Challenges, considerations, and approaches for developing a cost-effectiveness model for the adjuvant treatment of muscle-invasive urothelial carcinoma: with a spotlight on nivolumab versus placebo

Figures & data

Table 1. Advantages and limitations of absorbing health states and tunnel health states for modeling post-recurrence costs and outcomes.

Consideration	Tunnel health states	Absorbing health states
Accounting for time of transitioning into health state	Captures time of transition into health state and allows for adequate discounting of cost and outcomes with time	Does not account for effect of time of transitioning into health state on outcome of subsequent therapy. Thus, for example, discounting of cost and outcomes for subsequent therapies is not fully captured
Transparency	All data and modeling of (for example) extrapolations are included within the economic model, which aids transparency	Could be perceived as not fully transparent given that total one-off costs and outcomes specific to the DR health state are modeled external to the core model structure. However, could also be seen as more transparent if costs and outcomes are sourced from previous HTA assessments of treatment of interest (if available), where costs and outcomes have been validated by the relevant HTA
Model complexity	Commonly seen as requiring a complex matrix structure to adequately capture transitions. However, can be programmed in a more simplistic way than full transition matrix per treatment using a sum product function in Microsoft Excel (see example in supplementary material). This method captures survival from health state but has potential limitation for tracking time-dependent costs and QALYs. An individual Markov engine is required for each treatment, thus if multiple subsequent therapies are available, the model can become very large	Lump sum costs and outcomes are added when patients transition into a health state without further sub-modeling. This approach can be much less computationally complex than tunnel states if costs and outcomes are taken from, for example, previous HTA appraisals
Model validation	Outcomes are captured relative to model time, which allows for outcomes to be included in, for example, calculation of model OS, thus facilitating validation against external data	Given that costs and outcomes for remainder of time in health state are accounted for in the cycle the patients enter the health state, an OS curve (for example) cannot be calculated from the model. This limits the possibility to validate long-term projections of overall model outcomes in relation to external data

Abbreviations. DR distant recurrence; HTA health technology assessment; OS overall survival; QALY quality-adjusted life-year.

Figure 1. Four-state model structures: (A) tunnel health state structure adopted in the current model and (B) absorbing one-off structure. DF: disease-free; DR: distant recurrence; LR: local recurrence; P(Death|DF): probability of death from DF; P(Death|LR): probability of death from LR; P(DF|DF): probability of staying in DF; P(DR|DF): probability of moving from DF to DR; P(DR|LR): probability of moving from LR to DR; P(LR|DF): probability of moving from DF to LR; P(LR|LR): probability of staying in LR.

Data availability statement

Data are available upon reasonable request. Bristol Myers Squibb’s policy on data sharing may be found online at https://www.bms.com/researchers-and-partners/independent-research/data-sharing-request-process.html.