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Record W3206304124 · doi:10.1007/s40273-021-01095-6

Systematic Literature Review to Assess Economic Evaluations in Spinal Muscular Atrophy (SMA)

2021· review· en· W3206304124 on OpenAlexaboutno aff
Noman Paracha, Pollyanna Hudson, Stephen Mitchell, C. Simone Sutherland

Bibliographic record

VenuePharmacoEconomics · 2021
Typereview
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsnot available
FundersF. Hoffmann-La RocheRoche
KeywordsMedicineSMA*Neuromuscular diseaseSystematic reviewEconomic evaluationMEDLINEPhysical medicine and rehabilitationCochrane LibraryReimbursementCost effectivenessEconLitQuality of life (healthcare)Spinal muscular atrophyPhysical therapyHealth careIntensive care medicineDiseaseRandomized controlled trialSurgeryPathologyRisk analysis (engineering)Nursing

Abstract

fetched live from OpenAlex

BACKGROUND: Spinal muscular atrophy (SMA) is a rare, progressive neuromuscular disease that affects individuals with a broad age range. SMA is typically characterised by symmetrical muscle weakness but is also associated with cardiac defects, life-limiting impairments in respiratory function and bulbar function defects that affect swallowing and speech. Despite the advent of three innovative disease-modifying therapies (DMTs) for SMA, the cost of DMTs in addition to the costs of standard of care can be a barrier to treatment access for patients. Health Technology Assessment (HTA) decision makers evaluate the cost effectiveness of a new treatment before making a reimbursement decision. OBJECTIVE: The primary objective was to conduct a systematic literature review (SLR) to identify the modelling approaches used in economic evaluations that assess current approved treatments in SMA, with a secondary objective to widen the scope and identify economic evaluations assessing other (non-SMA) neuromuscular disorders. METHODS: An SLR was performed to identify available economic evaluations associated with any type of SMA (Type 1, 2, 3 and/or 4). Economic evaluations associated with other (non-SMA) neuromuscular disorders were identified but not further analysed. Electronic searches were conducted in Embase, MEDLINE, Evidence-Based Medicine Reviews and EconLit via the Ovid platform in August 2019, and were supplemented by searches of the grey literature (reference lists, conference proceedings, global HTA body websites and other relevant sources). Eligibility criteria were based on the population, interventions, comparators and outcomes (PICO) framework. Quality assessment of full publications was conducted with reference to a published checklist. RESULTS: Nine publications covering eight unique studies met all eligibility criteria for inclusion in the SLR, including four conference abstracts, two peer-reviewed original research articles and three HTA submissions (conducted in Canada, the US and the UK). Evaluations considered patients with early infantile-onset (most likely to develop Type 1 or Type 2 SMA), later-onset SMA and both infantile- and later-onset SMA. Data for the identified economic models were collected from literature reviews and relatively short-term clinical trials. Several intent-to-treat clinical trial populations were used in the studies, which resulted in variation in cycle length and different outcome measures to determine clinical efficacy. The results of the quality assessment on the five full-text, peer-reviewed publications found that they generally provided clear descriptions of objectives, modelling methods and results. However, key decisions, such as choice of economic evaluation, model type and choice of variables for sensitivity analysis, were often not adequately justified. CONCLUSIONS: This SLR highlights the need for economic evaluations in SMA to better align in modelling approaches with respect to (i) consistency in model structure and use of motor function milestones as health states; (ii) consensus on measuring quality of life to estimate utilities; (iii) consistency in data collection by registries; and (iv) consensus on SMA-type classification and endpoints that determine intervention efficacy. Future economic evaluations should also incorporate the review group critiques of previous HTA submissions relating to data inputs and approaches to modelling and should include patient data reflective of the SMA population being modelled. Economic evaluations would also be improved with inclusion of long-term efficacy and safety data from clinical trials and valid patient and caregiver utility data.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.557
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.109
GPT teacher head0.497
Teacher spread0.387 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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