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Record W4399785372 · doi:10.1093/neuonc/noae064.516

MDB-67. MEDULLOBLASTOMA MOLECULAR SUBGROUPING AND OUTCOMES DATA OF A SINGLE CENTER FROM A LOW-MIDDLE-INCOME COUNTRY

2024· article· en· W4399785372 on OpenAlexaffabout
Naureen Mushtaq, Farrah Bashir, Quratulain Riaz, Soha Zahid, Gohar Javed, Maria Tariq, Bilal Mazhar Qureshi, Kiran Hilal, Vijay Ramaswamy, Cynthia Hawkins, Éric Bouffet, Khurram Minhas

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsCenter (category theory)MedulloblastomaMiddle income countryLow and middle income countriesSingle CenterLow incomeGeographyPolitical scienceDemographic economicsEconomic growthMedicineEconomicsDeveloping countryInternal medicine

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Medulloblastoma is the most common malignant childhood brain tumor. The molecular subgrouping of medulloblastoma is a major determinant of management in high-income countries. Subgrouping is still very limited in low- and middle-income countries, and its relevance to management has yet to be evaluated in this setting. We describe molecular findings and their implications in the outcome of a single tertiary care center. METHODS Children between 3 and 18 years diagnosed with medulloblastoma between April 2014 and December 2020 at Aga Khan University Hospital were included. Subgrouping was performed by nanostring through a collaboration with the Hospital for Sick Children, Toronto. RESULTS Thirty-five children were identified (85.17% male); the median age was 8. Nineteen patients were high-risk, including 9 with metastatic disease. In 28 children, there was a clear molecular subgroup: 4 WNT (11.4%), 7 Sonic Hedgehog (20%), 3 Group 3 (8.6%), and 14 Group 4 (40%) medulloblastomas. Molecular subgrouping was inconclusive for two patients (5.7%) and not done in 5 patients (14.3%). All patients underwent surgery; 91.4% received radiation therapy and chemotherapy. Of 35 children, overall Survival at 5 years was 100%, 57.1%, 66.7%, and 85.7% for WNT, Sonic Hedgehog, Group 3, and Group 4, respectively. WNT and Group 3 had 100% Progression-free survival, whereas Sonic Hedgehog and Group 4 had decreased progression-free survival of 42.9% and 85.7%, respectively. Average-risk patients had an overall survival of 93.8%, whereas high-risk patients exhibited a statistically significant lower overall survival of 63.2% (P=0.014). CONCLUSION Our cohort demonstrates excellent outcomes for WNT and Group 4, despite one WNT being metastatic and four Group 4 patients being high-risk. Modern risk stratification is an excellent predictor of survival, suggesting that treatment can be tailored according to subgrouping in the LMIC setting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.031
GPT teacher head0.305
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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