Therapeutics for people with COVID-19

Impact of COVID-19

3.1 COVID-19 is the acute respiratory illness caused by the SARS-CoV-2 virus. It can range from mild to severe infections. In severe infections, excessive immune response to the virus may cause severe complications associated with hospitalisation and death. The need for organ system support, particularly respiratory support, is also a key feature of severe disease and can lead to substantial longer-term morbidity. COVID-19 may cause long-term symptoms that continue or develop after acute infection called 'long COVID'. These are health problems that can last several months which severely impact a person's physical or mental health, or both, and potentially affect their ability to work or do their usual activities. Many people are at increased risk of hospitalisation or death from COVID-19, including people who are immunosuppressed (who have, for example, inflammatory diseases, primary immunodeficiency, chemotherapy, or a transplant) or who have comorbidities (such as heart disease, respiratory disease, diabetes, neurological conditions). Some immunocompromised people are at risk of persistent viral infection if no immunological control is established. Patient experts explained that the increased risk of hospitalisation and death has led to changes in treatment, lifestyle and behaviour during the COVID-19 pandemic because of the need to shield. Patient organisations emphasised the need for treatments to prevent progression to severe COVID-19. They considered that routine availability of these treatments would support a return to normality for many people who already have disease burden from other comorbidities. The committee agreed that the risk of hospitalisation and death, and other longer-term impacts of COVID-19, can result in severe physical and mental burden.

The rapidly evolving SARS-CoV-2 virus

3.2 The global COVID-19 pandemic has caused unprecedented challenges to the healthcare system and this is reflected in the evidence collected on COVID-19 and treatments for it. The SARS-CoV-2 virus has evolved throughout the pandemic, as has the healthcare system's ability to respond to the virus. New variants of the virus and subvariants, referred to as variants of concern, have emerged throughout the pandemic. Each variant can have different properties, such as levels of transmissibility and disease severity. The clinical experts explained that understanding of the disease has changed throughout the pandemic, with increasingly effective supportive care, vaccination and greater natural immunity. At the time of first evaluation committee meeting, the dominant variant of concern in the UK was the Omicron variant, which also has multiple subvariants based on mutations in specific spike proteins. The clinical experts explained that changes in the epidemiology and context of COVID-19 have led to different characteristics of people with COVID-19 than seen earlier in the pandemic. Overall, hospitalisation and mortality from COVID-19 has reduced, and the incidence of COVID-19 pneumonitis in hospital has lowered, as has the need for supplemental oxygen or mechanical ventilation. People may stay longer in hospital, but this is to avoid potential onwards transmission to people with underlying conditions rather than because of complications. The committee noted the changing nature of SARS-CoV-2 and context of the pandemic would impact the generalisability of the evidence for the treatments being evaluated. It agreed that the most appropriate approach would be considering how relevant the clinical data are to the most current context of the disease, but noted that the context and relevant variants are still changing at a fast pace.

Key definitions

3.3 The committee noted that the marketing authorisations for casirivimab plus imdevimab, molnupiravir, nirmatrelvir plus ritonavir, sotrovimab and remdesivir which aim to lower risk of progressing to severe COVID-19 were based on evidence from populations with slightly different definitions of high risk. For example, some trials included people with at least 1 risk factor for severe COVID-19 whereas some had specific age requirements. Understanding of the prognostic effects of risk factors has developed throughout the pandemic, and therefore the available evidence may represent a heterogeneous population. The committee acknowledged the potential limitations of the available evidence but considered it important to clearly define treatment eligibility. The PANORAMIC trial was a large UK platform trial that included people with many different potential risk factors, including chronic conditions and immunosuppression, and allowed enrolment of people over 50. It also allowed for clinical judgement of clinical vulnerability. The independent advisory group report commissioned by the Department of Health and Social Care defined groups of people at highest risk for adverse COVID-19 outcomes, including hospitalisation and death (the McInnes report from here on). The McInnes report was used by the NHS interim commissioning policy on antivirals or neutralising monoclonal antibodies for people with COVID-19 who are not in hospital to define high risk and is a narrower definition than that in PANORAMIC. The clinical experts noted that access to some drugs was available through the commissioning policy at the time of PANORAMIC enrolment. These interim policies and McInnes report's high-risk definition would have influenced the risk level of people who enrolled in PANORAMIC. The committee considered this in its evaluation of the clinical evidence. The patient experts considered that the broadest definition of high risk should be used to maximise the number of people who could benefit from treatment. But 1 patient expert thought that subgroups should be considered separately because considering a mixed group of risk definitions disadvantages the highest risk groups. The committee considered the different definitions of risk and noted that the definition of high risk in the McInnes report is more restrictive than in PANORAMIC.

