Draft guidance consultation

Lennox–Gastaut syndrome (LGS) is a severe, lifelong and treatment-resistant form of epilepsy that begins in early childhood, generally before the age of 8 years. It is characterised by a specific electroencephalogram (EEG) pattern and developmental delay or cognitive impairment. It is also characterised by frequent seizures of different types. Drop seizures result in a loss of muscle tone or stiffening of muscles, which may result in falls, serious injury, pain, hospitalisation and death. Generalised tonic–clonic seizures are particularly severe. Uncontrolled and frequent generalised tonic–clonic seizures correlate to an increased risk of death. Non-drop seizures are typically not as severe as drop seizures and do not generally result in hospitalisation. The patient carer expert noted that LGS can also result in behavioural issues such as hyperactivity, anxiety, aggression, sleep disturbances and depression. They also noted that LGS has a substantial impact on families and carers, with some reporting feelings of despair and helplessness. People with the condition need round-the-clock care, and help with almost all aspects of daily life. Families and carers may find that it prevents them from leading normal lives and prevents family activities. The anxiety that a child with LGS may be injured because of a drop seizure can also significantly affect the mental wellbeing of their family. The patient carer expert explained that they must be within catching distance of their child at all times because their child could have a drop seizure at any moment. The committee concluded that LGS severely affects the quality of life of people with the condition, their families and carers.

The NICE guideline on epilepsies in children, young people and adults (from here referred to as NG217) recommends considering sodium valproate first. If seizures are inadequately controlled, NG217 recommends considering lamotrigine as a second-line add-on treatment or by itself. If second-line treatment is unsuccessful, cannabidiol plus clobazam, clobazam alone, rufinamide and topiramate can be considered as third-line add-on treatment options. If all other treatment options are unsuccessful, add-on treatment with felbamate (unlicensed use) can be considered, under the supervision of a neurologist with expertise in epilepsy. Non-pharmacological treatment options include vagus nerve stimulation, a ketogenic diet and surgery. The clinical experts stated that the NG217 treatment pathway for LGS is broadly reflective of clinical practice in the NHS. But, they noted that the choice of treatment regime is highly individualised and based on effectiveness, adverse effects, sedative effects and drug–drug interactions. The committee noted that it would be useful to see data on the proportion of people who would not have cannabidiol plus clobazam in NHS clinical practice. The company and clinical experts were unable to provide an estimate of the proportion of people who would not have cannabidiol plus clobazam because of the heterogeneity of LGS and the treatment options, and the rarity of LGS. The clinical experts noted that LGS can be difficult to diagnose because not all people display the characteristic symptoms (see section 3.1) at onset or at any one time. By the time people are diagnosed they have often already had most third-line treatment options. They also stated that current treatments often do not control seizures associated with LGS. The patient carer experts noted that the currently available drugs that comprise standard care (SC) that initially work, can lose efficacy. The committee concluded that LGS is a heterogenous condition and there is an unmet need for treatments that reduce the number of drop seizures without markedly increasing adverse events.

The company positioned fenfluramine as a third-line add-on therapy, in line with the positioning of cannabidiol plus clobazam. Based on this positioning, the comparator included in the company submission was cannabidiol plus clobazam (plus SC). The company also provided a scenario comparing fenfluramine with SC alone. SC comprised a basket of treatments that included:

• clobazam

• levetiracetam

• valproate

• lamotrigine

• topiramate and

• rufinamide.

