Market access update
How will Covid-19 shape the evidence assessed by payers and HTA decision-makers?
Written by Jan McKendrick
As the Covid-19 pandemic continues to affect the health and economic climate, pharmaceutical manufacturers are focused on ensuring that they can deliver clinical trial results that support regulatory approval while minimizing or avoiding delays in the approval process.
Although regulators have been issuing guidance on Covid-19, the consequences for health technology assessment (HTA) have not been explicitly discussed. Guidance from agencies to date has been mostly around how processes have had to adapt because of the pandemic, rather than on the potential impact on the evidence required to support the process.
Overall, it is expected that the pandemic will affect trial outcomes and other evidence collected during this period, which will inevitably have an impact on HTA. The potential issues arising from this may be with us for quite a few years to come.
Jan McKendrick, Senior Director at PRMA Consulting, has a background as a clinical trial statistician and has been working in HTA/market access for over 20 years. In this market access update, she summarizes 3 of the key issues arising from the pandemic that relate to evidence that payers and HTA agencies will need to assess in the future:
- Quality of clinical trials
- Interpreting endpoints
- Impact on real-world evidence (RWE)
1. Quality of the trial
The quality of the clinical evidence is a key consideration for many HTA agencies. In some markets there are specific criteria and patient retention rates for trials, beyond which the trial results are considered to be too uncertain for a meaningful HTA review. It is quite possible that staying within the acceptable patient drop-out thresholds may not be feasible for some trials conducted during the Covid-19 period.
In Germany, for example, missing data can reduce the level of certainty about the evidence. This could result in the scenario where a large proportion of patients in a trial are lost between baseline and the first post-baseline assessment, potentially due to Covid-19, leading to a negative impact on the consideration of additional benefit.
And in terms of data quality, how will agencies assess the impact of any treatment interruptions? How will trial quality be assessed if the frequency and/or timing of endpoint assessment has had to be amended? To what extent will HTA agencies accept a potentially higher rate of protocol violations?
So will HTA agencies have to change how they assess trial quality during and after the Covid-19 pandemic?
2. Interpreting endpoints
Careful thought will need to be given as to how to disentangle the impact of disease, treatment, and Covid-19 on clinical outcomes. For example, how will the impact of Covid-19 be reflected in HRQL data collected over a longer period of time, such as comparisons of data collected in 2019 vs 2020? How will the safety profile and adverse event data be viewed if vulnerable patients have been shielded from all infections?
Mortality data collected over this time period will potentially reflect changes in the underlying mortality rates in many countries due to the pandemic– the expected one-to-one correspondence between cause-specific hazard and event rates is lost. The measurement of many other endpoints that are more directly linked to the virus symptoms, such as measures of respiratory function, will also potentially be impacted and the link to Covid-19 may not be fully understood.
How will agencies and manufacturers view the value and credibility of different endpoints?
3. Impact on RWE
There is increasing use of RWE to support HTA reviews and it is likely that the real-world data collected in the Covid-19 period will reflect a different kind of “real world” to the one before or after the pandemic.
When using data from disease registries, for example, it may not be possible to establish the impact of Covid-19 on the data collected if the registries did not collect evidence on patients’ Covid-19 status; in this scenario, it may not be possible to make analytical adjustments for this as a potential confounder. This may lead to concerns about uncertainty and bias being introduced to the data and will also impact comparisons using historical controls.
There will also be an impact on analyses that rely on RWE as an external control group – when different data sets are compared, consideration should be given to whether one data set is collected during a Covid-19 period and, if so, how that impacts the outcomes.
How should manufacturers identify and adjust for the impact of Covid-19 on different data sources, particularly those that reflect the “real world”?
What potential issues would you add to this list?
We would be interested to hear from you about the issues that you would add to this list.
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