Other key risk groups

3.4 The clinical experts gave examples of additional considerations around how high-risk groups are affected differently:

Age as an independent risk factor

3.5 PANORAMIC allowed enrolment of people over 50 years who did not have any comorbidities. The committee questioned the inclusion of age over 50 years as an independent risk factor for progression to severe COVID-19. The clinical experts considered that age was an important risk factor, citing the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) study of mortality in the earlier stages of the pandemic that defined age over 50 as a risk factor (Knight et al. 2020). They noted that age over 70 years may be an important determinant of mortality but also considered that the relationship between age and comorbidities is complex, particularly for immunocompromised people. One of the companies considered that age was an important risk factor but noted ongoing debate about what age is appropriate for inclusion in the high-risk group. The clinical experts agreed it was challenging to define an exact age that defines high risk. The committee was concerned that making a recommendation based on age might cause inequality, given that age is a protected characteristic. For this reason, NICE technology appraisal guidance on medicines for cardiovascular disease do not include criteria based on age, despite it being a well-recognised risk factor. The committee noted that age is a protected characteristic and any recommendation including age would need to be assessed for impact on equity of treatment. The committee concluded that more evidence is needed on the impact of age to justify including it as an independent factor that increases risk at similar levels to other comorbidities defined in the McInnes report. This should include evidence, adjusted for comorbidities, from a vaccinated population with the Omicron variant.

High-risk definition conclusion

3.6 The assessment group (AG) explained the approach used to model high-risk groups in its economic model (see section 3.13). It assumes that people have general population survival, have a starting age of 56.6 years and the same hospitalisation rate as PANORAMIC. Therefore, no individual high-risk group is modelled through any other baseline characteristic, and these variables are explored in sensitivity analyses to represent the entire group that would be eligible for treatment. The experts acknowledged the difficulties of defining high risk by various subgroups. The committee recognised that the decision problem required a definition of who has a high risk for progressing to severe COVID-19. It recognised the limitations of the model in characterising a group at high risk but considered the hospitalisation rate to be the most important variable for sensitivity to the clinical inputs (see section 3.13 - 3.14). The committee considered that a single definition of high risk should be used because of the model limitations. Additional functionality would be required to make differential subgroup recommendations and this would not be practical or proportionate to the decision problem. This increased uncertainty of individual subgroup definitions and the need to include the most appropriate risk groups. It considered that the McInnes report's definition of high risk included the most robust evidence of people who have a high risk for progressing to severe COVID-19, and this did not include age as an independent risk factor. The committee considered the use of the Q‑COVID risk calculator in clinical practice but concluded it had limited applicability because of the limitations of the model. The committee noted a wider definition of risk in PANORAMIC was included in the marketing authorisations for each of the treatments. But, it concluded that the definition of risk in the McInnes report is the most robust definition..

Treatments for mild COVID-19

3.7 Current clinical management of COVID-19 in people who have a high risk for progressing to severe COVID-19 includes treatments available through an NHS interim commissioning policy (see section 3.3). As of June 2022, the policy recommendations are as follows:

Treatments for severe COVID-19 in hospital

3.8 In hospital, anti-inflammatories are used along with antivirals and neutralising monoclonal antibodies in people with severe disease. Anti-inflammatories treat the multisystem inflammation which develops later in the COVID-19 disease pathway. The clinical experts said a hierarchical flow of treatments is followed in the hospital and recommending one treatment over another is challenging. The suitability of certain interventions can vary based on respiratory support requirements, minimum COVID-19 symptom duration or renal impairment status. Dexamethasone is standard of care for people who need supplemental oxygen because of COVID-19 progression. Both tocilizumab and baricitinib are available through NHS commissioning policies. Sarilumab is also an option, but only if tocilizumab is not available. Remdesivir is offered to people who need low-flow oxygen. The clinical experts considered that antivirals may have a limited role for people in hospital with COVID-19 because their mechanism of action focuses on blocking viral replication rather than controlling inflammation.

AG's indirect comparison approach

3.9 In line with best practice guidance for assessing COVID-19 treatments (Elvidge et al. 2021), the AG used systematic reviews and network meta-analyses from publicly available sources. These reviews (COVID-NMA and metaEvidence) are updated regularly as 'living' systematic reviews.

