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PB1809 REAL‐WORLD HEALTHCARE RESOURCE UTILIZATION (HRU) AND COSTS OF PRIMARY MEDIASTINAL LARGE B‐CELL LYMPHOMA (PMBCL) PATIENTS INITIATED ON ANTI‐CANCER THERAPIES IN THE UNITED STATES (US)

2019· article· en· W2952759225 on OpenAlexaff
Xiaoqin Yang, François Laliberté, Guillaume Germain, Monika Raut, Mei Sheng Duh, Saugata Sen, Dominique Lejeune, Kaushal Desai, Philippe Armand

Bibliographic record

VenueHemaSphere · 2019
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsMedicineMedical diagnosisLymphomaCancerHealth careInternal medicineOncologyPathology

Abstract

fetched live from OpenAlex

Background: There is limited data describing HRU and treatment costs associated with PMBCL, a rare mature B‐cell neoplasm accounting for 2–4% of all non‐Hodgkin lymphoma. In October 2015, PMBCL administrative claims were differentiated from diffuse large B‐cell lymphoma (DLBCL) with the advent of ICD‐10‐CM disease‐specific codes in the US. In light of this new classification, a more reliable assessment of HRU and costs in patients with PMBCL could be performed. Aims: This study aimed to describe real‐world HRU and costs among patients diagnosed with PMBCL who initiated anti‐cancer therapies using a US claims database. Methods: A retrospective database analysis was conducted using the Optum Clinformatics TM Data Mart database (01/2013–03/2018). Patients who had a first encounter with an ICD‐10‐CM diagnosis for PMBCL (with or without an antecedent ICD‐10‐CM diagnosis of DLBCL/other lymphoma, which may have been assigned before PMBCL confirmation) after October 1 st , 2015 (index date for incident patients) were classified as (1) incident if they had no prior ICD‐9‐CM diagnosis for unspecified PMBCL or DLBCL, or as (2) prevalent if they had a prior ICD‐9‐CM diagnosis for unspecified PMBCL or DLBCL before October 2015 (index date for prevalent patients). Patients ≥18 years of age as of the index date with PMBCL diagnoses on ≥2 medical visits and ≥12 months of continuous enrollment pre‐index date (baseline period) were included. Patients with baseline diagnoses of Hodgkin or follicular lymphoma, or multiple myeloma, were excluded. All‐cause HRU (i.e., inpatient stays, outpatient [OP], emergency room, and other visits), and associated costs, including pharmacy costs, were calculated per patient per year (PPPY). HRU and costs were assessed from the start of the first line (1L) treatment up to the earliest of end of data availability or end of insurance coverage and reported for all treated patients and those treated with R‐CHOP (i.e., the most used 1L treatment). Results: Among 148 PMBCL patients (118 incident; 30 prevalent), median (IQR) age was 66 (42–77) years; ∼60% were female. Incident and prevalent patients had mean Charlson comorbidity index scores of 2.2 and 1.7, respectively. Mean ± SD total healthcare (medical plus pharmacy) costs for all incident PMBCL patients treated and those treated with R‐CHOP were $149,340 ± 117,757 and $129,881 ± 88,637 PPPY, respectively. Corresponding OP costs (including costs of administered therapies) were $90,329 ± 87,548 and $74,063 ± 63,099, and were the main cost driver of total healthcare costs. Mean (± SD) total healthcare costs for all treated prevalent patients ($92,799 ± 106,770) and those treated with R‐CHOP ($97,961 ± 125,702) were lower relative to incident patients; however, the follow‐up periods for prevalent patients (∼2.3 years) were approximately double that of incident patients. A sensitivity analysis restricting patients’ evaluation periods up to 12 months (mean follow‐up periods of 9 months for incident and 12 months for prevalent patients) showed more similar costs findings among incident and prevalent patients (mean ± SD total healthcare costs, all treated patients: $187,241 ± 104,938 and $167,553 ± 75,788, respectively) and highlighted higher costs of care over the first year. Similar trends were found for the associated HRU results (Table). Summary/Conclusion: Overall, this study highlighted the substantial economic burden of patients with PMBCL, particularly within the first year following the initiation of treatment. image

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

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

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 head0.032
GPT teacher head0.292
Teacher spread0.260 · 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.

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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Citations0
Published2019
Admission routes1
Has abstractyes

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