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BACKGROUND: Since 2011, the therapeutic landscape of melanoma has changed dramatically because of the adoption of immune checkpoint inhibitor and targeted therapies. The authors sought to quantify the effects of these changes on short-term treatment costs by comparing the first-year cancer-attributable costs in novel (2011)(2012)(2013)(2014)(2015) and historical (2004)(2005)(2006)(2007)(2008)(2009)(2010) treatment eras. METHODS: The authors estimated the first-year cancer-attributable and out-of-pocket (OOP) costs by cancer stage at diagnosis by using a case-control approach. Patients aged ≥67 years with melanoma results were used to calculate the total direct costs of treatment during the first year after the diagnosis of melanoma in the US Medicare population older than 65 years. Costs were reported in 2018 dollars. RESULTS: Costs increased with the stage at diagnosis. Average first-year cancer-attributable costs per patient for stage IV patients increased significantly by 61.

Background: Benefit–harm tradeoffs of melanoma screening depend on disease risk and treatment efficacy. We developed a model to project outcomes of screening for melanoma in populations with different risks under historic and novel systemic treatments. Methods: Computer simulation model of a screening program with specified impact on overall and advanced-stage incidence. Inputs included meta-analyses of treatment trials, cancer registry data, and a melanoma risk prediction study Results: Assuming 50% reduction in advanced stage under screening, the model projected 59 and 38 lives saved per 100,000 men under historic and novel treatments, respectively. With 10% increase in stage I, the model projects 2.9 and 4.7 overdiagnosed cases per life saved and number needed to be screened (NNS) equal to 1695 and 2632 under historical and novel treatments. When screening was performed only for the 20% of individuals with highest predicted risk, 34 and 22 lives per 100,000 were saved under historic and novel treatments. Similar results were obtained for women, but lives saved were lower. Conclusions: Melanoma early detection programs must shift a substantial fraction of cases from advanced to localized stage to be sustainable. Advances in systemic therapies for melanoma might noticeably reduce benefits of screening, but restricting screening to individuals at highest risk will likely reduce intervention efforts and harms while preserving >50% of the benefit of nontargeted screening. Impact: Our accessible modeling framework will help to guide population melanoma screening programs in an era of novel treatments for advanced disease.

This paper presents a new non-parametric seasonal unit root testing framework that is robust to periodic non-stationary volatility in innovation variance by making an extension to the fractional seasonal variance ratio unit root tests of Eroğlu et al. (Econ Lett 167:75–80, 2018). The setup allows for both periodic heteroskedasticity structure of Burridge and Taylar (J Econ 104(1):91–117, 2001) and non-stationary volatility structure of Cavaliere and Taylor (Econ Theory 24(1):43-71, 2008). We show that the limiting null distributions of the variance ratio tests depend on nuisance parameters derived from the underlying volatility process. Monte Carlo simulations show that the standard variance ratio tests can be substantially oversized in the presence of such effects. Consequently, we propose wild bootstrap implementations of the variance ratio tests. Wild bootstrap resampling schemes are shown to deliver asymptotically pivotal inference. The simulation evidence depicts that the proposed bootstrap tests perform well in practice and essentially correct the size problems observed in the standard fractional seasonal variance ratio tests, even under extreme patterns of heteroskedasticity. Supplementary Information The online version contains supplementary material available at 10.1007/s00180-022-01211-w.

Background Since low‐dose computed tomography (LDCT) screening was shown to be effective in the National Lung Screening Trial (NLST), novel targeted therapies and immunotherapies for advanced lung cancer have become available. This study investigated the impact of these treatment advances on the expected benefits of LDCT screening. Methods A microsimulation model of LDCT screening for high‐risk individuals under standard systemic treatments (chemotherapy and radiation therapy) and novel treatments (immunotherapy and targeted therapy) was used. The model assumed a reduction in advanced‐stage disease consistent with the NLST, and given the stage at diagnosis, it projected survival. The disease‐specific relative mortality reduction (MR) due to LDCT screening was projected in the trial setting and in a population eligible for LDCT screening under the current US Preventive Services Task Force (USPSTF) recommendations. Results The availability of novel treatments reduced the MR in the LDCT arm of the NLST from 15% to 13.5% and the number of lung cancer deaths prevented from 310 to 224 per 100,000 persons screened. Over 10 years, population LDCT screening based on USPSTF recommendations prevented 374 lung cancer deaths per 100,000 under standard treatments (13.3% MR) and 236 per 100,000 under fully adopted novel treatments (10.6% MR). The number needed to screen to avert one death over 10 years was 270 under standard treatments and 440 under novel treatments. Conclusions The transition from standard systemic treatments to novel treatments is expected to reduce the relative and absolute mortality benefits of LDCT screening. Benefit–harm tradeoffs of LDCT screening are likely to change as novel treatments become widespread.