Weiguang Xue

Aim

This study evaluated event-free survival (EFS) as a surrogate outcome for overall survival (OS) in neoadjuvant therapy for early-stage triple-negative breast cancer (eTNBC).

Methods

Meta-regression analyses based on a targeted literature review were used to evaluate the individual- and trial-level associations between EFS and OS.

Results

In the individual-level analyses, 3-year EFS was a significant predictor of 5-year OS (p < 0.01; coefficient of determinations [R2]: 0.82 [95% CI: 0.68-0.91]). Additionally, there was a statistically significant association between the treatment effect on EFS and OS at the trial level (p < 0.001; R2: 0.64 [95% CI: 0.45-0.82]).

Conclusion

This study demonstrates significant associations between EFS and OS and suggests that EFS is a valid surrogate for OS following neoadjuvant therapy for eTNBC.

Introduction

The randomized phase III KEYNOTE-522 trial demonstrated that addition of pembrolizumab to neoadjuvant chemotherapy provided a significant improvement in event-free survival and a favorable trend in overall survival for high-risk early-stage triple-negative breast cancer (eTNBC). This analysis evaluated the cost-effectiveness of pembrolizumab in combination with chemotherapy as neoadjuvant treatment and continued as a single-agent adjuvant treatment after surgery vs. neoadjuvant chemotherapy for patients with high-risk eTNBC in the USA.

Methods

The analysis was conducted from a US third-party public healthcare payer perspective. A multistate transition model was developed using efficacy and safety data from the KEYNOTE-522 trial. The model included four mutually exclusive health states: event-free, locoregional recurrence, distant metastasis, and death to simulate patients' lifetime disease course. Quality-adjusted life years (QALYs) were calculated on the basis of EuroQoL-5 Dimensions utility data collected in KEYNOTE-522. Costs for drug acquisition/administration, adverse events, disease management, and subsequent therapies were reported (2021 US dollars). Costs and outcomes were discounted at 3% annually. A series of sensitivity analyses were performed to test the robustness of the main results.

Results

In the base case scenario, pembrolizumab plus chemotherapy followed by pembrolizumab resulted in expected gains of 3.37 life years (LYs) and 2.90 QALYs, and an incremental cost of $79,046 versus chemotherapy. The incremental cost per QALY gained was $27,285, which is lower than all commonly cited US willingness-to-pay thresholds. Sensitivity analyses showed the results were robust over plausible values of key model inputs and assumptions.

Conclusions

Compared with neoadjuvant chemotherapy, pembrolizumab in combination with chemotherapy as neoadjuvant treatment and continued as a single-agent adjuvant treatment after surgery is considered a cost-effective option for high-risk eTNBC in the USA.

In this review, we summarize the challenges faced by existing oncology treatment sequence decision models and introduce a general framework to conceptualize such models. In the proposed framework, patients with cancer receive at least two lines of therapy (LOTs) followed by palliative care throughout their lifetime. Patients cycle through progression-free and progressive disease health states in each LOT before death. Under this framework, four broad aspects of modeling effectiveness of treatment sequences need exploration. First, disease progression, treatment discontinuation, and the relationship between the two events should be considered. Second, the effectiveness of each LOT depends on its placement in a treatment sequence as the effectiveness of later LOTs may be influenced by the earlier LOTs. Third, the treatment-free interval (TFI; time between discontinuation of earlier LOT and initiation of later LOT) may impact a therapy's effectiveness. Fourth, in the absence of head-to-head trials directly comparing LOTs, indirect treatment comparison (ITC) of outcomes for a specific LOT or even for the entire treatment sequence is important to consider. A search of decision models that estimated effectiveness of at least two lines of oncology therapy was conducted in PubMed (N = 20) and technology appraisals by the National Institute for Health and Care Excellence (N = 26) to assess four methodological aspects related to the model framework: (1) selection of outcomes for effectiveness in a treatment sequence, (2) approaches to adjust the efficacy of a treatment in consideration of its place in the sequence, (3) approaches to address TFIs between LOTs, and (4) incorporation of ITCs to estimate comparators' effectiveness in the absence of direct head-to-head evidence. Most models defined health states based on disease progression on different LOTs while estimating treatment duration outside of the main model framework (30/46) and used data from multiple data sources in different LOTs to model efficacy of a treatment sequence (41/46). No models adjusted efficacy for the characteristics of patients who switched from an earlier LOT to a later LOT or adjusted for the impact of prior therapies, and just six models considered TFIs. While 11 models applied ITC results to estimate efficacy in comparator treatment sequences, the majority limited the ITC to one LOT in the sequence. Thus, there is substantial room to improve the estimation of effectiveness for treatment sequences using existing data when comparing effectiveness of alternative treatment sequences.

Aims

To estimate the budget impact of adding capmatinib, the first FDA approved MET inhibitor, to a US commercial or Medicare health plan for patients with metastatic non-small cell lung cancer (mNSCLC) whose tumors have a mutation that leads to MET exon 14 (METex14) skipping.

Methods

Target population size was estimated using published epidemiology data. Clinical data were obtained from the GEOMETRY mono-1 capmatinib trial and published trials. Treatments in the market mix included crizotinib, pembrolizumab, ramucirumab, and chemotherapy. Uptake of capmatinib and testing rates were based on market research. All costs (drug acquisition and administration, pre-progression, progression, terminal care, adverse event, and testing) were estimated based on public sources (2020 USD).

Results

The number of patients eligible for capmatinib in the first three years was estimated to be 2-3 in a hypothetical 1 million member commercial plan and 34-44 in a hypothetical 1 million member Medicare plan each year. The estimated total budget impact ranged from $9,695 to $67,725 for a commercial plan and $141,350 to $985,695 for Medicare. With capmatinib included, a marginal per member per month budget impact was estimated (commercial: $0.0008 to $0.0056; Medicare: $0.0118 to $0.0821). Capmatinib inclusion resulted in lower medical costs (commercial: -$0.0003 to -$0.0007; Medicare: -$0.0037 to -$0.0106), partially offsetting increased drug costs ($0.0011 to $0.0064; $0.0154 to $0.0928, respectively), and were primarily driven by reductions in progression and terminal care costs (-$0.0003 to -$0.0009; -$0.0037 to -$0.0125, respectively). The results were most sensitive to capmatinib market share, capmatinib price, and treatment duration.

Limitations

Certain assumptions were applied to the model to account for inputs with limited evidence.

Conclusions

The estimated budget impact of including capmatinib for mNSCLC with a METex14 skipping mutation is minimal, and the increased drug costs were partially offset by savings in AEs, and progression-related and terminal care costs.