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1.
Value Health ; 23(11): 1423-1426, 2020 11.
Artículo en Inglés | MEDLINE | ID: mdl-33127011

RESUMEN

It is expected that the coronavirus disease 2019 (COVID-19) pandemic will leave large deficits in the budgets of many jurisdictions. Funding for other treatments, in particular new treatments, may become more constrained than previously expected. Therefore, a robust health technology assessment (HTA) system is vital. Many clinical trials carried out during the pandemic may have been temporarily halted, while others may have had to change their protocols. Even trials that continue as normal may experience external changes as other aspects of the healthcare service may not be available to the patients in the trial, or the patients themselves may contract COVID-19. Consequently, many limitations are likely to arise in the provision of robust HTAs, which could have profound consequences on the availability of new treatments. Therefore, the National Centre for Pharmacoeconomics Review Group wishes to discuss these issues and make recommendations for applicants submitting to HTA agencies, in ample time for these HTAs to be prepared and assessed. We discuss how the pandemic may affect the estimation of the treatment effect, costs, life-years, utilities, discontinuation rates, and methods of evidence synthesis and extrapolation. In particular, we note that trials conducted during the pandemic will be subject to a higher degree of uncertainty than before. It is vital that applicants clearly identify any parameters that may be affected by the pandemic. These parameters will require considerably more scenario and sensitivity analyses to account for this increase in uncertainty.


Asunto(s)
Comités Consultivos , Infecciones por Coronavirus , Pandemias , Neumonía Viral , Evaluación de la Tecnología Biomédica , Betacoronavirus , Presupuestos , Infecciones por Coronavirus/tratamiento farmacológico , Economía Farmacéutica , Humanos , Neumonía Viral/tratamiento farmacológico , Calidad de Vida , Resultado del Tratamiento , Privación de Tratamiento
2.
Eur J Prev Cardiol ; 27(3): 247-255, 2020 02.
Artículo en Inglés | MEDLINE | ID: mdl-31615283

RESUMEN

AIMS: This analysis aims to estimate the comparative efficacy of anti-hypertensive medications and exercise interventions on systolic and diastolic blood pressure reduction in people with hypertension. METHODS: A systematic review was conducted focusing on randomised controlled trials (RCTs) of exercise interventions and first-line anti-hypertensives where blood pressure reduction was the primary outcome in those with hypertension. Network meta-analyses were conducted to generate estimates of comparative efficacy. RESULTS: We identified 93 RCTs (N = 32,404, mean age in RCTs: 39-70 years) which compared placebo or usual care with first-line antihypertensives including angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, calcium channel blockers and thiazide-like diuretics and exercise interventions including aerobic training and dynamic resistance training. Of these, there were 81 (87%) trials related to medications (n = 31,347, 97%) and 12 (13%) trials related to exercise (n = 1057, 3%). The point estimates suggested that antihypertensive medications were more effective than exercise but there was insufficient evidence to suggest that first-line medications significantly reduced blood pressure to a greater extent than did the exercise interventions. Of the first-line treatments, angiotensin receptor blockers and calcium channel blockers had the highest treatment ranking, while exercise had the second lowest treatment ranking, followed by control conditions. CONCLUSION: The current evidence base with a bias towards medication research may partly explain the circumspection around the efficacy of exercise in guidelines and practice. Clinicians may justifiably consider exercise for low risk hypertension patients who confirm a preference for such an approach.

