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Record W4396677006 · doi:10.1080/14796694.2024.2342227

Management of urothelial cancer in patients with chronic kidney disease receiving platinum-based chemotherapy

2024· review· en· W4396677006 on OpenAlexaff
Richard Thomas O'Dwyer, Di Maria Jiang, Abhijat Kitchlu, Antoine Morin Coulombe, Srikala S Sridhar

Bibliographic record

VenueFuture Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsToronto General HospitalUniversité LavalPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineCisplatinKidney diseaseUrothelial cancerChemotherapyIntensive care medicineInternal medicineOncologyCancerDiseaseRenal functionBladder cancerUrology

Abstract

fetched live from OpenAlex

Despite recent advances in the management of urothelial cancer (UC), cisplatin-based combination chemotherapy regimens remain critical. However, their use can be complicated in patients with chronic kidney disease (CKD), which is not uncommon in UC patients. Based on the Galsky criteria for cisplatin ineligibility, most patients with CKD will be excluded from receiving cisplatin-based chemotherapy altogether. For patients with borderline kidney function, several strategies - such as the use of split-dose cisplatin, dose reductions, or extra hydration - may facilitate the use of cisplatin, but these need to be prospectively validated. This review highlights the critical need for a multidisciplinary team, including onco-nephrologists, to help manage renal complications and optimize delivery of cancer care in complex UC patients with CKD.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.335
Teacher spread0.320 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes1
Has abstractyes

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