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Record W4281777545 · doi:10.1093/neuonc/noac079.389

MEDB-14. Clinical outcome of pediatric medulloblastoma patients with Li-Fraumeni syndrome

2022· article· en· W4281777545 on OpenAlexaff
Anna Kołodziejczak, Léa Guerrini‐Rousseau, Julien Masliah‐Planchon, Jonas Ecker, Florian Selt, Martin Mynarek, Denise Obrecht, Martin Sill, Steffen Hirsch, Dominik Sturm, Sebastian M. Waszak, Vijay Ramaswamy, Virve Pentikäinen, Hacı Ahmet Demir, Steven C. Clifford, Ed C. Schwalbe, Luca Massimi, Matija Snuderl, Kristyn Galbraith, Matthias A. Karajannis, Katie Hill, Bryan Li, Christine L. White, Shelagh Redmond, Loizos Loizou, Marcus Jakob, Uwe Kordes, Irene Schmid, Julia Hauer, Claudia Blattmann, Maria Filippidou, Wolfram Scheurlen, Udo Kontny, Kerstin Grund, Christian Sutter, Torsten Pietsch, Cornelis M. van Tilburg, Stephan Frank, Denis M. Schewe, David Malkin, Michael D. Taylor, Uri Tabori, Éric Bouffet, Marcel Kool, Felix Sahm, Andreas von Deimling, Andrey Korshunov, Katja von Hoff, Christian P. Kratz, David Jones, Stefan Rutkowski, Olaf Witt, Gaëlle Bougeard, Kristian W. Pajtler, Stefan M. Pfister, Franck Bourdeaut, Till Milde

Bibliographic record

VenueNeuro-Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedulloblastomaMedicineRetrospective cohort studyChemotherapyRadiation therapyInternal medicineOncologyMissense mutationIncidence (geometry)PathologyMutationBiology

Abstract

fetched live from OpenAlex

Abstract PURPOSE: The prognosis for SHH-medulloblastoma (MB) patients with Li-Fraumeni syndrome (LFS) is poor. Due to lack of comprehensive data for these patients, it is challenging to establish effective therapeutic recommendations. We here describe the largest retrospective cohort of pediatric LFS SHH-MB patients to date and their clinical outcomes. PATIENTS AND METHODS: N=31 patients with LFS SHH-MB were included in this retrospective multicenter study. TP53 variant type, clinical parameters including treatment modalities, event-free survival (EFS) and overall survival (OS), as well as recurrence patterns and incidence of secondary neoplasms, were evaluated. RESULTS: All LFS-MBs were classified as SHH subgroup, in 30/31 cases based on DNA methylation analysis. The majority of constitutional TP53 variants (72%) represented missense variants, and all except two truncating variants were located within the DNA-binding domain. 54% were large cell anaplastic, 69% gross totally resected and 81% had M0 status. The 2-(y)ear and 5-(y)ear EFS were 26% and 8,8%, respectively, and 2y- and 5y-OS 40% and 12%. Patients who received post-operative radiotherapy (RT) followed by chemotherapy (CT) showed significantly better outcomes (2y-EFS:43%) compared to patients who received CT before RT (30%) (p<0.05). The 2y-EFS and 2y-OS were similar when treated with protocols including high-dose chemotherapy (EFS:22%, OS:44%) compared to patients treated with maintenance-type chemotherapy (EFS:31%, OS:45%). Recurrence occurred in 73.3% of cases independent of resection or M-status, typically within the radiation field (75% of RT-treated patients). Secondary malignancies developed in 12.5% and were cause of death in all affected patients. CONCLUSIONS: Patients with LFS-MBs have a dismal prognosis. This retrospective study suggests that upfront RT may increase EFS, while intensive therapeutic approaches including high-dose chemotherapy did not translate into increased survival of this patient group. To improve outcomes of LFS-MB patients, prospective collection of clinical data and development of treatment guidelines are required.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.317
Teacher spread0.291 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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