Assessment of the American Joint Commission on Cancer 8th Edition Staging System for Patients with Pancreatic Neuroendocrine Tumors: A Surveillance, Epidemiology, and End Results analysis

Surgical Management and Long-Term Evaluation of Pancreatic Neuroendocrine Tumors

Pancreatic neuroendocrine tumors (PNETs) arise from neuroendocrine cells and are a rare class of heterogenous tumors with increasing incidence. The diagnosis, staging, treatment, and prognosis of PNETs depend heavily on identifying the histologic features and biological mechanisms. Here, the authors provide an overview of the diagnostic workup (biomarkers and imaging), grade, and staging of PNETs. The authors also explore associated genetic mutations and molecular pathways and describe updated guidelines on surgical and systemic treatment modalities.

Prognostic value of CT-based radiomics in grade 1-2 pancreatic neuroendocrine tumors

BACKGROUND

Surgically resected grade 1-2 (G1-2) pancreatic neuroendocrine tumors (PanNETs) exhibit diverse clinical outcomes, highlighting the need for reliable prognostic biomarkers. Our study aimed to develop and validate CT-based radiomics model for predicting postsurgical outcome in patients with G1-2 PanNETs, and to compare its performance with the current clinical staging system.

METHODS

This multicenter retrospective study included patients who underwent dynamic CT and subsequent curative resection for G1-2 PanNETs. A radiomics-based model (R-score) for predicting recurrence-free survival (RFS) was developed from a development set (441 patients from one institution) using least absolute shrinkage and selection operator-Cox regression analysis. A clinical model (C-model) consisting of age and tumor stage according to the 8th American Joint Committee on Cancer staging system was built, and an integrative model combining the C-model and the R-score (CR-model) was developed using multivariable Cox regression analysis. Using an external test set (159 patients from another institution), the models' performance for predicting RFS and overall survival (OS) was evaluated using Harrell's C-index. The incremental value of adding the R-score to the C-model was evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS

The median follow-up periods were 68.3 and 59.7 months in the development and test sets, respectively. In the development set, 58 patients (13.2%) experienced recurrence and 35 (7.9%) died. In the test set, tumors recurred in 14 patients (8.8%) and 12 (7.5%) died. In the test set, the R-score had a C-index of 0.716 for RFS and 0.674 for OS. Compared with the C-model, the CR-model showed higher C-index (RFS, 0.734 vs. 0.662, p = 0.012; OS, 0.781 vs. 0.675, p = 0.043). CR-model also showed improved classification (NRI, 0.330, p < 0.001) and discrimination (IDI, 0.071, p < 0.001) for prediction of 3-year RFS.

CONCLUSIONS

Our CR-model outperformed the current clinical staging system in prediction of the prognosis for G1-2 PanNETs and added incremental value for predicting postoperative recurrence. The CR-model enables precise identification of high-risk patients, guiding personalized treatment planning to improve outcomes in surgically resected grade 1-2 PanNETs.

Risk Stratification of Pancreatic Neuroendocrine Neoplasms Based on Clinical, Pathological, and Molecular Characteristics

Pancreatic neuroendocrine neoplasms consist of heterogeneous diseases. Depending on the novel features detected by various modern technologies, their classification and related prognosis predictions continue to change and develop. The role of traditional clinicopathological prognostic factors, including classification systems, is also being refined, and several attempts have been made to predict a more accurate prognosis through novel serum biomarkers, genetic factors, and epigenetic factors that have been identified through various state-of-the-art molecular techniques with multiomics sequencing. In this review article, the latest research results including the traditional approach to prognostic factors and recent advanced strategies for risk stratification of pancreatic neuroendocrine neoplasms based on clinical, pathological, and molecular characteristics are summarized. Predicting prognosis through multi-factorial assessments seems to be more efficacious, and prognostic factors through noninvasive methods are expected to develop further advances in liquid biopsy in the future.