The primary clinical evidence for fenfluramine plus SC came from Study 1601 and an interim analysis of the Study 1601 open-label extension (OLE) study. Study 1601 was a phase 3, double-blind, international randomised controlled trial (RCT). It compared the efficacy and safety of fenfluramine 0.2 mg/kg/day (n=89) and fenfluramine 0.7 mg/kg/day (n=87) as an add-on therapy to SC, with placebo plus SC (n=87). The trial period was 20 weeks. It recruited people aged between 2 and 35 years, with Epilepsy Study Consortium-confirmed LGS diagnoses, on stable antiseizure medication regimens. The EAG noted that the final scope outcomes included seizure frequency (overall and by seizure type) and seizure severity. But, it noted that the company reported seizure frequency for only drop seizures and seizure severity was not collected in the trial. The primary outcome was percentage reduction from baseline in drop-seizure frequency (DSF) per 28 days in the fenfluramine 0.7 mg/kg/day arm. At week 14 of the titration and maintenance period, the median percentage change from baseline in DSF was a 26.5% reduction in the fenfluramine 0.7 mg/kg/day arm. This was compared with a 7.6% reduction in the placebo arm (p=0.001). At week 14, the proportion of people with a reduction in DSF of 50% or more was 25.3% in the fenfluramine 0.7 mg/kg/day arm and 10.3% in the placebo arm (p=0.015). Study 1601 OLE (n=247) is an ongoing flexible-dose, single-arm study to assess the safety and efficacy of fenfluramine plus SC for people who completed Study 1601. All people were initially started on 0.2 mg/kg/day fenfluramine and after 1 month were titrated by effectiveness and tolerability, which were assessed at 3-month intervals. At the latest data cut, 142 people had completed 12 months of follow up. At year 1 of the OLE, the median percentage reduction in DSF from baseline was 51.8% (p<0.0001). The committee concluded that fenfluramine as an add-on to SC is more effective at reducing DSF than SC alone. The committee also noted the adverse events reported in Study 1601 (available in the summary of product characteristics [SPC] for fenfluramine). It acknowledged that the most common treatment-emergent adverse events were decreased appetite, drowsiness and fatigue, which occurred at a higher rate in the fenfluramine 0.7 mg/kg/day arm than in the fenfluramine 0.2 mg/kg/day arm.

Because there was no direct head-to-head evidence for fenfluramine plus SC compared with cannabidiol plus clobazam plus SC, the company did a series of network meta-analyses (NMAs). Outcomes captured between 10- and 20-week timepoints were considered. Outcomes assessed were:

• median percentage reduction in frequency of generalised tonic–clonic seizures

• reductions in DSF of:

  • 25% or more

  • 50% or more

  • 75% or more

• discontinuation due to adverse events.

The company presented a 6-state cohort-based Markov model with a lifetime time horizon of 86 years. The model compared fenfluramine plus SC with cannabidiol plus clobazam plus SC and SC alone. Four health states were based on percentage reduction in DSF from baseline:

• state 0, for people with a less than 25% decrease in DSF

• state 1, for people with a 25% to less than 50% decrease in DSF

• state 2, for people with a 50% to less than 75% decrease in DSF

• state 3, for people with a 75% or greater decrease in DSF.

The EAG highlighted concerns with basing health states on the relative reductions in drop seizures. It noted that this results in people with different numbers of absolute drop seizures being in the same health state, despite having significant differences in health-related quality of life (HRQoL) and costs. It added that this model structure based on relative reduction in drop seizures deviated from other published models in LGS and from the model used in TA615. So, it would prefer a model based on absolute reduction in drop seizures. The company stated that a modelling approach using absolute reductions in drop seizures was not feasible because of the lack of absolute trial data for cannabidiol plus clobazam plus SC. It also highlighted that in its model, relative reduction in the percentage of DSF was translated to absolute DSF using the midpoint approach in Neuberger et al. (2020). This allowed the incorporation of healthcare resource use data from TA615, based on absolute DSF categories. The committee noted the very large interquartile ranges for the baseline median DSF in Study 1601 (2 to 1,761 and 7 to 1,803 for placebo and fenfluramine 0.7 mg/kg/day, respectively). It questioned the plausibility of using a relative approach, given the large difference in the absolute number of drop seizures for the treatment population. The committee noted that, as a result, it is highly uncertain to assume people in the same relative reduction in DSF health state have the same utility values and healthcare resource use. It considered that a model based on absolute reduction in DSF would be more robust. But it acknowledged other limitations that would have been present with a model with health states based on absolute DSF categories. So, although the committee had significant reservations about the appropriateness of the model structure, it agreed to use it to inform its decision making. It concluded that the model structure added uncertainty to the cost-effectiveness estimates.

