Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model.

BACKGROUND: Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors. METHODS: The authors analyzed data from 8448 ever-smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997-2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC-RAT and further explored the potential of improving SPLC detection through risk model-based surveillance using SPLC-RAT versus existing clinical surveillance guidelines. RESULTS: Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person-years. The application of SPLC-RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10-year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC-RAT development cohort), the observed SPLC incidence was significantly elevated in the high-risk versus low-risk subgroup (13.1% vs. 1.1%, p < 1 × 10-6 ). The risk-based surveillance through SPLC-RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow-ups needed to detect one SPLC (162 vs. 202). CONCLUSION: In a large, hospital-based cohort, the authors validated the predictive performance of SPLC-RAT in identifying high-risk survivors of SPLC and showed its potential to improve SPLC detection through risk-based surveillance. PLAIN LANGUAGE SUMMARY: Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.

Advancing peristalsis deciphering in mouse small intestine by multi-parameter tracking.

Assessing gastrointestinal motility lacks simultaneous evaluation of intraluminal pressure (ILP), circular muscle (CM) and longitudinal muscle (LM) contraction, and lumen emptying. In this study, a sophisticated machine was developed that synchronized real-time recordings to quantify the intricate interplay between CM and LM contractions, and their timings for volume changes using high-resolution cameras with machine learning capability, the ILP using pressure transducers and droplet discharge (DD) using droplet counters. Results revealed four distinct phases, BPhase, NPhase, DPhase, and APhase, distinguished by pressure wave amplitudes. Fluid filling impacted LM strength and contraction frequency initially, followed by CM contraction affecting ILP, volume, and the extent of anterograde, retrograde, and segmental contractions during these phases that result in short or long duration DD. This comprehensive analysis sheds light on peristalsis mechanisms, understand their sequence and how one parameter influenced the other, offering insights for managing peristalsis by regulating smooth muscle contractions.

Genome-Wide Association Study of Gallstone Disease Identifies Novel Candidate Genomic Variants in a Latino Community of Southwest USA.

Gallstone disease (GSD) is a prevalent health condition that impacts many adults and is associated with presence of stones in gallbladder cavity that results in inflammation, pain, fever, nausea and vomiting. Several genome-wide association studies (GWAS) in the past have identified genes associated with GSD but only a few were focused on Latino population. To identify genetic risk factors for GSD in Latino population living in the Southwest USA we used self-reported clinical history, physical and lab measurements data in Sangre Por Salud (SPS) cohort and identified participants with and without diagnosis of GSD. We performed a GWAS on this phenotype using GSD cases matched to normal controls based on a tight criterion. We identified several novel loci associated with GSD as well as loci that were previously identified in past GWAS studies. The top 3 loci (MATN2, GPRIN3, GPC6) were strongly associated with GSD phenotype in our combined analysis and a sex stratified analysis results in females were closest to the overall results reflecting a general higher disease prevalence in females. The top identified variants in MATN2, GPRIN3, and GPC6 remain unchanged after local ancestry adjustment in SPS Latino population. Follow-up pathway enrichment analysis suggests enrichment of GO terms that are associated with immunological pathways; enzymatic processes in gallbladder, liver, and gastrointestinal tract; and GSD pathology. Our findings suggest an initial starting point towards better and deeper understanding of differences in gallstone disease pathology, biological mechanisms, and disease progression among Southwest US Latino population.

Finite element analysis of covered microstents.

Currently available neuroendovascular devices are inadequate for effective treatment of many wide-necked or fusiform intracranial aneurysms and intracranial carotid-cavernous fistulae (CCF). Placing a covered microstent across the intracranial aneurysm neck and CCF rent could restore normal vessel morphology by preventing blood flow into the aneurysm lumen or CCF rent. To fabricate covered microstents, our research group has developed highly flexible ultra thin (approximately 150 microm) silicone coverings and elastomerically captured them onto commercially available metal stents without stitching. Preliminary in vivo studies were conducted by placing these covered microstents in the common carotid artery of rabbits. The feasibility of using covered stents was demonstrated. However, the cover affected the deployment pressure and the stents failed occasionally during deployment due to tearing of the cover. Appropriate modeling of covered stents will assist in designing suitable coverings, and help to reduce the failure rate of covered microstents. The purpose of this study is to use the finite element method to determine the mechanical properties of the covered microstent and investigate the effects of the covering on the mechanical behavior of the covered microstent. Variations in the mechanical properties of the covered microstent such as deployment pressure, elastic recoil and longitudinal shortening due to change in thickness and material properties of the cover have been investigated. This work is also important for custom design of covered microstents such as adding cutout holes to save adjacent perforating arteries.