Pancreatic neuroendocrine neoplasms: a 2022 update for radiologists

Pancreatic neuroendocrine neoplasms (PaNENs) are a unique group of pancreatic neoplasms with a wide range of clinical presentations and behaviors. Given their heterogeneous appearance and increasing detection on cross-sectional imaging, it is essential that radiologists understand the variable presentation and distinctions PaNENs display compared to other pancreatic neoplasms. Additionally, some of these neoplasms may be hormonally functional, and it is imperative that radiologists be aware of the common clinical presentations of hormonally active PaNENs. Knowledge of PaNEN pathology and treatments may influence which imaging modality is optimal for each patient. Each imaging modality used for PaNENs has distinct advantages and disadvantages, particularly in different treatment settings. Thus, the focus of this manuscript is to provide an update for the radiologist on PaNEN pathology, imaging, and treatments.

Surgical Outcomes, Long-Term Survivals and Staging Systems of World Health Organization G3 Pancreatic Neuroendocrine Tumors

Background: In 2017, the World Health Organization (WHO) defined a new category of pancreatic neuroendocrine neoplasms named G3 pancreatic neuroendocrine tumors (p-NETs), whose surgical outcomes, long-term survivals and staging systems have not been well documented. Methods: Data from eligible patients with G3 p-NETs defined using the WHO 2017 grading classification at our institute were retrospectively analyzed. Results: Our study enrolled 80 patients with WHO G3 p-NETs, including 50 women and 30 men. The accumulative 5-year overall survival (OS) of G3 p-NETs was 29.7%. The current staging system by the American Joint Committee on Cancer (AJCC) failed to discriminate the survival difference between Stage II and Stage III (p = 0.172), while notable differences with regard to the OS were statistically offered between each stage using the modified tumor−node−metastasis (mTNM) staging system (all p < 0.05). The OS of patients receiving surgical resection was significantly better than those with palliative operation (p < 0.05). Both the current AJCC system and proposed mTNM system were independent predictors for the OS of G3 p-NETs (p = 0.017 and p = 0.032, respectively). The 95% confidence intervals of the proposed mTNM staging system were smaller than that of the current AJCC system (0.626−8.217 and 0.329−10.013, respectively), indicating a relatively more accurate predictive ability. Conclusion: Our demonstration revealed that surgical resection was an independent predictor for the favorable prognosis of patients with G3 p-NETs. Moreover, the new mTNM staging system was more suitable and practical than the current AJCC system for stratifying G3 p-NETs into prognostic groups.

Development and Validation of a Modified Eighth AJCC Staging System for Primary Pancreatic Neuroendocrine Tumors

OBJECTIVE

To improve the prognostic accuracy of the eighth edition of AJCC staging system for pNETs with establishment and validation of a new staging system.

BACKGROUND

Validation of the updated eighth AJCC staging system for pNETs has been limited and controversial.

METHODS

Data from the SEER registry (1975-2016) (n = 3303) and a multi-institutional database (2000-2016) (n = 825) was used as development and validation cohorts, respectively. A mTNM was proposed by maintaining the eighth AJCC T and M definitions, and the recently proposed N status as N0 (no LNM), N1 (1-3 LNM), and N2 (≥4 LNM), but adopting a new stage classification.

RESULTS

The eighth TNM staging system failed to stratify patients with stage I versus IIA, stage IIB versus IIIA, and overall stage I versus II relative to long-term OS in both database. There was a monotonic decrement in survival based on the proposed mTNM staging classification among patients derived from both the SEER (5-year OS, stage I 87.0% vs stage II 80.3% vs stage III 72.9% vs stage IV 57.2%, all P < 0.001), and multi-institutional (5-year OS, stage I 97.6% vs stage II 82.7% vs stage III 78.4% vs stage IV 50.0%, all P < 0.05) datasets. On multivariable analysis, mTNM staging remained strongly associated with prognosis, as the hazard of death incrementally increased with each stage among patients in the 2 cohorts.

