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Dos Santos Soares F, de Carvalho JR, de Lima BAM, Felix RCM, Bulzico DA, Pujatti PB. Improvement of Laboratory Hepatic Parameters After Treatment With 177 Lu-DOTATATE : Cohort in an Oncology Reference Center. Clin Nucl Med 2024; 49:917-923. [PMID: 39087646 DOI: 10.1097/rlu.0000000000005375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
PURPOSE Well-differentiated neuroendocrine neoplasms (NETs) overexpress the somatostatin receptor, which is the target for the peptide receptor radionuclide therapy (PRRT). NETs have a slow growth rate and can metastasize to liver, bone, and lungs. In NETs patients, liver metastasis is an important prognostic marker because liver failure is one of the most common causes of death in this population. In this regard, we aimed to describe the changes in laboratorial parameters in patients submitted to PRRT with 177 Lu-DOTATATE, focusing on hepatic parameters. PATIENTS AND METHODS One hundred ten patients treated with 1 to 4 cycles of 7.4 GBq (200 mCi) of 177 Lu-DOTATATE from January 2011 to December 2021 were analyzed in this retrospective observational single-center study. Patients were submitted to blood tests before and after each cycle of PRRT. Laboratory measurements were collected to assess liver function, cholestasis, kidney, and bone marrow function. RESULTS In the general population (n = 110), ALP ( P = 0.013) and GGT ( P < 0.001) showed a statistically significant reduction. Patients with high liver disease volume showed a statistically significant reduction in ALT ( P = 0.016), whereas patients with low liver disease volume showed a statistically significant reduction in GGT ( P = 0.013). All parameters for bone marrow function showed a statistically significant decrease in all population subsets. CONCLUSIONS Patients treated with 177 Lu-DOTATATE showed a significant improvement in liver function and cholestasis parameters, and a consistent decrease in bone marrow function, even in the presence of advanced liver disease.
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Gheorghișan-Gălățeanu AA, Ilieșiu A, Lambrescu IM, Țăpoi DA. The Complex Histopathological and Immunohistochemical Spectrum of Neuroendocrine Tumors-An Overview of the Latest Classifications. Int J Mol Sci 2023; 24:1418. [PMID: 36674939 PMCID: PMC9863618 DOI: 10.3390/ijms24021418] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 01/05/2023] [Accepted: 01/08/2023] [Indexed: 01/12/2023] Open
Abstract
Neuroendocrine neoplasms (NENs) originate from the neuroendocrine cell system, which may either take the shape of organoid cell aggregations or be composed of dispersed cells across various organs. Therefore, these tumors are heterogenous regarding the site of origin, functional status, degree of aggressiveness, and prognosis. When treating patients with neuroendocrine tumors, one of the most significant challenges for physicians is determining the correct tumor grade and thus classifying patients into risk categories. Over the years, the classification of these tumors has changed significantly, often causing confusion due to clinical, molecular, and immunohistochemical variability. This review aims to outline the latest NENs classifications regardless of their site of origin. Thus, an overview of the key histopathological and immunohistochemical characteristics of NENs could pave the way to validate possible predictive and prognostic markers and also guide the therapeutic conduct.
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Affiliation(s)
- Ancuța-Augustina Gheorghișan-Gălățeanu
- Department of Cellular and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
- C.I. Parhon National Institute of Endocrinology, 011863 Bucharest, Romania
| | - Andreea Ilieșiu
- Department of Pathology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Department of Pathology, University Emergency Hospital, 050098 Bucharest, Romania
| | - Ioana Maria Lambrescu
- Department of Cellular and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Victor Babes National Institute of Pathology, 050096 Bucharest, Romania
| | - Dana Antonia Țăpoi
- Department of Pathology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Department of Pathology, University Emergency Hospital, 050098 Bucharest, Romania
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Proposal for a New Diagnostic Histopathological Approach in the Evaluation of Ki-67 in GEP-NETs. Diagnostics (Basel) 2022; 12:diagnostics12081960. [PMID: 36010311 PMCID: PMC9407142 DOI: 10.3390/diagnostics12081960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/28/2022] [Accepted: 08/11/2022] [Indexed: 11/17/2022] Open
Abstract
Introduction: Studies have shown that the Ki-67 index is a valuable biomarker for the diagnosis, and classification of gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs). We re-evaluated the expression of Ki-67 based on the intensity of the stain, basing our hypothesis on the fact that the Ki-67 protein is continuously degraded. Background: The aim was to evaluate whether a new scoring method would be more effective in classifying NETs by reducing staining heterogeneity. Methods: Patients with GEP-NET (n = 87) were analyzed. The classification difference between the two methods was determined. Results: The classification changed significantly when the Ki-67 semiquantal index was used. The percentage of G1 patients increased from 18.4% to 60.9%, while the G2 patients decreased from 66.7% to 29.9% and the G3 patients also decreased from 14.9% to 9.2%. Moreover, it was found that the traditional Ki-67 was not significantly related to the overall survival (OS), whereas the semiquantal Ki-67 was significantly related to the OS. Conclusions: The new quantification was a better predictor of OS and of tumor classification. Therefore, it could be used both as a marker of proliferation and as a tool to map tumor dynamics that can influence the diagnosis and guide the choice of therapy.