3.
Res Synth Methods ; 10(4): 546-568, 2019 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-31368653

RESUMEN

If IPD is available for some or all trials in a network meta-analysis (NMA), then incorporating this IPD into an NMA is routinely considered to be preferable. However, the situation often arises where a researcher has IPD for trials concerning a particular treatment (eg, from a sponsor) but none for other trials. Therefore, one can reweight the IPD so that the covariate characteristics in the IPD trials match that of the aggregate data (AgD) trials, using a matching-adjusted indirect comparison (MAIC). We assess the impact of using the reweighted aggregated data, obtained by the MAIC, in a Bayesian NMA for a connected treatment network. We apply this method to a network of multiple myeloma treatments in newly diagnosed patients (ndMM), where the outcome is progression free survival. We investigate the reliability of the methods and results through a simulation study. The ndMM network consists of three IPD studies comparing lenalidomide to placebo (Len-Placebo), one AgD study comparing Len-Placebo, and one AgD study comparing thalidomide to placebo (Thal-Placebo). We therefore investigate two options of weighting the covariates: (a) All three studies are weighted separately to match the AgD Thal-Placebo trial. (b) Patients are weighted across all three IPD studies to match the AgD Thal-Placebo trial, but the NMA considers each trial separately. We observe limited benefit to MAIC in the full network population. While MAIC can be beneficial as a sensitivity analysis to confirm results across patient populations, we advise that MAIC is used and interpreted with caution.


Asunto(s)
Teorema de Bayes , Mieloma Múltiple/tratamiento farmacológico , Metaanálisis en Red , Simulación por Computador , Supervivencia sin Enfermedad , Humanos , Lenalidomida/uso terapéutico , Mieloma Múltiple/mortalidad , Placebos , Ensayos Clínicos Controlados Aleatorios como Asunto , Reproducibilidad de los Resultados , Proyectos de Investigación , Factores de Riesgo , Talidomida/uso terapéutico
4.
Res Synth Methods ; 10(4): 615-617, 2019 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-31250534

RESUMEN

Indirect treatment comparisons are useful to estimate relative treatment effects when head-to-head studies are not conducted. Statisticians at the National Centre for Pharmacoeconomics Ireland (NCPE) and Scottish Medicines Consortium (SMC) assess the clinical and cost-effectiveness of new medicines as part of multidisciplinary teams. We describe some shared observations on areas where reporting of population-adjustment indirect comparison methods is causing uncertainty in our recommendations to decision-making committees when assessing reimbursement of medicines.


Asunto(s)
Análisis Costo-Beneficio , Recolección de Datos/métodos , Costos de los Medicamentos , Mecanismo de Reembolso , Proyectos de Investigación , Ensayos Clínicos como Asunto , Toma de Decisiones , Humanos , Comunicación Interdisciplinaria , Irlanda , Modelos Estadísticos , Curva ROC , Escocia , Evaluación de la Tecnología Biomédica/métodos , Incertidumbre
5.
Stat Med ; 38(14): 2505-2523, 2019 06 30.
Artículo en Inglés | MEDLINE | ID: mdl-30895655

RESUMEN

Increasingly, single-armed evidence is included in health technology assessment submissions when companies are seeking reimbursement for new drugs. While it is recognized that randomized controlled trials provide a higher standard of evidence, these are not available for many new agents that have been granted licenses in recent years. Therefore, it is important to examine whether alternative strategies for assessing this evidence may be used. In this work, we examine approaches to incorporating single-armed evidence formally in the evaluation process. We consider matching aggregate level covariates to comparator arms or trials and including this evidence in a network meta-analysis. We consider two methods of matching: (i) we include the chosen matched arm in the data set itself as a comparator for the single-arm trial; (ii) we use the baseline odds of an event in a chosen matched trial to use as a plug-in estimator for the single-arm trial. We illustrate that the synthesis of evidence resulting from such a setup is sensitive to the between-study variability, formulation of the prior for the between-design effect, weight given to the single-arm evidence, and extent of the bias in single-armed evidence. We provide a flowchart for the process involved in such a synthesis and highlight additional sensitivity analyses that should be carried out. This work was motivated by a hepatitis C data set, where many agents have only been examined in single-arm studies. We present the results of our methods applied to this data set.


