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Symptoms in primary care with time to diagnosis of brain tumours.

ABSTRACT: Background:Brain tumours often present with varied, non-specific features with other diagnoses usually being more likely. Objective:To examine how different symptoms and patient demographics predict variations in time to brain tumour diagnosis. Methods:We conducted a secondary analysis of brain tumour cases from National Audit of Cancer Diagnosis in Primary Care. We grouped neurological symptoms into six domains (headache, behavioural/cognitive change, focal neurology, 'fits, faints or falls', non-specific neurological, and other/non-specific) and calculated times for patient presentation, GP referral, specialist consultation and total pathway interval. We calculated odds ratios (ORs) for symptom domains comparing the slowest to other quartiles. Results:Data were available for 226 cases. Median (interquartile range) time for the total pathway interval was 24 days (7-65 days). The most common presentation was focal neurology (33.2%) followed by 'fits, faints or falls' and headache (both 20.8%). Headache only (OR = 4.11, 95% CI = 1.10, 15.5) and memory complaints (OR = 4.82, 95% CI = 1.15, 20.1) were associated with slower total pathway compared to 'fits, faints or falls'. GPs were more likely to consider that there had been avoidable delays in referring patients with headache only (OR = 4.17, 95% CI = 1.14, 15.3). Conclusion:Patients presenting to primary care with headache only or with memory complaints remain problematic with potentially avoidable delays in referral leading to a longer patient pathway. This may or may not impact on the efficacy and morbidity of therapies. Additional aids are required to help doctors differentiate when to refer headaches and memory complaints urgently for a specialist opinion.

SUBMITTER: Ozawa M

PROVIDER: S-EPMC6142711 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Symptoms in primary care with time to diagnosis of brain tumours.

Ozawa Mio M Brennan Paul M PM Zienius Karolis K Kurian Kathreena M KM Hollingworth William W Weller David D Hamilton Willie W Grant Robin R Ben-Shlomo Yoav Y

Family practice 20180901 5

<h4>Background</h4>Brain tumours often present with varied, non-specific features with other diagnoses usually being more likely.<h4>Objective</h4>To examine how different symptoms and patient demographics predict variations in time to brain tumour diagnosis.<h4>Methods</h4>We conducted a secondary analysis of brain tumour cases from National Audit of Cancer Diagnosis in Primary Care. We grouped neurological symptoms into six domains (headache, behavioural/cognitive change, focal neurology, 'fit ...[more]

PMID: 29420713

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Project description:DNA methylation is increasingly used for tumour classification and has expanded upon the > 100 currently known brain tumour entities. A correct diagnosis is the basis for suitable treatment for patients with brain tumours, which is the leading cause of cancer-related death in children. DNA methylation profiling is required for diagnosis of certain tumours, and used clinically for paediatric brain tumours in several countries. We therefore evaluated if the methylation-based classification is robust in different locations of the same tumour, and determined how the methylation pattern changed over time to relapse. We sampled 3-7 spatially separated biopsies per patient, and collected samples from paired primary and relapse brain tumours from children. Altogether, 121 samples from 46 paediatric patients with brain tumours were profiled with EPIC methylation arrays. The methylation-based classification was mainly homogeneous for all included tumour types that were successfully classified, which is promising for clinical diagnostics. There were indications of multiple subclasses within tumours and switches in the relapse setting, but not confirmed as the classification scores were below the threshold. Site-specific methylation alterations did occur within the tumours and varied significantly between tumour types for the temporal samples, and as a trend in spatial samples. More alterations were present in high-grade tumours compared to low-grade, and significantly more alterations with longer relapse times. The alterations in the spatial and temporal samples were significantly depleted in CpG islands, exons and transcription start sites, while enriched in OpenSea and regions not affiliated with a gene, suggesting a random location of the alterations in less conserved regions. In conclusion, more DNA methylation changes accumulated over time and more alterations occurred in high-grade tumours. The alterations mainly occurred in regions without gene affiliation, and did not affect the methylation-based classification, which largely remained homogeneous in paediatric brain tumours.

Project description:Abstract Purpose: Positron emission tomography with carbon-11 labelled methionine (11C-METH PET) is a well-established imaging modality allowing to characterise tumour lesions on a metabolic and molecular level. The aim of the current study was to evaluate the relationship between 11C-METH PET semi-quantitative metrics and molecular biomarkers in patients affected by brain gliomas candidate to surgery, and determine their prognostic role with respect to disease outcome. Materials and Methods: A consecutive series of 145 patients affected by pathologically proven gliomas, who were referred to our Institution for tumour resection from March 2012 to January 2015 and submitted to pre-operative evaluation with 11C-METH PET, was retrospectively analyzed. The trial was registered at www.clinicaltrials.com (NCT02518061). Demographics, clinical-radiological features and follow up data were available for 109 patients (M:F=64:45; median age 43 years). In all cases, semi-quantitative metrics were obtained on 11C-METH PET, i.e. SUVmax, SUVratio and metabolic tumour volume (MTV). These data were correlated to disease outcome, in terms of progression-free survival (PFS), and compared to other clinical-biological information, i.e. IDH1 mutation, 1p/19q co-deletion and MGMT promoter methylation. The entire cohort was monitored for a mean period of 16.7 months (median 13). Results: According to WHO classification, we investigated 40 low grade gliomas (LGG; 36.7%) and 69 high grade gliomas (HGG; 63.3%). In all patients, tumours were identified on 11C-METH PET: median SUVmax 3.3, median SUVratio 2.3, and median MTV 9.6 cm3. We observed a statistically significant difference for SUVmax, SUVratio and MTV values based on tumour grade (p<0.001) and glioblastoma tumours (p<0.001, p<0.001 and p=0.045, respectively). According to molecular analyses, IDH1 resulted mutated in 49 patients, 1p/19q co-deleted in 58 patients and MGMT promoter methylated in 74 patients. We observed a statistically significant correlation between SUVmax and SUVratio and IDH1 mutation (p<0.001). During follow up, relapse or progression was documented in 48 cases (median PFS 8.7 months). We observed a statistically significant correlation to PFS on univariate analysis for SUVmax and SUVratio, tumour grade, IDH1 mutation, 1p/19q co-deletion and MGMT promoter methylation,. Conclusions: Metabolic characteristics on 11C-METH PET significantly correlate with histological grading and IDH1 mutation status in primary brain tumours. With respect to disease outcome, grading, molecular biomarkers, SUVmax and SUVratio resulted prognostic factors to PFS in this cohort of patients candidate to surgery.

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Symptoms in primary care with time to diagnosis of brain tumours.

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Symptoms in primary care with time to diagnosis of brain tumours.

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