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Record W3210814554 · doi:10.1158/1055-9965.epi-21-0667

Impact of Risk-Stratified Therapy on Health Status in Survivors of Childhood Acute Lymphoblastic Leukemia: A Report from the Childhood Cancer Survivor Study

2021· article· en· W3210814554 on OpenAlexaff
Stephanie B. Dixon, Yan Chen, Yutaka Yasui, Ching‐Hon Pui, Stephen P. Hunger, Lewis B. Silverman, Kirsten K. Ness, Daniel M. Green, Rebecca M. Howell, Wendy M. Leisenring, Nina S. Kadan‐Lottick, Kevin R. Krull, Kevin C. Oeffinger, Joseph P. Neglia, Melissa M. Hudson, Leslie L. Robison, Ann C. Mertens, Gregory T. Armstrong, Paul C. Nathan

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2021
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHospital for Sick ChildrenUniversity of Alberta
FundersNational Center for Advancing Translational SciencesNational Cancer Institute
KeywordsMedicineConfidence intervalSiblingPediatricsInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Prior studies have identified that survivors of childhood acute lymphoblastic leukemia (ALL) report poor health status. It is unknown how risk-stratified therapy impacts the health status of ALL survivors. Methods: We estimated and compared the prevalence of self-reported poor health status among adult (≥18 years) survivors of childhood ALL diagnosed at age <21 years from 1970 to 1999 and sibling controls, excluding proxy reports. Therapy combinations defined treatment groups representative of 1970s therapy (70s), standard- and high-risk 1980s and 1990s therapy (80sSR, 80sHR, 90sSR, 90sHR), and relapse/bone marrow transplant (R/BMT). Log-binomial models, adjusted for clinical and demographic factors, compared outcomes between groups using prevalence ratios (PR) with 95% confidence intervals (CI). Results: Among 5,119 survivors and 4,693 siblings, survivors were more likely to report poor health status in each domain including poor general health (13.5% vs. 7.4%; PR = 1.92; 95% CI, 1.69–2.19). Compared with 70s, 90sSR and 90sHR were less likely to report poor general health (90sSR: PR = 0.75; 95% CI, 0.57–0.98; 90sHR: PR = 0.58; 95% CI, 0.39–0.87), functional impairment (90sSR: PR = 0.56; 95% CI, 0.42–0.76; 90sHR: PR = 0.63; 95% CI, 0.42–0.95), and activity limitations (90sSR: 0.61; 95% CI, 0.45–0.83; 90sHR: PR = 0.59; 95% CI, 0.38–0.91). An added adjustment for chronic conditions in multivariable models partially attenuated 90sSR risk estimates. Conclusions: Risk-stratified ALL therapy has succeeded in reducing risk for poor general health, functional impairment, and activity limitations among more recent survivors of standard- and high-risk therapy. Impact: Future research into the relationship between risk-stratified therapy, health status, and late health outcomes may provide new opportunities to further improve late morbidity among survivors.

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)0.004
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.053
GPT teacher head0.408
Teacher spread0.354 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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