Object: It is becoming well-established that increasing extent of resection with decreasing residual volume is associated with delayed recurrence and prolonged survival for patients with glioblastoma ...(GBM). These prior studies are based on evaluating the contrast-enhancing (CE) tumour and not the surrounding fluid attenuated inversion recovery (FLAIR) volume. It therefore remains unclear if the resection beyond the CE portion of the tumour if it translates into improved outcomes for patients with GBM.
Methods: Adult patients who underwent resection of a primary glioblastoma at a tertiary care institution between January 1, 2007 and December 31, 2012 and underwent radiation and temozolomide chemotherapy were retrospectively reviewed. Pre and postoperative MRI images were measured for CE tumour and FLAIR volumes. Multivariate proportional hazards were used to assess associations with both time to recurrence and death. Values with p < 0.05 were considered statistically significant.
Results: 245 patients met the inclusion criteria. The median IQR preoperative CE and FLAIR tumour volumes were 31.9 13.9-56.1 cm
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and 78.3 44.7-115.6 cm
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, respectively. Following surgery, the median IQR postoperative CE and FLAIR tumour volumes were 1.9 0-7.1 cm
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and 59.7 29.7-94.2 cm
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, respectively. In multivariate analyses, the postoperative FLAIR volume was not associated with recurrence and/or survival (p > 0.05). However, the postoperative CE tumour volume was significantly associated with both recurrence HR (95%CI); 1.026 (1.005-1.048), p = 0.01 and survival HR (95%CI); 1.027 (1.007-1.032), p = 0.001. The postoperative FLAIR volume was also not associated with recurrence and/or survival among patients who underwent gross total resection of the CE portion of the tumour as well as those who underwent supratotal resection.
Conclusions: In this study, the volume of CE tumour remaining after resection is more important than FLAIR volume in regards to recurrence and survival for patients with GBM.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We aimed to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of coronavirus disease 2019 (COVID-19), to identify patients at risk of ...critical outcomes.
We used data from the SEMI-COVID-19 Registry, a cohort of consecutive patients hospitalized for COVID-19 from 132 centres in Spain (23rd March to 21st May 2020). For the development cohort, tertiary referral hospitals were selected, while the validation cohort included smaller hospitals. The primary outcome was a composite of in-hospital death, mechanical ventilation, or admission to intensive care unit. Clinical signs and symptoms, demographics, and medical history ascertained at presentation were screened using least absolute shrinkage and selection operator, and logistic regression was used to construct the predictive model.
There were 10 433 patients, 7850 in the development cohort (primary outcome 25.1%, 1967/7850) and 2583 in the validation cohort (outcome 27.0%, 698/2583). The PRIORITY model included: age, dependency, cardiovascular disease, chronic kidney disease, dyspnoea, tachypnoea, confusion, systolic blood pressure, and SpO2 ≤93% or oxygen requirement. The model showed high discrimination for critical illness in both the development (C-statistic 0.823; 95% confidence interval (CI) 0.813, 0.834) and validation (C-statistic 0.794; 95%CI 0.775, 0.813) cohorts. A freely available web-based calculator was developed based on this model (https://www.evidencio.com/models/show/2344).
The PRIORITY model, based on easily obtained clinical information, had good discrimination and generalizability for identifying COVID-19 patients at risk of critical outcomes.
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