The committee noted that the model only included drop seizures, and so did not include the impact of fenfluramine on other seizure types. It noted that it was unclear whether the exclusion of non-drop seizures from the model would favour fenfluramine or the comparators. It recognised that reducing non-drop seizures is important to people with LGS and their carers. But it understood that non-drop seizures are harder to measure and verify than drop seizures. It concluded that the absence of non-drop seizures in the model adds to the uncertainty around the economic analysis.

The company's model had a lifetime time horizon of 86 years. But, only 15 months of data for fenfluramine plus SC was available from Study 1601 and the OLE. So, extrapolation of treatment effect was needed beyond the trial period. For fenfluramine plus SC, the company's initial modelling approach assumed that the transition probabilities for cycles 6 to 9 equalled the transition probabilities of cycles 4 to 5, which were based on the last 3 months of the Study 1601 OLE. That is, it was assumed that the treatment effect for fenfluramine plus SC increased after the observed trial period. In contrast, the company assumed the treatment effect for cannabidiol plus clobazam plus SC was stable for cycles 6 to 9. This assumption was based on the experience of healthcare professionals using fenfluramine to treat Dravet syndrome and state occupancy data of fenfluramine and cannabidiol from the respective OLE studies. The company stated that the data suggested that the treatment effect of fenfluramine is sustained and increases, based on increasing percentages of people showing improvement in DSF reduction over time. The EAG highlighted that in NICE's technology appraisal guidance on fenfluramine for treating seizures associated with Dravet syndrome (from here referred to as TA808) a maintained treatment effect of fenfluramine was modelled based on the efficacy data. The EAG preferred to model a maintained treatment effect for fenfluramine plus SC treatment during cycle 6 to cycle 9 in its base case (in line with the assumed maintained treatment effect for cannabidiol plus clobazam plus SC). A clinical expert stated that the peak effect with fenfluramine is achieved quickly and would likely be achieved within the trial period. The committee analysed the Study 1601 OLE data that the company provided to support an increased treatment effect after the trial period. The committee noted from figure 9 of the company submission that 247 people entered the OLE study. But the number of people with data at 12 months was substantially reduced, which the committee considered biased the data (see section 3.6). The company acknowledged this limitation with the Study 1601 OLE data. So, the committee was not convinced that the data supported an increasing treatment effect for fenfluramine after the trial period. After the first committee meeting, the company did imputation analyses based on all people who received open-label fenfluramine and used resulting data to perform an additional NMA (see section 3.7). The results of the NMA were used to populate health states for cycles 2 to 5 for fenfluramine plus SC and cannabidiol plus clobazam plus SC (see section 3.12). It also updated its base-case assumption for fenfluramine plus SC, assuming that treatment effect is maintained from cycles 6 to 9, in line with cannabidiol plus clobazam plus SC. That is, people stay in same health state as cycle 5 for cycles 6 to 9. The committee recalled that it had not seen OLE ITT data that appropriately accounted for attrition (see section 3.6). So it considered that there was substantial uncertainty regarding the plausibility of the extrapolation of treatment effect for cycles 6 to 9. It noted that the company's updated base-case analysis and EAG's base-case analysis both assumed a maintained treatment effect for fenfluramine plus SC and cannabidiol plus clobazam plus SC for cycles 6 to 9. Based on the lack of robust evidence to suggest an increased treatment effect for fenfluramine, the committee concluded that it would use the following as a basis for its decision making:

• a maintained treatment effect assumed for cycles 6 to 9 (for fenfluramine plus SC and cannabidiol plus clobazam plus SC)

• state occupancy based on the cycle 5 state occupancies for fenfluramine plus SC and cannabidiol plus clobazam plus SC in the EAG's base-case model.

From cycle 10 onwards in the model, people in the fenfluramine plus SC and cannabidiol plus clobazam plus SC arms stayed in the same health state unless they experienced treatment waning, stopped treatment, or died. The company calculated the proportion of people experiencing treatment waning by:

• taking the proportion of people stopping because of lack of efficacy in the last 3 months of the Study 1601 OLE, which was 5.2%

• multiplying this proportion with the deteriorating transition probabilities based on all people on treatment from last 3 months of the Study 1601 OLE.

