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Record W2579765256 · doi:10.1038/bjc.2016.443

Evaluation of treatment-related mortality among paediatric cancer deaths: a population based analysis

2017· article· en· W2579765256 on OpenAlexafffundabout
Jason D. Pole, Paul Gibson, Marie‐Chantal Ethier, Tanya Lazor, Donna L. Johnston, Carol Portwine, Mariana Silva, Sarah Alexander, Lillian Sung

Bibliographic record

VenueBritish Journal of Cancer · 2017
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsKingston General HospitalChildren's Hospital of Eastern OntarioInstitute for Clinical Evaluative SciencesPediatric Oncology GroupSickKids FoundationHospital for Sick ChildrenMcMaster Children's HospitalLondon Health Sciences Centre
FundersNational Cancer InstitutePediatric Oncology Group of Ontario
KeywordsMedicineCancerPediatricsPopulationCancer registryCohortMortality rateInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Objectives were to describe the proportion of deaths due to treatment-related mortality (TRM) and to identify risk factors and probable causes of TRM among paediatric cancer deaths in a population-based cohort. METHODS: We included children with cancer ⩽18 years diagnosed and treated in Ontario who died between January 2003 and December 2012. Deaths were identified using a provincial registry, the Pediatric Oncology Group of Ontario Networked Information System. Probable causes of TRM were described. RESULTS: Among the 964 deaths identified, 821 were included. The median age at diagnosis was 6.6 years (range 0-18.8) and 51.8% had at least one relapse. Of the deaths examined, TRM occurred in 217/821 (26.4%) while 604/821 (73.6%) were due to progressive cancer. Deaths from TRM did not change over time. Using multiple regression, younger age, leukaemia diagnosis and absence of relapse were independently positively associated with TRM. The most common probable causes of TRM were respiratory, infection and haemorrhage. CONCLUSIONS: TRM was responsible for 26.4% of deaths in paediatric cancer. Underlying diagnosis, younger age and absence of relapse were associated with TRM and causes of TRM differed by diagnosis group. Future work should evaluate TRM rate and risk factors among newly diagnosed cancer patients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.045
GPT teacher head0.393
Teacher spread0.348 · 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 teacher head, not a consensus.

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
Published2017
Admission routes3
Has abstractyes

Explore more

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