The committee was aware that quality-of-life data had been collected in RM‑493‑023. But, at the first committee meeting, the company stated that the quality-of-life instruments used in the trial (PedsQL, IWQOL‑Lite and EQ‑5D) lacked the sensitivity to capture the full effect of hyperphagia. Instead, for hyperphagia, it used utility multipliers associated with severity status (mild, moderate and severe) derived from a vignette study in the general public. For each of the 7 BMI health states, utility values came from a US study of Short Form Survey (SF)‑12 utilities according to BMI by Alsumali et al. (2018). Utility values for the 7 BMI‑Z health states came from Riazi et al. (2010). These values were mapped to EQ‑5D‑3L using a mapping algorithm from Khan et al. (2014). The EAG highlighted that, although the company's utility values had been accepted in NICE's highly specialised technology guidance on LEPR or POMC deficiency, Forsythe et al (2021) had recently published PedsQL results from RM‑493‑023. This was were collected data from people with BBS instead of general obesity. At technical engagement, the company provided a scenario that mapped the PedsQL data from RM‑493‑023 to EQ‑5D estimates. The EAG noted that the company scenario had not applied the mapping algorithm from Khan et al. correctly, and corrected this error. The EAG suspected that this error likely applied to values mapped from Riazi et al. in the company's base case as well. At consultation, the company provided a scenario that corrected this error. At the first committee meeting, the committee preferred to use utility values from Riazi et al. for BMI‑Z health states. This was because they were based on 96 children living with obesity, whereas the EAG's mapping was based on 5 people with BBS. One of these 5 informed the lowest BMI‑Z health state (BMI‑Z scores 0 to 1). The other 4 informed the highest (BMI‑Z score over 4), with the utilities for the middle BMI‑Z health states extrapolated. So, because there was only 1 person informing the lowest health state, any variation in baseline PedsQL score from the general BBS population could have biased the extrapolated values. After consultation, the EAG updated its base case to use values mapped from the literature, but the company's revised base case used values mapped from RM‑493‑023. The EAG was unclear about why the company chose to use a source of utility values that differed from that preferred by the committee. It noted that the company had not provided the utility values for its scenario that corrected the mapping of literature values. So, it used the uncorrected values provided by the company at the first meeting. At the second committee meeting, the committee reconsidered this but maintained its preference for utility values from the literature. It acknowledged that the NICE health technology evaluations: the manual specifies a preference for using trial-based utilities when available. But, given the uncertainty introduced by the small sample size (n=5) from the trial available for mapping, the committee agreed that this constituted an exceptional circumstance. The committee would have preferred to use the utilities from the literature that used the corrected mapping approach. But, given that the company did not provide these, it concluded that utilities from the EAG's base case were appropriate for decision making.