CONCLUSION

A mTNM pNETs clinical staging system using N0, N1, N2 nodal categories was better at stratifying patients relative to long-term OS than the eighth AJCC staging.

Prognostic validity of the American joint committee on cancer eighth edition staging system for well-differentiated pancreatic neuroendocrine tumors

BACKGROUND

The American Joint Committee on Cancer (AJCC) made improvements for staging pancreatic neuroendocrine tumors (pNETs) in its 8th Edition; however, multicenter studies were not included.

METHODS

We collected multicenter datasets (n = 1,086, between 2004 and 2018) to validate the value of AJCC 8 and other coexisting staging systems through univariate and multivariate analysis for well-differentiated (G1/G2) pNETs.

RESULTS

Compared to other coexisting staging systems, AJCC 7 only included 12 (1.1%) patients with stage III tumors. Patients with European Neuroendocrine Tumor Society (ENETS) stage IIB disease had a higher risk of death than patients with stage IIIA (hazard ratio [HR]: 4.376 vs. 4.322). For the modified ENETS staging system, patients with stage IIB disease had a higher risk of death than patients with stage III (HR: 6.078 vs. 5.341). According to AJCC 8, the proportions of patients with stage I, II, III, and IV were 25.7%, 40.3%, 23.6%, and 10.4%, respectively. As the stage advanced, the median survival time decreased (NA, 144.7, 100.8, 72.0 months, respectively), and the risk of death increased (HR: II = 3.145, III = 5.925, and IV = 8.762).

CONCLUSION

These findings suggest that AJCC 8 had a more reasonable proportional distribution and the risk of death was better correlated with disease stage.

What Are the Place and Modalities of Surgical Management for Pancreatic Neuroendocrine Neoplasms? A Narrative Review

Pancreatic neuroendocrine neoplasms (panNENs) are a heterogeneous group of tumors derived from cells with neuroendocrine differentiation. They are considered malignant by default. However, their outcomes are variable depending on their presentation in the onset of hereditary syndromes, hormonal secretion, grading, and extension. Therefore, although surgical treatment has long been suggested as the only treatment of pancreatic neuroendocrine neoplasms, its modalities are an evolving landscape. For selected patients (small, localized, non-functional panNENs), a "wait and see" strategy is suggested, as it is in the setting of multiple neuroendocrine neoplasia type 1, but the accurate size cut-off remains to be established. Parenchyma-sparring pancreatectomy, aiming to limit pancreatic insufficiency, are also emerging procedures, which place beyond the treatment of insulinomas and small non-functional panNENs (in association with lymph node picking) remains to be clarified. Furthermore, giving the fact that the liver is generally the only metastatic site, surgery keeps a place of choice alongside medical therapies in the treatment of metastatic disease, but its modalities and extensions are still a matter of debate. This narrative review aims to describe the current recommended surgical management for pancreatic NENs and controversies in light of the actual recommendations and recent literature.

Patterns and predictors of pancreatic neuroendocrine tumor prognosis: Are no two leaves alike?

Pancreatic neuroendocrine tumors (PanNETs) are heterogeneous; thus, individual prognostic prediction is important. Clinicopathological features, like TNM stage, grade, and differentiation, are independent clinical predictors. However, single predictors are insufficient, as patients sharing similar clinicopathological features usually show distinct prognoses. Accordingly, novel nomograms and risk stratifications have been developed for more accurate PanNET prognostic prediction. Moreover, the exploration of molecular mechanisms has identified novel prognostic predictors for PanNET. Multi-analyte assays of molecular biomarkers provide a deeper understanding of PanNET features; however, the priority, and the optimal combination of classic and novel predictors for PanNET prognosis prediction remain unclear. In this review, we summarized the patterns and predictors of PanNET prognosis and discussed their clinical utility; we emphasized that PanNET at different stages have different superior predictor, and that multi-analyte assays are more sensitive than mono-analyte biomarkers. Therefore, combined biomarkers improve the accuracy of surveillance and optimize decision-making in clinical practice.

