Primary Risk Drivers
Below is a snapshot of domains that materially influence the MARA Rating.
Clinical effectiveness
The evidence suggests that lorlatinib improves progression-free survival compared to crizotinib, but crizotinib is not typically used as a first-line treatment in the Healthcare. The indirect comparison with alectinib and brigatinib indicates potential benefits, but the ongoing nature of the clinical trial and uncertainties surrounding overall survival limit the strength of the evidence. This strengthens the market access risk assessment and overall reimbursement probability.
Cost effectiveness
The cost-effectiveness estimates for lorlatinib are substantially above the threshold considered acceptable by NICE. The committee concluded that, even with potential discounts, the ICERs remain unacceptably high, indicating that lorlatinib is unlikely to be cost-effective at its current price. This informs pricing and reimbursement risk and pharmaceutical reimbursement forecasting.
Quality of life
While there are indications that lorlatinib may improve quality of life for some patients, the evidence is mixed, and significant side effects have been reported that could negatively impact HRQoL. The committee noted that some patients experienced better quality of life on lorlatinib, but this was not universally applicable. These outcomes align with HTA decision predictors and support pricing and reimbursement assessment.
Supporting Domains
Safety and Adverse Effects
Lorlatinib has a safety profile that is generally acceptable, with manageable adverse events. However, the incidence of grade 3 or 4 adverse events is higher compared to other ALK TKIs, which raises concerns about its overall tolerability. This profile reduces payer uncertainty and supports access risk forecasting.
Comparator Selection
The primary comparator in the CROWN trial, crizotinib, is rarely used as a first-line treatment in the Healthcare, which raises concerns about the relevance of the trial results. The committee noted that alectinib and brigatinib are the standard first-line treatments, making the comparison less applicable. This aligns with HTA comparator analysis and strengthens the market access submission.
Patient Population and Subgroups
The trial population in CROWN is not fully representative of the Healthcare population, particularly regarding ECOG performance status. The committee noted that the lack of evidence for patients with an ECOG of 2 limits the generalizability of the findings. This enhances reimbursement likelihood rating and payer relevance.
Care Pathway Integration
Lorlatinib can be integrated into existing treatment pathways with minor adjustments. The committee noted that while it may require some planning, it does not necessitate significant changes to current clinical practice. This supports budget impact analysis and facilitates market access feasibility.
Resource Use and Cost Implications
The resource implications of lorlatinib are significant, and the committee expressed concerns about the overall budget impact, particularly given the high ICERs. The economic model’s assumptions contribute to uncertainty regarding the broader resource implications. This supports pricing model stress-testing and payer evidence expectations.
Evidence Quality and Robustness
The evidence base is primarily derived from the ongoing CROWN trial, which has limitations due to its immaturity and the uncertainties surrounding the data. The committee noted that while the trial design is robust, the lack of mature data raises concerns about the reliability of the findings. These outcomes align with HTA decision predictors and support pricing and reimbursement assessment.
Uncertainty, Sensitivity, and Broader Impacts
There are significant uncertainties in the clinical evidence and economic modeling, particularly regarding the applicability of trial results to the Healthcare. The committee highlighted that these uncertainties could impact decision-making and the potential for effective use of resources. These factors elevate access risk forecasting within HTA evaluation frameworks.
