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Record W4417013131 · doi:10.1182/blood-2025-6268

Patterns of palliative care utilization across health sectors in patients with aggressive non-Hodgkin lymphoma.

2025· article· en· W4417013131 on OpenAlexaffabout
Joanne Britto, Ana Gayowsky, Hira Mian, Amaris Balitsky, Graeme Fraser, Gwynivere A Davies, Tom Kouroukis, Ronan Foley, Hsien Seow

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsMcMaster UniversityInstitute for Clinical Evaluative SciencesMcMaster University Medical Centre
Fundersnot available
KeywordsPalliative careRetrospective cohort studyCohortDiseaseCancerHealth careLymphomaAggressive lymphoma

Abstract

fetched live from OpenAlex

Abstract Introduction: Patients with aggressive non-Hodgkin lymphoma (NHL) experience high physical and psychological burden related to their disease and intensive treatment regimens especially with advances in treatment options for relapsed/refractory disease. Palliative care focuses on improving quality of life and controlling symptoms for patients with serious illness at any point during their disease trajectory. Data regarding the patterns of palliative care provision and utilization among patients with aggressive NHL is lacking. Methods: A retrospective cohort study was conducted using population-based health care data in Ontario, Canada. Patients aged 18 years or over who were diagnosed with diffuse large B-cell lymphoma (DLBCL) or transformed follicular lymphoma (tFL) and died between January 2007 and December 2023 were included. We abstracted patient and clinical characteristics and information on the patterns of palliative care services including the timing and setting of palliative encounters and types of services delivered. Results: The cohort included 7270 decedents; 6998 (96.2%) had DLBCL and 272 (3.74%) had tFL. The median age at death was 76 years (IQR 67-83). The mean survival from time of diagnosis to death was 3.38 years. Among 3660 patients with known cancer stage, 2443 (66.7%) presented with stage III or IV disease. 4553 patients (62.2%) had lived for 12 months or longer after their lymphoma diagnosis. Of the 7270 patients who died, 2301 (32%) received palliative care within the last 3 months of life. Over half of these patients (1208/2301; 52.5%) received palliative care within the last month of life. 27% of the entire cohort did not receive any palliative care service prior to death. Of the patients who received palliative care late (within 3 months of death), their first palliative care encounter occurred a median of 55 days before death (IQR 41-72) and largely through community-based palliative services (777/1093; 71%) either via outpatient physician visit or palliative home care services. The remainder 29% of patients received their first palliative care encounter in an institutional setting, most commonly an inpatient hospital admission. Of those who received palliative care early (> 3 months before death), their first palliative care encounter occurred a median of 268 days before death (IQR 159-510) and largely in a community setting (2531/2997; 84.5%). Conclusions: Our study demonstrates that palliative care is initiated very late in the disease trajectory for the majority of patients diagnosed with aggressive NHL, and a significant proportion of patients do not receive any specialty palliative care prior to death. The majority of patients receive their first palliative care encounter in the community as opposed to institutional settings. This suggests an opportunity for close collaboration between hematologists and primary palliative care teams to ensure timely and integrative palliative care for patients with aggressive lymphoma.

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)0.002
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 score0.419
Threshold uncertainty score0.833

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.266
Teacher spread0.248 · 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
Published2025
Admission routes2
Has abstractyes

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