Imaging of Pancreatic Neuroendocrine Neoplasms

Pancreatic neuroendocrine neoplasms (panNENs) represent the second most common pancreatic tumors. They are a heterogeneous group of neoplasms with varying clinical expression and biological behavior, from indolent to aggressive ones. PanNENs can be functioning or non-functioning in accordance with their ability or not to produce metabolically active hormones. They are histopathologically classified according to the 2017 World Health Organization (WHO) classification system. Although the final diagnosis of neuroendocrine tumor relies on histologic examination of biopsy or surgical specimens, both morphologic and functional imaging are crucial for patient care. Morphologic imaging with ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) is used for initial evaluation and staging of disease, as well as surveillance and therapy monitoring. Functional imaging techniques with somatostatin receptor scintigraphy (SRS) and positron emission tomography (PET) are used for functional and metabolic assessment that is helpful for therapy management and post-therapeutic re-staging. This article reviews the morphological and functional imaging modalities now available and the imaging features of panNENs. Finally, future imaging challenges, such as radiomics analysis, are illustrated.

Neuroendocrine and Adrenal Tumors, Version 2.2021, NCCN Clinical Practice Guidelines in Oncology

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Neuroendocrine and Adrenal Gland Tumors focus on the diagnosis, treatment, and management of patients with neuroendocrine tumors (NETs), adrenal tumors, pheochromocytomas, paragangliomas, and multiple endocrine neoplasia. NETs are generally subclassified by site of origin, stage, and histologic characteristics. Appropriate diagnosis and treatment of NETs often involves collaboration between specialists in multiple disciplines, using specific biochemical, radiologic, and surgical methods. Specialists include pathologists, endocrinologists, radiologists (including nuclear medicine specialists), and medical, radiation, and surgical oncologists. These guidelines discuss the diagnosis and management of both sporadic and hereditary neuroendocrine and adrenal tumors and are intended to assist with clinical decision-making. This article is focused on the 2021 NCCN Guidelines principles of genetic risk assessment and counseling and recommendations for well-differentiated grade 3 NETs, poorly differentiated neuroendocrine carcinomas, adrenal tumors, pheochromocytomas, and paragangliomas.

Symptomatic spinal metastases from neuroendocrine neoplasms: surgical outcomes and prognostic analysis

OBJECTIVES

In this article, we investigated the efficiency of surgery in treating symptomatic spinal metastases from neuroendocrine neoplasms and performed univariate analysis for identification of possible prognostic factors.

METHODS

A retrospective study was performed, enrolling a total of 19 patients who received surgeries in our center for symptomatic spinal metastases from neuroendocrine neoplasms (NEN). The Kaplan-Meier method was adopted to estimate overall survival (OS) and recurrence free survival (RFS). Univariate analysis was performed for identification of possible prognostic factors.

RESULTS

All patients recruited displayed stable recovery after surgical intervention, with a median OS of 27.3 months (95% Confidence Interval: 16.4-38.1 months) and a median RFS of 23.0 months (95% Confidence Interval: 12.1-33.8 months). Postoperatively, 15 patients exhibited improved neurological function based on the Frankel classification, while 16 patients experienced significant pain relief, with mean visual analog scale (VAS) score decreasing from 7.47 ± 2.32-2.47 ± 1.25 (p < 0.05). Univariate analysis revealed that the presence of visceral metastases (p = 0.034) and extraspinal bone metastases (p = 0.016) are both related with poor prognosis. Additionally, well histologic differentiation (p = 0.010) and administration of postoperative octreotide (p = 0.041) or bisphosphonate (p = 0.023) are all indicators for better outcome.

CONCLUSIONS

Surgery is an efficient option for treating symptomatic spinal metastases from NEN due to its immediate and assured benefits in pain alleviation, restoration of function and stability reconstruction.

