Draft guidance consultation

Multiple myeloma is an incurable, relapsing and remitting cancer of plasma cells. It is a chronic condition that affects how long people live and the quality of their lives. The patient experts emphasised that multiple myeloma is a highly individual and complex cancer that has a wide range of symptoms and varies in severity. They explained that the condition has a large psychological impact because of the constant possibility of relapse. With each relapse, the condition is more difficult to treat and the number of future treatment options becomes more limited. The patient experts added that the condition can also have a large impact on quality of life, affecting all aspects of life for people with the condition, and their family and carers. The committee acknowledged that multiple myeloma is a chronic, incurable highly individual condition that can have a negative impact on quality of life for people with the condition, and their families and carers.

First-line treatment options for people with multiple myeloma depend on whether a stem cell transplant may be suitable. NICE recommends the following treatments as options at first line when a stem cell transplant is not suitable:

• thalidomide, cyclophosphamide and dexamethasone (see NICE's technology appraisal guidance on bortezomib and thalidomide for the first\u2011\line treatment of multiple myeloma, from here TA228)

• bortezomib, cyclophosphamide and dexamethasone (Cyclo-Bor-Dex; see TA228)

• bortezomib, melphalan and prednisone (Mel-Bor-Pred; see TA228)

• lenalidomide and dexamethasone (Len-Dex; NICE's technology appraisal guidance on Len-Dex for previously untreated multiple myeloma, from here TA587)

• daratumumab, lenalidomide and dexamethasone (Dar-Len-Dex; see NICE's technology appraisal guidance on Dar-Len-Dex for untreated multiple myeloma when a stem cell transplant is unsuitable).

The clinical-effectiveness evidence for Isa-Bor-Len-Dex came from IMROZ, a phase 3, multicentre, international, randomised, open-label, 2‑arm, parallel-group study. It compared Isa-Bor-Len-Dex (n=265) with bortezomib, lenalidomide and dexamethasone (Bor-Len-Dex; n=181) in adults with newly diagnosed multiple myeloma when an ASCT was unsuitable. IMROZ had an initiation phase comprising 4 cycles of 6 weeks of treatment. This was followed by a maintenance phase of 4‑week treatment cycles in which bortezomib was no longer used. In the maintenance phase, people randomised to the Bor-Len-Dex arm whose condition had progressed were allowed to crossover from Len-Dex to Isa-Len-Dex.

The primary endpoint was progression-free survival (PFS) as assessed by an independent review committee. The EAG noted that the company had presented results using data from the 26 September 2023 data cut, at which time median follow up was 59.7 months. It explained that this data could be considered somewhat immature. This was because median PFS had not been reached in the Isa-Bor-Len-Dex arm and median overall survival (OS) had not been reached in either trial arm. Clinical advice to the EAG was that people in IMROZ had similar demographic and disease characteristics to people seen in the NHS. So, the results of the trial were generalisable to NHS clinical practice. The committee noted that the average age of people in IMROZ was 71.6 years, which was younger than would be expected for people in the NHS. One reason for this was because IMROZ excluded people who were over 80 years. The clinical experts explained that quadruplet combination treatments are usually only suitable for people who are fit enough to have them. They advised that a small proportion of people over 80 years would be considered fit enough to have Isa-Bor-Len-Dex. They added that only about 60% of people currently offered Dar-Len-Dex would be considered fit enough to have Isa-Bor-Len-Dex because of the additional treatment burden of quadruplet over triplet treatment combinations. The committee concluded that the IMROZ population was younger and fitter than the NHS population. But it agreed that the relative effects from IMROZ are likely to be generalisable to NHS clinical practice. It considered whether the data from IMROZ was sufficiently mature. It concluded that, while the data was immature and that this contributed to uncertainty in the survival analysis, the results of the trial were suitable for decision making.