Asunto(s)
Modelos Estadísticos , Metaanálisis en Red , Evaluación de la Tecnología Biomédica/métodos , Sesgo , Evaluación de Medicamentos , Hepatitis C , Humanos , Ensayos Clínicos Controlados Aleatorios como Asunto/estadística & datos numéricos
6.
BMC Med Res Methodol ; 18(1): 66, 2018 06 28.
Artículo en Inglés | MEDLINE | ID: mdl-29954322

RESUMEN

BACKGROUND: Network meta-analysis (NMA) allows for the estimation of comparative effectiveness of treatments that have not been studied in head-to-head trials; however, relative treatment effects for all interventions can only be derived where available evidence forms a connected network. Head-to-head evidence is limited in many disease areas, regularly resulting in disconnected evidence structures where a large number of treatments are available. This is also the case in the evidence of treatments for relapsed or refractory multiple myeloma. METHODS: Randomised controlled trials (RCTs) identified in a systematic literature review form two disconnected evidence networks. Standard Bayesian NMA models are fitted to obtain estimates of relative effects within each network. Observational evidence was identified to fill the evidence gap. Single armed trials are matched to act as each other's control group based on a distance metric derived from covariate information. Uncertainty resulting from including this evidence is incorporated by analysing the space of possible matches. RESULTS: Twenty five randomised controlled trials form two disconnected evidence networks; 12 single armed observational studies are considered for bridging between the networks. Five matches are selected to bridge between the networks. While significant variation in the ranking is observed, daratumumab in combination with dexamethasone and either lenalidomide or bortezomib, as well as triple therapy of carfilzomib, ixazomib and elozumatab, in combination with lenalidomide and dexamethasone, show the highest effects on progression free survival, on average. CONCLUSIONS: The analysis shows how observational data can be used to fill gaps in the existing networks of RCT evidence; allowing for the indirect comparison of a large number of treatments, which could not be compared otherwise. Additional uncertainty is accounted for by scenario analyses reducing the risk of over confidence in interpretation of results.


Asunto(s)
Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Mieloma Múltiple/tratamiento farmacológico , Metaanálisis en Red , Estudios Observacionales como Asunto , Anticuerpos Monoclonales/administración & dosificación , Teorema de Bayes , Bortezomib/administración & dosificación , Dexametasona/administración & dosificación , Humanos , Lenalidomida/efectos adversos , Mieloma Múltiple/patología , Oligopéptidos/administración & dosificación , Ensayos Clínicos Controlados Aleatorios como Asunto , Análisis de Supervivencia , Revisiones Sistemáticas como Asunto
7.
Res Synth Methods ; 9(3): 441-469, 2018 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-29923679

RESUMEN

The use of individual patient data (IPD) in network meta-analysis (NMA) is becoming increasingly popular. However, as most studies do not report IPD, most NMAs are performed using aggregate data for at least some, if not all, of the studies. We investigate the benefits of including varying proportions of IPD studies in an NMA. Several models have previously been developed for including both aggregate data and IPD in the same NMA. We performed a simulation study based on these models to examine the impact of additional IPD studies on the accuracy and precision of the estimates of both the treatment effect and the covariate effect. We also compared the deviance information criterion (DIC) between models to assess model fit. An increased proportion of IPD resulted in more accurate and precise estimates for most models and datasets. However, the coverage probability sometimes decreased when the model was misspecified. The use of IPD leads to greater differences in DIC, which allows us choose the correct model more often. We analysed a Hepatitis C network consisting of 3 IPD observational studies. The ranking of treatments remained the same for all models and datasets. We observed similar results to the simulation study: The use of IPD leads to differences in DIC and more precise estimates for the covariate effect. However, IPD sometimes increased the posterior SD of the treatment effect estimate, which may indicate between study heterogeneity. We recommend that IPD should be used where possible, especially for assessing model fit.


Asunto(s)
Interpretación Estadística de Datos , Hepatitis C/terapia , Metaanálisis en Red , Evaluación de Resultado en la Atención de Salud/métodos , Algoritmos , Simulación por Computador , Humanos , Estudios Observacionales como Asunto , Probabilidad , Ensayos Clínicos Controlados Aleatorios como Asunto , Reproducibilidad de los Resultados , Proyectos de Investigación , Resultado del Tratamiento
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