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Record W2953676957 · doi:10.2217/cer-2019-0052

Cost–effectiveness of lenalidomide plus low-dose dexamethasone for newly diagnosed multiple myeloma patients ineligible for stem cell transplantation in China

2019· review· en· W2953676957 on OpenAlexaff
Jin Lu, Wendong Chen

Bibliographic record

VenueJournal of Comparative Effectiveness Research · 2019
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineMultiple myelomaLenalidomideCost effectivenessQuality-adjusted life yearTransplantationBortezomibDexamethasoneAutologous stem-cell transplantationChinaInternal medicineOncologyRisk analysis (engineering)

Abstract

fetched live from OpenAlex

Aim: To assess the cost–effectiveness of lenalidomide plus low dose dexamethasone (Rd) relative to bortezomib-contained therapy (BCT) for newly diagnosed multiple myeloma patients ineligible for stem cell transplantation (ndMM) in China. Materials & methods: A literature review was conducted to identify appropriate evidence for developing a cost–effectiveness model comparing Rd with BCT for lifetime health outcomes and direct medical costs in Chinese ndMM patients. Results: The estimated incremental cost–effectiveness ratio per gained quality-adjusted life years for Rd versus BCT was ¥49,793. The chance for Rd to be cost effective, under the cost–effectiveness thresholds of three-times the 2018 Chinese gross domestic goods per capita, was 90.8%. Conclusion: The cost–effectiveness of Rd relative to BCT for ndMM in Chinese patients is highly attractive.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.239
GPT teacher head0.490
Teacher spread0.251 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2019
Admission routes1
Has abstractyes

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