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Record W2949104201 · doi:10.1186/s13643-019-1047-z

Immunotherapy with check-point inhibitors (CPI) in adult malignancies: a protocol for the systematic review of the quality of economic analyses

2019· article· en· W2949104201 on OpenAlexafffund
Ying Wang, Pierre Camateros, Denise Smith, David E. Dawe, Peter Ellis

Bibliographic record

VenueSystematic Reviews · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsJuravinski Cancer CentreMcMaster UniversityCancerCare ManitobaUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsMedicineProtocol (science)ImmunotherapyQuality (philosophy)Intensive care medicineAlternative medicineInternal medicineCancerPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Immuno-oncology, and in particular, check-point inhibitors (CPIs), have led to a paradigm shift in the field of cancer care. The cost of new drug development is high, and many novel agents in oncology are significantly more expensive than older agents. Therefore, healthcare funders have factored measures of cost-effectiveness into decisions concerning drug reimbursement and incorporation of new agents into treatment algorithms. The methodology of cost-effectiveness evaluations, however, is less rigorously applied than those evaluating clinical efficacy and safety data. Thus, in spite of many regulatory bodies having approved CPIs based on existing economic analyses, to date, there has not been a systematic evaluation of the quality of health economic studies conducted on this new class of agents. Therefore, we propose to systematically review the methodologic and reporting quality of cost-effectiveness and cost-utility studies assessing CPIs to alternate established therapies, other immuno-oncology regimens, or placebo, in adults with malignancies. METHODS/DESIGN: The systematic review will include all published economic evaluations of CPIs compared with at least one other treatment in adult patients with solid or hematologic malignancies. A search will be performed to identify relevant studies in Ovid MEDLINE, EMBASE, Cost-effectiveness Analysis Registry, Evidence-Based Medicine Reviews, and the NIHR-HTA database. The titles and abstracts of all identified studies will be independently reviewed by two reviewers, who will then assess the full text of all articles deemed to meet eligibility criteria. Assessed articles will be screened for compliance with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) criteria. The association, with CHEERS criteria, of the journal impact factor, publication year, funding source, tumor site, trial or model-based study, and CPIs studied, will then be assessed. DISCUSSION: The systematic review will aim to provide an overview of the quality of economic analyses evaluating CPIs for the treatment of malignancies in adult patients. Any systemic or recurrent deficiencies in methodological or reporting quality will be described and used to inform recommendations for improved reporting of economic analyses. SYSTEMATIC REVIEW REGISTRATION: This review will not be registered with PROSPERO, it does not meet the eligibility criterion of addressing an outcome of the direct patient or clinical relevance.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearch
Domain: Evaluation · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.054
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
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 head0.078
GPT teacher head0.410
Teacher spread0.332 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
DomainEvaluation
GenreProtocol

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

Citations1
Published2019
Admission routes2
Has abstractyes

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