OBJECTIVES: As the incidence of cancer is increasing and the concern about the sustainability of cancer treatment benefits is rising, recognizing the value of anti-PD(L)-1 inhibitors in neo-adjuvant/adjuvant settings is crucial. Research has shown that anti-PD(L)-1 inhibitors improve recurrence -free survival time in different tumor types for patients diagnosed with an early-stage cancer. We developed a health outcomes projection tool to estimate the health benefits of introducing anti-PD(L)-1 inhibitors to treat patients with an early-stage cancer across different tumor types in Belgium.

METHODS: A multi-tumor, multi-indication model was developed to compare the health outcomes at the population level for two scenarios: one where anti-PD(L)1s can be used for patients with early-stage cancers for the approved neoadjuvant/adjuvant indications, versus a second scenario where anti-PD(L)1s are reserved for patients who develop advanced/metastatic cancer. The model assessed patients with early-stage melanoma (stage III), renal cell carcinoma (RCC), and triple-negative breast cancer (TNBC). For each tumor/indication, a 4-health state Markov model was implemented to quantify life years (LYs) without recurrence/event, quality-adjusted life years (QALYs), number of patients treated with metastatic disease, and deaths. Inputs included clinical trial data and Belgian publicly available data (i.e. number of eligible patients, treatment uptake, etc.)

RESULTS: In Belgium, the introduction of anti-PD(L)1s to treat early-stage cancers (stage III melanoma, RCC and TNBC) is anticipated to avoid 1,199 recurrences (25%), while increasing in 4,154 the LYs without recurrence (13%), preventing 1,384 active treatments (29%) for metastatic disease, and avoiding 663 post-recurrence deaths (29%) between 2022 and 2031.

CONCLUSIONS: Using anti-PD(L)1 inhibitors to treat early-stage cancers can reduce the number of recurrences, extend the time spent by patients free of cancer, and reduce the number of patients requiring metastatic treatment. This model can help inform planning and future discussions around investment in innovative treatments for early-stage cancers.