Evidence Synthesis

Network meta-analysis (NMA)

Scope of service:

• Protocol and study design: The protocol will be developed to define the scope of the analysis, describe the statistical methods used, and specify the available data sets.

• Data preparation: The identification, extraction and aggregation of data is undertaken so that its scope and format are appropriate for the analysis to be performed.

• Advanced statistical analysis: The advanced statistical analyses that will be conducted using the Lumley and Bayesian methods are intended to provide a comparison of the effectiveness and safety of different interventions. The analysis will be facilitated by the use of sophisticated data analysis software, including R, Python and WinBUGS.

• Reporting and visualisation of results: A comprehensive report will be compiled, encompassing the findings, conclusions and recommendations. The results will be presented in the form of clear and easy-to-understand visualisations, the purpose of which is to facilitate interpretation.

Benefits:

• Clear ranking: The analysis facilitates the simultaneous comparison of multiple interventions and the compilation of rankings.

• New knowledge about the clinical value of a drug: Network meta-analysis enables the comparative analysis of alternative options for which there are no randomised studies that simultaneously evaluate the product being assessed and its alternatives.

• A reliable tool: The tool under development complies with the latest guidelines, thus ensuring both transparency and reliability.

Indirect evidence synthesis using the Bucher Method

Scope of service:

• Statistical analysis: To perform indirect comparisons, the Bucher method is used, which allows for pairwise comparisons of the efficacy and safety of different interventions, even if they have not been directly compared in clinical trials. The analysis is conducted using sophisticated data analysis software, including R, Python and WinBUGS.

• Reporting and visualisation of results: A comprehensive report will be compiled, covering the findings, conclusions and recommendations. Developing clear, comprehensible visualisations of the results will facilitate their interpretation.

Benefits:

• New knowledge about the clinical value of a drug: The Bucher method also allows for comparative analysis of alternative options for which there are no randomised studies that simultaneously evaluate the product being assessed and its alternatives.

• A reliable tool: The tool developed is in accordance with the most recent guidelines, ensuring transparency and reliability.

Adjusted indirect comparisons (STC, MAIC)

Scope of service:

• Feasibility study: The validity and feasibility of MAIC and STC analyses will be assessed based on the available clinical evidence.

• MAIC (Matching-Adjusted Indirect Comparison) analysis: The MAIC method is utilised to align patient characteristics across clinical trials, thereby facilitating the development of precise comparisons regarding the efficacy and safety of diverse therapeutic interventions.

• STC (Simulated Treatment Comparison) analysis: The STC method is used to simulate treatment outcomes based on available clinical data, which allows for the evaluation of therapies in the absence of direct comparisons.

• Comparative analysis: Specialised software for data analysis is used in this case, including R, Python and WinBUGS.

• Reporting and visualisation of results: A comprehensive report will be compiled, encompassing the findings, conclusions and recommendations. The development of clear and comprehensible visualisations of the results is to be undertaken, with the objective of facilitating their interpretation.

Benefits:

• Individual approach: The services provided are customised to suit the particular requirements of each client, with consideration given to demographic characteristics and the clinical context.

• New knowledge about the clinical value of a drug: Adjusted indirect comparison methods enable comparative analysis even in the absence of randomised trials for the product being evaluated and its alternatives.

• Greater reliability: When randomised trials are available, methods of adjusted indirect comparisons increase the reliability of such comparisons by limiting the impact of heterogeneity between trials.

Meta-analysis of clinical trials

Scope of service:

• Literature review: A systematic review of the available clinical studies will be conducted in order to identify relevant data for analysis.

• Assessment of study quality and subgroup analysis: The quality and homogeneity of the included studies are analysed in order to ensure that the meta-analysis provides reliable results. Subgroup analyses are performed in order to identify differences in treatment efficacy based on patient demographics or clinical characteristics.

• Advanced meta-analysis techniques: The statistical methods used to obtain reliable results include fixed and random effects modelling.

• Reporting and visualisation of results: A detailed report will be compiled, encompassing a description of the methodology, results, key findings, and recommendations.

Benefits:

• Individual approach: Our metanalyses are tailored to the specific needs of our clients, with due consideration for patient population characteristics and clinical context.

