Prognostic Role of Examined and Positive Lymph Nodes after Distal Pancreatectomy for Non-Functioning Neuroendocrine Neoplasms

The Value of Textbook Outcome in Benchmarking Pancreatoduodenectomy for Nonfunctioning Pancreatic Neuroendocrine Tumors

BACKGROUND

Textbook outcome (TO) is a composite variable that can define the quality of pancreatic surgery. The aim of this study is to evaluate TO after pancreatoduodenectomy (PD) for nonfunctioning pancreatic neuroendocrine tumors (NF-PanNETs).

PATIENTS AND METHODS

All patients who underwent PD for NF-PanNETs (2007-2016) in different centers were included in this retrospective study. TO was defined as the absence of severe postoperative complications and mortality, length of hospital stay ≤ 19 days, R0 resection, and at least 12 lymph nodes harvested.

RESULTS

Overall, 477 patients were included. The TO rate was 32%. Tumor size [odds ratio (OR) 1.696; p = 0.013], a minimally invasive approach (OR 12.896; p = 0.001), and surgical volume (OR 2.062; p = 0.023) were independent predictors of TO. The annual frequency of PDs increased over time as well as the overall rate of TO. At a median follow-up of 44 months, patients who achieved TO had similar disease-free (p = 0.487) and overall survival (p = 0.433) rates compared with patients who did not achieve TO. TO rate in patients with NF-PanNET > 2 cm was 35% versus 27% in patients with NF-PanNET ≤ 2 cm (p = 0.044). Considering only NF-PanNETs > 2 cm, patients with TO and those without TO had comparable 5-year overall survival rates (p = 0.766) CONCLUSIONS: TO is achieved in one-third of patients after PD for NF-PanNETs and is not associated with a benefit in terms of long-term survival.

Accuracy and Prognostic Impact of Nodal Status on Preoperative Imaging for Management of Pancreatic Neuroendocrine Tumors: A Multi-Institutional Study

BACKGROUND

We sought to define the accuracy of preoperative imaging to detect lymph node metastasis (LNM) among patients with pancreatic neuroendocrine tumors (pNETs), as well as characterize the impact of preoperative imaging nodal status on survival.

METHODS

Patients who underwent curative-intent resection for pNETs between 2000 and 2020 were identified from eight centers. Sensitivity and specificity of computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)-CT, and OctreoScan for LNM were evaluated. The impact of preoperative lymph node status on lymphadenectomy (LND), as well as overall and recurrence-free survival was defined.

RESULTS

Among 852 patients, 235 (27.6%) individuals had LNM on final histologic examination (hN1). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 12.4%, 98.1%, 71.8%, and 74.4% for CT, 6.3%, 100%, 100%, and 80.1% for MRI, 9.5%, 100%, 100%, and 58.7% for PET, 11.3%, 97.5%, 66.7%, and 70.8% for OctreoScan, respectively. Among patients with any combination of these imaging modalities, overall sensitivity, specificity, PPV, and NPV was 14.9%, 97.9%, 72.9%, and 75.1%, respectively. Preoperative N1 on imaging (iN1) was associated with a higher number of LND (iN1 13 vs. iN0 9, p = 0.003) and a higher frequency of final hN1 versus preoperative iN0 (iN1 72.9% vs. iN0 24.9%, p < 0.001). Preoperative iN1 was associated with a higher risk of recurrence versus preoperative iN0 (median recurrence-free survival, iN1→hN1 47.5 vs. iN0→hN1 92.7 months, p = 0.05).

CONCLUSIONS

Only 4% of patients with LNM on final pathologic examine had preoperative imaging that was suspicious for LNM. Traditional imaging modalities had low sensitivity to determine nodal status among patients with pNETs.

Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis

INTRODUCTION

Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis.

METHODS

Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs).

RESULTS

Eleven studies were included. Tumor size (>2 cm or >2.5 cm; OR, 5.80 [95% CI, 4.07-8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05-2.94]) were significant preoperative predictors of lymph node metastasis. Old age (OR, 1.07 [95% CI, 0.68-1.68]) and male sex (OR, 1.12 [95% CI, 0.74-1.70]) were not significantly associated with lymph node metastasis.

CONCLUSIONS

A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.

