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Record W3095664040 · doi:10.1182/blood-2020-141088

Comparison of Outcomes and Utilization of Therapy in Multiple Myeloma Patients in the USA and Alberta, Canada

2020· article· en· W3095664040 on OpenAlexaffabout
Andrew J. Cowan, Shasank Chennupati, Yuan Xu, Ang Li, David García, Edward N. Libby, Catherine R. Fedorenko, Scott D. Ramsey, Veena Shankaran, Winson Y. Cheung

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMedicineLenalidomideMultiple myelomaBortezomibInternal medicineComorbidityMalignancyPediatrics

Abstract

fetched live from OpenAlex

Background: Multiple myeloma (MM) is a common global hematologic malignancy, contributing to substantial morbidity and mortality amongst diagnosed patients. Novel agents - bortezomib (Btz) and lenalidomide (Len) have changed dramatically over the past 20 years and have contributed to improvements in survival and long term outcomes for MM patients. Research has shown that there are differences in how MM is treated globally. We sought to evaluate the differences in outcomes and therapies received amongst patients treated in Alberta (AB), Canada, and in the United States (USA). Methods: Adult patients with multiple myeloma over the age of 65, diagnosed between 2007 and 2013, were identified. Data sources used for AB was the CA National Ambulatory Care Reporting System (NACRS), Discharge Abstracts Database (DAD), and CT records from AB Health Services. For the USA we used the SEER-Medicare database; MM diagnosis was extracted using a previously published algorithm. We extracted demographic data, novel agent utilization in the first year, comorbidities, and survival. Kaplan-Meier analysis was used to determine survival. Results: Patients meeting study criteria included 4,330 MM patients in the USA and 793 patients with MM in AB. The median age at diagnosis in the USA and AB was 76.6 and 75 years, respectively. Median Charlson Comorbidity index in the USA and AB was 1, and 0, respectively. With respect to frontline therapies, both AB and USA had increasing utilization of Btz and Len from 2007-2013 (Figure), with Btz use more common in AB, while Len use was more common in the US. The proportion of all patients who did not receive any therapy in the first year of diagnosis fell dramatically from 2007 to 2013 in both AB (from 86% to 25%) and the USA (from 56% to 40%). Receipt of autologous stem cell transplant was uncommon in this older cohort, in only 3.2% of MM patients in AB and 4% of patients in the US. Similar proportions of patients in the USA and AB received radiotherapy in the first year (19% US, 25% AB). Median overall survival was improved in AB at 2.8 years, (95% CI 2.6-3.2 yrs), compared with the USA, 2.2 yrs (95% CI 2.1 - 2.30, as was 5 year survival - 30% in the USA, compared with 34% in AB. Conclusions: In this cross-country comparison of MM patients in the USA and AB both treated in a single-payer health care system - AB Health Services and Medicare - novel agents are a common treatment in the first year of diagnosis. We demonstrate similar uptake of novel agents Btz and Len over 2007-2013, however, Btz utilization was higher in AB from 2011-2013, while Len was more often used in the USA from 2011-2013. Median overall survival was better in AB (2.8 years) compared with USA (2.3 years), as was long term survival at 5 years. The differences in utilization of therapy and survival are possibly related to variability in healthcare delivery systems, burden of comorbidities in these populations, and approval of anti-MM therapy over time, and require further study to better understand reasons for differential outcomes. Figure Disclosures Cowan: Sanofi: Consultancy; Cellectar: Consultancy; Bristol Myers Squibb: Research Funding; Janssen: Consultancy, Research Funding; Abbvie: Research Funding. Ramsey:AstraZeneca: Other: Personal Fees.

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)0.003
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 score0.028
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.008
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.067
GPT teacher head0.328
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 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
Published2020
Admission routes2
Has abstractyes

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