Increased expression of caspase 1 during active phase of connective tissue disease

Use of machine learning models to predict prognosis of combined pulmonary fibrosis and emphysema in a Chinese population

Background

Combined pulmonary fibrosis and emphysema (CPFE) is a novel clinical entity with a poor prognosis. This study aimed to develop a clinical nomogram model to predict the 1-, 2- and 3-year mortality of patients with CPFE by using the machine learning approach, and to validate the predictive ability of the interstitial lung disease-gender-age-lung physiology (ILD-GAP) model in CPFE.

Methods

The data of CPFE patients from January 2015 to October 2021 who met the inclusion criteria were retrospectively collected. We utilized LASSO regression and multivariable Cox regression analysis to identify the variables associated with the prognosis of CPFE and generate a nomogram. The Harrell's C index, the calibration curve and the area under the receiver operating characteristic (ROC) curve (AUC) were used to evaluate the performance of the nomogram. Then, we performed likelihood ratio test, net reclassification improvement (NRI), integrated discrimination improvement (IDI) and decision curve analysis (DCA) to compare the performance of the nomogram with that of the ILD-GAP model.

Results

A total of 184 patients with CPFE were enrolled. During the follow-up, 90 patients died. After screening out, diffusing lung capacity for carbon monoxide (DLCO), right ventricular diameter (RVD), C-reactive protein (CRP), and globulin were found to be associated with the prognosis of CPFE. The nomogram was then developed by incorporating the above five variables, and it showed a good performance, with a Harrell's C index of 0.757 and an AUC of 0.800 (95% CI 0.736–0.863). Moreover, the calibration plot of the nomogram showed good concordance between the prediction probabilities and the actual observations. The nomogram also improved the discrimination ability of the ILD-GAP model compared to that of the ILD-GAP model alone, and this was substantiated by the likelihood ratio test, NRI and IDI. The significant clinical utility of the nomogram was demonstrated by DCA.

Conclusion

Age, DLCO, RVD, CRP and globulin were identified as being significantly associated with the prognosis of CPFE in our cohort. The nomogram incorporating the 5 variables showed good performance in predicting the mortality of CPFE. In addition, although the nomogram was superior to the ILD-GAP model in the present cohort, further validation is needed to determine the clinical utility of the nomogram.

Ultrasound-Targeted Microbubble Destruction: Modulation in the Tumor Microenvironment and Application in Tumor Immunotherapy

Tumor immunotherapy has shown strong therapeutic potential for stimulating or reconstructing the immune system to control and kill tumor cells. It is a promising and effective anti-cancer treatment besides surgery, radiotherapy and chemotherapy. Presently, some immunotherapy methods have been approved for clinical application, and numerous others have demonstrated promising in vitro results and have entered clinical trial stages. Although immunotherapy has exhibited encouraging results in various cancer types, however, a large proportion of patients are limited from these benefits due to specific characteristics of the tumor microenvironment such as hypoxia, tumor vascular malformation and immune escape, and current limitations of immunotherapy such as off-target toxicity, insufficient drug penetration and accumulation and immune cell dysfunction. Ultrasound-target microbubble destruction (UTMD) treatment can help reduce immunotherapy-related adverse events. Using the ultrasonic cavitation effect of microstreaming, microjets and free radicals, UTMD can cause a series of changes in vascular endothelial cells, such as enhancing endothelial cells' permeability, increasing intracellular calcium levels, regulating gene expression, and stimulating nitric oxide synthase activities. These effects have been shown to promote drug penetration, enhance blood perfusion, increase drug delivery and induce tumor cell death. UTMD, in combination with immunotherapy, has been used to treat melanoma, non-small cell lung cancer, bladder cancer, and ovarian cancer. In this review, we summarized the effects of UTMD on tumor angiogenesis and immune microenvironment, and discussed the application and progress of UTMD in tumor immunotherapy.