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Record W4401010505 · doi:10.1007/s40273-024-01413-8

Systematic Review of Economic Evaluations of Systemic Treatments for Advanced and Metastatic Gastric Cancer

2024· review· en· W4401010505 on OpenAlexaff
Shikha Sharma, Niamh Carey, David J. McConnell, Maeve A. Lowery, Jacintha O’Sullivan, Laura McCullagh

Bibliographic record

VenuePharmacoEconomics · 2024
Typereview
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsTrinity College
FundersEnterprise Ireland
KeywordsQuality of Life ResearchHealth economicsMedicineCancerPharmacoeconomicsIntensive care medicineHealth administrationPublic healthInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Recent advances in the development of biomarker-directed therapy and immunotherapy, for advanced and metastatic gastric cancers, have the potential to improve survival and quality of life. Much attention has been directed towards second- and later-line treatments, and the landscape here is evolving rapidly. However, uncertainty in relative effectiveness, high costs and uncertainty in cost effectiveness represent challenges for decision makers. OBJECTIVE: To identify economic evaluations for the second-line or later-line treatment of advanced and metastatic gastric cancer. Also, to assess key criteria (including model assumptions, inputs and outcomes), reporting completeness and methodological quality to inform future cost-effectiveness evaluations. METHODS: A systematic literature search (from database inception to 5 March 2023) of EconLit via EBSCOhost, Cochrane Library (restricted to National Health Service [NHS] Economic Evaluation Database and Health Technology Assessment [HTA] Database), Embase, MEDLINE and of grey literature was conducted. This aimed to identify systemic treatments that align with National Comprehensive Cancer Network (NCCN) and European Society for Medical Oncology (ESMO) Clinical Practice Guidelines. Data were collected on key criteria and on reporting completeness and methodological quality. A narrative synthesis focussed on cost-effectiveness and cost-of-illness studies. Outcomes of interest included total and incremental costs and outcomes (life-years and quality-adjusted life-years), ratios of incremental costs per unit outcome and other summary cost and outcome measures. Also, for cost-effectiveness studies, reporting completeness and the methodological quality were assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) and the Philips Checklist, respectively. RESULTS: A total of 19 eligible economic evaluations were identified (cost-effectiveness studies [n = 15] and cost-of-illness studies [n = 4]). There was a general lack of consistency in the methodological approaches taken across studies. In the main, the cost-effectiveness studies indicated that the intervention under consideration was more effective and more costly than the comparator(s). However, most interventions were not cost effective. No studies were fully compliant with reporting-completeness and methodological-quality requirements. Given the lack of consistency in the approaches taken across cost-of-illness studies, outcomes could not be directly compared. CONCLUSIONS: To our knowledge, this is the first published systematic literature review that has qualitatively synthesised economic evaluations for advanced and metastatic gastric cancer. There were differences in the approaches taken across the cost-effectiveness studies and the cost-of-illness studies. The conclusions of most of the cost-effectiveness studies were consistent despite identified differences in approaches. In the main, the interventions under consideration were not cost effective, presenting challenges to sustainability and affordability. We highlight a requirement for cost-effectiveness evaluations and for second-line or later-line treatments of advanced and metastatic gastric cancer that consider all relevant comparators and that are compliant with reporting-completeness and methodological-quality requirements. By addressing the methodological gaps identified here, future healthcare decision-making, within the context of this rapidly changing treatment landscape, would be better informed. PROSPERO REGISTRATION NUMBER: CRD42023405951.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.168
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.079
GPT teacher head0.469
Teacher spread0.391 · 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.

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

Citations8
Published2024
Admission routes1
Has abstractyes

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