A Machine Learning Decision Support System (DSS) for Neuroendocrine Tumor Patients Treated with Somatostatin Analog (SSA) Therapy

The application of machine learning (ML) techniques could facilitate the identification of predictive biomarkers of somatostatin analog (SSA) efficacy in patients with neuroendocrine tumors (NETs). We collected data from 74 patients with a pancreatic or gastrointestinal NET who received SSA as first-line therapy. We developed three classification models to predict whether the patient would experience a progressive disease (PD) after 12 or 18 months based on clinic-pathological factors at the baseline. The dataset included 70 samples and 15 features. We initially developed three classification models with accuracy ranging from 55% to 70%. We then compared ten different ML algorithms. In all but one case, the performance of the Multinomial Naïve Bayes algorithm (80%) was the highest. The support vector machine classifier (SVC) had a higher performance for the recall metric of the progression-free outcome (97% vs. 94%). Overall, for the first time, we documented that the factors that mainly influenced progression-free survival (PFS) included age, the number of metastatic sites and the primary site. In addition, the following factors were also isolated as important: adverse events G3–G4, sex, Ki67, metastatic site (liver), functioning NET, the primary site and the stage. In patients with advanced NETs, ML provides a predictive model that could potentially be used to differentiate prognostic groups and to identify patients for whom SSA therapy as a single agent may not be sufficient to achieve a long-lasting PFS.

Association between MGMT status and response to alkylating agents in patients with neuroendocrine neoplasms: a systematic review and meta-analysis

Background: O⁶-methylguanine-DNA methyltransferase (MGMT) is a specific DNA damage reversal repair protein. The influence of MGMT status on alkylating agent sensitivity in patients with neuroendocrine neoplasms (NENs) is controversial. We conducted a meta-analysis to assess the influence of MGMT status on the therapeutic sensitivity of alkylating agents in patients with NENs.

Methods: We searched PubMed, EmBase, and Cochrane library public databases through 3 July 2019. The objective response rate (ORR) was the outcome data of interest. Subgroup analysis was performed according based on MGMT methylation and expression of MGMT protein.

Results: Eleven studies were included in the meta-analysis. The proportion of patients with NENs that achieved an ORR after alkylating agent treatment was higher in the MGMT-deficient group than the non-deficient group (OR: 5.00; 95% CI: 3.04–8.22; P < 0.001; I²: 3%). Similar results were noted in the MGMT methylation and MGMT protein expression subgroups.

Conclusion: Patients with NENs and MGMT methylation or low protein expression had a higher ORR proportion than patients without MGMT methylation or high protein expression. The MGMT status can be used as a biological indicator of the response to alkylating agent treatment in patients with NENs.

Prognostic Nomograms to Predict Overall Survival and Cancer-Specific Survival of Patients With Pancreatic Neuroendocrine Tumors: A Population-Based Study

OBJECTIVE

The objective of this research was to construct and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) in patients with pancreatic neuroendocrine tumors (pNETs).

METHODS

We extracted 3787 patients with pNETs from the Surveillance, Epidemiology and End Results database. Nomograms for estimating 3- and 5-year OS and CSS were first established. Then, we used Harrell's Concordance Index, calibration plots, and the area under receiver operating characteristic curve to evaluate the nomograms. The Kaplan-Meier curve was plotted to evaluate the different survival outcomes.

RESULTS

In the multivariate analysis, age, grade, functional status, American Joint Committee on Cancer stage, and surgery were associated with OS and CSS. The established nomograms had good discriminative ability, with a Harrell's Concordance Index of 0.830 for OS and 0.855 for CSS. The calibration plots also revealed good agreement. The area under receiver operating characteristic curve values of the nomograms predicting 3- and 5-year OS and CSS rates were 0.836, 0.816 and 0.859, 0.841, respectively. In addition, Kaplan-Meier curve indicated that patients with higher risk had worse survival outcomes.