The company collected data from responses to the Quality of Life in Childhood Epilepsy-16 item questionnaire (QOLCE‑16) in Study 1601 and the OLE. But it did not use the data in its model. It stated that the QOLCE‑16 is a disease-specific measure and that long-term data was not yet available. The company used EQ-5D utility values from Verdian et al. (2008), a vignette-based conference abstract, to inform patient utility values. It chose this because it matched NICE's EQ-5D reporting requirements, had been used previously in LGS models and aligned with the model's relative health-state structure. The company also considered 2 other studies reporting relevant utility values (Auvin et al. 2021 and Lo et al. 2021) but these were deemed less appropriate. Auvin et al. examined various types of epilepsies, including Dravet syndrome, which did not align with the patient population. Lo et al. did not align with the model's structure because it reported utilities for health states based on the total number of drop seizures per month. The EAG noted that the vignette approach used by Verdian et al. is condition-orientated and so may not capture all aspects that influence dimensions of the EQ-5D. Also, the values are not directly from people living with LGS. The company highlighted that vignette-based utility values may be useful in rare conditions such as LGS, where it is not possible to recruit a large enough representative sample. The EAG also considered the utility values to be relatively low and lack face validity when compared with the mean baseline QOLCE‑16 scores from Study 1601. Also, it noted that the overall quality-of-life domain and most other domains of the QOLCE‑16 showed hardly any clinically relevant change at visit 12 (end of study or end of treatment) compared with baseline. This indicates that the HRQoL of people with LGS may not be very sensitive to improvements in DSF. So, it considered that the large differences in utility values between the health states in the model seemed to lack face validity. The EAG used the Verdian et al. utility values in its base case, but considered that none of the sources of utility values in the company submission were ideal for informing HRQoL for people with LGS. The committee considered that all utility values presented in the company submission were associated with limitations. But, it recognised the challenges associated with obtaining robust utility values in rare conditions such as LGS. The committee concluded that the Verdian et al. utility values are associated with substantial uncertainty. But, they are likely the best available source of utility values given the use of health states based on relative reductions in drop seizures.

The committee recalled that caring for someone with LGS has a substantial impact on carers' quality of life (see section 3.1). It considered that capturing this in the model is appropriate. The company included carer utilities for each health state in its base case by applying the same utility values from Verdian et al. (2008) used for people with LGS (see section 3.15). The company assumed 1.8 carers per person with LGS. The company assumed that the utility value of carers equalled that of people with LGS. This was because of a lack of LGS carer utility values in the literature and the substantial impact of LGS on carers who provide round-the-clock care. The EAG considered this assumption to be unrealistic. It highlighted that Auvin et al. (2021) and Lo et al. (2021) reported higher utility values for carers compared with people with LGS. It also noted that the Zarit Caregiver Burden Inventory results in Study 1601 suggested a mild to moderate carer burden and that carer burden may not be sensitive to changes in seizure frequency. The company's carer utility approach also meant that when a person with LGS in the model died, the corresponding carer utility value is set to 0. This overestimates this impact of mortality, given that the carer does not die together with the person they care for. The company also provided a scenario analysis in which carer disutility values were used (instead of utility values). The disutility values were obtained by calculating the difference between the visual analogue scale utility value for the UK general population and the UK carer utility scores for LGS estimated in Auvin et al. The resulting disutility value was then used to calculate a decrement applied to the QALYs for each treatment. Given the limitations with the carer utility approach, the EAG preferred to use the carer disutility approach in its base case. But, the EAG preferred to use disutility values calculated from Lo et al. in its base case (rather than Auvin et al.). This was because it considered that:

• the time trade-off approach from Lo et al. is better aligned with the NICE reference case (stating that a choice-based method should be used) than the visual analogue scale approach used by Auvin et al.

• the sample size of Lo et al. (n=150) was larger than the sample size of Auvin et al. (n=30)

• the DSF categories in Lo et al. better aligned with the DSF categories in the model compared with the DSF categories Auvin et al.

