PCN224 TREATMENT BENEFIT DISCONTINUATION: COMPARISON OF A PARTITIONED SURVIVAL ANALYSIS AND A SEMI-MARKOV MULTI-STATE MODEL APPROACH USING AN ONCOLOGY CASE STUDY

Abstract

To compare three scenarios modelling treatment benefit discontinuation (TBD), also known as treatment waning, within a partitioned survival analysis (PartSA) or semi-Markov multi-state model (MSM) framework. The PartSA was developed using data from a cohort of patients with late-stage cancer (N>700) enrolled within a randomised, controlled trial. Health states were pre-progression, progressed disease and death. Patients were treated until progression. Clinician feedback indicated that treatment effect would be unlikely to extend beyond treatment discontinuation. To incorporate TBD, the PartSA considered two scenarios: (1) survival rates in the TX1 arm equal to TX2 after the median follow-up (15-months) and (2) survival rates in the TX1 arm equal to TX2 after the maximum follow-up (24-months). The MSM was constructed using the same data and inputs, but no TBD inputs were required as the long-term extrapolation for the transition from progressed disease to death was based on empirical data collected beyond progression. The PartSA estimated an incremental cost-effectiveness ratio (ICER) of £342,474 without adjustment for TBD. When considering TBD, the ICER increased by 135% (£803,992) and 91% (£653,301) for scenarios (1) and (2), respectively. The MSM estimated an ICER of £483,097. Despite adjusting for TBD, the PartSA framework resulted in more optimistic long-term survival for patients in the progressed disease health state compared with the MSM framework. An increasingly common theme in UK health technology appraisals is exploring the discontinuation of the treatment effect when extrapolating survival data. However, there are no guidelines as to how this should be approached within the PartSA framework. It is important to note that attempting to incorporate dependency of endpoints within a PartSA – as is attempted within the TBD scenarios – invalidates the assumptions underpinning a PartSA. Alternative model structures, such as the MSM approach, may provide a more robust estimate.