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Record W3049396862 · doi:10.1101/2020.08.12.20171801

Clinical phenotypes and prognostic features of ETMRs (Embryonal Tumor with Multi-layered Rosettes) a new CNS tumor entity: A Rare Brain Tumor Registry study

2020· preprint· en· W3049396862 on OpenAlexaffabout
Sara Khan, Palma Solano‐Páez, Tannu Suwal, Mei Lu, Salma Al‐Karmi, Ben Ho, CV AlmeidaGonzalez, Derek Stephens, Andrew Dodgshun, Mary Shago, Paula Marrano, Adriana Fonseca, Lindsey M. Hoffman, Sarah Leary, Holly Lindsay, Álvaro Lassaletta, Anne Bendel, Christopher L. Moertel, Andres Morales, Vicente Santa‐María, Cinzia Lavarino, Eloy Rivas, Sebastian Perreault, Benjamin Ellezam, Nada Jabado, Angélica Oviedo, Michal Yalon-Oren, Laura Amariglio, Helen Toledano, James Loukides, Timothy Van Meter, Hideo Nakamura, Tai‐Tong Wong, Kuo-Sheng Wu, Chien-Jui Cheng, Young‐Shin Ra, Milena La Spina, Luca Massimi, Anna Maria Buccoliero, Alyssa Reddy, Rong Li, G. Yancey Gillespie, Dariusz Adamek, Jason Fangusaro, David Scharnhorst, Joseph C. Torkildson, Donna L. Johnston, Jean Michaud, Lucie Lafay‐Cousin, Jennifer A. Chan, Frank K.H. van Landeghem, Beverly Wilson, Sandra Camelo‐Piragua, Nabil Kabbara, Mahjouba Boutarbouch, Derek Hanson, Chad Jacobsen, Karen Wright, Jean M. Mulcahy Levy, Yin Wang, Daniel Catchpoole, Nicolas Gerber, Michael A. Grotzer, Violet Shen, Ashley Plant, Christopher Dunham, Maria João Gil‐da‐Costa, Ramya Ramanujachar, Eric H. Raabe, Jeffery Rubens, Joanna J. Philips, Nalin Gupta, Ahmet Muzaffer Demir, Christine Dahl, Mette Jorgensen, Eugene Hwang, Amy Smith, Enrica E. K. Tan, Sharon Y. Y. Low, Jian‐Qiang Lu, Ho‐Keung Ng, Jesse Kresak, Sridharan Gururangan, Scott L. Pomeroy, Nongnuch Sirachainan, Suradej Hongeng, Vanan Magimairajan, Roona Sinha, Naureen Mushtaq, Reuben Antony, Mariko Sato, David Samuel, Michal Zápotocký, Samina Afzal, Nisreen Amayiri, Maysa Al‐Hussaini, Andrew W. Walter, Tarık Tihan, Gino R. Somers, Amar Gajjar, Paul Wood, Nicolas Gottardo, Jason E. Cain, Peter Downie, Helen M. Branson, Suzanne Laughlin, Birgit Ertl‐Wagner, Derek S. Tsang, Vijay Ramaswamy, James M. Drake, Abhaya V. Kulkarni, David S. Ziegler, Sumihito Nobusawa, Uri Tabori, Michael D. Taylor, George M. Ibrahim, James T. Rutka, Peter B. Dirks, Lili‐Naz Hazrati, Richard G. Grundy, Maryam Fouladi, Pr Laetitia Padovani, Franck Bourdeaut, Jordan R. Hansford, Ute Bartels, Christelle Dufour, Cynthia Hawkins, Nicolás André, Éric Bouffet, Annie Huang

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of ManitobaUniversity Health NetworkCancerCare ManitobaMcMaster UniversityUniversity of British ColumbiaUniversity of AlbertaStollery Children's HospitalIzaak Walton Killam Health CentreAlberta Children's HospitalMcGill UniversityUniversity of OttawaPrincess Margaret Cancer CentreUniversity of CalgaryChildren's Hospital of Eastern OntarioHospital for Sick ChildrenUniversité de MontréalSickKids FoundationRoyal University HospitalUniversity of TorontoCentre Hospitalier Universitaire Sainte-Justine
FundersJunta de Andalucía
KeywordsMedicineHazard ratioInternal medicineChemotherapyProportional hazards modelBrain tumorOncologyDiseasePhenotypeGastroenterologyPathologyConfidence intervalBiologyGene

Abstract

fetched live from OpenAlex

Background ETMRs are a newly recognized rare paediatric brain tumor with alterations of the C19MC microRNA locus. Due to varied diagnostic practices and limited clinical data, disease features and determinants of outcome are poorly defined. We performed an integrated clinico-pathologic and molecular analyses of 159 primary ETMRs to define clinical phenotypes, identify predictors of survival and critical treatment modalities for this orphan disease. Methods Primary ETMR patients were identified from the Rare Brain Tumor Consortium (rarebraintumorconsortium.ca) global registry using histopathologic and molecular assays. Event-Free (EFS) and Overall Survival (OS) for 108 patients treated with curative multi-modal regimens were determined using Cox proportional hazard and log rank analyses. Findings ETMRs were predominantly non-metastatic (73%) tumors arising from multiple sites; 55% were cerebral tumors, 45% arose at sites characteristic of other brain tumors. Hallmark C19MC alterations were seen in 91%; 9% were ETMR-NOS. Survival and hazard analyses showed a 6 month median EFS and 2-4yr OS of 27-29% with metastatic disease (HR=0.44, 95% CI 0.26-0.74; p=0.002) and brainstem location (HR=0.40, 95% CI 0.021-0.75; p=0.005) correlating with adverse OS. Gross total resection (GTR: HR=0.38, 95% CI 0.21-0.68; p=0.001), high dose chemotherapy (HDC: HR=0.55, 95% CI 0.31-0.97; p=0.04) and radiation (RT: HR=0.32, 95% CI 0.16-0.60; p=<0.001) correlated with improved EFS and OS in multi-variable analyses. EFS and OS for patients treated with only conventional dose chemotherapy (CC) was 0% and respectively 37%±14% and 32%± 13% for patients treated with HDC. Patients with GTR or sub-total resection (STR) treated with HDC and RT had superior EFS (GTR 73%±14%, p=0.018; STR 67%±19% p=0.009) and OS (GTR 66%±17%, p=0.05; STR 67%±16%, p=0.005). Amongst 21 long-term survivors (OS 24-202 months); 38%, 24% and 24% respectively received craniospinal, focal or no RT. Interpretation Prompt molecular diagnosis and post-surgical treatment with multi-modal therapy tailored to patient-specific risk features improves ETMR survival. Funding This work was supported by the Canadian Institute of Health Research Grant No. 137011, Canada Research Chair Awards to AH. Funds from Miracle Marnie, Phoebe Rose Rocks, Tali’s Funds, Garron Cancer Centre, Grace’s Walk, Meagan’s Walk, Nelina’s Hope and Jean Martel Foundation are gratefully acknowledged. SK and PS were respectively supported by the Australian Lions Children’s Cancer Foundation and the Spanish Society of Pediatrics, Consejería de Salud y Familias de la Junta de Andalucía Project EF-0451-2017.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.046
GPT teacher head0.329
Teacher spread0.283 · 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
Published2020
Admission routes2
Has abstractyes

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