Pharmaceuticals Pricing Board (HILA), Finnish Medicines Agency (Fimea), Council for Choices in Health Care in Finland (COHERE Finland), Finnish Coordinating Center for Health Technology Assessment (FinCCHTA) and Social Insurance Institution of Finland (KELA) organize a hearing on methods used for Health Technology Assessment (HTA) on Tuesday April 16th 2024. In the event, the developers were given an opportunity to present their methods potentially used in the upcoming reimbursement submissions or appraisals to Finnish authorities involved in HTA. The deadline for applying as a presenter was March 1st 2024. Two presenters were selected based on the applicability to authorities’ work while trying to avoid excessive similarities between presentations, including those presented in the previous event.
At the hearing, Suzy van Sanden, who works as lead Statistician and methods expert at J&J pharmaceutical company, presented statistical methods for adjusting the effect of treatment switching on overall survival. According to van Sanden, ignoring the switch and focusing solely on the intention to treat results may lead to underestimation of the relative efficacy of the new treatment. A typical time of switching treatment groups in clinical trials is at or soon after disease progression among the patients in the control group. Three typical methods for adjusting the overall life expectancy of the control group were presented: RPSFTM, Two-Stage Estimation (TSE) and Inverse Probability of Censoring Weights (IPCW). In her presentation, Van Sanden summarized the assumptions inherent to the different methods, the data required by them and compared the results produced by them using an example.
A presentation by Jarkko Malviniemi, innovation manager and Niklas Kokkola, senior data scientist at Gesund partners, accompanied by Arho Virkki, analytics manager at Varha, introduced synthetic data and its possible role in developing digital health innovations and healthcare technology assessment. The presenters saw that the advantage of synthetic data is in preserving the essence and behaviour of the original data without violating the data protection and privacy. Differential privacy was defined in the presentation as a procedure where small changes are made to increase noise, preventing conclusions from being drawn on individual persons without deviating the aggregate statistics. According to the presentation, published or publishable synthetic data can be used as an alternative to genuine patient data in complex statistical analyses. The presentation highlighted different alternatives for producing synthetic data and for assessing its utlity and privacy protection.