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Impact of center case volume on cardiotoxicity during adjuvant trastuzumab in breast cancer.

2013· article· en· W2602619722 on OpenAlexaffabout
Nicolas Chin‐Yee, Andrew T. Yan, George Tomlinson, Craig C. Earle, Maureen Trudeau, Murray Krahn, Dennis T. Ko, Monika K. Krzyzanowska, Raveen Pal, Christine B. Brezden, Kelvin Chan

Bibliographic record

VenueJournal of Clinical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsKingston General HospitalPrincess Margaret Cancer CentreSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesUniversity of TorontoUniversity Health NetworkSt. Michael's Hospital
Fundersnot available
KeywordsMedicineCardiotoxicityTrastuzumabInternal medicineBreast cancerHeart failureCohortDiscontinuationCancerOncologyCardiologyChemotherapy

Abstract

fetched live from OpenAlex

6625 Background: A recent study suggested that cardiotoxicity from trastuzumab (T) was associated with regional variation and insufficient cardiac monitoring (Ng et al.SABCS 2012). Few studies have examined the impact of centre or physician (MD) case volume (vol) on outcomes in systemic therapy. Methods: All breast cancer patients who were diagnosed in 2003-2009 in Ontario and treated with adjuvant T were identified through a provincial drug funding program, and linked to administrative databases to ascertain patient demographics, hospitalizations, cardiac risk factors, cardiac imaging, comorbidities, and treating centre and MD. For each year, we calculated case vol as the number of patients treated with adjuvant T by each MD and by each centre. Cardiotoxicity was defined as receiving less than 16 out of 18 doses of T because of heart failure (HF) admission, HF diagnosis by physician claims, or discontinuation after cardiac imaging. Insufficient cardiac monitoring was defined as per recent guideline and per Ng et al. Logistic regression and mixed models were constructed to examine factors associated with cardiotoxicity. Results: Our cohort consisted of 3,777 patients, 214 MDs and 68 centres. For patients, 16.5% were over age 65; 30.3%, 9.4%, and 1.2% had previous diagnoses of hypertension, diabetes, and HF, respectively; 16.9% had cardiotoxicity. Univariate analyses found that high centre vol, but not MD vol, was associated with lower cardiotoxicity. Cardiotoxicity rates by centre vol quintiles (Q) were 23.4% (Q1-3), 18.2% (Q4), and 15.2% (Q5). Multivariable analyses found that lower cardiotoxicity was associated with higher centre vol (OR=0.85 per Q, p=0.02) and diagnosis in recent years (2008-2009 vs. before 2008; OR=0.50, p<0.001), after adjusting for age, previous HF, comorbidities, regional variation, and cardiac monitoring. Accounting for clustering within centres, there remained a strong trend of lower cardiotoxicity with higher centre vol (OR=0.77 per Q, p=0.06) and recent diagnosis (OR=0.50, p<0.001). Conclusions: Our findings suggest a reduction in cardiotoxicity with experience and over time, and support the notion of centralization of systemic therapy in high vol centres to optimize outcomes.

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)0.002
metaresearch head score (Gemma)0.014
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.062
GPT teacher head0.445
Teacher spread0.384 · 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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Citations2
Published2013
Admission routes2
Has abstractyes

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