The SPC for fenfluramine recommends increasing the dose of fenfluramine as tolerated up to the recommended maintenance dosage of 0.7 mg/kg/day. The company implemented a base-case maintenance dosage for fenfluramine of 0.413 mg/kg/day. It stated the dosage was based on the mean daily dosage for fenfluramine for people in the Study 1601 OLE, in which efficacy continued to improve at lower average doses than used in Study 1601. This mean daily dosage excluded people who had dosages of more than 0.7 mg/kg/day (maximum licensed dosage) in the OLE. The company considered that the OLE dosage is more reflective of clinical practice than those in Study 1601 because dosages were titrated based on safety and tolerability in the OLE. It also suggested that the dosage was comparable to the average dosage of people with Dravet syndrome who are not on stiripentol. The EAG agreed that in clinical practice, dosages will be titrated based on tolerability, efficacy and safety. It noted that the mean daily dosage was lower than the maintenance dosage recommended in the SPC (that is, 0.7 mg/kg/day). The dosage also differed from the dosages that people had in Study 1601 (see section 3.4), which was used to inform the indirect treatment comparison. The EAG disagreed with the company's rationale for excluding people who had mean dosages of more than 0.7 mg/kg/day in the OLE from the calculation. It noted that people with a mean daily dose lower than the initial titration dosage (0.2 mg/kg/day) were included in company's calculation. And that people who had more than 0.7 mg/kg/day were included in clinical-effectiveness data used in the model. So the EAG preferred using the mean daily dosage for fenfluramine for all people in the Study 1601 OLE (including those who had more than 0.7 mg/kg/day), which was 0.416 mg/kg/day. The committee concluded that it preferred to use the mean dose from the Study 1601 OLE as this dose is likely to be most reflective of clinical practice. It agreed with the EAG's rationale that the maintenance dosage calculation should include people that had mean dosages of more than 0.7 mg/kg/day. So, the committee preferred to include a mean daily dosage for fenfluramine of 0.416 mg/kg/day.

The SPC for cannabidiol states that the dosage can be increased from a maintenance dosage of 10 mg/kg/day to 20 mg/kg/day. At the first committee meeting, the company assumed a base-case maintenance dosage for cannabidiol of 16 mg/kg/day. The company considered that 16 mg/kg/day is conservative based on clinical expert opinion and the cannabidiol OLE study. It highlighted that the mean modal dosage within the cannabidiol OLE was 24 mg/kg/day. The EAG noted that an average dosage of 12 mg/kg/day was used in TA615. It highlighted that the company also used the same data to model cannabidiol efficacy as that used in TA615. The clinical experts stated that in their experience the average maintenance dosage of cannabidiol was around 12 mg/kg/day to 15 mg/kg/day. The committee requested scenario analyses exploring a range of cannabidiol maintenance dosages from 12 mg/kg/day to 16 mg/kg/day. After the first committee meeting, the company provided these scenarios and updated its base-case maintenance dosage for cannabidiol to 14 mg/kg/day. But it considered that the mean maintenance dosage in practice is closer to 16 mg/kg/day. But the committee noted that cannabidiol RCTs demonstrated a statistically significant reduction in the number of drop and non-drop seizures at 10 mg/kg/day. The EAG modelled an average maintenance dosage of 12 mg/kg/day for cannabidiol in its base case. But it noted that this was uncertain and considered that the range between 12 mg/kg/day and 16 mg/kg/day should be considered for decision making. Based on clinical expert opinion and data from the cannabidiol OLE, the committee considered that it was appropriate to consider a range of cannabidiol maintenance dosages between 12 mg/kg/day and 16 mg/kg/day for decision making.

At the first committee meeting, clinical experts stated that there may be treatment wastage caused by bottle breakages or leftover liquid medicine in the bottle. Because the company's and EAG's initial analyses all assumed no wastage, the committee requested scenarios accounting for the expected wastage costs associated with both cannabidiol and fenfluramine. The company provided scenarios in which it assumed:

• 5% wastage for both treatment arms

• 5% wastage for fenfluramine and 10% wastage for cannabidiol

• 0% wastage for fenfluramine and 10% wastage for cannabidiol.