CONCLUSIONS

We have proposed and validated the nomograms predicting OS and CSS of pNETs. They can be convenient individualized tools to facilitate clinical decision making.

c-Myc promotes lymphatic metastasis of pancreatic neuroendocrine tumor through VEGFC upregulation

Pancreatic neuroendocrine tumor (pNET) is a pancreatic neoplasm with neuroendocrine differentiation. pNET in early stage can be treated with surgical resection with long‐term survival, whereas the prognosis of pNET with locoregional or distant metastasis is relatively poor. Lymphangiogenesis is essential for tumor metastasis via the lymphatic system and may overhead distant metastasis. c‐Myc overexpression is involved in tumorigenesis. The role of c‐Myc in lymphangiogenesis is unclear. In this study, we evaluated the mechanism and effect of c‐Myc on lymphangiogenesis of pNET via interaction of lymphatic endothelial cells (LECs) and pNET cells. Lymph node metastasis was evaluated in pNET xenograft mice. Potential target agents to inhibit lymph node metastasis were evaluated in an animal model. We found that vascular endothelial growth factor C (VEGFC) expression and secretion was increased in pNET cell lines with c‐Myc overexpression. c‐Myc transcriptionally upregulates VEGFC expression and the secretion of pNET cells by directly binding to the E‐box of the VEGFC promoter and enhances VEGF receptor 3 phosphorylation and the tube formation of LECs. c‐Myc overexpression is associated with lymph node metastasis in pNET xenograft mice. Combinational treatment with an mTOR inhibitor and c‐Myc inhibitor or VEGFC‐neutralizing chimera protein reduced lymph node metastasis in the mice with c‐Myc overexpression. The mTOR inhibitor acts on lymphangiogenesis by reducing VEGFC expression in pNET cells and inhibiting the tube formation of LECs. In conclusion, mTOR and c‐Myc are important for lymphangiogenesis of pNET and are potential therapeutic targets for prevention and treatment of lymph node metastasis in pNET.

A comprehensive validation of the novel 8th edition of American Joint Committee on Cancer staging manual for the long-term survivals of patients with non-functional pancreatic neuroendocrine neoplasms

Histologically, the World Health Organization has classified pancreatic neuroendocrine neoplasms (p-NENs) into well-differentiated pancreatic neuroendocrine tumors (G1/G2 p-NETs) and poorly-differentiated pancreatic neuroendocrine carcinoma (G3 p-NECs) based on tumor mitotic counts and Ki-67 index. Recently, the 8th edition of American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging manual has incorporated some major changes in 2017 that the TNM staging system for p-NENs should only be applied to well-differentiated G1/G2 p-NETs, while poorly-differentiated G3 p-NECs be classified according to the new system for pancreatic exocrine adenocarcinomas. However, this new manual for p-NENs has seldom been evaluated.Data of patients with both G1/G2 and G3 non-functional p-NENs (NF-p-NENs) from our institution was retrospectively collected and analyzed using 2 new AJCC 8th staging systems. We also made survival comparisons between the 8th and 7th edition system separately for different subgroups.For G1/G2 NF-p-NETs, there were 52 patients classified in AJCC 8th edition stage I, 40 in stage II, 41 in stage III and 19 in stage IV. As for G3 NF-p-NECs, 17, 19, 24, and 18 patients were respectively defined from AJCC 8th edition stage I to stage IV. In terms of the AJCC 7th staging system, the 230 patients with NF-p-NENs were totally distributed from stage I to stage IV (94, 63, 36, 37, respectively). For the survival analysis of both G1/G2 NF-p-NETs and G3 NF-p-NECs, the AJCC 7th edition system failed to discriminate the survival differences when compared stage III with stage II or stage IV (P > .05), while the 8th edition ones could perfectly allocate patients into 4 statistically different groups (P < .05). The HCIs of AJCC 8th stage for G1/G2 NF-p-NETs [HCI=0.658, 95% confidence interval (CI)=0.602-0.741] and stage for G3 NF-p-NECs (HCI=0.704, 95% CI=0.595-0.813) was both statistically larger than those of AJCC 7th stage for different grading NF-p-NENs [(HCI=0.578, 95% CI=0.557-0.649; P=.031), (HCI=0.546, 95% CI=0.531-0.636; P = .019); respectively], indicating a more accurate predictive ability for the survivals of NF-p-NENs.Our data suggested the 2 new AJCC 8th staging systems were superior to its 7th edition for patients with both G1/G2 NF-p-NETs and G3 NF-p-NECs.

