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Factors associated with acute kidney injury among patients with cancer treated with immune checkpoint inhibitor therapy: A population-based study.

2022· article· en· W4286295746 on OpenAlexaffabout
Phillip Blanchette, Lucie Richard, Salimah Z. Shariff, Jacques Raphael, Craig C. Earle, Amit X. Garg, Abhijat Kitchlu

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversity Health NetworkUniversity of TorontoLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineAcute kidney injuryInternal medicineInterquartile rangeKidney diseaseNephrologyCancerRenal replacement therapyDialysisPopulationAdverse effectCreatinineOncology

Abstract

fetched live from OpenAlex

2584 Background: Cancer immune checkpoint inhibitor (ICI) therapy may be associated with kidney immune-related adverse events (IRAEs) and other causes of acute kidney injury (AKI). In clinical trials, the frequency of AKI events was uncommon, however, further real-world study is warranted. Methods: We evaluated the proportion of AKI events among patients with advanced cancer (bladder, head and neck, lung, kidney and malignant melanoma) treated with ICI therapy in Ontario, Canada from 2012 - 2018. AKI was defined by a rise in the concentration of serum creatinine as per Kidney Disease: Improving Global Outcomes (KDIGO) criteria. A multivariable regression model was used to identify predictors of AKI while accounting for the competing risk of death. Results: A total of 4,380 patients received ICI therapy. In follow-up, 1,283 (29%) had recorded AKI event (any stage AKI) and 289 (7%) had a severe AKI event (≥ stage 2). Median time to AKI was 6 months (Interquartile Range 2-16 months) and ≤ 1 % of patients received dialysis therapy. Within 30 days of any observed AKI event, 853 (58%) discontinued ICI therapy, 372 (29%) were hospitalized and 266 (21%) died. Mortality was significantly higher among patients who experiencing a severe AKI event (≥ stage 2) as compared to patients with a less severe AKI event (stage 1) or no observed AKI event. Among patients alive at 30 days following an AKI event, 14% received an outpatient corticosteroid or immunosuppressive therapy prescription, 7% had a visit with a nephrologist. Characteristics associated with a higher risk of AKI included female sex, bladder or kidney cancer (reference malignant melanoma), history of hypertension or diabetes, higher Charlson comorbidity score, a baseline estimated glomerular filtration rate less than 30 mL/min/1.73 m2, or outpatient prescription for either a proton pump inhibitor or non-steroidal anti-inflammatory drug. Among patients with an AKI event and treatment discontinuation, re-challenge of ICI therapy was infrequent (16%) with a significant risk of a recurrent AKI event (57%). Conclusions: In a population-based study among patients with cancer receiving ICI therapy, the rate of AKI was common (29%) but severe AKI was less frequent (7%). Rates of ICI discontinuation, hospitalization and death are substantial following an AKI event. Kidney function should be monitored carefully among patients undergoing ICI therapy who have common risk factors for developing renal disease. Nephrology consultation may be optimized among patients who develop a severe AKI event, especially among individuals who are considered for ICI therapy re-challenge.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.179
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.059
GPT teacher head0.389
Teacher spread0.330 · 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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