In its submission the company stated that most people will need residential care. The company did not include the impact of residential care in its initial base-case model but provided a scenario analysis including residential-care costs applied to 10% of people who reach age 18. This approach was similar to that used in TA615. In that appraisal, 10% of people experiencing seizures were assumed to need residential care by the time they were 18 compared with 2% for people who were drop-seizure free. The EAG preferred to include the cost of residential care in its base case. It used the residential-care rate of 10% provided by the company, but noted that it was uncertain whether this figure was representative of NHS clinical practice. The EAG also considered that the impact of residential care on carer HRQoL should be modelled. In its base case it assumed that people who need residential care will need 0.7 carers (rather than 1.8). This was calculated based on the proportion of days per year that people who need residential care are expected to be at home. The patient carer experts explained that they would expect that most carers would prefer to look after people with LGS themselves rather than opting for residential care. The committee considered that some carers may not be able to provide adequate care because of their own health and so residential care may be the only option. The committee concluded that it was appropriate to assume 10% of people with LGS reaching 18 years old will need residential care. It also concluded that it was appropriate to include residential-care costs and to assume 0.7 carers for people needing residential care, to account for the reduced carer responsibility. The company updated its base-case model after the first committee meeting to align with the committee's preferences for residential care.

The marketing authorisation for fenfluramine does not specify a stopping rule. But the company initially proposed a stopping rule whereby treatment is stopped if DSF has not reduced by at least 25% from baseline, assessed every 3 months. The EAG noted that in TA808, the committee recommended a stopping rule for people who had less than 30% reduction in DSF over a period of 6 months. This stopping rule was also in line with current practice for cannabidiol plus clobazam in LGS. At the clarification stage, healthcare professionals consulted by the company considered it reasonable to stop treatment if the reduction in DSF was less than 25% to 30%. They also agreed it would be reasonable to assess outcomes every 6 months. The EAG preferred to apply the stopping rule applied in TA808. But, it noted that the stopping rule at 6 months appeared to be incorrectly implemented in the model. It explained that all people from health state 0 discontinued every 6 months, instead of only the people who were in health state 0 for 6 months. As a result, people who were in health state 0 for only 3 months also discontinued. In response to the draft guidance, the company stated that tracking people in the model in the cannabidiol plus clobazam plus SC arm would not be possible without transition probabilities, because patient-level data would be needed. The company implemented a revised stopping rule but the EAG considered this also had limitations and so preferred the company's initial approach. The committee concluded a stopping rule whereby fenfluramine is stopped if the DSF has not reduced by at least 30% from baseline, assessed every 6 months is reasonable. The company updated its base case after the first committee meeting to align with the committee's preferred stopping rule, whereby fenfluramine is stopped if the DSF has not reduced by at least 30% from baseline, assessed every 6 months.

There were no cases of pulmonary arterial hypertension or valvular heart disease reported at any point in Study 1601 and its OLE. But, the committee were aware of a previous study by Souza et al. (2008). In that study, which analysed a cohort of fenfluramine-associated pulmonary hypertension cases, there was a median of 4.5 years between exposure and onset of symptoms. The committee questioned whether pulmonary arterial hypertension could be a cumulative dose-related adverse event and could potentially be an issue after using fenfluramine for more than 5 years. It considered whether the cost of treating pulmonary hypertension should be included in the model. The company highlighted that fenfluramine, when previously used as a weight-loss medication, was prescribed at 60 mg/day, with dosages as high as 220 mg/day. And the association with heart disease was complicated by the lack of pretreatment echocardiograms and consideration of other risk factors. In contrast, the maximum daily dose of fenfluramine for LGS is 26 mg. The company explained that, based on the latest data, fenfluramine has been exposed for 5,203-patient years globally and there have been no confirmed cases of pulmonary arterial hypertension. After the second committee meeting, the company noted that pulmonary arterial hypertension has now been reported in 1 child having fenfluramine (at a dosage of 10.12 mg/day) for Dravet syndrome. When the child stopped taking fenfluramine, the reaction resolved. The committee considered that it would be helpful to have more information about pulmonary arterial hypertension in this population to understand if the associated costs should be included within the model. The company noted that as part of the controlled access programme stipulated by the Medicines and Healthcare products Regulatory Agency, people must have an echocardiogram every 6 months for the first 2 years on fenfluramine and annually thereafter. If an abnormality is detected, then fenfluramine would be stopped. The committee concluded that, based on the latest available data, it is appropriate not to model the cost of treatment for pulmonary arterial hypertension, but they would consider if this was still appropriate based on the most up to date data available.

