scholarly journals The Benefits of Smoking Cessation

2003 ◽  
Vol 10 (8) ◽  
pp. 422-423
Author(s):  
Nick R Anthonisen
Keyword(s):  
Lung Cancer ◽  
Smoking Cessation ◽  
Medical School ◽  
Cancer Outcomes ◽  
Cancer Rates ◽  
State Of Affairs ◽  
Better Than

In this issue of theCanadian Respiratory Journal, Demeter et al (pages 435-441) describe lung cancer outcomes in a recent Alberta cohort. Not much is new; outcomes are bad, not much better than they were when I was in medical school more than 40 years ago. This is a particularly sad state of affairs in view of the fact that lung cancer is a self-inflicted phenomenon related to smoking. Further, this has been known for 40 years, and only recently have lung cancer rates levelled off in men, though they have continued to increase in women.

scholarly journals Improving lung cancer outcomes through smoking cessation: the Women Against Lung Cancer in Europe (WALCE) experience

2020 ◽  
Vol 12 (7) ◽  
pp. 3877-3882
Author(s):  
Enrica Capelletto ◽  
Francesco Passiglia ◽  
Federica Ferraresi ◽  
Stefania Vallone ◽  
Silvia Novello
Keyword(s):  
Lung Cancer ◽  
Smoking Cessation ◽  
Cancer Outcomes

A Better Solution to the General Problem of Creation

2017 ◽  
Vol 9 (1) ◽  
pp. 147-162
Author(s):  
Jeremy W. Skrzypek
Keyword(s):  
Recent Work ◽  
General Problem ◽  
The State ◽  
State Of Affairs ◽  
Better Than

It is often suggested that, since the state of affairs in which God creates a good universe is better than the state of affairs in which He creates nothing, a perfectly good God would have to create that good universe. Making use of recent work by Christine Korgaard on the relational nature of the good, I argue that the state of affairs in which God creates is actually not better, due to the fact that it is not better for anyone or anything in particular. Hence, even a perfectly good God would not be compelled to create a good universe.

Role of sex hormones in lung cancer

2021 ◽  
pp. 153537022110196
Author(s):  
Nathalie Fuentes ◽  
Miguel Silva Rodriguez ◽  
Patricia Silveyra
Keyword(s):  
Lung Cancer ◽  
Sex Differences ◽  
Sex Hormones ◽  
Hormone Receptors ◽  
Occupational Exposures ◽  
Lung Carcinogenesis ◽  
Male And Female ◽  
Female Sex ◽  
Incidence And Mortality ◽  
Cancer Rates

Lung cancer represents the world’s leading cause of cancer deaths. Sex differences in the incidence and mortality rates for various types of lung cancers have been identified, but the biological and endocrine mechanisms implicated in these disparities have not yet been determined. While some cancers such as lung adenocarcinoma are more commonly found among women than men, others like squamous cell carcinoma display the opposite pattern or show no sex differences. Associations of tobacco product use rates, susceptibility to carcinogens, occupational exposures, and indoor and outdoor air pollution have also been linked to differential rates of lung cancer occurrence and mortality between sexes. While roles for sex hormones in other types of cancers affecting women or men have been identified and described, little is known about the influence of sex hormones in lung cancer. One potential mechanism identified to date is the synergism between estrogen and some tobacco compounds, and oncogene mutations, in inducing the expression of metabolic enzymes, leading to enhanced formation of reactive oxygen species and DNA adducts, and subsequent lung carcinogenesis. In this review, we present the literature available regarding sex differences in cancer rates, associations of male and female sex hormones with lung cancer, the influence of exogenous hormone therapy in women, and potential mechanisms mediated by male and female sex hormone receptors in lung carcinogenesis. The influence of biological sex on lung disease has recently been established, thus new research incorporating this variable will shed light on the mechanisms behind the observed disparities in lung cancer rates, and potentially lead to the development of new therapeutics to treat this devastating disease.

scholarly journals Automated tumor proportion scoring for PD-L1 expression based on multistage ensemble strategy in non-small cell lung cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Boju Pan ◽  
Yuxin Kang ◽  
Yan Jin ◽  
Lin Yang ◽  
Yushuang Zheng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Image Analysis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Automated Image Analysis ◽  
Small Cell Lung ◽  
Cutoff Values ◽  
Scoring Algorithm ◽  
Better Than

Abstract Introduction Programmed cell death ligand-1 (PD-L1) expression is a promising biomarker for identifying treatment related to non-small cell lung cancer (NSCLC). Automated image analysis served as an aided PD-L1 scoring tool for pathologists to reduce inter- and intrareader variability. We developed a novel automated tumor proportion scoring (TPS) algorithm, and evaluated the concordance of this image analysis algorithm with pathologist scores. Methods We included 230 NSCLC samples prepared and stained using the PD-L1(SP263) and PD-L1(22C3) antibodies separately. The scoring algorithm was based on regional segmentation and cellular detection. We used 30 PD-L1(SP263) slides for algorithm training and validation. Results Overall, 192 SP263 samples and 117 22C3 samples were amenable to image analysis scoring. Automated image analysis and pathologist scores were highly concordant [intraclass correlation coefficient (ICC) = 0.873 and 0.737]. Concordances at moderate and high cutoff values were better than at low cutoff values significantly. For SP263 and 22C3, the concordances in squamous cell carcinomas were better than adenocarcinomas (SP263 ICC = 0.884 vs 0.783; 22C3 ICC = 0.782 vs 0.500). In addition, our automated immune cell proportion scoring (IPS) scores achieved high positive correlation with the pathologists TPS scores. Conclusions The novel automated image analysis scoring algorithm permitted quantitative comparison with existing PD-L1 diagnostic assays and demonstrated effectiveness by combining cellular and regional information for image algorithm training. Meanwhile, the fact that concordances vary in different subtypes of NSCLC samples, which should be considered in algorithm development.

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