Real-world Use of and Spending on New Oral Targeted Cancer Drugs in the US, 2011-2018.

Importance: Launch prices of new cancer drugs in the US have substantially increased in recent years despite growing concerns about the quantity and quality of evidence supporting their approval by the US Food and Drug Administration (FDA). Objective: To assess the use of and spending on new oral targeted cancer drugs among US residents with employer-sponsored insurance between 2011 and 2018, stratified by the strength of available evidence of benefit. Design, Setting, and Participants: In this cross-sectional study, dispensing claims for oral targeted cancer drugs first approved by the FDA between January 1, 2011, and December 31, 2018, were analyzed. The number of patients with drugs dispensed and the total payment for all claims were aggregated by calendar year, and these outcomes were arrayed according to evidence underlying FDA approvals, including pivotal study design (availability of randomized clinical trials) and overall survival (OS) benefit, as documented in drug labels. This study was conducted from July 17, 2019, to July 23, 2021. Main Outcomes and Measures: Annual and cumulative numbers of patients who had dispensing events, and annual and cumulative sums of payment for eligible drugs. Results: Of 37 348 patients who had at least 1 of the 44 new oral targeted drugs dispensed between 2011 and 2018, 21 324 were men (57.1%); mean (SD) age was 64.1 (13.1) years. Most individuals (36 246 [97.0%]) received drugs for which evidence from randomized clinical trials existed; however, a growing share of patients received drugs without documented OS benefit during the study period: from 12.7% in 2011 to 58.8% in 2018. Cumulative spending on all sample drugs totaled $3.5 billion by the end of 2018, of which 96.8% was spent on drugs that were approved based on a pivotal randomized clinical trial. Cumulative spending on drugs without documented OS benefit ($1.8 billion [51.6%]) surpassed that on drugs with documented OS benefit ($1.7 billion [48.4%]) by the end of 2018. Conclusions and Relevance: The findings of this cross-sectional study suggest that drugs used for treatment of cancer without documented OS benefits are adopted in the health system and account for substantial spending.

CT and clinical assessment in asymptomatic and pre-symptomatic patients with early SARS-CoV-2 in outbreak settings.

OBJECTIVES: The early infection dynamics of patients with SARS-CoV-2 are not well understood. We aimed to investigate and characterize associations between clinical, laboratory, and imaging features of asymptomatic and pre-symptomatic patients with SARS-CoV-2. METHODS: Seventy-four patients with RT-PCR-proven SARS-CoV-2 infection were asymptomatic at presentation. All were retrospectively identified from 825 patients with chest CT scans and positive RT-PCR following exposure or travel risks in outbreak settings in Japan and China. CTs were obtained for every patient within a day of admission and were reviewed for infiltrate subtypes and percent with assistance from a deep learning tool. Correlations of clinical, laboratory, and imaging features were analyzed and comparisons were performed using univariate and multivariate logistic regression. RESULTS: Forty-eight of 74 (65%) initially asymptomatic patients had CT infiltrates that pre-dated symptom onset by 3.8 days. The most common CT infiltrates were ground glass opacities (45/48; 94%) and consolidation (22/48; 46%). Patient body temperature (p < 0.01), CRP (p < 0.01), and KL-6 (p = 0.02) were associated with the presence of CT infiltrates. Infiltrate volume (p = 0.01), percent lung involvement (p = 0.01), and consolidation (p = 0.043) were associated with subsequent development of symptoms. CONCLUSIONS: COVID-19 CT infiltrates pre-dated symptoms in two-thirds of patients. Body temperature elevation and laboratory evaluations may identify asymptomatic patients with SARS-CoV-2 CT infiltrates at presentation, and the characteristics of CT infiltrates could help identify asymptomatic SARS-CoV-2 patients who subsequently develop symptoms. The role of chest CT in COVID-19 may be illuminated by a better understanding of CT infiltrates in patients with early disease or SARS-CoV-2 exposure. KEY POINTS: • Forty-eight of 74 (65%) pre-selected asymptomatic patients with SARS-CoV-2 had abnormal chest CT findings. • CT infiltrates pre-dated symptom onset by 3.8 days (range 1-5). • KL-6, CRP, and elevated body temperature identified patients with CT infiltrates. Higher infiltrate volume, percent lung involvement, and pulmonary consolidation identified patients who developed symptoms.

Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge.

Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are often still obtained from manual segmentations on brain MR images, which is a laborious procedure. The automatic WMH segmentation methods exist, but a standardized comparison of the performance of such methods is lacking. We organized a scientific challenge, in which developers could evaluate their methods on a standardized multi-center/-scanner image dataset, giving an objective comparison: the WMH Segmentation Challenge. Sixty T1 + FLAIR images from three MR scanners were released with the manual WMH segmentations for training. A test set of 110 images from five MR scanners was used for evaluation. The segmentation methods had to be containerized and submitted to the challenge organizers. Five evaluation metrics were used to rank the methods: 1) Dice similarity coefficient; 2) modified Hausdorff distance (95th percentile); 3) absolute log-transformed volume difference; 4) sensitivity for detecting individual lesions; and 5) F1-score for individual lesions. In addition, the methods were ranked on their inter-scanner robustness; 20 participants submitted their methods for evaluation. This paper provides a detailed analysis of the results. In brief, there is a cluster of four methods that rank significantly better than the other methods, with one clear winner. The inter-scanner robustness ranking shows that not all the methods generalize to unseen scanners. The challenge remains open for future submissions and provides a public platform for method evaluation.