The company explored different options for comparing Isa-Bor-Len-Dex with the relevant comparators: Dar-Len-Dex, Len-Dex, Cyclo-Bor-Dex and Mel-Bor-Pred. No randomised controlled trials were identified to support an indirect treatment comparison (ITC) compared with Cyclo-Bor-Dex. For this comparison, the company explained that it chose an inverse probability weighting (IPW) approach. This used patient-level data from IMROZ and from a retrospective, observational, cohort study done using data from the Flatiron Health Multiple Myeloma Enhanced DataMart. The EAG agreed that, in the absence of direct evidence, this choice of ITC for Cyclo-Bor-Dex was appropriate. For the remaining comparators, the company first considered a network meta-analysis (NMA) for the comparison with Dar-Len-Dex, Len-Dex and Mel-Bor-Pred. The company explained that it had included SWOG S0777 to allow network connectivity but this may have introduced substantial biases to the NMA. This was because outcome data was not reported specifically for the transplant-ineligible subgroup relevant to this decision problem. Instead, it was categorised by:

• age ('under 65 years' compared with '65 years and over')

• intent to transplant ('yes' compared with 'no')

• whether there was a transplant ('yes' compared with 'no').

For the ITT population, death or disease progression occurred in 84 (31.7%) of people in the Isa-Bor-Len-Dex arm and 78 (43.1%) in the Bor-Len-Dex arm. Median follow up was 59.70 months. The hazard ratio was 0.596 (98.5% confidence interval [CI] 0.406 to 0.876; p=0.0005). This corresponded to a 40.4% reduction in the risk of disease progression or death with Isa-Bor-Len-Dex compared with Bor-Len-Dex. The median PFS was not reached (NR) in the Isa-Bor-Len-Dex group and was 54.34 months (95% CI 45.207 to NR) in the Bor-Len-Dex group. OS was a secondary endpoint. At median follow up, 69 (26.0%) of people had died in the Isa-Bor-Len-Dex arm and 59 (32.6%) had died in Bor-Len-Dex arm. The hazard ratio for OS for Isa-Bor-Len-Dex compared with Bor-Len-Dex was 0.776 (99.97% CI 0.407 to 1.480; p=0.0760). Results from the unanchored MAICs and the NMA for Dar-Len-Dex and Len-Dex are considered commercial in confidence by the company and cannot be reported here. For Mel-Bor-Pred, the hazard ratio for the comparison with Isa-Bor-Len-Dex for PFS was 0.20 (95% CI; 0.15 to 0.27) and for OS was 0.50 (95% CI; 0.37 to 0.67). For Cyclo-Bor-Dex, the hazard ratio for the comparison with Isa-Bor-Len-Dex for PFS was 0.34 (95% CI; 0.25 to 0.47) and for OS was 0.48 (95% CI; 0.33 to 0.69).

The company provided a partitioned survival model to estimate the cost effectiveness of Isa-Bor-Len-Dex compared with Dar-Len-Dex and the other comparator combinations. The model included 3 health states: progression free (with subhealth states for on and off treatment), progressed disease and death. The probability of being in each health state was calculated using extrapolated PFS and OS curves. The model used a cycle length of 2 weeks with a half-cycle correction over a lifetime horizon of 29 years (the starting age in the model was 71.6 years). The OS rate was capped by the age and gender-matched general population mortality rate. Everyone was assumed to be dead at age 100 years. In each cycle, the PFS rate was capped by the OS rate for the same time period to ensure that OS was always greater than PFS. The committee concluded that, overall, the company's model structure was acceptable for decision making. But it noted that the multiple myeloma treatment pathway is becoming increasingly complex and with increasing lines of treatment available. So, it noted that having a single progressed-disease health state was a simplification and may not fully reflect the current treatment pathway and quality of life in this health state. It also recalled that the starting age used in the model, based on the age in IMROZ, was younger than would be expected in NHS clinical practice (see section 3.3). So, it requested that the model be updated to include a starting age reflecting the NHS population and based on an appropriate source. Its preference was people having Dar-Len-Dex in Systemic Anti-Cancer Therapy (SACT) data.

