The Comparative Non-Small Cell Lung Cancer (NSCLC) Health Outcomes Model uses a Markov cohort model approach to estimate the population health outcomes of US patients with locally advanced or metastatic NSCLC under different access policies. The model comprises a base case which simulates health outcomes in the US, and five additional scenarios in which US access conditions are replaced by policies from five comparator countries (Australia, Canada, France, South Korea and the United Kingdom). Under each scenario the model controls for differences in regulatory approval timelines to focus on the timeliness and comprehensiveness of reimbursement coverage. Results: Model outcomes indicate that US patients diagnosed with locally advanced and metastatic NSCLC between 2006 and 2017 have gained 201,700 life years in total due to access to innovative medicines. US patients would lose half of this survival benefit if they instead experienced the access conditions of the other comparator countries. Significant variation in outcomes existed between the access conditions of different countries, with the Australian system leading to the largest decrease in life years (-74%). Conclusions: The difference in health outcomes among the scenarios demonstrates how access policies can impact the population health of NSCLC patients. Our study supports the importance of continued timely access to cancer medicines in the US and underscores the potential health impacts from adopting more restrictive approaches used by foreign countries.

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Scoring on ASCO and ESMO frameworks for 102 advanced oncology drugs were taken from Cherny 2018. Corresponding final appraisal documents by NICE were reviewed. Data were extracted for indication, comparators, clinical benefit assessment, toxicity, quality of life, and cost-effectiveness. NICE committee's final decision was recorded: recommended or not, with restriction in indication or with a patient access scheme (PAS) or on the cancer drugs fund (CDF). The relationship between ASCO/ESMO scores and NICE recommendation was investigated. Results: 79% of the 102 drugs included in Cherny 2018 were assessed by NICE; 45% were recommended by NICE, 22% were with PAS and 12% on the CDF. Of the recommended treatments, 82% and 93% were associated with a moderate to high clinical benefit score on ASCO (.40) and ESMO (.3), respectively. Treatments with restricted recommendation based on indication and on CDF were associated with the highest mean ASCO (54) and ESMO (4) benefit score. Cost-effectiveness was less correlated with clinical scoring, potentially suggesting that pricing does not fully reflect clinical benefit. The cost-effectiveness analysis was limited by the confidential nature of the final agreed price. Conclusions: An association was found between NICE recommendations and clinical benefit assessments by ASCO and ESMO despite the difference in performance criteria, clinical evidence, comparator choice, disease burden, and cost-effectiveness, adopted by payers and clinical frameworks.

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ysis, logistic analysis, survival analysis, and recursive partitioning decision analysis were used to estimate the relationship between the financial impact of a new drug indication and the probability of its reimbursement. The multivariable analyses controlled for other clinical and economic variables that have been shown to be correlated with the probability of reimbursement, including the cost per qualityadjusted life-year gained. RESULTS: In all analyses, financial impact was a significant predictor of the probability of reimbursement. For example, in the logistic analysis, the odds ratio of reimbursement for a drug submission with a financial impact greater than A$10 million compared with A$0 or less was 0.12 (95% confidence interval [CI]: 0.03-0.55); the odds ratio of reimbursement for a drug submission with a financial impact greater than A$0 up through A$10 million compared with A$0 or less was 0.16 (95% CI: 0.04-0.60). Similar results were obtained in the survival analysis. In the recursive partition decision analysis, the first split of the data was for submissions with a positive financial impact compared with those with a negative financial impact. CONCLUSIONS: In Australia, financial impact on the health care system is an important determinant of whether a new drug is recommended for reimbursement, even when cost-effectiveness estimates and other clinical and economic variables are controlled.OBJECTIVES: Cellular therapies and regenerative medicines, are poised to have the same paradigm-shifting influence on healthcare as monoclonal antibodies (mABs) and personalized medicine. While these therapies hold similarities to conventional biopharmaceuticals, they also differ in material ways including attributes of both medical devices and pharmaceuticals; use of multiple procedures to prepare and deliver cells; and the potential to cure some diseases. Because of their complexity, these technologies are also anticipated to be costly and face heavy scrutiny of value. The objective of this research is to evaluate recent reimbursement policies on regenerative medicines, compare them to current biopharmaceuticals, and evaluate lessons for health economics and outcomes research (HEOR) and reimbursement planning. METHODS: A search of US HTAs from the Centers for Medicare and Medicaid Services, the Agency for Healthcare Research and Quality (AHRQ), the BlueCross BlueShield Technology Evaluation Center and publicly available commercial payer coverage policies was conducted to identify reimbursement recommendations and supporting rationale. A review of the literature, including the Cochrane Library and PubMed was also conducted using relevant MeSH terms and text words to identify additional reimbursement issues associated with regenerative medicines. RESULTS: Although a nascent treatment area, over 15 technology assessments and coverage policies on regenerative medicines were available from US HTA agencies and payers. Different from most other technologies, some noncoverage positions have been established prior to t...