Prognostic Significance and Predictors of Nodal Recurrence After Surgery for Non-Functioning Pancreatic Neuroendocrine Tumors

BACKGROUND

The prognosis of nodal recurrence after surgery for non-functioning pancreatic neuroendocrine tumors (NF-PanNETs) and its predictors have been poorly investigated. This study aimed to compare clinicopathologic features and survival between patients with nodal relapse and those with distant relapse and to identify predictors of nodal relapse after surgery for NF-PanNETs.

METHODS

All patients (n = 321) submitted to surgery for NF-PanNETs were included. Nodal recurrence was defined as the presence of one or more enlarged LNs at high-quality radiologic examinations and always confirmed by ⁶⁸Ga-DOTA-PET or biopsy.

RESULTS

Altogether, 21 patients (6 %) experienced nodal (± distant) relapse, and 35 patients (11 %) had distant recurrence alone. Isolated nodal recurrence occurred for 23 % of patients with recurrence. Overall, 11 patients died of disease, one of whom (pT3N1G3) had an isolated nodal relapse. The rate of LN metastases (81 % vs 54 %; p = 0.044) and median number of positive LNs (PLN) (3 vs 0; p = 0.019) both were significantly higher for the patients with nodal (± distant) relapse than for those with distant relapse alone. Microvascular invasion (p = 0.046), T stage (p = 0.004), N stage (N1 [p = 0.049]; N2 [p = 0.001]), M stage (p < 0.001), and necrosis (p = 0.011) independently predicted nodal relapse. After distal pancreatectomy (n = 182), 13 patients experienced nodal recurrence, 9 of whom had left paraortic LNs involvement.

DISCUSSION

Lymph nodes are not rare sites of recurrence after surgery for NF-PanNETs. Lymph node involvement is a powerful determinant of nodal relapse. Nodal relapse frequently involves LNs that are not removed during standard lymphadenectomy.

Prediction of the characteristics of aggressiveness of pancreatic neuroendocrine neoplasms (PanNENs) based on CT radiomic features

OBJECTIVES

To predict tumor grade (G1 vs. G2/3), presence of distant metastasis (M+), metastatic lymph nodes (N+), and microvascular invasion (VI) of pancreatic neuroendocrine neoplasms (PanNEN) based on preoperative CT radiomic features (RFs), by applying a machine learning approach aimed to limit overfit.

METHODS

This retrospective study included 101 patients who underwent surgery for PanNEN; the entire population was split into training (n = 70) and validation cohort (n = 31). Based on a previously validated methodology, after tumor segmentation on contrast-enhanced CT, RFs were extracted from unenhanced CT images. In addition, conventional radiological and clinical features were combined with RFs into multivariate logistic regression models using minimum redundancy and a bootstrap-based machine learning approach. For each endpoint, models were trained and validated including only RFs (RF_model), and both (radiomic and clinicoradiological) features (COMB_model).

RESULTS

Twenty-five patients had G2/G3 tumor, 37 N+, and 14 M+ and 38 were shown to have VI. From a total of 182 RFs initially extracted, few independent radiomic and clinicoradiological features were identified. For M+ and G, the resulting models showed moderate to high performances: areas under the curve (AUC) for training/validation cohorts were 0.85/0.77 (RF_model) and 0.81/0.81 (COMB_model) for M+ and 0.67/0.72 and 0.68/0.70 for G. Concerning N+ and VI, only the COMB_model could be built, with poorer performance for N+ (AUC = 0.72/0.61) compared to VI (0.82/0.75). For all endpoints, the negative predictive value was good (≥ 0.75).

CONCLUSIONS

Combining few radiomic and clinicoradiological features resulted in presurgical prediction of histological characteristics of PanNENs. Despite the limited risk of overfit, external validations are warranted.

KEY POINTS

• Histology is the only tool currently available allowing characterization of PanNEN biological characteristics important for prognostic assessment; significant limitations to this approach exist. • Based upon preoperative contrast-enhanced CT images, a machine learning approach optimized to favor models' generalizability was successfully applied to train predictive models for tumor grading (G1 vs. G2/3), microvascular invasion, metastatic lymph nodes, and distant metastatic spread. • Moderate to high discriminative models (AUC: 0.67-0.85) based on few parameters (≤ 3) showing high negative predictive value (0.75-0.98) were generated and then successfully validated.

Prognostic Factors of Small Non-Functional Pancreatic Neuroendocrine Tumors and the Risk of Lymph Node Metastasis: A Population-Level Study

BACKGROUND

Small non-functional neuroendocrine tumors (NF-PNETs) are a heterogeneous subset of tumors with controversy regarding their optimal management. We aimed to analyze the prognostic factors of patients with small NF-PNETs and create a risk score for lymph node metastasis (LNM).

