Clinical characteristics of 3,030 glioblastoma multiforme (GBM) patients in high, upper middle and lower middle economic regions based on real-world data (RWD)
Bibliographic record
Abstract
Background: GBM is the most common and aggressive primary brain tumor in adults. This study investigated RWD-based differences among 3,030 GBM patients stratified by three economic regions. Methods: The analysis was based on IQVIA syndicated cross-sectional surveys, collecting anonymized patient-level data between January 2016 and September 2017 in different countries, grouped into three economically different regions. Region 1 (high): EU5 (France, Germany, Italy, UK, Spain), Canada, Australia; Region 2 (upper middle): Korea, China, Taiwan; Region 3 (lower middle): Brazil, Mexico. Results: The percentage of patients aged >65 years was 23.9 % for region 1, 6.33 % for region 2 and 13.62 % for region 3, confirming younger GBM population in region 2. The age difference among the regions was statistically significant (P < 0.0001). The incidence of male (65 %) and female (35 %) patients was homogenous across all regions. Region 1 showed the highest testing rate (60 %) for MGMT promoter methylation and region 3 the lowest (33 %). EGFR mutation was not studied in more than 50 % of patients across the regions. However, in overall tested population, the EGFR VIII mutations varied: 39 %, 90 %, and 73 % for regions 1, 2 and 3, respectively. Concerning drug treatment options, temozolomide was the leading therapy (> 90 %) in all three regions, regardless of MGMT and EGFR status. The highest percentage (35 %) for cognitive impairment studied by MMSE (Mini Mental State Examination) was found in region 2, followed by 25 % and 22 % in regions 1 and 3, respectively. We did not find any differences in Performance Status or comorbidities among the regions, with no reported comorbidities in > 60 % of patients. Conclusions: This multi-variable analysis from RWD shows differences in clinical characteristics (i.e., age, biomarkers and MMSE), which may be taken into consideration in the design of GBM global studies. To our best knowledge, this study was based on the largest GBM database ever published. Legal entity responsible for the study: IQVIA. Funding: IQVIA. Disclosure: All authors have declared no conflicts of interest.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".