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Clinical Data-CT Radiomics-Based Model for Predicting Prognosis of Patients with Gastrointestinal Pancreatic Neuroendocrine Neoplasms (GP-NENs). COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:4186305. [PMID: 36035279 PMCID: PMC9410919 DOI: 10.1155/2022/4186305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 07/08/2022] [Accepted: 07/23/2022] [Indexed: 12/01/2022]
Abstract
Purpose Based on computerized tomography (CT) radiomics and clinical data, a model was established to predict the prognosis of patients with gastrointestinal pancreatic neuroendocrine neoplasms (GP-NENs). Methods In the data collection, the clinical imaging and survival follow-up data of 225 GP-NENs patients admitted to Xiangyang No.1 People's Hospital and Jiangsu Province Hospital of Chinese Medicine from August 2015 to February 2021 were collected. According to the follow-up results, they were divided into the nonrecurrent group (n = 108) and the recurrent group (n = 117), based on which a training set and a test set were established at a ratio of 7/3. In the training set, a variety of models were established with significant clinical and imaging data (P < 0.05) to predict the prognosis of GP-NENs patients, and then these models were verified in the test set. Results Our newly developed combined prediction model had high predictive efficacy. Univariate analysis showed that Radscore 1/2/3, age, Ki-67 index, tumor pathological type, tumor primary site, and TNM stage were risk factors for the prognosis of GP-NENs patients (all P < 0.05). The area under the receiver operating characteristic (ROC) curves (AUC) of the combined model was significantly higher [AUC:0.824, 95% CI 0.0342 (0.751-0.883)] than that of the clinical data model [AUC:0.786, 95% CI 0.0384(0.709-0.851)] and the radiomics model [AUC:0.712, 95% CI 0.0426(0.631-0.785)]. The decision curve also confirmed that the combined model had a higher clinical net benefit. The same results were achieved in the test set. Conclusion The prognosis of patients with GP-NENs is generally poor. The combined model based on clinical data and CT radiomics can help to early predict the prognosis of patients with GP-NENs, and then necessary interventions could be provided to improve the survival rate and quality of life of patients.
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Sanguedolce F, Zanelli M, Palicelli A, Cavazza A, DE Marco L, Zizzo M, Ascani S, Landriscina M, Giordano G, Sollitto F, Loizzi D. The classification of neuroendocrine neoplasms of the lung and digestive system according to WHO, 5th Edition: similarities, differences, challenges & unmet needs. Panminerva Med 2022; 64:259-264. [PMID: 35146989 DOI: 10.23736/s0031-0808.22.04602-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Neuroendocrine neoplasms (NENs) are a group of disease entities sharing common morphological, ultrastructural and immunophenotypical features, yet with distinct biological behavior and clinical outcome, ranging from benign to frankly malignant. Accordingly, a spectrum of therapeutic options for each single entity is available, including somatostatin analogues (SSA), mTOR-inhibitors, peptide receptor radionuclide therapy (PRRT), non-platinum and platinum chemotherapy. In the last few decades, several attempts have been made in order to (1) better stratify these lesions refining the pathological classifications, so as to obtain an optimal correspondence between the scientific terminology and, the predictive and prognostic features of each disease subtype, and (2) achieve a global Classification encompassing NENs arising at different anatomical sites. Aim of this review is to analyze, compare and discuss the main features and issues of the latest WHO Classifications of NENs of the lung and the digestive system, in order to point out the strengths and limitations of our current understanding of these complex diseases.
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Affiliation(s)
| | - Magda Zanelli
- Pathology Unit, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Andrea Palicelli
- Pathology Unit, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Alberto Cavazza
- Pathology Unit, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Loredana DE Marco
- Pathology Unit, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Maurizio Zizzo
- Surgical Oncology Unit, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Stefano Ascani
- Pathology Unit, Azienda Ospedaliera Santa Maria di Terni, University of Perugia, Terni, Italy
| | - Matteo Landriscina
- Unit of Medical Oncology and Biomolecular Therapy, Department of Medical and Surgical Sciences, Policlinico Riuniti, University of Foggia, Foggia, Italy.,Laboratory of Pre-Clinical and Translational Research, IRCCS, Referral Cancer Center of Basilicata (CROB), Rionero in Vulture, Potenza, Italy
| | - Guido Giordano
- Unit of Medical Oncology and Biomolecular Therapy, Department of Medical and Surgical Sciences, Policlinico Riuniti, University of Foggia, Foggia, Italy
| | | | - Domenico Loizzi
- Institute of Thoracic Surgery, University of Foggia, Foggia, Italy
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