MétaCan
Menu
Back to cohort

The Association of Antibiotic (ATB) exposure prior to immune checkpoint inhibitor (ICI) treatment on early emergency room and hospitalization utilization: A population-based study.

2021· article· en· W3200258717 on OpenAlexaffabout
Lawson Eng, Rinku Sutradhar, Yue Niu, Ning Liu, Ying Liu, Yosuf Kaliwal, Melanie Powis, Geoffrey Liu, Jeffrey Peppercorn, Philippe L. Bédard, Monika K. Krzyzanowska

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsInstitute for Clinical Evaluative SciencesPrincess Margaret Cancer Centre
FundersConquer Cancer Foundation
KeywordsMedicineInternal medicineCohortPopulationCancerRetrospective cohort studyPembrolizumabMedical prescriptionHazard ratioEmergency medicineImmunotherapy

Abstract

fetched live from OpenAlex

304 Background: ICIs are becoming a common therapeutic option for many solid tumors. Prior studies have shown that ATB exposure can negatively impact ICI outcomes through gut microbiome changes leading to poorer overall survival; however, less is known about the potential impact of ATB exposure on toxicities from ICI. We undertook a population-based retrospective cohort study in patients receiving ICIs to evaluate the impact of ATB exposure on early acute care use, defined as emergency department visit or hospitalization, within 30 days of initiation of ICI therapy. Methods: Administrative data was utilized to identify a cohort of cancer patients > 65 years of age receiving ICIs from June 2012 to October 2018 in Ontario, Canada. We linked databases deterministically to obtain socio-demographic and clinical co-variates, ATB prescription claims and acute care utilization. Patients were censored if they died within 30 days of initiating ICI therapy. The impact of ATB exposure within 60 days prior to starting ICI on early acute care use was evaluated using multi-variable logistic regression models, adjusted for age, gender, rurality, recent hospitalization within 60 days prior to starting ICI and comorbidity score. Results: Among 2737 patients (median age 73 years), 43% received Nivolumab, 41% Pembrolizumab and 13% Ipilimumab, most commonly for lung cancer (53%) or melanoma (34%). Of these patients, 19% had ATB within 60 days prior to ICI with a median ATB treatment duration of 9 days (SD = 13). 647 (25%) patients had an acute care episode within 30 days of starting ICIs; 182 (7%) patients passed away within 30 days without acute care use and were censored from further analyses. Any ATB exposure within 60 days prior to ICI was associated with greater likelihood of acute care use (aOR = 1.34 95% CI [1.07-1.67] p = 0.01). A dose effect was seen based on weeks of ATB exposure within 60 days prior to ICI (aOR = 1.12 per week [1.04-1.21] p = 0.004) and early acute care use. ATB class analysis identified that exposure to penicillins (aOR = 1.54 [1.11-2.15] p = 0.01) and fluoroquinolones (aOR = 1.55 [1.11-2.17] p = 0.01) within 60 days of starting ICIs were associated with a greater likelihood of acute care use, while there was no significant association between cephalosporin exposure and early acute care use (p > 0.05). Conclusions: Exposure to ATBs, specifically fluoroquinolones and penicillins, prior to ICI therapy is associated with greater likelihood of hospitalization or emergency room visits within 30 days after initiation of ICIs, even after adjustment for relevant co-variates including age, comorbidity score and recent hospitalization prior to ICI initiation. Further studies are required to better understand the mechanisms of recent ATB exposure on early acute care use among patients receiving ICIs.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.305
Threshold uncertainty score0.606

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.076
GPT teacher head0.426
Teacher spread0.350 · 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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicNeutropenia and Cancer InfectionsFrench-language works237,207