Contrast-enhanced computed tomography assessment of aortic stenosis.

OBJECTIVES: Non-contrast CT aortic valve calcium scoring ignores the contribution of valvular fibrosis in aortic stenosis. We assessed aortic valve calcific and non-calcific disease using contrast-enhanced CT. METHODS: This was a post hoc analysis of 164 patients (median age 71 (IQR 66-77) years, 78% male) with aortic stenosis (41 mild, 89 moderate, 34 severe; 7% bicuspid) who underwent echocardiography and contrast-enhanced CT as part of imaging studies. Calcific and non-calcific (fibrosis) valve tissue volumes were quantified and indexed to annulus area, using Hounsfield unit thresholds calibrated against blood pool radiodensity. The fibrocalcific ratio assessed the relative contributions of valve fibrosis and calcification. The fibrocalcific volume (sum of indexed non-calcific and calcific volumes) was compared with aortic valve peak velocity and, in a subgroup, histology and valve weight. RESULTS: Contrast-enhanced CT calcium volumes correlated with CT calcium score (r=0.80, p<0.001) and peak aortic jet velocity (r=0.55, p<0.001). The fibrocalcific ratio decreased with increasing aortic stenosis severity (mild: 1.29 (0.98-2.38), moderate: 0.87 (1.48-1.72), severe: 0.47 (0.33-0.78), p<0.001) while the fibrocalcific volume increased (mild: 109 (75-150), moderate: 191 (117-253), severe: 274 (213-344) mm3/cm2). Fibrocalcific volume correlated with ex vivo valve weight (r=0.72, p<0.001). Compared with the Agatston score, fibrocalcific volume demonstrated a better correlation with peak aortic jet velocity (r=0.59 and r=0.67, respectively), particularly in females (r=0.38 and r=0.72, respectively). CONCLUSIONS: Contrast-enhanced CT assessment of aortic valve calcific and non-calcific volumes correlates with aortic stenosis severity and may be preferable to non-contrast CT when fibrosis is a significant contributor to valve obstruction.

The Cost-Effectiveness of High-Risk Lung Cancer Screening and Drivers of Program Efficiency.

INTRODUCTION: Lung cancer risk prediction models have the potential to make programs more affordable; however, the economic evidence is limited. METHODS: Participants in the National Lung Cancer Screening Trial (NLST) were retrospectively identified with the risk prediction tool developed from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. The high-risk subgroup was assessed for lung cancer incidence and demographic characteristics compared with those in the low-risk subgroup and the Pan-Canadian Early Detection of Lung Cancer Study (PanCan), which is an observational study that was high-risk-selected in Canada. A comparison of high-risk screening versus standard care was made with a decision-analytic model using data from the NLST with Canadian cost data from screening and treatment in the PanCan study. Probabilistic and deterministic sensitivity analyses were undertaken to assess uncertainty and identify drivers of program efficiency. RESULTS: Use of the risk prediction tool developed from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial with a threshold set at 2% over 6 years would have reduced the number of individuals who needed to be screened in the NLST by 81%. High-risk screening participants in the NLST had more adverse demographic characteristics than their counterparts in the PanCan study. High-risk screening would cost $20,724 (in 2015 Canadian dollars) per quality-adjusted life-year gained and would be considered cost-effective at a willingness-to-pay threshold of $100,000 in Canadian dollars per quality-adjusted life-year gained with a probability of 0.62. Cost-effectiveness was driven primarily by non-lung cancer outcomes. Higher noncurative drug costs or current costs for immunotherapy and targeted therapies in the United States would render lung cancer screening a cost-saving intervention. CONCLUSIONS: Non-lung cancer outcomes drive screening efficiency in diverse, tobacco-exposed populations. Use of risk selection can reduce the budget impact, and screening may even offer cost savings if noncurative treatment costs continue to rise.

Resource utilization and costs during the initial years of lung cancer screening with computed tomography in Canada.

BACKGROUND: It is estimated that millions of North Americans would qualify for lung cancer screening and that billions of dollars of national health expenditures would be required to support population-based computed tomography lung cancer screening programs. The decision to implement such programs should be informed by data on resource utilization and costs. METHODS: Resource utilization data were collected prospectively from 2059 participants in the Pan-Canadian Early Detection of Lung Cancer Study using low-dose computed tomography (LDCT). Participants who had 2% or greater lung cancer risk over 3 years using a risk prediction tool were recruited from seven major cities across Canada. A cost analysis was conducted from the Canadian public payer's perspective for resources that were used for the screening and treatment of lung cancer in the initial years of the study. RESULTS: The average per-person cost for screening individuals with LDCT was $453 (95% confidence interval [CI], $400-$505) for the initial 18-months of screening following a baseline scan. The screening costs were highly dependent on the detected lung nodule size, presence of cancer, screening intervention, and the screening center. The mean per-person cost of treating lung cancer with curative surgery was $33,344 (95% CI, $31,553-$34,935) over 2 years. This was lower than the cost of treating advanced-stage lung cancer with chemotherapy, radiotherapy, or supportive care alone, ($47,792; 95% CI, $43,254-$52,200; p = 0.061). CONCLUSION: In the Pan-Canadian study, the average cost to screen individuals with a high risk for developing lung cancer using LDCT and the average initial cost of curative intent treatment were lower than the average per-person cost of treating advanced stage lung cancer which infrequently results in a cure.

Immunohistochemistry is a reliable screening tool for identification of ALK rearrangement in non-small-cell lung carcinoma and is antibody dependent.

INTRODUCTION: Fluorescence in situ hybridization (FISH) is the standard procedure for the detection of anaplastic lymphoma receptor tyrosine kinase (ALK) rearrangement in non-small-cell lung carcinoma (NSCLC) but is expensive and time consuming. We tested three antibodies to ALK, using various detection systems, and hypothesized that ALK immunohistochemistry (IHC) may represent a cost-effective and efficient means of screening for ALK rearrangement in NSCLC. METHODS: We screened 377 stage I or II NSCLC cases in a tissue microarray by FISH and IHC (5A4 [Leica Biosystems Newcastle Ltd, Newcastle upon Tyne, UYnited Kingdom] by Nichirei's N-Histofine ALK detection kit [Nichirei Biosciences inc., Tokyo, Japan], 5A4 by Novocastra with ADVANCE [Dako Canada inc., Burlington, Ontario, Canada], D5F3 by Cell Signaling Technology with ADVANCE [Cell Signalling Technologies inc., Danvers, MA], and DAKO clone ALK1 with FLEX [Dako Canada inc., Burlington, Ontario, Canada] and ADVANCE). IHC was scored as 0, 1+, 2+, or 3+. Possibly positive or positive cases were further analyzed by IHC and FISH on whole section. RESULTS: Tissue microarray results were available on 377 cases by IHC and 273 cases by FISH. Eleven cases were positive or possibly positive by either IHC or FISH, and three cases were positive or possibly positive by both methods. Three cases were ALK-positive by FISH on whole section validation. There was no correlation between semiquantitative IHC score (1+, 2+, 3+) and ALK rearrangement by FISH. D5F3 (Cell Signaling by ADVANCE) and 5A4 (Novocastra by ADVANCE) showed the greatest combination of sensitivity (100%) and specificity (87.5% for 5A4 by Novocastra and 75% for D5F3 by Cell Signaling), and produced no false-negative results. CONCLUSIONS: IHC is a reliable screening tool for identification of ALK rearrangement in NSCLC and is antibody dependent. D5F3 (Cell Signaling) and 5A4 (Novocastra) can be used with FISH for identification of IHC-positive cases to reduce screening costs.