METHODS

Data of 751 patients with NF-PNETs ≤ 2 cm were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate survival analysis was performed to analyze the prognostic factors. Logistic regression was used to identify risk factors for LNM.

RESULTS

Of the 751 patients, 99 (13.2%) were confirmed to have LNM. In multivariate survival analysis, LNM (hazard ratio [HR], 2.12; 95% CI, 1.04-4.32, p = 0.040) was independently associated with disease-specific survival. Logistic regression identified that tumor location in the head of the pancreas (odds ratio [OR], 4.33; 95% CI, 2.75-6.81; p < 0.001), size ≥ 1.5-2 cm (OR, 1.84; 95% CI, 1.17-2.87; p = 0.009), and grade III-IV (OR, 7.90; 95% CI, 1.79-34.90; p = 0.006) were independent risk factors of LNM. According to the OR value, the risk of LNM was scored as follows: a score of 1 for tumors located in the body/tail of the pancreas and 4 for those located in the head; a score of 1 for tumors <1 cm and 2 for those ≥1.5-2 cm; and a score of 1 for tumors with grade I-II and 8 for those with grade III-IV. Finally, the median score for this cohort was 4, with an interquartile range of 3-6. Therefore, patients were classified as three groups based on the risk score system: a total score of 1-3 for low risk, 4-6 for intermediate risk (OR, 2.98; 95% CI, 1.59-5.60; p = 0.001), and 7-14 for high risk (OR, 8.94; 95% CI, 4.50-17.7; p < 0.001), with an incidence of LNM 5.0%, 13.5%, and 31.8%, respectively (p < 0.001).

CONCLUSION

Surgical resection with regional lymphadenectomy is recommended for small NF-PNETs with malignant potential of LNM. A risk score for LNM based on tumor grade, location, and size may preoperatively predict LNM of small NF-PNETs and guide clinical practice.

Updated Principles of Surgical Management of Pancreatic Neuroendocrine Tumours (pNETs): What Every Surgeon Needs to Know

Pancreatic neuroendocrine tumours (pNETs) represent 1 to 2% of all pancreatic neoplasm with an increasing incidence. They have a varied clinical, biological and radiological presentation, depending on whether they are sporadic or genetic in origin, whether they are functional or non-functional, and whether there is a single or multiple lesions. These pNETs are often diagnosed at an advanced stage with locoregional lymph nodes invasion or distant metastases. In most cases, the gold standard curative treatment is surgical resection of the pancreatic tumour, but the postoperative complications and functional consequences are not negligible. Thus, these patients should be managed in specialised high-volume centres with multidisciplinary discussion involving surgeons, oncologists, radiologists and pathologists. Innovative managements such as "watch and wait" strategies, parenchymal sparing surgery and minimally invasive approach are emerging. The correct use of all these therapeutic options requires a good selection of patients but also a constant update of knowledge. The aim of this work is to update the surgical management of pNETs and to highlight key elements in view of the recent literature.

Surgical Management of Neuroendocrine Tumours of the Pancreas

Neuroendocrine tumours of the pancreas (pNET) are rare, accounting for 1-2% of all pancreatic neoplasms. They develop from pancreatic islet cells and cover a wide range of heterogeneous neoplasms. While most pNETs are sporadic, some are associated with genetic syndromes. Furthermore, some pNETs are 'functioning' when there is clinical hypersecretion of metabolically active peptides, whereas others are 'non-functioning'. pNET can be diagnosed at a localised stage or a more advanced stage, including regional or distant metastasis (in 50% of cases) mainly located in the liver. While surgical resection is the cornerstone of the curative treatment of those patients, pNET management requires a multidisciplinary discussion between the oncologist, radiologist, pathologist, and surgeon. However, the scarcity of pNET patients constrains centralised management in high-volume centres to provide the best patient-tailored approach. Nonetheless, no treatment should be initiated without precise diagnosis and staging. In this review, the steps from the essential comprehensive preoperative evaluation of the best surgical approach (open versus laparoscopic, standard versus sparing parenchymal pancreatectomy, lymphadenectomy) according to pNET staging are analysed. Strategies to enhance the short- and long-term benefit/risk ratio in these particular patients are discussed.