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Chronic Kidney Disease or Hypertension After Childhood Cancer

2025· article· en· W4410484238 on OpenAlexafffundabout
Asaf Lebel, Rahul Chanchlani, Vedran Cockovski, Allison Dart, Adam Fleming, Amit X. Garg, Nivethika Jeyakumar, Kirby Kim, Abhijat Kitchlu, Eric McArthur, Danielle M. Nash, Paul C. Nathan, Rulan S. Parekh, Rachel Pearl, Jason D. Pole, Raveena Ramphal, Jennifer Reid, Tal Schechter‐Finkelstein, Lillian Sung, Ron Wald, Stella Wang, Peter Wong, Michael Zappitelli

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsWilliam Osler Health SystemSt. Michael's HospitalLawson Health Research InstituteChildren's Hospital of Eastern OntarioInstitute for Clinical Evaluative SciencesHospital for Sick ChildrenPediatric Oncology GroupUniversity of TorontoMcMaster Children's HospitalLondon Health Sciences CentreMcMaster UniversityUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMedicineKidney diseaseCohortCancerPopulationHazard ratioPediatric cancerInternal medicineCohort studyDiseasePediatricsConfidence intervalEnvironmental health

Abstract

fetched live from OpenAlex

Importance: Post-cancer therapy kidney outcomes, including chronic kidney disease (CKD) and hypertension, are common in childhood cancer survivors (CCS). The incidence and timing of CKD and hypertension in CCS compared with other at-risk or general populations are unclear. Objective: To determine the association of childhood cancer treatment with post-cancer therapy CKD or hypertension. Design, Setting, and Participants: Population-based matched cohort study of children treated for cancer between April 1993 and March 2020 in Ontario, Canada, with follow-up until March 2021. The CCS (exposed) cohort included children (≤18 years) surviving cancer. Comparator cohorts were a hospitalization cohort (children who were hospitalized) and a general pediatric population (GP) cohort (all other Ontario children). Exclusion criteria were history of previous cancer, organ transplant, CKD, dialysis, or hypertension. Matching with each of the 2 comparator cohorts was performed separately and in a 1:4 ratio by age, sex, rural vs urban status, income quintile, index year, and presence of previous hospitalization. Data were analyzed from March 2021 to August 2024. Exposure: Treatment for cancer. Main Outcomes and Measures: The primary outcome was the composite of CKD or hypertension, defined by administrative health care diagnosis and procedure codes. Fine and Gray subdistribution hazard modeling, accounting for competing risks (death and new cancer diagnosis or relapse) and adjusting for cardiac disease, liver disease, and diabetes, was used to determine the association of cancer treatment with outcomes. Results: There were 10 182 CCS (median [IQR] age at diagnosis, 7 [3-13] years; 5529 male [54.3%]; median [IQR] follow-up time, 8 [2-15] years) matched to 40 728 hospitalization cohort patients (median [IQR] age at diagnosis, 7 [2-12] years; 5529 male [weighted percentage, 54.3%]; median [IQR] follow-up time, 11 [6-18] years) and 8849 CCS (median [IQR] age at diagnosis, 5 [2-11] years; 4825 male [54.5%]; median [IQR] follow-up time, 7 [2-14] years) matched to 35 307 GP cohort individuals (median [IQR] age at diagnosis, 6 [2-11] years; 4825 male [weighted percentage, 54.5%]; median [IQR] follow-up time, 10 [5-16] years). Most frequent cancer types were leukemia (2948 patients [29.0%]), central nervous system neoplasms (2123 patients [20.9%]), and lymphoma (1583 patients [15.5%]). During observation, cumulative incidence of CKD or hypertension was 20.85% (95% CI, 18.75%-23.02%) in the CCS cohort vs 16.47% (95% CI, 15.21%-17.77%) in the hospitalization cohort and 19.24% (95% CI, 15.99%-22.73%) in the CCS cohort vs 8.05% (95% CI, 6.76%-9.49%) in the GP cohort. CCS were at increased risk of CKD or hypertension compared with the hospitalization cohort (adjusted hazard ratio, 2.00; 95% CI, 1.86-2.14; P < .001) and the GP cohort (adjusted hazard ratio, 4.71; 95% CI, 4.27-5.19; P < .001). Conclusions and Relevance: In this population-based study, CCS were at increased risk for CKD and hypertension, which are associated with mortality, suggesting that early detection and treatment of these conditions in CCS may decrease late complications and mortality.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.323
Teacher spread0.299 · 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 designNot applicable
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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Citations3
Published2025
Admission routes3
Has abstractyes

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