The eighth version of American Joint Committee on Cancer nodal classification for high grade pancreatic neuroendocrine tumor should be generalized for the whole population with this disease

Several indexes evaluating the lymph node metastasis of pancreatic neuroendocrine tumor (pNET) have been raised. We aimed to compare the prognostic value of the indexes via the analysis of Surveillance, Epidemiology, and End Results (SEER) database.We identified pNETs patients from SEER database (2004-2015). The prognostic value of N classification which adopted the 8th American Joint Committee on Cancer (AJCC) N classification for well differentiated pNET, revised N classification (rN) which adopted the AJCC 8th N classification for exocrine pancreatic cancer (EPC) and high grade pNET, lymph node ratio and log odds of positive nodes were analyzed.A total of 1791 eligible patients in the SEER cohort were included in this study. The indexes N, rN, lymph node ratio, and log odds of positive nodes were all significant independent prognostic factors for the overall survival. Specifically, the rN had the lowest akaike information criterion of 4050.19, the highest likelihood ratio test (χ) of 48.87, and the highest C-index of 0.6094. The rN was significantly associated with age, tumor location, tumor differentiation, T classification and M classification (P < .05 for all).The 8th version of AJCC N classification for high grade pNET could be generalized for the pNET population.

State of the Art and Recent Developments of Radiopharmaceuticals for Pancreatic Neuroendocrine Tumors Imaging

Background:

Neuroendocrine Tumors (NETs) are relatively rare tumors, mainly originating from the digestive system, that tend to grow slowly and are often diagnosed when metastasised. Surgery is the sole curative option but is feasible only in a minority of patients. Among them, pancreatic neuroendocrine tumors (pancreatic NETs or pNETs) account for less than 5% of all pancreatic tumors. Viable therapeutic options include medical treatments such as biotherapies and more recently Peptide Receptor Radionuclide Therapies (PRRT) with radiolabeled somatostatin analogues. Molecular imaging, with main reference to PET/CT, has a major role in patients with pNETs.

Objective:

The overexpression of specific membrane receptors, as well as the ability of cells to take up amine precursors in NET, have been exploited for the development of specific targeting imaging agents.

Methods:

SPECT/CT and PET/CT with specific isotopes such as [68Ga]-1,4,7,10-tetra-azacyclododecane- N,N’,N’’,N’’’-tetra-acetic acid (DOTA)-somatostatin analogs, [18F]-FDG and [18F]-fluorodopa have been clinically explored.

Results:

To overcome the limitations of SSTR imaging, interesting improvements are connected with the availability of new radiotracers, activating with different mechanisms compared to somatostatin analogues, such as glucagon-like peptide 1 receptor (GLP-1 R) agonists or antagonists.

Conclusion:

This paper shows an overview of the RPs used so far in the imaging of pNETs with insight on potential new radiopharmaceuticals currently under clinical evaluation.

Competing risks and cause-specific mortality in patients with pancreatic neuroendocrine tumors

BACKGROUND AND OBJECTIVE

Currently, there are no competing risk analyses of cause-specific mortality in patients with pancreatic neuroendocrine tumors.

MATERIALS AND METHODS

We estimated a cumulative incidence function for cause-specific mortality. The first nomogram for predicting cause-specific mortality was constructed using a proportional subdistribution hazard model, validated using bootstrap cross-validation, and evaluated with decision curve analysis.

