A genomic-augmented multivariate prognostic model for the survival of natural-killer/T-cell lymphoma patients from an international cohort.

With lowering costs of sequencing and genetic profiling techniques, genetic drivers can now be detected readily in tumors but current prognostic models for Natural-killer/T cell lymphoma (NKTCL) have yet to fully leverage on them for prognosticating patients. Here, we used next-generation sequencing to sequence 260 NKTCL tumors, and trained a genomic prognostic model (GPM) with the genomic mutations and survival data from this retrospective cohort of patients using LASSO Cox regression. The GPM is defined by the mutational status of 13 prognostic genes and is weakly correlated with the risk-features in International Prognostic Index (IPI), Prognostic Index for Natural-Killer cell lymphoma (PINK), and PINK-Epstein-Barr virus (PINK-E). Cox-proportional hazard multivariate regression also showed that the new GPM is independent and significant for both progression-free survival (PFS, HR: 3.73, 95% CI 2.07-6.73; p < .001) and overall survival (OS, HR: 5.23, 95% CI 2.57-10.65; p = .001) with known risk-features of these indices. When we assign an additional risk-score to samples, which are mutant for the GPM, the Harrell's C-indices of GPM-augmented IPI, PINK, and PINK-E improved significantly (p < .001, χ2 test) for both PFS and OS. Thus, we report on how genomic mutational information could steer toward better prognostication of NKTCL patients.

Simulating the Fiscal Impact of Anti-Obesity Medications as an Obesity Reduction Strategy.

While substantial public health investment in anti-smoking initiatives has had demonstrated benefits on health and fiscal outcomes, similar investment in reducing obesity has not been undertaken, despite the substantial burden obesity places on society. Anti-obesity medications (AOMs) are poorly prescribed despite evidence that weight loss is not sustained using other strategies alone.We used a simulation model to estimate the potential impact of 100% uptake of AOMs on Medicare and Medicaid spending, disability payments, and taxes collected relative to status quo with negligible AOM use. Relative to status quo, AOM use simulation would result in Medicare and Medicaid savings of $231.5 billion and $188.8 billion respectively over 75 years. Government tax revenues would increase by $452.8 billion. Overall, the net benefit would be $746.6 billion. Anti-smoking efforts have had substantial benefits for society. A similar investment in obesity reduction, including broad use of AOMs, should be considered.

Changes in mortality associated with cancer drug approvals in the United States from 2000 to 2016.

AIMS: To estimate the extent to which the approvals of new pharmacological therapies were associated with cancer mortality in the USA between 2000 and 2016. MATERIALS AND METHODS: The analysis quantified cancer drug approvals across the 15 tumor types with the highest incidence. Number of approvals in a given time period for each tumor was translated into a treatment stock measure, defined as a weighted sum of new indication approvals since 1976. The primary outcome was the annual tumor-specific cancer mortality, defined as the number of deaths per 100,000 U.S. population. The analysis used a multivariable ordinary least squares and a fixed effects model, controlling for incidence (new cases per 100,000 U.S. population) and the primary exposure, the treatment stock measure by year. RESULTS: Between 2000 and 2016, deaths per 100,000 population across the 15 most common tumor types declined by 24%. Additionally, 10.2 new indications were approved per year across the 15 most common tumor types. Cancer drug approvals were associated with statistically significant deaths averted in 2016 for colorectal cancer (4,991, p = 0.004), lung cancer (33,825, p < 0.001), breast cancer (11,502, p < 0.001), non-Hodgkin's lymphoma (6,636, p < 0.001), leukemia (4,011, p < 0.001), melanoma (1,714, p < 0.001), gastric cancer (758, p = 0.019), and renal cancer (739, p < 0.001). Between 2000 and 2016, new cancer treatments were correlated with 1,291,769 (p < 0.001) total deaths prevented across the 15 most common tumor types. LIMITATIONS AND CONCLUSIONS: Cancer drug approvals between 2000 and 2016 were associated with significant reduction in deaths from the most common cancers in the USA. Mortality changes were largest in prevalent tumor types with relatively more approvals, i.e. lung cancer, breast cancer, melanoma, lymphoma and leukemia. Future research evaluating the relationship between drug approvals and cancer mortality post 2016 is needed.

The potential impact of CAR T-cell treatment delays on society.

OBJECTIVES: To date, breakthrough chimeric antigen receptor (CAR) T-cell therapies, such as tisagenlecleucel, indicated for pediatric acute lymphoblastic leukemia (pALL) and diffuse large B-cell lymphoma (DLBCL), and axicabtagene ciloleucel, indicated for DLBCL, although clinically effective, have been limited by treatment delays. Our study measured the social value of CAR T-cell therapy (CAR T) for relapsed or refractory pALL and DLBCL in the United States and quantified social value lost due to treatment delays. STUDY DESIGN: We used an economic framework for therapy valuation, measuring social value as the sum of consumer surplus and manufacturer profit. Consumer surplus is the difference between the value of health gains from a therapy and its incremental cost, while accounting for indirect costs and benefits to patients. METHODS: For 20 incident cohorts of pALL (n = 20 × 400 = 8000) and DLBCL (n = 20 × 5902 = 118,040), we quantified patient value, calculated as the value of additional quality-adjusted life-years gained with CAR T, minus the incremental cost of CAR T compared with standard of care (SOC). We calculated manufacturer profits using a range of production costs given uncertainties in the production process. Patient value and manufacturer profits were summed to obtain total social value. We measured social value lost from treatment delays, assuming that patients received the SOC while awaiting CAR T-cell treatment. RESULTS: Depending on production costs, as much as $6.5 billion and $34.8 billion in social value was generated for patients with pALL and DLBCL, respectively. However, with 1, 2, or 6 months of treatment delay (assuming $200,000 production costs), the pALL population lost 9.8%, 36.2%, and 67.3% of social value, respectively, whereas the DLBCL population lost 4.2%, 11.5%, and 46.0%, relative to no delay. CONCLUSIONS: The social value of CAR T is significantly limited by treatment delays. Efficient payment mechanisms, adequate capital, and payment policy reform are urgently needed to increase patient access and maximize the value of CAR T.