Dataset Information

Mortality following a brain tumour diagnosis in patients with multiple sclerosis.

ABSTRACT:

Objectives

As brain tumours and their treatment may theoretically have a poorer prognosis in inflammatory central nervous system diseases such as multiple sclerosis (MS), all-cause mortality following a brain tumour diagnosis was compared between patients with and without MS. The potential role of age at tumour diagnosis was also examined.

Setting

Hospital inpatients in Sweden with assessment of mortality in hospital or following discharge.

Participants

Swedish national registers identified 20 543 patients with an MS diagnosis (1969-2005) and they were matched individually to produce a comparison cohort of 204 163 members of the general population without MS. Everyone with a primary brain tumour diagnosis was selected for this study: 111 with MS and 907 without MS.

Primary and secondary outcome measures

5-year mortality risk following brain tumour diagnosis and age at brain tumour diagnosis.

Results

A non-statistically significant lower mortality risk among patients with MS (lower for those with tumours of high-grade and uncertain-grade malignancy and no notable difference for low-grade tumours) produced an unadjusted HR (and 95% CI) of 0.75 (0.56 to 1.02). After adjustment for age at diagnosis, grade of malignancy, sex, region of residence and socioeconomic index, the HR is 0.91 (0.67-1.24). The change in estimate was largely due to adjustment for age at brain tumour diagnosis, as patients with MS were on average 4.7 years younger at brain tumour diagnosis than those in the comparison cohort (p<0.001).

Conclusions

Younger age at tumour diagnosis may contribute to mortality reduction in those with high-grade and uncertain-grade brain tumours. Survival following a brain tumour is not worse in patients with MS; even after age at brain tumour diagnosis and grade of malignancy are taken into account.

SUBMITTER: Montgomery S

PROVIDER: S-EPMC3831093 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Conventional magnetic resonance imaging (cMRI) is poorly sensitive to pathological changes related to multiple sclerosis (MS) in normal-appearing white matter (NAWM) and gray matter (GM), with the added difficulty of not being very reproducible. Quantitative MRI (qMRI), on the other hand, attempts to represent the physical properties of tissues, making it an ideal candidate for quantitative medical image analysis or radiomics. We therefore hypothesized that qMRI-based radiomic features have added diagnostic value in MS compared to cMRI. This study investigated the ability of cMRI (T1w) and qMRI features extracted from white matter (WM), NAWM, and GM to distinguish between MS patients (MSP) and healthy control subjects (HCS). We developed exploratory radiomic classification models on a dataset comprising 36 MSP and 36 HCS recruited in CHU Liege, Belgium, acquired with cMRI and qMRI. For each image type and region of interest, qMRI radiomic models for MS diagnosis were developed on a training subset and validated on a testing subset. Radiomic models based on cMRI were developed on the entire training dataset and externally validated on open-source datasets with 167 HCS and 10 MSP. Ranked by region of interest, the best diagnostic performance was achieved in the whole WM. Here the model based on magnetization transfer imaging (a type of qMRI) features yielded a median area under the receiver operating characteristic curve (AUC) of 1.00 in the testing sub-cohort. Ranked by image type, the best performance was achieved by the magnetization transfer models, with median AUCs of 0.79 (0.69-0.90, 90% CI) in NAWM and 0.81 (0.71-0.90) in GM. The external validation of the T1w models yielded an AUC of 0.78 (0.47-1.00) in the whole WM, demonstrating a large 95% CI and a low sensitivity of 0.30 (0.10-0.70). This exploratory study indicates that qMRI radiomics could provide efficient diagnostic information using NAWM and GM analysis in MSP. T1w radiomics could be useful for a fast and automated check of conventional MRI for WM abnormalities once acquisition and reconstruction heterogeneities have been overcome. Further prospective validation is needed, involving more data for better interpretation and generalization of the results.

Project description:Among people with multiple sclerosis, cognitive impairment occurs commonly and is a potent predictor of disability. Some multiple sclerosis patients present with severe cognitive impairment, and distinguishing multiple sclerosis-related cognitive impairment from co-existent progressive neurodegenerative diseases such as Alzheimer disease poses a diagnostic challenge. The use of biomarkers such as PET and CSF proteins may facilitate this distinction. The study was a retrospective, descriptive study on convenience samples of separate cohorts, one of cognitively impaired multiple sclerosis patients evaluated on autopsy to demonstrate coincidence of both multiple sclerosis and neurodegenerative cognitive diseases. The second cohort were cognitively impaired multiple sclerosis patients evaluated by biomarker to investigate possible additional neurodegenerative cognitive disorders contributing to the cognitive impairment. We investigated selected biomarkers among 31 severely impaired patients (biomarker cohort) and 12 severely impaired patients assessed at autopsy and selected 24 (23 biomarker cohort, 1 autopsy cohort) had comprehensive neurocognitive testing. Biomarker cohort investigations included 18F-Fluorodeoxyglucose PET and/or CSF amyloid Aβ1-42, phospho-tau and total tau levels. The autopsy cohort was evaluated with comprehensive neuropathological assessment for aetiology of cognitive impairment. The cohorts shared similar sex, age at multiple sclerosis onset and multiple sclerosis clinical course. The autopsy-cohort patients were older at diagnosis (69.5 versus 57 years, P = 0.006), had longer disease duration [median (range) 20 years (3-59) versus 9 (1-32), P = 0.001] and had more impaired bedside mental status scores at last follow-up [Kokmen median (range) 23 (1-38) versus 31 (9-34) P = 0.01]. Autopsy-cohort patients confirmed, or excluded, coexistent neurogenerative disease by neuropathology gold standard. Most biomarker-cohort patients had informative results evaluating coexistent neurogenerative disease. Biomarkers may be useful in indicating a coexistent neurodegenerative disease earlier, and in life, in patients with multiple sclerosis and significant cognitive impairment.