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Record W2588909661 · doi:10.1177/2054358117690338

Design and Methods of the Pan-Canadian Applying Biomarkers to Minimize Long-Term Effects of Childhood/Adolescent Cancer Treatment (ABLE) Nephrotoxicity Study

2017· article· en· W2588909661 on OpenAlexafffundabout
Kelly R. McMahon, Shahrad R. Rassekh, Kirk R. Schultz, Maury Pinsk, Tom Blydt‐Hansen, Cherry Mammen, Ross T. Tsuyuki, Prasad Devarajan, Geoff D.E. Cuvelier, Lesley Mitchell, Sylvain Baruchel, Ana Palijan, Bruce Carleton, Colin J.D. Ross, Michael Zappitelli

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2017
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced organ toxicity mitigation
Canadian institutionsChild and Family Research InstituteUniversity of AlbertaHospital for Sick ChildrenStollery Children's HospitalUniversity of British ColumbiaMcGill University Health CentreCancerCare ManitobaBC Children's HospitalUniversity of ManitobaMontreal Children's Hospital
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesUniversity of British Columbia
KeywordsMedicineRenal functionKidney diseaseAcute kidney injuryInternal medicineNephrotoxicityCancerNephrologyMicroalbuminuriaIntensive care medicineUrologyKidney

Abstract

fetched live from OpenAlex

Background: Childhood cancer survivors experience adverse drug events leading to lifelong health issues. The Applying Biomarkers to Minimize Long-Term Effects of Childhood/Adolescent Cancer Treatment (ABLE) team was established to validate and apply biomarkers of cancer treatment effects, with a goal of identifying children at high risk of developing cancer treatment complications associated with thrombosis, graft-versus-host disease, hearing loss, and kidney damage. Cisplatin is a chemotherapy well known to cause acute and chronic nephrotoxicity. Data on biomarkers of acute kidney injury (AKI) and late renal outcomes in children treated with cisplatin are limited. Objective: To describe the design and methods of the pan-Canadian ABLE Nephrotoxicity study, which aims to evaluate urine biomarkers (neutrophil gelatinase–associated lipocalin [NGAL] and kidney injury molecule-1 [KIM-1]) for AKI diagnosis, and determine whether they predict risk of long-term renal outcomes (chronic kidney disease [CKD], hypertension). Design: This is a 3-year observational prospective cohort study. Setting: The study includes 12 Canadian pediatric oncology centers. Patients: The target recruitment goal is 150 patients aged less than 18 years receiving cisplatin. Exclusion criteria: Patients with an estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m 2 or a pre-existing renal transplantation at baseline. Measurements: Serum creatinine (SCr), urine NGAL, and KIM-1 are measured during cisplatin infusion episodes (pre-infusion, immediate post-infusion, discharge sampling). At follow-up visits, eGFR, microalbuminuria, and blood pressure are measured and outcomes are collected. Methods: Outcomes: AKI is defined as per SCr criteria of the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. CKD is defined as eGFR <90 mL/min/1.73m2 or albumin-to-creatinine ratio≥3mg/mmol. Hypertension is defined as per guidelines. Procedure: Patients are recruited before their first or second cisplatin cycle. Participants are evaluated during 2 cisplatin infusion episodes (AKI biomarker validation) and at 3, 12, and 36 months post-cisplatin treatment (late outcomes). Limitations: The study has a relatively moderate sample size and short follow-up duration. There is potential for variability in data collection since multiple sites are involved. Conclusions: ABLE will provide a national platform to study biomarkers of late cancer treatment complications. The Nephrotoxicity study is a novel study of AKI biomarkers in children treated with cisplatin that will greatly inform on late cisplatin renal outcomes and follow-up needs.

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)0.000
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.095
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.030
GPT teacher head0.351
Teacher spread0.321 · 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.

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

Citations18
Published2017
Admission routes3
Has abstractyes

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