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Phase-specific costs of care in diffuse large B-cell lymphoma in Ontario, Canada.

2022· article· en· W4286297417 on OpenAlexaffabout
Judy Truong, Matthew C. Cheung, Soo Jin Seung, Christoffer Dharma, Stephanie Y. Cheng, Craig C. Earle, Simron Singh, Nicole Mittmann

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsInstitute for Clinical Evaluative SciencesSunnybrook Health Science CentreSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineCohortDiffuse large B-cell lymphomaCancer registryCancerHealth careLymphomaPediatricsEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

e18840 Background: This Canadian study analyzes real-world data to estimate phase-specific costs and health care resource utilization for patients with diffuse large B-cell lymphoma (DLBCL). Methods: A cohort of adult patients diagnosed with DLBCL were identified between 2003-2014 from the Ontario Cancer Registry (OCR) and linked to treatment data from Cancer Care Ontario and other provincial administrative health care databases. Health system costs and resource utilization were determined for four defined phases of care in which index date was defined as the OCR diagnosis date, including: pre-diagnosis (90 days prior to index date), initial treatment (index date to 6 months), follow-up (end of treatment phase to beginning of end-of-life or completion of cohort follow-up) and end-of-life (last 6 months of life for patients who died). Costs (Canadian dollars in 2014) and resource utilization were normalized to 30-days. Results: There were 5,392 individuals (53% males; median age 64 years (IQR 53-74)) diagnosed with DLBCL. The median follow-up was 1,903 days (IQR 1,194-2,882) from index date. At follow-up completion, 4,015 (74.5%) individuals were alive. Total mean 30-day cost was $1,175 (±2,267) in pre-diagnosis, $9,166 (±5,581) during initial treatment, $1,462 (±2,757) during follow-up, and $7,965 (±7,104) during end-of-life. The total 30-day cost for inpatient care was $3,864 (±5,013) during treatment (n = 3,362 hospitalized during treatment) and $5,045 (±5,908) for end-of-life (n = 1,367 hospitalized during end-of-life). For home care, the mean 30-day costs were $528 (±512) during initial treatment (n = 3,508, 65% of cohort) and $725 (±884) during end-of-life (n = 1,211, 23% of cohort). Mean 30-day cost of cancer medication was $80 (±455) in pre-diagnosis, $3,115 (±1,236) during initial treatment, $232 (±712) during follow-up, and $305 (±694) during end-of-life. A subset of 239 individuals had autologous stem cell transplantation (ASCT) for relapsed/refractory DLBCL. For the ASCT subgroup, the mean total 30-day cost was $11,653 (±4632) in pre-ASCT phase, $1,542 (±2961) in post-ASCT phase, and $14,094 (±12,845) in end-of-life phase for those that subsequently died (n = 118). A further subset of 52 individuals had relapsed and proceeded to third-line therapy. The total mean total 30-day cost was $8,288 (±8,943) in the first 6-month follow-up, $2,584 (±4,000) in the post 6-month follow-up, and $14,999 (±9,443) in end-of-life phase for those that died (n = 29). Conclusions: Total mean 30-day cost was highest in initial treatment phase and end-of-life phases following a U-shaped pattern. Inpatient care was the cost driver across all phases. Individuals who required ASCT had significantly increased costs. Home care was less frequently accessed during end-of-life phase compared to initial treatment phase (23% vs. 65%). These findings can help allocate appropriate resources throughout the different phases of cancer care.

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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)0.004
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 score0.920
Threshold uncertainty score0.582

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.070
GPT teacher head0.337
Teacher spread0.266 · 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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Citations1
Published2022
Admission routes2
Has abstractyes

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