A treatment-impact model of alectinib for the prediction of recurrence and associated costs in treating resectable ALK+ non-small cell lung cancer

Objectives

Based on the Phase III ALINA trial, alectinib gained US approval as the first anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitor for adjuvant treatment of resectable ALK + non-small cell lung cancer (NSCLC). We used a treatment impact model to estimate associated population-level clinical benefits and cost savings of alectinib vs chemotherapy.

Materials and Methods

Treatment-associated costs for alectinib vs chemotherapy were estimated for five annual cohorts of US patients with stage IB-IIIA ALK+ NSCLC between 2024 and 2028; each cohort was followed for 10 years. Data sources included ALINA. Two treatment scenarios were modelled, with all patients receiving adjuvant treatment with (1) alectinib and (2) chemotherapy. For each scenario, the model simulated the number of patients who received adjuvant treatment and experienced metastatic or non-metastatic recurrence or death and treatment-associated and downstream recurrence costs. Key assumptions were varied in sensitivity analyses. The impact of joint parameter uncertainty was evaluated using probabilistic sensitivity analysis.

Results

In 2024–2028, an estimated 3,130 patients with resectable ALK+ NSCLC would be eligible for adjuvant alectinib treatment. Relative to chemotherapy, alectinib was estimated to prevent 1,531 recurrences and deaths, including 1,059 recurrences to metastatic NSCLC, thus avoiding of $1.31 billion (USD) in costs associated with recurrences and death. Considering upfront adjuvant treatment costs, alectinib was estimated to save $347 million vs chemotherapy.

Conclusions

Adjuvant alectinib treatment improved population-level clinical outcomes and was predicted to generate cost savings in the US. Predicted alectinib benefits were maximized when all indicated patients were tested for the ALK biomarker.