The non-hospital setting included these clinical endpoints:

The hospital setting included these clinical endpoints:

The AG highlighted some significant limitations of the approach, because of the changing nature of COVID-19 (see section 3.2). Each trial included in the analysis was done at a different time in the pandemic. Most trials compared an individual treatment against the standard care at the time. This care has evolved in response to better understanding of the disease course, changes to respiratory support and use of dexamethasone. The context of the disease also changed with different circulating variants of concern, and changes in protection through vaccinations and natural immunity over time. Each of these limitations were compounded by significant differences in trial design, baseline characteristics and geographical locations. The AG explained that the analysis assumed any relative effect of treatment is transferable to current clinical management. The clinical experts commented that meta-analysing the trial results may not be appropriate. This is because the weighting of each trial in a meta-analysis may not consider the relevance of the context of each trial within the analysis, for example, with different variants. The committee recognised the high levels of uncertainty with each treatment effect and the context-specific nature of the evidence. To characterise the uncertainty, rather than use probabilistic sensitivity analysis, the AG ran scenarios using the upper and lower confidence limits of each efficacy estimate. This provided scenarios showing 'lower efficacy' and 'higher efficacy' estimates. The AG cautioned the committee that these efficacy scenarios also had limitations because they represented a different uncertainty to that in the evidence base; they represented uncertainty on the estimates in the trial and were therefore sensitive to the number of events in each trial, rather than the context in which the trial happened. Therefore, they would not be sensitive to changes in efficacy against new circulating variants of concern. The committee understood the limitations of the scenario analysis. The committee considered it represented an attempt to address some aspects of uncertainty in the absence of alternative methods to model the uncertainty.

Generalisability to the Omicron variant

3.10 The committee acknowledged that most trials informing the clinical efficacy data pre-dated the Omicron wave, which was the dominant circulating variant of concern at the time of this evaluation. Clinical experts said extrapolating data from past trials was misleading because epidemiology and virus characteristics have changed (see section 3.2). All experts and the committee considered it appropriate to consider how the clinical evidence would generalise to the Omicron variant and its subvariants. The committee recognised that the different treatment mechanisms need to be considered separately as follows:

The committee recognised that the neutralising monoclonal antibodies had shown effectiveness against previous variants. However, it considered that the generalisability concerns in relation to Omicron were too substantial to ignore. It could not comment on the validity of the in vitro data and welcomes comments in response to consultation on this. The committee also could not comment on altering dosages outside of marketing authorisations because the risk–benefit profiles of increased doses have not been assessed by the Medicines and Healthcare Regulatory products Agency (MHRA). The committee considered it unclear how much reduced neutralising effect impacted clinical efficacy and therefore how that uncertainty could be characterised in the different clinical efficacy scenario analyses. It concluded that the WHO's recommendations against the use of casirivimab plus imdevimab and sotrovimab were reasonable. Based on similar evidence suggesting reduced neutralisation effect against new variants, the committee considered it reasonable to extend the likelihood of reduced efficacy to tixagevimab plus cilgavimab. The committee noted that the effectiveness of neutralising monoclonal antibodies will need continuous monitoring for each variant. It considered that antivirals and anti-inflammatories are more likely to maintain effectiveness against new variants but there are still substantial generalisability concerns with the clinical efficacy evidence.

Relative treatment effects for the non-hospital setting

3.11 For the non-hospital setting, the clinical experts considered the relative treatment effects of each treatment to be uncertain without considering the wider context of the trials (see section 3.2). They also noted that multiple interventions could be required and cautioned against the side-by-side comparison of treatment effects (as a fully incremental analysis).

The committee noted the potential for bias in all the comparisons because the indirect comparison used pairwise analysis rather than a network to produce its comparisons. However, the committee considered the heterogeneity of trial outputs and generalisability contributed greater uncertainty to the decision problem.

Relative treatment effects for the hospital setting

3.12 For the hospital setting, the clinical experts noted that standard care had significantly changed over time (see section 3.2). They also cautioned against directly comparing treatments because there is a distinct pathway of care in the hospital setting. This includes when to use respiratory support, anticoagulation treatments and corticosteroids.

Model structure and key drivers of cost-effectiveness

3.13 The economic model for this appraisal was developed by the AG and informed by a previous publication (Rafia et al. 2021) that evaluated COVID-19 treatment in a pre-hospital setting. The AG used a decision tree model structure for treatments in the non-hospital setting that joined with a partitioned survival model in the hospital setting. The decision tree had either an active treatment or standard care arm offered to people with COVID-19. People were hospitalised at a baseline standard care rate, or not hospitalised. Those that were hospitalised entered the partitioned survival model. This section of the model had 3 mutually exclusive health states: discharged from hospital and alive, hospitalised with or without COVID-19, and death (from COVID-19 or any other cause). For people in hospital, level of respiratory support was assumed based on COVID-19 severity, with associated costs and disutilities by health state. The clinical inputs for each of the clinical efficacy scenarios were from the indirect treatment comparison (see section 3.9). The AG fitted parametric distributions to long COVID data from the Office of National Statistics (ONS) and estimated the mean duration of long COVID to be 108.6 weeks. The AG assumed that 100% of people in the hospital setting and 10% in the non-hospital setting would have long COVID. The committee noted that the treatment efficacy was highly uncertain and the most important driver of cost effectiveness, but also noted the following other key drivers of model outputs:

Hospitalisation rates

3.14 The rate of hospitalisation is a key driver of model outputs (see section 3.13) with multiple potential evidence sources. Hospitalisation rate is one the key model input variables that define the group at high risk. To closely align with the marketing authorisations, the AG used a hospitalisation rate of 0.77% from PANORAMIC in its base case to generate the decision-making incremental cost-effectiveness ratios (ICERs) presented in the confidential appendix. PANORAMIC was reflective of the current COVID-19 landscape, including the Omicron variant, but may have excluded some people at higher risk who were eligible for treatment through interim NHS clinical commissioning policies (see section 3.3). Hospitalisation rates varied in other sources of data, including: 1.45% (OPENSAFELY study, people having sotrovimab and molnupiravir); 2.79% (DISCOVER-NOW database interim analysis, UK observational study of people covered in the McInnes report); and 18.4% (study of people with primary and secondary immunodeficiency [Shields et al. 2022]). The clinical experts agreed given the committee's preferred definition of high risk (see section 3.6) that 0.77% could be an underestimation because the highest risk group may have been underrepresented in PANORAMIC (see section 3.3). They acknowledged the difficulty of determining hospitalisation rate without analysing the baseline population and all appropriate groups at risk. The rate is likely to vary substantially based on types of underlying conditions in the high-risk group, with potentially higher rates for severely immunocompromised people, such as transplant recipients and people having chemotherapy. The committee acknowledged significant uncertainty in estimating the hospitalisation rate for the population who have high risk of progressing to severe COVID-19. Based on the strength of the evidence it concluded that it was likely to fall between the underestimate of PANORAMIC at 0.77% and the estimate of 2.79% from the interim database analysis.

Time to discharge

3.15 The amount of time spent in hospital is a key driver of cost effectiveness because of the costs of hospitalisation. Evidence on each treatment showed a relative reduction in time spent in hospital. But the AG noted that this evidence was collected during the pandemic, which could lead to substantial generalisability concerns because the context of care has changed. The committee noted that in clinical practice, time to discharge can sometimes overestimate time in high-cost health states because it can depend on multiple factors (for example, waiting for a negative COVID-19 test). Time to discharge was also considered more important for people who are being discharged to a care home. The AG included scenarios that removed treatment effects on time to discharge and clinical improvement at 28 days to try and account for these potential uncertainties. It noted that the model was not sensitive to these parameters and they had minimal impact on the cost-effectiveness estimates. The committee considered these scenarios to be plausible but potentially conservative if treatments had effects outside of hospitalisation and mortality. However, it considered these were difficult to disentangle from the evidence available.

Utility value assumptions

3.16 The AG used UK age- and sex-adjusted utility values (EQ‑5D‑3L) for the baseline utility estimates in the model. The AG did not apply additional utility decrements in the non-hospital setting for people who did not have long COVID. The age- and sex-adjusted UK general population utility estimates were used for this population instead. During consultation on the AG's draft report, stakeholders critiqued this assumption. They said this may not capture the full benefit of the treatments versus standard care and disadvantage community-based treatments. The AG agreed this was a simplified assumption, but scenario analysis showed it had limited impact on the final ICERs. The committee agreed with the AG's assumption and acknowledged the minor impact on the ICERs. For the hospital setting, the AG used utility decrements from a recent publication of a cost-effectiveness analysis of remdesivir. The utility decrements were originally from a population with recurrent Clostridium difficile infection and influenza. The same in-hospital utility decrements were also applied across ordinal scales 3 to 5. The ordinal scale was an 8‑point scale (1 to 8) used to define progression of COVID-19 severity in the model. During consultation, stakeholders critiqued the use of utility decrements from a non-COVID-19 population. An alternative approach for a utility study was proposed. The approach was to use COVID-19 severity-specific vignettes with EQ-5D-3L questionnaires completed by the UK general population. Some stakeholders also highlighted recent COVID-19 utility-specific systematic reviews that could be used. The AG said a vignette study would not be possible because of the restricted timelines. Across both settings, the AG did not find alternative COVID-19 utility decrements from the stakeholder-suggested systematic reviews. The AG used post-discharge long COVID utility decrements from Evans et al. 2022. The same utility decrement was assumed regardless of ordinal scale status at hospital admission. At AG report consultation, stakeholders suggested an alternative source of post-discharge utility decrements split by history of ordinal scale status. The AG explained that the model structure was unable to allocate post-discharge utility based on historical ordinal scale admission status. It also said that these utility decrements are only applied for the duration of long COVID and are not a key driver of ICERs. The committee agreed with the AG's rationale and the long COVID utility decrement assumptions.