• Reliable conclusions: When there are multiple clinical trials with inconsistent conclusions, the appropriate aggregation of data allows for reliable conclusions about the efficacy and safety of a given intervention.

Survival analysis

Scope of service:

• Data collection and processing: For time-to-event endpoints (e.g. overall survival, progression-free survival), data is collected from clinical trials, medical registries and clinical practice (RWE) in order to establish a solid foundation for analysis.

• Advanced survival analysis techniques: The survival analysis methods used include Kaplan-Meier modelling, Cox regression analysis, and other techniques, which are implemented to accurately model the time-to-event occurrence.

• Risk factor analysis: The identification and analysis of risk factors that influence the occurrence of an event is undertaken, thereby facilitating a more comprehensive understanding of the key determinants of health.

• Data extrapolation: Using parametric models, we extrapolate data beyond the reporting period of clinical trials.

• Visualisation of results and reporting: The presentation of results is through clear visualisations, including survival curves, hazard ratios, tables and other graphical tools to facilitate data interpretation. The preparation of detailed reports containing the analysis methodology, survival analysis results, and their interpretation in a clinical context is a key part of the service.

Benefits:

• In-depth product knowledge: Survival analysis is a key tool for understanding product value. The analysis identifies factors that determine observed health outcomes while identifying subgroups of patients who achieve the best treatment results.

• Compliance with HTA requirements: Survival analyses are mandatory for time-to-event endpoints (e.g. overall survival, progression-free survival).

• Improving the accuracy of economic models: Survival analysis constitutes a pivotal element within economic models, determining the value of ICUR.

Analysis of individual patient data (IPD)

Scope of service:

• Evaluation of individual patient data: The analysis of individual patient data (IPD) is conducted in the universal ADAM format, which is in accordance with statistical standards for clinical trials.

• Feasibility study: The verification process is undertaken to ascertain the potential of the available data to exert a substantial influence on the optimisation or enhancement of the reliability of clinical comparisons or the economic model.

• Statistical analysis: A range of advanced statistical analyses are performed, including regressions, adjusted indirect comparisons, and survival analysis. The analysis involves the use of sophisticated software for data analysis, including R, Python and WinBUGS.

• Data reporting and visualisation: The preparation of detailed reports and data visualisations facilitates the interpretation of analysis results and supports decision-making processes.

Benefits:

• The optimisation of clinical results: By analysing individual patient data (IPD), it is possible to verify various clinical comparison scenarios that are not possible when only aggregated results from published studies are available.

• The optimisation of economic model results: The analysis will provide unique data that will optimize the results obtained by the economic model.

• Reliable assessment of patients' quality of life: The analysis of individual patient data is often the only method by which data on patients' quality of life can be obtained, and this is necessary for implementation in an economic model.

• Development of a reliable economic model: Frequently, the analysis of individual patient data is the only way to develop a reliable economic model, with the result that data gaps are filled in. This is especially evident in the context of oncology products, where survival analyses are conducted based on individual patient data from clinical trials.

Statistical report

Scope of service:

• Description of data and sources: The data used in the analyses is presented in a clear manner, with the sources indicated. The indications are provided as how they are used in individual analyses and in the economic model.

• Description of statistical methods: Statistical methods employed for the analysis of data, indirect comparative analyses of product efficacy and safety, and the development of an economic model will be described in this document.

• Data Visualisation: including charts, diagrams and tables, are presented in a clear and accessible manner to facilitate comprehension of the analysis outcomes. We interpret the data and describe all conclusions derived from it.

Benefits:

• A pragmatic tool: The statistical report contains comprehensive information on all data and analyses performed for the purpose of building and parameterising the economic model.

• Time savings: The report ensures that the model can be effectively adapted to the requirements of diverse markets.

• Efficient communication with the HTA Agency: On the basis of the detailed descriptions contained in this report, it is possible to prepare a well-documented set of analyses to be submitted to the HTA Agency and to respond efficiently to any questions they may have during the product evaluation process.

• Effective communication with local HTA providers: The entities responsible for local adaptation of the reimbursement portfolio will find answers in this report to the most detailed questions regarding the methodology and analyses performed to build the model