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Record W3212852675 · doi:10.1177/20543581211057708

A Canadian Study of Cisplatin Metabolomics and Nephrotoxicity (ACCENT): A Clinical Research Protocol

2021· article· en· W3212852675 on OpenAlexafffundabout
Anshika Jain, Ryan S. Huang, Jasmine Lee, Natasha Jawa, Yong Jin Lim, Mike Guron, Sharon Abish, Paul C. Boutros, Michael Brudno, Bruce Carleton, Geoff D.E. Cuvelier, Lakshman Gunaratnam, Cheryl Ho, Khosrow Adeli, Sara Kuruvilla, Giles Lajoie, Geoffrey Liu, Paul C. Nathan, Shahrad R. Rassekh, Michael Rieder, Sushrut S. Waikar, Stephen Welch, Matthew A. Weir, Eric Winquist, David S. Wishart, Alexandra P. Zorzi, Tom Blydt‐Hansen, Michael Zappitelli, Bradley L. Urquhart

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2021
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced organ toxicity mitigation
Canadian institutionsChildren's Hospital of Western OntarioUniversity of AlbertaPrincess Margaret Cancer CentreUniversity of ManitobaUniversity Health NetworkCancerCare ManitobaOntario Institute for Cancer ResearchInstitute for Clinical Evaluative SciencesMcGill University Health CentreUniversity of TorontoMontreal Children's HospitalWestern UniversityBC Children's HospitalSickKids FoundationUniversity of British ColumbiaHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsMedicineNephrotoxicityCisplatinKidney diseaseCreatinineAcute kidney injuryInternal medicineNephrologyMetabolomicsBiomarkerCohortUrinary systemIntensive care medicineOncologyKidneyChemotherapyBioinformaticsBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Cisplatin, a chemotherapy used to treat solid tumors, causes acute kidney injury (AKI), a known risk factor for chronic kidney disease and mortality. AKI diagnosis relies on biomarkers which are only measurable after kidney damage has occurred and functional impairment is apparent; this prevents timely AKI diagnosis and treatment. Metabolomics seeks to identify metabolite patterns involved in cell tissue metabolism related to disease or patient factors. The A Canadian study of Cisplatin mEtabolomics and NephroToxicity (ACCENT) team was established to harness the power of metabolomics to identify novel biomarkers that predict risk and discriminate for presence of cisplatin nephrotoxicity, so that early intervention strategies to mitigate onset and severity of AKI can be implemented. OBJECTIVE: Describe the design and methods of the ACCENT study which aims to identify and validate metabolomic profiles in urine and serum associated with risk for cisplatin-mediated nephrotoxicity in children and adults. DESIGN: Observational prospective cohort study. SETTING: Six Canadian oncology centers (3 pediatric, 1 adult and 2 both). PATIENTS: Three hundred adults and 300 children planned to receive cisplatin therapy. MEASUREMENTS: During two cisplatin infusion cycles, serum and urine will be measured for creatinine and electrolytes to ascertain AKI. Many patient and disease variables will be collected prospectively at baseline and throughout therapy. Metabolomic analyses of serum and urine will be done using mass spectrometry. An untargeted metabolomics approach will be used to analyze serum and urine samples before and after cisplatin infusions to identify candidate biomarkers of cisplatin AKI. Candidate metabolites will be validated using an independent cohort. METHODS: Patients will be recruited before their first cycle of cisplatin. Blood and urine will be collected at specified time points before and after cisplatin during the first infusion and an infusion later during cancer treatment. The primary outcome is AKI, defined using a traditional serum creatinine-based definition and an electrolyte abnormality-based definition. Chart review 3 months after cisplatin therapy end will be conducted to document kidney health and survival. LIMITATIONS: It may not be possible to adjust for all measured and unmeasured confounders when evaluating prediction of AKI using metabolite profiles. Collection of data across multiple sites will be a challenge. CONCLUSIONS: ACCENT is the largest study of children and adults treated with cisplatin and aims to reimagine the current model for AKI diagnoses using metabolomics. The identification of biomarkers predicting and detecting AKI in children and adults treated with cisplatin can greatly inform future clinical investigations and practices.

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)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.024
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 integrity0.0000.001
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 head0.098
GPT teacher head0.444
Teacher spread0.347 · 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

Citations4
Published2021
Admission routes3
Has abstractyes

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