How to live with a meningioma: experiences, symptoms, and challenges reported by patients
Bibliographic record
Abstract
Abstract Background We aimed to explore gaps in the care of meningioma patients that could improve quality of care by better understanding symptoms experienced by patients at various stages of treatment, and afterwards. Methods A novel 19-item self-administered questionnaire was provided for patients with meningiomas to complete by the American Brain Tumor Association (ABTA) over a 3-month period. Results A total of 1852 unique respondents were included. Nearly one-third of all respondents felt they received insufficient information about meningiomas at initial diagnosis (N = 607, 32.9%) and 28.8% (N = 530) believed they received insufficient information about treatment options. In fact, 34.5% of respondents received the majority of their information from the internet and nonhealthcare professionals. The most common concerns after initial diagnosis were risks associated with surgery and/or treatment (36.5%) followed by how the tumor would impact daily life (25%) and the risk of tumor recurrence (12.4%). Respondents indicated that a list of resources available for patients with meningiomas (N = 597, 32.3%) would have been most beneficial in regards to their disease experience after their initial diagnosis. Moreover, we found that a substantial proportion of patients continued to report symptoms long after treatment, with fatigue being the most common compared to before treatment (38.2% vs. 57.7%, χ2 = 128, P < .001). Conclusions Patients with meningiomas exhibit symptoms that continue well after treatment with fatigue and cognitive impairments as the most bothersome. Moreover, patients report key communication gaps that can be addressed to improve their disease experience and care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".