A Retrospective Study of the Prognostic Value of Various Pathological and Immunohistochemical Features in Tissue Samples from Patients with Pancreatic Neuroendocrine Neoplasms

Abstract Casestudy: Pancreatic neuroendocrine neoplasms (PanNEN) are rare accounting for 2-5% of pancreatic tumors. Although mostly sporadic, 10-20% are associated with inherited syndromes, notably MEN-1, Von Hippel- Lindau disease, neurofibromatosis type 1, and tuberous sclerosis (TS). When compared to sporadic cases, PanNEN in hereditary syndromes occur at a younger age, are often multifocal, cystic, and may show characteristic microscopic patterns. TS is an autosomal dominant multi-system disorder with mutations involving TSC1 or TSC2 genes which function as tumor suppressors by inhibiting mTORC1 kinase. PanNEN is observed in 1.5-1.8% of patients with TS and no surveillance guidelines for the assessment of pancreatic lesions are established. Compared to other syndromes, PanNEN associated with TS are solitary. To our knowledge, only two cases of multifocal PanNEN in TS patients have been reported. We present a case of a 67-year-old gentleman with a history of TS also affecting two daughters. He presented to the emergency department with severe abdominal pain. Abdominal ultrasound suggested acute appendicitis and an incidental 2.0 cm solid lesion was noted in the head of the pancreas. Follow-up MRI revealed two additional non-cystic masses in the pancreatic tail. Endoscopic ultrasound-guided biopsy of a tail lesion revealed monomorphic tumor cells with stippled chromatin without cytologic atypia. Immunohistochemical staining was positive for synaptophysin and chromogranin. Ki-67 labelling index was under 1%. Diagnosis of a well-differentiated neuroendocrine tumor (G1) was made. The patient denied symptoms of the carcinoid syndrome and no biologically active hormones were detected. Gallium PET scan revealed multiple foci of radiotracer uptake throughout the pancreas in addition to those described on MRI. Although PanNEN are rare in TS, malignant behavior has been reported. This case reinforces the importance of early detection through active surveillance, especially as surgical options may be limited in multifocal disease.

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Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study

Biomarker Insights ◽

10.1177/11772719211027022 ◽

2021 ◽

Vol 16 ◽

pp. 117727192110270

Author(s):

Gönül Açıksarı ◽

Mehmet Koçak ◽

Yasemin Çağ ◽

Lütfiye Nilsun Altunal ◽

Adem Atıcı ◽

...

Keyword(s):

Retrospective Study ◽

Hospital Mortality ◽

Prognostic Value ◽

Current Knowledge ◽

Area Under The Curve ◽

Prognostic Nutritional Index ◽

Inflammatory Biomarkers ◽

Single Center ◽

Discriminative Ability ◽

Lymphocyte Ratio

Background: The current knowledge about novel coronavirus-2019 (COVID-19) indicates that the immune system and inflammatory response play a crucial role in the severity and prognosis of the disease. In this study, we aimed to investigate prognostic value of systemic inflammatory biomarkers including C-reactive protein/albumin ratio (CAR), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in patients with severe COVID-19. Methods: This single-center, retrospective study included a total of 223 patients diagnosed with severe COVID-19. Primary outcome measure was mortality during hospitalization. Multivariate logistic regression analyses were performed to identify independent predictors associated with mortality in patients with severe COVID-19. Receiver operating characteristic (ROC) curve was used to determine cut-offs, and area under the curve (AUC) values were used to demonstrate discriminative ability of biomarkers. Results: Compared to survivors of severe COVID-19, non-survivors had higher CAR, NLR, and PLR, and lower LMR and lower PNI ( P < .05 for all). The optimal CAR, PNI, NLR, PLR, and LMR cut-off values for detecting prognosis were 3.4, 40.2, 6. 27, 312, and 1.54 respectively. The AUC values of CAR, PNI, NLR, PLR, and LMR for predicting hospital mortality in patients with severe COVID-19 were 0.81, 0.91, 0.85, 0.63, and 0.65, respectively. In ROC analysis, comparative discriminative ability of CAR, PNI, and NLR for hospital mortality were superior to PLR and LMR. Multivariate analysis revealed that CAR (⩾0.34, P = .004), NLR (⩾6.27, P = .012), and PNI (⩽40.2, P = .009) were independent predictors associated with mortality in severe COVID-19 patients. Conclusions: The CAR, PNI, and NLR are independent predictors of mortality in hospitalized severe COVID-19 patients and are more closely associated with prognosis than PLR or LMR.

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