Search

Lung cancer screening (LCS) is effective in reducing mortality, particularly when patients adhere to follow-up recommendations standardized by the Lung CT Screening Reporting & Data System (Lung-RADS). Nevertheless, patient adherence to recommended intervals varies, potentially diminishing benefit from screening. We conducted a systematic review and meta-analysis of patient adherence to Lung-RADS-recommended screening intervals. We systematically searched MEDLINE, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials, and major radiology and oncology conference archives between April 28, 2014, and December 17, 2020. Eligible studies mentioned patient adherence to the recommendations of Lung-RADS. The review protocol was registered with PROSPERO (CRD42020189326). We identified 24 eligible studies for qualitative summary, of which 21 were suitable for meta-analysis. The pooled adherence rate was 57% (95% confidence interval: 46%-69%) for defined adherence (e.g., an annual incidence screen was performed within 15 mo) among 6689 patients and 65% (95% confidence interval: 55%-75%) for anytime adherence among 5085 patients. Large heterogeneity in adherence rates between studies was observed (I 2  = 99% for defined adherence, I 2  = 98% for anytime adherence). Heterogeneous adherence rates were associated with Lung-RADS scores, with significantly higher adherence rates among Lung-RADS 3 to 4 than Lung-RADS 1 to 2 (p < 0.05). Patient adherence to Lung-RADS-recommended screening intervals is suboptimal across clinical LCS programs in the United States, especially among patients with results of Lung-RADS categories 1 to 2. To improve adherence rates, future research may focus on implementing tailored interventions after identifying barriers to LCS. We also propose a minimum standardized set of data elements for future pooled analyses of LCS adherence on the basis of our findings., (Copyright © 2021 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

The potential for small molecule organic crystalline materials to become disordered as a result of high shear mechanical processing was investigated. A data-driven model was generated from a database of critical materials properties, which were expected to correlate with the potential of a small molecule organic crystalline solid to become fully disordered by the application of mechanical energy. The model was compared with a previously published disordering model based on fundamental thermodynamic relationships. Samples of 23 crystalline solids were subjected to extensive comminution under controlled temperature conditions; powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC) were used to confirm disordering. Logistic regression was used to investigate the significance of each materials property with respect to the prediction of disordering potential. Seven materials properties (glass transition temperature, melting temperature, heat of fusion, crystallographic density, Young's modulus, molar volume and attachment energy) were identified as having a significant correlation with the potential for material disordering. Stepwise multivariate logistic regression was used to further assess the correlation between disordering potential and each of the seven properties. A linear probability model based on two materials properties (glass transition temperature and molar volume) was developed for the prediction of disordering potential., (Copyright 2009 Wiley-Liss, Inc.)