). [21] reported that ki67 index was higher in PD group than in the other response groups (p 0.001). A rate of 71% of G3 NETs was in PD after PRRT vs 11% in G1 + G2 NETs; p0.001). No statistically difference was demonstrated between G1 and G2 tumors [21]. G3 tumors were also found to be associated with shorter PFS, together with gender, in a paper by [59]. [52] considered for their retrospective analysis only patients with high Ki67 proliferation index (>15%) and found that DCR was 87% in patients with a Ki-67 index of ≤35% (9% PR + 78% SD) and 30% in patients with a Ki-67 index of >35%, although no p is reported. Ten studies reported grade as a predictor of OS [1, 5, 15, 19, 23, 24, 32, 35, 52, 61]. A paper by [24] focalized on the predictors of long-term outcome after PRRT. Among different factors assessed at univariate and multivariate analysis, ki67 index proved to be the strongest predictor of OS. Tumors with ki67 > 10% showed earlier progression after PRRT compared to tumors with Ki67 < 10% (median PFS 19 vs 31 months) and this translated in a shorter survival time (median OS 34 vs 55 months, p 0.004). The same group [23] in a cohort of G1 and G2 panNET found that G2 is associated with a shorter PFS, when analyzed with WHO 2010 cut-off of ki67 2%, and even when the analysis was performed applying a cut-off of 5% (median PFS 24 vs 40 months, p 0.03). Moreover, the study demonstrated that tumor grading was an independent predictor of OS (≤2% vs >2%, median OS not reached vs 49 months respectively). In fact, ki67 index (≤2% or > 2%) remained significant (p 0.044) in the multivariate analysis among factors contributing to OS.
Best OS was achieved, in the large cohort of patients studied by [5], in the G1 group (88 months, p = 0.0025), followed by G2. G3 NENs were observed to have the shortest overall survival with 23 months. Compared to G2, OS of G1 patients was significantly longer and significantly shorter in the G3 group (p = 0.0023). PFS was found to be significantly shorter only in patients with G3 tumors (p < 0.001), without any significant difference between G1 and G2 tumors [5].
Similar results were described by [35], in which study the only significant difference was between the G3 group and the other groups, with the first one showing both shorter OS (p = 0.04) and PFS (p = 0.03) [35]. [19] also found positive correlation between histological grade and OS rates (P < 0.05).
A multi-institutional registry study with prospective follow-up [32], in a large cohort of 450 NET patients, reported that grading had no significant impact on PFS, but determined significant differences in OS between G1 and G3 groups (median OS 33 months for G3 tumors, p 0.0098). However, the statistically significance was not maintained between G1 and G2 groups. In a cohort of only G3 neoplasms (Ki67 > 20%), Carlsen and collaborators defined two different populations on the base of Ki67 index (21–55% and > 55%), finding that median PFS and OS were significantly longer for patients with a Ki-67 21–54% (P < 0.001); another parameter evaluated in the study was the grade of differentiation of the primary tumor: well-differentiated tumor had longer OS and PFS than poorly differentiated (P < 0.001) even in an all-G3 neoplasms cohort [15]. Consistent with these results are the findings by [52], also considering only patients with a high Ki67 proliferation index; in this study, a significant difference in PFS (26.3 vs 6.8 months, p = 0.005) and OS (52.9 vs 12.6 months, p = 0.012) was found using a cut off of a Ki67 of 35%. A different stratification was operated by [1], dividing its large cohort of patients in four quartiles considering the Ki67 valor (Q1 < 2%, Q2 2–5%, Q3 5–10%, Q4 > 10%); in their study they found significantly lower OS for Q4 subgroup only when compared with Q1 subgroup (p = 0.01).
Sabet et al. in 2013 performed a retrospective analysis of a cohort of GEP NET with bone metastases (BM). The results of this paper demonstrated that ki67 > 10% was associated with a shorter TTP (p 0.004). Furthermore, ki67 index was an important prognostic factor that had an impact on OS in this cohort of patients, remaining significant on multivariate analysis (ki67 > 10% vs ki67 < 10% median OS 30 vs 55 months, p 0.008) [61].
A study by Cwikla et al. in 2009 reported that the differences in OS and PFS in patients with G1 and G2 tumors were not statistically significant. On the contrary, G1 and G2 tumors were different in terms of ORR evaluated at 12 months by RECIST criteria (p < 0.05) (Cwikla et al 2009).
“Negative studies”
Six studies [17, 22, 49, 60, 62, 82] reported no significant difference neither in ORR nor in survival (PFS or OS) according to G after PRRT. In some of these studies [49, 82] the influence of G on ORR, PFS and OS was significant only at univariate analysis but not maintained at subsequently multivariate analysis.