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Record W4312114812 · doi:10.1200/jco.21.02968

Outcomes of Infants and Young Children With Relapsed Medulloblastoma After Initial Craniospinal Irradiation–Sparing Approaches: An International Cohort Study

2022· article· en· W4312114812 on OpenAlexaff
Craig Erker, Martin Mynarek, Simon Bailey, Claire Mazewski, Lorena Baroni, Maura Massimino, Juliette Hukin, Dolly Aguilera, Andréa Maria Cappellano, Vijay Ramaswamy, Álvaro Lassaletta, Sébastien Perreault, Cassie Kline, Revathi Rajagopal, George Michaiel, Michal Zápotocký, Vicente Santa‐María López, Andrés Morales La Madrid, Chantel Cacciotti, Eric Sandler, Lindsey M. Hoffman, Darren Klawinski, Sara Khan, Ralph Salloum, Valérie Larouche, Kathleen Dorris, Helen Toledano, Stephen W. Gilheeney, Mohamed S Abdelbaki, Beverly Wilson, Derek S. Tsang, Jeffrey Knipstein, Michal Oren, Shafqat Shah, Jeffrey C. Murray, Kevin Ginn, Zhihong J. Wang, Gudrun Fleischhack, Denise Obrecht, Svenja Tonn, Virginia L. Harrod, Kara Matheson, Bruce Crooks, Douglas Strother, Kenneth J. Cohen, Jordan R. Hansford, Sabine Mueller, Ashley Margol, Amar Gajjar, Girish Dhall, Jonathan L. Finlay, Paul A. Northcott, Stefan Rutkowski, Giles Robinson, Éric Bouffet, Lucie Lafay‐Cousin

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsNova Scotia Health AuthorityPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of AlbertaUniversity of TorontoWestern UniversityBC Children's HospitalUniversité LavalHospital for Sick ChildrenUniversité de MontréalDalhousie UniversityCentre Hospitalier Universitaire Sainte-JustineSickKids FoundationUniversity of British ColumbiaAlberta Children's HospitalStollery Children's HospitalIzaak Walton Killam Health Centre
FundersBrain Tumour CharityCancer Research UK
KeywordsMedicineMedulloblastomaCohortNeurocognitiveProportional hazards modelPropensity score matchingSalvage therapyHazard ratioChemotherapyInternal medicineOncologyPediatricsSurgeryConfidence intervalPathology

Abstract

fetched live from OpenAlex

PURPOSE Infant and young childhood medulloblastoma (iMB) is usually treated without craniospinal irradiation (CSI) to avoid neurocognitive late effects. Unfortunately, many children relapse. The purpose of this study was to assess salvage strategies and prognostic features of patients with iMB who relapse after CSI-sparing therapy. METHODS We assembled a large international cohort of 380 patients with relapsed iMB, age younger than 6 years, and initially treated without CSI. Univariable and multivariable Cox models of postrelapse survival (PRS) were conducted for those treated with curative intent using propensity score analyses to account for confounding factors. RESULTS The 3-year PRS, for 294 patients treated with curative intent, was 52.4% (95% CI, 46.4 to 58.3) with a median time to relapse from diagnosis of 11 months. Molecular subgrouping was available for 150 patients treated with curative intent, and 3-year PRS for sonic hedgehog (SHH), group 4, and group 3 were 60%, 84%, and 18% ( P = .0187), respectively. In multivariable analysis, localized relapse ( P = .0073), SHH molecular subgroup ( P = .0103), CSI use after relapse ( P = .0161), and age ≥ 36 months at initial diagnosis ( P = .0494) were associated with improved survival. Most patients (73%) received salvage CSI, and although salvage chemotherapy was not significant in multivariable analysis, its use might be beneficial for a subset of children receiving salvage CSI < 35 Gy ( P = .007). CONCLUSION A substantial proportion of patients with relapsed iMB are salvaged after initial CSI-sparing approaches. Patients with SHH subgroup, localized relapse, older age at initial diagnosis, and those receiving salvage CSI show improved PRS. Future prospective studies should investigate optimal CSI doses and the role of salvage chemotherapy in this population.

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)0.001
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.079
GPT teacher head0.414
Teacher spread0.335 · 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

Citations28
Published2022
Admission routes1
Has abstractyes

Explore more

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