NICE's manual for health technology evaluations notes that judgements about the acceptability of a technology as an effective use of NHS resources will take into account the degree of certainty around the incremental cost-effectiveness ratio (ICER). The committee will be more cautious about recommending a technology if it is less certain about the ICERs presented. The committee noted concerns around the high level of uncertainty, specifically:

• The lack of clinical-effectiveness and cost-effectiveness data for fenfluramine plus SC compared with rufinamide plus SC, topiramate plus SC and clobazam plus SC (see section 3.3 and section 3.5).

• The lack of clinical-effectiveness data for fenfluramine on seizure severity and frequency of seizure types other than drop seizures (see section 3.4).

• The results of the OLE NMA and the comparative clinical effectiveness of fenfluramine plus SC and cannabidiol plus clobazam plus SC (see section 3.7).

• The appropriateness of the company's model structure based on relative reduction in DSF (see section 3.9).

• The appropriateness of only using drop seizures in the modelling, and not other seizure types (see section 3.10).

• The lack of fenfluramine and cannabidiol ITT OLE data that account for data attrition in an appropriate manner, leading to uncertainty about:

  • The appropriateness of the data used to inform state occupancy between cycles 2 and 5 for the fenfluramine plus SC and cannabidiol plus clobazam plus SC arms (see section 3.12).

  • The appropriateness of assuming a maintained treatment effect between cycles 6 and 9 for the fenfluramine plus SC and cannabidiol plus clobazam plus SC arms (see section 3.13).

• The appropriateness of the patient utility values presented in the company submission (see section 3.15).

In response to the draft guidance, the company only presented cost-effectiveness results against cannabidiol plus clobazam plus SC. But, in its response, the EAG included cost-effectiveness results, with the company's preferred assumptions, against cannabidiol plus clobazam plus SC and SC alone, for committee consideration. Because of confidential commercial arrangements for fenfluramine, the comparators and other treatments in the model, the exact cost-effectiveness estimates are confidential and cannot be reported here. The company's deterministic base-case ICER for the comparison with cannabidiol plus clobazam plus SC was above the range normally considered an acceptable use of NHS resources. In the EAG's deterministic base-case analysis, for the comparison with cannabidiol plus clobazam plus SC, fenfluramine plus SC was dominated (that is, fenfluramine generated fewer QALYs and was more expensive than cannabidiol plus clobazam plus SC). The EAG's base ICER for the comparison with SC alone was higher than the range normally considered an acceptable use of NHS resources.

The clinical experts highlighted that people with LGS have learning disabilities, so support is needed at appointments. A clinical expert also considered fenfluramine treatment will be started by specialists. But, because adults with LGS may not be under the care of a specialist, they may not have access to new treatments. A patient carer expert noted that some of the tests potentially needed to start fenfluramine may be traumatic for people with LGS who have sensory issues. The committee was aware of the need for equitable access to fenfluramine if it is recommended, but noted that access to treatments is an implementation issue that cannot be addressed in a technology appraisal recommendation. It was also aware of monitoring requirements for fenfluramine and noted that these should be considered before starting fenfluramine.

The committee also considered potential benefits of fenfluramine that were not included in the economic model. The company stated that there are a number of benefits not captured in the economic model, such as:

• reductions in:

  • duration of drop and non-drop seizures

  • losses to work productivity, which may also provide wider societal benefit

• improvements in:

  • the quality of life of siblings and other family members of people with LGS

  • the intellectual development of children with LGS, due to fewer seizures

  • motor function and

  • executive function.