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Temporal changes in treatment exposures in the Childhood Cancer Survivor Study (CCSS).

2015· article· en· W2619344661 on OpenAlexaff
Ann C. Mertens, John Whitton, Joseph Philip Neglia, Daniel M. Green, Todd M. Gibson, Marilyn Stovall, Melissa M. Hudson, Leslie L. Robison, Gregory T. Armstrong, Yutaka Yasui, Wendy M. Leisenring

Bibliographic record

VenueJournal of Clinical Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineCohortSoft tissue sarcomaCancerPsychosocialSarcomaLogistic regressionInternal medicineCohort studyMedical recordPathology

Abstract

fetched live from OpenAlex

10074 Background: Well-designed epidemiologic investigations of pediatric cancer survivors inform clinical practice guidelines and future clinical trials. Expansion of the CCSS cohort to include survivors diagnosed across three decades (1970-99) affords the opportunity to evaluate associations between key temporal changes in survivor and treatment characteristics and risk for subsequent adverse health outcomes. Methods: We analyzed cancer and treatment characteristics of 24,000 CCSS participants. Treatment exposures were abstracted from medical records. Trends across 5 year intervals were evaluated using logistic regression models with weights to account for sampling probabilities. Results: Within the expanded CCSS, the use of chemotherapy significantly increased overall (Table, T1-T6) for all diagnoses except leukemia which was always 100%. Exposure to radiation (RT) decreased overall and for all diagnoses except soft tissue sarcoma. Overall, chest RT exposure was reduced and notably, exposures of ≥ 30 Gy declined from 85% to 6% (T1 to T6) for Hodgkin lymphoma. Alkylating agent use increased by 15% overall, and among leukemia, lymphoma and sarcoma patients proportions were on the order of 40% higher at T6 than at T1. Use of anthracyclines (ANT) increased significantly, predominantly for doses lower than 250 mg/m2. Conclusions: The expansion of the CCSS cohort provides a unique resource to evaluate the impact of historical changes in primary cancer therapy, including reduction of therapeutic intensity for low- and standard-risk populations, as well as intensification of specific therapies for high-risk populations on health and psychosocial outcomes. % With Characteristic T1 1970-74 T2 1975-79 T3 1980-84 T4 1985-89 T5 1990-94 T6 1995-99 Any RT* 79 75 64 50 40 34 RT to brain* 30 36 32 24 18 16 RT to neck* 24 19 16 9 7 7 RT to abdomen* 28 22 19 12 8 9 RT to chest ≥ 30 Gy* 21 13 8 4 1 1 Any Chemotherapy* 75 81 81 85 86 87 Any alkylating agents* 45 49 55 57 58 60 ANT 1-250 mg/m2* 3 12 18 34 45 52 ANT >250 mg/m2* 11 24 24 23 17 14 Any epipodophyllotoxins* 1 4 9 25 34 36 Platinum* <1 2 7 12 14 17 *Trend p-value <0.0001.

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)0.003
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 score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.326
GPT teacher head0.537
Teacher spread0.211 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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