RESUMO
Background: Sinonasal neuroendocrine carcinoma is a rare head and neck tumor that represents only 5% of sinonasal neoplasms. This lesion has a high risk of invasion to adjacent structures such as the orbit, skull base, and soft tissues, with symptoms usually being nonspecific. Most cases are diagnosed in late stages, decreasing overall survival without treatment. To date, there is no consensus on management given its low prevalence; however, it has been shown that multimodal therapy, with the correct surgical approach as the mainstay, offers a better disease-free prognosis. Case Description: A 46-year-old woman presented with a 1 year history of nasal symptoms, characterized by obstruction and epistaxis. Imaging studies showed an extra-axial mass causing skull base erosion and displacement of the right fronto-orbital region, without invasion of brain parenchyma or meninges. A biopsy was performed and an unresectable poorly differentiated sinonasal neuroendocrine carcinoma was diagnosed. Treatment with radio and chemotherapy was initiated and, as the tumoral volume decreased, she was referred for neurosurgical intervention; an endonasal endoscopic approach was performed. Gross total resection was achieved and the patient was discharged without postoperative complications and no residual lesion on imaging. Conclusion: We describe the evolution of a rare advanced-stage neoplasm. It highlights that despite receiving an initial diagnosis of an unresectable mass, multimodal therapy, and an adequate surgical approach deemed the entire lesion to be resected. Despite the favorable clinical evolution, the follow-up of neuroendocrine carcinoma is prioritized as a neoplasm with a high rate of recurrence and metastasis.
RESUMO
Background The mean survival duration of patients with glioblastoma after diagnosis is 15 months (14-21 months), while progression-free survival is 10 months (+/- one month). Although there are well-defined overall survival statistics for glioblastoma, individual survival prediction remains a challenge. Therefore, there is a need to validate an accessible and cost-effective prognostic tool to provide valuable data for decision-making. This study aims to calculate the mean survival of patients with glioblastoma at a tertiary-level hospital in Mexico using the online glioblastoma survival calculator developed by researchers at Harvard Medical School & Brigham and Women's Hospital and compare it with the actual mean survival. Methodology We conducted a retrospective observational study of patients who received a histopathological diagnosis of glioblastoma from the National Institute of Neurology and Neurosurgery "Manuel Velasco Suárez" between 2015 and 2021. We included 50 patients aged 20-83 years, with a tumor size of 15-79 mm, and who had died 30 days after surgery. Patient survival was estimated using the online calculator developed at Harvard Medical School & Brigham and Women's Hospital. The estimated mean survival was then compared with the actual mean survival of the patient. A two-tailed equivalence test for paired samples was performed to conduct this comparison. A value of p < 0.05 was considered significant. Results The mean age of the sample was 55.5 years (confidence interval (CI) 95%, 52.61-58.71). The mean tumor size in our sample was 49.12 mm (±14.9mm). We identified a difference between the mean estimated survival and the mean actual survival of -1.37 months (CI 95%; range of -3.7 to +0.9). After setting the inferior (IL) and superior limits (SL) at -3.8 and +3.8 months, respectively, we found that the difference between the mean estimated survival and the actual mean survival is within the equivalence interval (IL: p = 0.0453; SL: p = 0.0002). Conclusions The actual survival of patients diagnosed with glioblastoma at the National Institute of Neurology and Neurosurgery was equivalent to the estimated survival calculated by the online prediction calculator developed at Harvard Medical School & Brigham and Women's Hospital. This study validates a practical, cost-effective, and accessible tool for predicting patient survival, contributing to significant support for medical and personal decision-making for glioblastoma management.