In its base case, the company modelled differences in PFS and OS between treatments based on extrapolated data from IMROZ Kaplan–Meier curves and the ITCs. The company jointly fitted distributions to MAIC-adjusted IMROZ data (Isa-Bor-Len-Dex) and comparator (Dar-Len-Dex, Mel-Bor-Pred and Len-Dex) trial OS and PFS Kaplan–Meier data. For Cyclo-Bor-Dex, the company also jointly fitted distributions to IMROZ ITT data for Isa-Bor-Len-Dex and the IPW-adjusted OS and PFS data for Cyclo-Bor-Dex. The company then estimated time-varying hazard ratios by comparing intervention and comparator survival estimates at different time points. These hazard ratios were applied to IMROZ ITT population OS and PFS distributions to generate survival estimates for people having Dar-Len-Dex, Mel-Bor-Pred, Len-Dex and Cyclo-Bor-Dex. The company considered that the most appropriate distributions to generate long-term survival estimates were the Gompertz distribution for OS and the Gamma distribution for PFS. The EAG explained its view that the company's approach was overly complicated. It thought that the fitted distributions used to estimate time-varying hazard ratios could have been used directly in the company's model. It further explained that, at all time points, survival estimates based on IMROZ MAIC-adjusted OS and PFS data were lower than the survival estimates based on IMROZ ITT data. So, generating survival estimates based on IMROZ Isa-Bor-Len-Dex ITT Kaplan–Meier data generated optimistic OS estimates for Isa-Bor-Len-Dex. The EAG also noted that the company had fitted distributions to the full 68 months of available IMROZ data but that, after 60 months, the only events remaining were censoring events. The company agreed with the EAG that most events past 60 months were censoring events. But it explained that limiting analysis to 60 months did not take into account all the available evidence. This was particularly true in the case of the MAIA trial (Dar-Len-Dex compared with Len-Dex in people with newly diagnosed multiple myeloma in whom an ASCT is unsuitable). Survival data from this trial was available for up to 100 months of follow up.

The company further explained that conventional extrapolation techniques apply less emphasis to the tail of data when there are fewer people at risk. Censoring people after 60 months for Isa-Bor-Len-Dex only marginally changed the survival estimates for OS and PFS. This suggested that the tail did not introduce statistically significant uncertainty. The EAG disagreed with the company's preference for including data beyond 60 months, and noted that including this data also contributed to overly optimistic OS estimates for Isa-Bor-Len-Dex. So, at the clarification stage, it asked the company to provide analysis in which distributions were fitted only to the first 60 months of data. The company provided 2 new analyses in response to the EAG's request. Scenario A was limited to 60 months of data from the IMROZ and MAIA, and was the analysis preferred by the EAG. Scenario B used the full 68‑month follow up of IMROZ and also included additional follow up from MAIA up to 100 months. But the company did not do as the EAG had requested. This was to fit separate distributions to the first 60 months of MAIC-adjusted IMROZ Isa-Bor-Len-Dex data and comparator trial data and use these distributions directly in the economic model. Instead, the company maintained its original approach, but using the 60‑month data. The clinical experts explained that the high proportion of censoring events after 60 months in IMROZ added uncertainty to the survival analysis. They added that it is often preferable to use as much clinical trial data as is available. But they thought it was reasonable to exclude IMROZ data after 60 months from the analysis.

After the EAG's request at the clarification stage for new analyses up to 60 months, the company revised its selection of parametric curves for Isa-Bor-Len-Dex. It preferred using Weibull for PFS and generalised gamma for OS. For PFS, the EAG explained that it thought that the Gompertz distribution was a better choice than Weibull. This was because it was similarly ranked and generated estimates that were more closely aligned to clinical expert opinion. For OS, the EAG noted that the Gompertz distribution was a better fit based on Akaike information criterion and Bayesian information criterion statistics. It also generated OS estimates that were closer to clinician landmark estimates. The clinical experts noted that, because of the age of people at diagnosis, it was very difficult to validate estimates of PFS and OS. This was particularly difficult out to a 20‑year timepoint in which the model extrapolations were all overoptimistic. But, despite this caveat, the clinical experts thought that the clinical expert opinion provided by the company was reasonable. They also preferred the EAG's chosen distributions because of their closer alignment with these clinician landmark estimates. The EAG explained that the choice of extrapolation had a relatively small impact on cost effectiveness. This was particularly so when compared with the choice of whether to use the 60‑month or 68‑month analysis.

