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The 1‐year mortality and health consequences of COVID‐19 in cancer patients are relatively underexplored. In this multicenter cohort study, 166 COVID‐19 patients with cancer were compared with 498 non‐cancer COVID‐19 patients and 498 non‐COVID cancer patients. The 1‐year all‐cause mortality and hospital mortality rates in Cancer COVID‐19 Cohort (30% and 20%) were significantly higher than those in COVID‐19 Cohort (9% and 8%, both P <.001) and Cancer Cohort (16% and 2%, both P < 0.001). The 12‐month all‐cause post‐discharge mortality rate in survival discharged Cancer COVID‐19 Cohort (8%) was higher than that in COVID‐19 Cohort (0.4%, P <.001) but similar to that in Cancer Cohort (15%, P =.084). The incidence of sequelae in Cancer COVID‐19 Cohort (23%, 26/114) is similar to that in COVID‐19 Cohort (30%, 130/432, P =.13). The 1‐year all‐cause mortality was high among patients with hematologic malignancies (59%), followed by those who have nasopharyngeal, brain, and skin tumors (45%), digestive system neoplasm (43%), and lung cancers (32%). The rate was moderate among patients with genitourinary (14%), female genital (13%), breast (11%), and thyroid tumors (0). COVID‐19 patients with cancer showed a high rate of in‐hospital mortality and 1‐year all‐cause mortality, but the 12‐month all‐cause post‐discharge mortality rate in survival discharged cancer COVID‐19 patients was similar to that in Cancer Cohort. Comparing to COVID‐19 Cohort, risk stratification showed that hematologic, nasopharyngeal, brain, digestive system, and lung tumors were high risk (44% vs 9%, P < 0.001), while genitourinary, female genital, breast, and thyroid tumors had moderate risk (10% vs 9%, P =.85) in COVID‐19 Cancer Cohort. Different tumor subtypes had different effects on COVID‐19. But if cancer patients with COVID‐19 manage to survive their COVID‐19 infections, then long‐term mortality appears to be similar to the cancer patients without COVID‐19, and their long‐term clinical sequelae were similar to the COVID‐19 patients without cancer. [ABSTRACT FROM AUTHOR]

Abstract Background NBS1 is a key DNA repair protein in the homologous recombination repair pathway and a signal modifier in the intra-S phase checkpoint that plays important roles in maintaining genomic stability. The NBS1 8360G>C (Glu185Gln) is one of the most commonly studied polymorphisms of the gene for their association with risk of cancers, but the results are conflicting. Methods We performed a meta-analysis using 16 eligible case-control studies (including 17 data sets) with a total of 9,734 patients and 10,325 controls to summarize the data on the association between the NBS1 8360G>C (E185Q) polymorphism and cancer risk. Results Compared with the common 8360GG genotype, the carriers of variant genotypes (i.e., 8360 GC/CC) had a 1.06-fold elevated risk of cancer (95% CI = 1.00–1.12, P = 0.05) in a dominant genetic model as estimated in a fixed effect model. However, the association was not found in an additive genetic model (CC vs GG) (odds ratio, OR = 0.98, 95% CI = 0.85–1.13, P = 0.78) nor in a recessive genetic model (CC vs GC +GG) (OR = 0.94, 95% CI = 0.82–1.07, P = 0.36). The effect of the 8360G>C (E185Q) polymorphism was further evaluated in stratification analysis. It was demonstrated that the increased risk of cancer associated with 8360G>C variant genotypes was more pronounced in the Caucasians (OR = 1.07, 95% CI = 1.01–1.14, P = 0.03). Conclusion Our meta-analysis suggests that the NBS1 E185Q variant genotypes (8360 GC/CC) might be associated with an increased risk of cancer, especially in Caucasians.

Longitudinal data arise frequently in medical studies and it is a common practice to analyze such complex data with nonlinear mixed-effects (NLME) models. However, the following four issues may be critical in longitudinal data analysis. (i) A homogeneous population assumption for models may be unrealistically obscuring important features of between-subject and within-subject variations; (ii) normality assumption for model errors may not always give robust and reliable results, in particular, if the data exhibit skewness; (iii) the responses may be missing and the missingness may be nonignorable; and (iv) some covariates of interest may often be measured with substantial errors. When carrying out statistical inference in such settings, it is important to account for the effects of these data features; otherwise, erroneous or even misleading results may be produced. Inferential procedures can be complicated dramatically when these four data features arise. In this article, the Bayesian joint modeling approach based on a finite mixture of NLME joint models with skew distributions is developed to study simultaneous impact of these four data features, allowing estimates of both model parameters and class membership probabilities at population and individual levels. A real data example is analyzed to demonstrate the proposed methodologies, and to compare various scenarios-based potential models with different specifications of distributions. [ABSTRACT FROM PUBLISHER]

Background: The p16INK4a is an important tumor suppressor gene (TSG) and aberrant methylation of promoter is known to be a major inactivation mechanism of the tumor suppressor and tumor-related genes. Aberrant TSG methylation was considered an important epigenetic silencing mechanism in the progression of head and neck squamous cell carcinoma (HNSCC). However, some studies have reported differences in the methylation frequencies of P16INK4a promoter between cancer and the corresponding control group. Therefore, we conducted a meta-analysis to better identify the association. Methods: PubMed, Ovid, ISI Web of Science, and EMBASE were searched to identify eligible studies to evaluate the association of p16INK4a promoter methylation and HNSCC. Odds ratio (ORs) and 95% confidence intervals (95%CI) were calculated to evaluate the strength of association between p16INK4a promoter methylation and HNSCC. Results: A total of twenty-one studies with 1155 cases and 1017 controls were included in the meta-analysis. The frequencies of p16INK4a promoter methylation in the cancer group were significantly higher than those in the control group (cancer group: median: 46.67%, range = 7.84%-95.12%; control group: median: 18.37%, range = 0–83.33%; respectively). The pooled odds ratio was 3.37 (95%CI = 2.32–4.90) in the cancer group versus the corresponding control group under the random-effects model. Conclusion: This meta-analysis of 21 published studies identified that aberrant methylation of p16INK4a promoter was found to be significantly associated with HNSCC. [ABSTRACT FROM AUTHOR]

Background: The RAS association domain family protein 1a gene (RASSF1A) is one of the tumor suppressor genes (TSG). Inactivation of RASSF1A is critical to the pathogenesis of cancer. Aberrant TSG methylation was considered an important epigenetic silencing mechanism in the progression of ovarian cancer. A number of studies have discussed association between RASSF1A promoter methylation and ovarian cancer. However, they were mostly based on a small number of samples and showed inconsist results, Therefore, we conducted a meta-analysis to better identify the association. Methods: Eligible studies were identified by searching the PubMed, EMBASE, Web of Science, and CNKI databases using a systematic searching strategy. We pooled the odds ratio (ORs) from individual studies using a fixed-effects model. We performed heterogeneity and publication bias analysis simultaneously. Results: Thirteen studies, with 763 ovarian cancer patients and 438 controls were included in the meta-analysis. The frequencies of RASSF1A promoter methylation ranged from 30% to 58% (median is 48%) in the cancer group and 0 to 21% (median is 0) in the control group. The frequencies of RASSF1A promoter methylation in the cancer group were significantly higher than those in the control group. The pooled odds ratio was 11.17 (95% CI = 7.51–16.61) in the cancer group versus the corresponding control group under the fixed-effects model. Conclusion: The results suggested that RASSF1A promoter methylation had a strong association with ovarian cancer. [ABSTRACT FROM AUTHOR]