Being Transparent About Brilliant Failures: An Attempt to Use Real-World Data in a Disease Model for Patients with Castration-Resistant Prostate Cancer.

BACKGROUND: Real-world disease models spanning multiple treatment lines can provide insight into the (cost) effectiveness of treatment sequences in clinical practice. OBJECTIVE: Our objective was to explore whether a disease model based solely on real-world data (RWD) could be used to estimate the effectiveness of treatments for patients with castration-resistant prostate cancer (CRPC) that could then be suitably used in a cost-effectiveness analysis. METHODS: We developed a patient-level simulation model using patient-level data from the Dutch CAPRI registry as input parameters. Time to event (TTE) and overall survival (OS) were estimated with multivariate regression models, and type of event (i.e., next treatment or death) was estimated with multivariate logistic regression models. To test internal validity, TTE and OS from the simulation model were compared with the observed outcomes in the registry. RESULTS: Although patient characteristics and survival outcomes of the simulated data were comparable to those in the observed data (median OS 20.6 vs. 19.8 months, respectively), the disease model was less accurate in estimating differences between treatments (median OS simulated vs. observed population: 18.6 vs. 17.9 [abiraterone acetate plus prednisone], 24.0 vs. 25.0 [enzalutamide], 20.2 vs. 18.7 [docetaxel], and 20.0 vs. 23.8 months [radium-223]). CONCLUSIONS: Overall, the disease model accurately approximated the observed data in the total CRPC population. However, the disease model was unable to predict differences in survival between treatments due to unobserved differences. Therefore, the model is not suitable for cost-effectiveness analysis of CRPC treatment. Using a combination of RWD and data from randomised controlled trials to estimate treatment effectiveness may improve the model.

Cost-effectiveness analysis of the first-line EGFR-TKIs in patients with non-small cell lung cancer harbouring EGFR mutations.

OBJECTIVES: To compare the cost-effectiveness of first-line gefitinib, erlotinib, afatinib, and osimertinib in patients with non-small cell lung cancer (NSCLC) harbouring epidermal growth factor receptor (EGFR) mutations. METHODS: A systematic review and network meta-analysis (NMA) were conducted to compare the relative efficacy of gefitinib, erlotinib, afatinib, and osimertinib in EGFR-mutated NSCLC. To assess the cost-effectiveness of these treatments, a Markov model was developed from Dutch societal perspective. The model was based on the clinical studies included in the NMA. Incremental costs per life-year (LY) and per quality-adjusted life-year (QALY) gained were estimated. Deterministic and probabilistic sensitivity analyses (PSA) were conducted. RESULTS: Total discounted per patient costs for gefitinib, erlotinib, afatinib, and osimertinib were €65,889, €64,035, €69,418, and €131,997, and mean QALYs were 1.36, 1.39, 1.52, and 2.01 per patient, respectively. Erlotinib dominated gefitinib. Afatinib versus erlotinib yielded incremental costs of €27,058/LY and €41,504/QALY gained. Osimertinib resulted in €91,726/LY and €128,343/QALY gained compared to afatinib. PSA showed that gefitinib, erlotinib, afatinib, and osimertinib had 13%, 19%, 43%, and 26% probability to be cost-effective at a threshold of €80,000/QALY. A price reduction of osimertinib of 30% is required for osimertinib to be cost-effective at a threshold of €80,000/QALY. CONCLUSIONS: Osimertinib has a better effectiveness compared to all other TKIs. However, at a Dutch threshold of €80,000/QALY, osimertinib appears not to be cost-effective.

First-line tyrosine kinase inhibitors in EGFR mutation-positive non-small-cell lung cancer: a network meta-analysis.

BACKGROUND: EGFR-tyrosine kinase inhibitors (EGFR-TKIs) including afatinib, dacomitinib, erlotinib, gefitinib, and osimertinib have proven efficacy in terms of progression-free survival (PFS) in patients with non-small-cell lung cancer (NSCLC) harboring EGFR mutations. However, an overall view for comparing efficacy and toxicity on a meta-level is lacking. This study compared efficacy and toxicity of first-line treatment with five different EGFR-TKIs by conducting a network meta-analysis (NMA). METHODS: A systematic review was performed, aiming to find eligible literature. Data of PFS, overall survival (OS), objective response rate (ORR), and adverse events were extracted. An NMA based on Bayesian statistics was established to synthesize the efficacy and toxicity of all treatments. RESULTS: Thirteen randomized controlled trials, including data from 3,539 patients with EGFR-mutated NSCLC, were analyzed. Rank probabilities showed that osimertinib had a potentially better efficacy in terms of PFS and OS compared to all other TKIs. For ORR, afatinib and osimertinib showed a trend of superiority compared to the other four TKIs. Furthermore, there was a high risk of diarrhea and rash for patients treated with afatinib or dacomitinib as well as a moderate risk for treatment with erlotinib, gefitinib, and osimertinib. CONCLUSION: Our study showed a favorable efficacy of osimertinib in terms of PFS and OS compared to all other EGFR-TKIs in patients with NSCLC harboring activating EGFR mutations. Furthermore, gefitinib, erlotinib, and osimertinib were associated with fewer toxicities compared to the other TKIs. Therefore, osimertinib is indicated as a preferable first-line TKI in patients with activating EGFR-mutated NSCLC.

Determining the Comparative Value of Pharmaceutical Risk-Sharing Policies in Non-Small Cell Lung Cancer Using Real-World Data.

BACKGROUND: Risk-sharing arrangements (RSAs) can be used to mitigate uncertainty about the value of a drug by sharing the financial risk between payer and pharmaceutical company. We evaluated the projected impact of alternative RSAs for non-small cell lung cancer (NSCLC) therapies based on real-world data. METHODS: Data on treatment patterns of Dutch NSCLC patients from four different hospitals were used to perform "what-if" analyses, evaluating the costs and benefits likely associated with various RSAs. In the scenarios, drug costs or refunds were based on response evaluation criteria in solid tumors (RECIST) response, survival compared to the pivotal trial, treatment duration, or a fixed cost per patient. Analyses were done for erlotinib, gemcitabine/cisplatin, and pemetrexed/platinum for metastatic NSCLC, and gemcitabine/cisplatin, pemetrexed/cisplatin, and vinorelbine/cisplatin for nonmetastatic NSCLC. RESULTS: Money-back guarantees led to moderate cost reductions to the payer. For conditional treatment continuation schemes, costs and outcomes associated with the different treatments were dispersed. When price was linked to the outcome, the payer's drug costs reduced by 2.5% to 26.7%. Discounted treatment initiation schemes yielded large cost reductions. Utilization caps mainly reduced the costs of erlotinib treatment (by 16%). Given a fixed cost per patient based on projected average use of the drug, risk sharing was unfavorable to the payer because of the lower than projected use. The impact of RSAs on a national scale was dispersed. CONCLUSIONS: For erlotinib and pemetrexed/platinum, large cost reductions were observed with risk sharing. RSAs can mitigate uncertainty around the incremental cost-effectiveness or budget impact of drugs, but only when the type of arrangement matches the setting and type of uncertainty.