The committee agreed with the EAG that the company's approach was overly complicated, and that the calculation of time-varying hazard ratios was an unnecessary step. The committee noted that the company's and EAG's approach to modelling OS and PFS was highly uncertain because it relied on the results from the unanchored MAIC. It recalled that it would have preferred to see ITC results from an NMA that maintained randomisation (see section 3.4). So, it was unable to conclude on the most appropriate OS and PFS parametric distribution, and whether 60 or 68 months of data should be used. The committee concluded that its preferred method to model OS and PFS for Isa-Bor-Len-Dex and comparators would be to apply the hazard ratio generated from an NMA to an appropriate reference curve, such as Dar-Len-Dex OS and PFS curves from MAIA or Dar-Len-Dex SACT data.

The company explained that the MAIC results suggested an OS benefit for Isa-Bor-Len-Dex compared with Dar-Len-Dex because the hazard ratio was less than 1. Based on Kaplan–Meier curves, the mortality rates for Isa-Bor-Len-Dex and Dar-Len-Dex were:

• equal for the first 12 months

• possibly higher for Dar-Len-Dex between months 12 and 24

• possibly higher for Isa-Bor-Len-Dex between months 24 and 36, becoming equal again from month 36 onwards.

To estimate the proportion of people having subsequent treatments, the company used IMROZ data after Isa-Bor-Len-Dex and MAIA data after Dar-Len-Dex. It modelled PFS to be substantially longer for people having Isa-Bor-Len-Dex compared with people having Dar-Len-Dex. But it also modelled time to treatment discontinuation (TTD) for Isa-Bor-Len-Dex to be shorter than for Dar-Len-Dex. This resulted in a large difference between PFS and TTD for Isa-Bor-Len-Dex but no substantial difference between PFS and TTD for Dar-Len-Dex. The durations are considered commercial in confidence by the company and cannot be reported here. The EAG noted that both treatments are used until progression and the model assumed that the adverse events profile of Dar-Len-Dex is less favourable than that of Isa-Bor-Len-Dex. So, the EAG would have expected TTD for Isa-Bor-Len-Dex to be longer than for Dar-Len-Dex. It explained that this had an impact on subsequent treatment usage and costs in the model. This was because it was assumed that some people stop treatment with Isa-Bor-Len-Dex but do not have any further treatment until progression. The clinical experts confirmed that some people may stop treatment because of reasons such as toxicity or a desire to avoid repeated hospital visits. They also confirmed that some people may have a deep and lasting response to Isa-Bor-Len-Dex even after treatment has stopped. The EAG noted that IMROZ had a shorter follow up than MAIA, so there was less time for people who had progressed to start a subsequent treatment. It suggested that the total cost associated with Isa-Bor-Len-Dex could have been underestimated in the company's economic model if:

• the difference between PFS and TTD modelled for Isa-Bor-Len-Dex is not reflected in NHS practice

• people who stop treatment with Isa-Bor-Len-Dex have subsequent treatments before progression.

