Impact of smoking cessation duration on lung cancer mortality: A systematic review and meta-analysis.

BACKGROUND: Smoking history is a heterogeneous situation for different populations, and numerous studies suggest that smoking cessation is conducive to reduce the mortality of lung cancer. However, no quantitative meta-analysis regarding smoking cessation duration based on different populations has demonstrated it clearly. METHODS: We systematically searched four electronic databases (PubMed, Embase, the Cochrane Central Register of Controlled Trials, and Scoups) till February 2023. Eligible studies reported the association between lung cancer survival and duration of smoking cessation. Additionally, we stratified the study population according to whether they had lung cancer at the time they quit smoking. Studies were pooled with the random-effects model. RESULTS: Out of the 11,361 potential studies initially identified, we included 24 studies involving 969,560 individuals in our analysis. Lung cancer mortality varied across two groups: general quitters and peri-diagnosis quitters. For general quitters, those who had quit smoking for less than 10 years exhibited an RR of 0.64 (95% CI [0.55-0.76]), while those who quit for 10-20 years had an RR of 0.33 (0.25-0.43), over 20 years had an RR of 0.16 (0.11-0.24), and never-smokers had an RR at 0.11 (0.07-0.15). Among peri-diagnosis quitters, the 1-year Overall Survival (OS) showed an RR of 0.80 (0.67-0.96), the 2-year OS had an RR of 0.89 (0.80-0.98), the 3-year OS had an RR of 0.93 (0.84-1.03), and the 5-year OS had an RR of 0.85 (0.76-0.96). CONCLUSIONS: Earlier and longer smoking cessation is associated with reduced lung cancer mortality, no matter in which cessation stage for two different populations.

Clinical characteristics and prognostic outcomes for adenocarcinoma of esophagogastric junction in early-onset patients: a population-based appraisal.

PURPOSE: Malignancies of the upper gastrointestinal tract are rare in early-onset patients outside the hereditary genetic disorders. There are few reports describing adenocarcinoma of the esophagogastric junction (AEG) in extremely early-onset patients aged under 50 years old. The aim of this study was to describe the clinicopathological features and prognosis of adenocarcinoma of esophagogastric junction (AEG) in early-onset patients among three successive periods: 1975-1989 (period 1), 1990-2004 (period 2), and 2005-2017 (period 3). METHODS: Between 1975 and 2017, data were extracted from the Surveillance, Epidemiology, and End Results database, and 18,278 patients with AEG were enrolled. Three age groups of patients were identified: < 50, 50-69, and ≥ 70 years of age. Clinicopathological characteristics and prognostic outcomes were reviewed and compared among three groups over three periods (1975-89, 1990-04, and 2005-2017). Multivariate Cox regression analysis was performed to adjust for covariate effects related to both overall survival (OS) and cancer-specific survival (CSS). RESULTS: Among three age groups, early-onset patients were more likely to present with higher tumor grade, advanced nodal, and distant metastatic disease at diagnosis than other groups (p < 0.01 for both). In comparison to the older group, a higher proportion of patients in the early-onset group received chemotherapy and radiation treatment. After adjusting for covariates, early-onset patients had a better CSS and OS than elderly patients. CONCLUSIONS: Early-onset AEG patients were more likely than other age groups to present with advanced disease upon diagnosis. However, the prognosis of early-onset patients was better than their older counterparts after adjustment for covariates. The dissimilarities in tolerance to treatment among early-onset, middle-aged, and elderly patients could be the reason for this difference.

Comparison of an Artificial Neural Network and a Response Surface Model during the Extraction of Selenium-Containing Protein from Selenium-Enriched Brassica napus L.

In this study, the extraction conditions for selenium-enriched rape protein (SEP) were optimized by applying a response surface methodology (RSM) and artificial neural network (ANN) model, and then, the optimal conditions were obtained using a genetic algorithm (GA). Then, the antioxidant power of the SEP was examined by using the DPPH, ABTS, and CCK-8 (Cell Counting Kit-8), and its anticancer activities were explored by conducting a cell migration test. The results showed that compared with the RSM model, the ANN model was more accurate with a higher determination coefficient and fewer errors when it was applied to optimize the extraction method. The data obtained for SEP using a GA were as follows: the extraction temperature was 59.4 °C, the extraction time was 3.0 h, the alkaline concentration was 0.24 mol/L, the liquid-to-material ratio was 65.2 mL/g, and the predicted content of protein was 58.04 mg/g. The protein was extracted under the conditions obtained by the GA; the real content of protein was 57.69 mg/g, and the protein yield was 61.71%. Finally, as the concentration of the selenium-containing protein increased, it showed increased ability in scavenging free radicals and was influential in inhibiting the proliferation and migration of HepG2 cells.

Comparison of Four Lymph Node Staging Systems in Gastric Adenocarcinoma after Neoadjuvant Therapy - A Population-Based Study.

Introduction: Neoadjuvant treatment leads in a reduction in positive lymph nodes and examined lymph nodes (ELN), which may affect assessment of lymph node staging and postoperative treatment. We aimed to compare the staging systems of lymph node ratio (LNR), the positive logarithm ratio of lymph nodes (LODDS), negative lymph nodes (NLN), and the 8th AJCC ypN stage for patients with gastric adenocarcinoma after neoadjuvant therapy. Materials and Methods: Data was collected from the Surveillance, Epidemiology, and End Results database and 1,551 patients with gastric adenocarcinoma who underwent neoadjuvant therapy and radical surgery were enrolled. Harrell's concordance index, the Receiver Operative Curve, the likelihood ratio test, and the Akaike information criterion were used to compare the predictive abilities of the different staging systems. Results: Among the 1,551 patients, 689 (44.4%) had ELN < 16 and node-negative patients accounted for 395 (25.5%). When regarded as the categorical variable, LNR had better discrimination power, higher homogeneity, and better model fitness for CSS and OS compared to other stage systems, regardless of the status of ELN. When regarded as the continuos variable, LODDS outperformed others for CSS. Furthermore, the NLN staging system performed superior to others in node-negative patients. Conclusions: LNR had a better predictive performance than ypN, LODDS and NLN staging systems regardless of the status of ELN when regarded as the categorical variable, whereas LOODS became the better predictive factor for CSS when regarded as the continuos variable. In node-negative patients, NLN might be a feasible option for evaluating prognosis. A combination of LNR and NLN should be considered as user-friendly method in the clinical prognostic assessment.