RESULTS

Sex, age, positive lymph node status, metastasis, surveillance, epidemiology, and end results historic stage, grade, and surgery strongly predicted cause-specific mortality. The discrimination performance of Fine-Gray models was evaluated using the c-index, which was 0.864. In addition, the calibration plot of the developed nomogram demonstrated good concordance between the predicted and actual outcomes. Decision curve analysis yielded a range of threshold probabilities (0.014-0.779) at which the clinical net benefit of the risk model was greater than that in hypothetical all-screening or no-screening scenarios.

CONCLUSION

Our nomogram allows selection of a patient population at high risk for cancer-specific mortality and thus facilitates the design of prevention trials for the affected population.

Prognostic Validity of the American Joint Committee on Cancer Eighth Edition TNM Staging System for Surgically Treated and Well-Differentiated Pancreatic Neuroendocrine Tumors: A Comprehensive Analysis of 254 Consecutive Patients From a Large Chinese Institution

OBJECTIVES

We aimed to validate the novel American Joint Committee on Cancer (AJCC) eighth edition staging manual for well-differentiated (G1/G2) pancreatic neuroendocrine tumors (pNETs).

METHODS

Data of eligible patients were retrospectively collected, grouped, and analyzed by applying the new AJCC system.

RESULTS

According to the AJCC eighth staging manual for pNETs, 93, 66, 53, and 42 patients had stage I, II, III, and IV disease, respectively, with estimated 5-year overall survival (OS) rates of 96.9%, 92.8%, 48.4%, and 16.8% (P < 0.005), respectively. A total of 57, 28, 20, and 17 patients with G1 pNETs and 36, 38, 33, and 25 ones with G2 tumors were defined by the new AJCC system as having stage I, II, III, and IV disease, respectively. The estimated 5-year OS for stage I, II, III and IV disease was 100.0%, 97.1%, 52.5%, and 18.2%, respectively, for G1 pNETs (P < 0.005) and 94.2%, 90.3%, 38.7%, and 12.7%, respectively, for G2 tumors (P < 0.005). The novel AJCC classification, tumor grading, and radical resection were all prognostic predictors for OS in patients with pNETs.

CONCLUSIONS

The new AJCC eighth staging system for well-differentiated pNETs was prognostic and might be adopted in clinical practice.

What Is New in the 2017 World Health Organization Classification and 8th American Joint Committee on Cancer Staging System for Pancreatic Neuroendocrine Neoplasms?

The diagnosis and management of pancreatic neuroendocrine neoplasms (NENs) have evolved significantly in recent years. There are several diagnostic and therapeutic challenges and controversies regarding the management of these lesions. In this review, we focus on the recent significant changes and controversial issues regarding the diagnosis and management of NENs and discuss the role of imaging in the multidisciplinary team approach.

Development and Validation of a Nomogram for Predicting Overall Survival in Pancreatic NeuroendocrineTumors

BACKGROUND: The objective of current study was to develop and validate a nomogram to predict overall survival in pancreatic neuroendocrine tumors (PNETs). METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was queried for patients with PNETs between 2004 and 2015. Patients were randomly separated into the training set and the validation set. Cox regression model was used in training set to obtain independent prognostic factors to develop a nomogram for predicting overall survival (OS). The discrimination and calibration plots were used to evaluate the predictive accuracy of the nomogram. RESULTS: A total of 3142 patients with PNETs were collected from the SEER database. Sex, age, marital status, primary site, TNM stage, tumor grade, and therapy were associated with OS in the multivariate models. A nomogram was constructed based on these variables. The nomogram for predicting OS displayed better discrimination power than the Tumor-Node-Metastasis (TNM) stage systems 7th edition in the training set and validation set. The calibration curve indicated that the nomogram was able to accurately predict 3- and 5-year OS. CONCLUSIONS: The nomogram which could predict 3- and 5-year OS were established in this study. Our nomogram showed a good performance, suggesting that it could be served as an effective tool for prognostic evaluation of patients with PNETs.