The company did not use the post-progression health-state utility value from IMROZ to inform the economic model. The utility value is considered commercial in confidence by the company, so cannot be reported here. The company thought that the utility value was overly optimistic because health-related quality-of-life records were clustered after progression events. So, it did not fully take account of the full post-progression period. The company also explained that the utility value only accounted for second-line treatment. But it should have accounted for multiple relapses up to fourth line in the economic model. The company also explained its view that this utility value was not sufficiently robust because it was derived from relatively few people. For these reasons the company explained that it preferred to use the post-progression utility value of 0.557 from TA587 (that is, Len-Dex for untreated multiple myeloma). But the EAG noted that the post-progression utility value in IMROZ was based on data from 97 people. It thought this was a large enough sample for the utility value to be robust. It also explained that the PFS utility value from TA587 was low compared with the PFS utility value from IMROZ. So, it follows that the post-progression utility value from TA587 was also potentially too low. The EAG further noted that TA587 was done 12 years ago, and that there were now many more effective treatments available. It explained that the company's economic model was too simplistic to account for utility values falling as people progressed through multiple relapses and subsequent lines of treatment. The EAG also explained that the oversimplification of assuming that everyone would have a post-progression utility value as low as that at the time of TA587 was not clinically plausible. It preferred to use the IMROZ post-progression utility value in the model. The clinical experts agreed that the post-progression utility value should capture health-related quality of life over the course of multiple lines of treatment. So, they thought that it would have been preferable to look at more recent trials that were more representative of treatments used in the NHS. The committee noted that the company had included utility values from the study by Hatswell et al. (2019) as a scenario in the model. The committee agreed that the post-progression utility value from TA587 was low. This was because, at the time of that evaluation, fewer treatment options were available post-progression, which is not reflective of the current treatment pathway. So, the committee concluded that it was not appropriate to use utility values from TA587. It would prefer to use post-progression utility values from IMROZ, or treatment-independent progressed-disease utility values derived by applying a decrement based on Hatswell et al. to the IMROZ PFS utility value.

NICE's manual on health technology evaluations notes that, above a most plausible incremental cost-effectiveness ratio (ICER) of £20,000 per QALY gained, judgements about the acceptability of a technology as an effective use of NHS resources will take into account the degree of certainty around the ICER. The committee will be more cautious about recommending a technology if it is less certain about the ICERs presented. But it will also take into account other aspects including uncaptured health benefits. Because of confidential commercial prices for isatuximab, bortezomib and some comparator treatments, the ICERs are confidential and cannot be reported here. The committee noted the high level of uncertainty, specifically:

• the robustness of the company's ITCs (see section 3.4)

• insufficient clinical evidence for an OS benefit for Isa-Bor-Len-Dex compared with Dar-Len-Dex (see section 3.8)

• inconsistencies in the modelling of TTD and subsequent treatment costs between Isa-Bor-Len-Dex and Dar-Len-Dex (see section 3.9)

• the appropriateness of the company's choice of utility value for the post-progression health state (see section 3.10).

The committee considered that neither the company's nor the EAG's base case included all its preferred assumptions, which were that:

• the economic model be informed by an NMA using SWOG S0777 with randomisation preserved using the ITT population and the no intent-to-transplant subgroup as a proxy for the transplant-ineligible population (see section 3.4)

• the economic model be updated to include a starting age that reflects the NHS population and based on an appropriate source, preferably SACT (see section 3.6)

• OS and PFS for Isa-Bor-Len-Dex and comparators be modelled by applying the hazard ratio generated from the revised NMA to an appropriate reference curve (see section 3.7)

• the economic model use post-progression utility values from IMROZ or values from Hatswell et al (2019; see section 3.10).

The committee considered that there were many areas of uncertainty (see section 3.11) and would like to see clarification on whether:

• it is feasible to do an NMA using SWOG S0777 with randomisation preserved using the no intent-to-transplant subgroup as a proxy for the transplant-ineligible population (see section 3.4)

• there is further clinical evidence and a more robust justification to support the claim of an OS benefit for Isa-Bor-Len-Dex compared with Dar-Len-Dex (see section 3.8)

• the inconsistencies in the modelling of TTD and PFS are clinically justified and would be expected in NHS practice (see section 3.9).

The committee considered the cost effectiveness of Isa-Bor-Len-Dex compared with Dar-Len-Dex and the other relevant comparators. It noted that all the deterministic and probabilistic ICERs were substantially above £30,000 per QALY gained. The exact ICERs cannot be reported here because some prices are confidential.

The committee did not identify any equality issues.

All the ICERs in the company's and EAG's analyses were substantially higher than the range considered to be a cost-effective use of NHS resources. So, Isa-Bor-Len-Dex should not be used for routine commissioning in the NHS for treating newly diagnosed multiple myeloma in adults when a stem cell transplant is unsuitable.