Economic evaluation of nivolumab for the treatment of second-line advanced squamous NSCLC in Canada: a comparison of modeling approaches to estimate and extrapolate survival outcomes

Abstract

Background Lung cancer is the most common type of cancer in the world and is associated with significant mortality. Nivolumab demonstrated statistically significant improvements in progression-free survival (PFS) and overall survival (OS) for patients with advanced squamous non-small cell lung cancer (NSCLC) who were previously treated. The cost-effectiveness of nivolumab has not been assessed in Canada. A contentious component of projecting long-term cost and outcomes in cancer relates to the modeling approach adopted, with the two most common approaches being partitioned survival (PS) and Markov models. The objectives of this analysis were to estimate the cost-utility of nivolumab and to compare the results using these alternative modeling approaches. Methods Both PS and Markov models were developed using docetaxel and erlotinib as comparators. A three-health state model was used consisting of progression-free, progressed disease, and death. Disease progression and time to progression were estimated by identifying best-fitting survival curves from the clinical trial data for PFS and OS. Expected costs and health outcomes were calculated by combining health-state occupancy with medical resource use and quality-of-life assigned to each of the three health states. The health outcomes included in the model were survival and quality-adjusted-life-years (QALYs). Results Nivolumab was found to have the highest expected per-patient cost, but also improved per-patient life years (LYs) and QALYs. Nivolumab cost an additional $151,560 and $140,601 per QALY gained compared to docetaxel and erlotinib, respectively, using a PS model approach. The cost-utility estimates using a Markov model were very similar ($152,229 and $141,838, respectively, per QALY gained). Conclusions Nivolumab was found to involve a trade-off between improved patient survival and QALYs, and increased cost. It was found that the use of a PS or Markov model produced very similar estimates of expected cost, outcomes, and incremental cost-utility.

Cost Effectiveness of PD-L1-Based Test-and-Treat Strategy with Pembrolizumab as the First-Line Treatment for Metastatic NSCLC in Hong Kong

“…A potential for inherent bias in a partitioned survival model has recently been raised by hypothetical modelling and simulated data [39,40]. However, an empirical analysis using real-world data by Goeree et al [41] found that the partitioned survival model and the Markov model produced similar ICER estimates in advanced NSCLC, confirming the structural validity of the partitioned survival approach in the current analysis [41]. Still, uncertainty is inherent in the survival projections/extrapolation of PFS and OS to model beyond the trial period.…”

Cost-Effectiveness of Nivolumab in Recurrent Metastatic Head and Neck Squamous Cell Carcinoma

“…Similar economic evaluations of nivolumab for the treatment of various tumors types have consistently come to the same conclusion. An economic evaluation of nivolumab for the treatment of NSCLC in Canada resulted in an ICER of $151,560 CAD per QALY compared with docetaxel . Similarly, in Switzerland, an evaluation of nivolumab compared with docetaxel for the treatment of advanced NSCLC resulted in an ICER of 177,478 Swiss francs ($245,962 CAD) per QALY .…”

Scientific Advances in Thoracic Oncology 2016

“…Cost-effectiveness studies suggest that the costs of many new treatments, including multiplex genomic testing, 250 novel targeted kinase inhibitors 251 and checkpoint inhibitors, are above traditional willingness-to-pay thresholds. [252][253][254] Each jurisdiction must determine its own willingness to pay for new treatments, which varies across countries and health care systems. Given that severe financial toxicity is recognized as a potential predictor of early mortality in lung and other cancers, 255 implementing strategies to ensure affordable access to treatment has never been more important for patients with lung cancer and their families.…”