Long COVID costs

3.17 The AG assumed the annual per person management costs of long COVID to be comparable with chronic fatigue syndrome (£1,013). The clinical experts explained there were differences between people with long COVID who were in hospital versus not in hospital. People in hospital would be more likely to have severe complications that incur greater costs from multisystem complications. The AG considered the costs had minimal impact on the cost-effectiveness estimates because they were only applied for the duration of long COVID. But, it also provided scenario analyses with increased average yearly costs (£2,500). The committee agreed these scenarios had minimal effect on the cost-effectiveness estimates but considered that any new UK-specific evidence on long COVID costs should be included if available.

Administration costs

3.18 The AG did not originally include administration costs for oral or subcutaneous treatments. For intravenous treatments a cost of £221 was assumed based on NHS reference code SB12Z. After consultation, the AG updated the assumptions in the model with costs provided by NHS England. NHS England provided Covid Medicines Delivery Unit (CMDU) deployment costs for the administration of oral antivirals (£410) and neutralising monoclonal antibodies (£820). Some companies disagreed with using CMDU deployment costs because these include costs based in secondary care. However, future delivery may be in primary care, which would likely reduce these costs. The NHS England representative explained that the delivery of service is subject to change. In future, integrated care boards will be responsible for treatment delivery currently done by the CMDUs. They also noted that these costs were calculated before implementation of nirmatrelvir plus ritonavir which may increase resource use because of expected requirements to assess contraindications. The committee considered that CMDU deployment costs would likely be similar in the future. This is because the resource required to deliver the treatments would be proportionately similar although in the format of a permanent staffing structure.

Hospitalisation costs

3.19 The AG used unit costs per hospital bed-day from the NHS National Schedule of NHS costs. Before AG draft report consultation, the AG used the following codes for the respective ordinal scales:

During AG report consultation, 1 stakeholder had suggested using alternative codes for ordinal scales 3, 4 and 5 which were as follows: for ordinal scale 3, a weighted average of currency codes DZ11R to DZ11V (lobar, atypical or viral pneumonia, without interventions); for ordinal scale 4, a weighted average of currency codes DZ11N to DZ11Q (lobar, atypical or viral pneumonia, with single interventions); and for ordinal scale 5 a weighted average of DZ11K to DZ11M (lobar, atypical or viral pneumonia, with multiple interventions).

The AG explained these codes were plausible but when it calculated the cost per bed-day, the results lacked face validity. The cost for the more severe ordinal scale 5 was cheaper than ordinal scales 3 and 4. The AG used the stakeholder-suggested approach for ordinal scale 3. An alternative approach was taken for ordinal scales 4 and 5 with more plausible results. The committee acknowledged the changes implemented by the AG and agreed with the AG's final approach.

Incremental cost effectiveness

Uncaptured benefits

3.23 Clinical experts said hospitalisation and mortality rates are becoming less relevant clinical efficacy measures for COVID-19 treatments. They explained this was because of the changing COVID-19 landscape (see section 3.2). In future COVID-19 evaluations, higher QALY gains could be captured if the model includes the impact of treatments on the following outcomes:

Equality issues

3.24 The committee considered potential equality issues, including:

Addressing health inequalities

3.25 The committee noted the equalities issues outlined in section 3.24, and considered flexibility as part of the principles that guide the development of NICE guidance and standards. This emphasises the importance of considering the distribution of health resources fairly within society as a whole, and factors other than relative costs and benefits alone. The committee acknowledged and considered the contraindications of nirmatrelvir plus ritonavir and tocilizumab. It noted that this could affect some people with protected characteristics disproportionately which would contribute to health inequality. The committee said that in theory it would be willing to accept an ICER slightly more than what is usually acceptable if it addressed such health inequalities. However, it noted that departing from NICE's usual range needs to be done with caution, as it risks displacing funding from more cost-effective treatments elsewhere in the NHS, with an overall net loss of health gain Even considering greater flexibility, the ICERs of alternative treatments were substantially higher than what is considered a cost-effective use of resources.