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1.
Med Sci Monit ; 26: e921571, 2020 May 07.
Article in English | MEDLINE | ID: mdl-32378682

ABSTRACT

BACKGROUND The evidence on the link of dietary calcium (DCa) to human papillomavirus (HPV) infection is limited. Thus, this research was conducted to explore whether DCa is independently associated with HPV infection status in American women with age of 18 to 59 years old. MATERIAL AND METHODS We performed a secondary analysis from the National Health and Nutrition Examination Survey (NHANES) data set including 7 cycles from 2003 to 2016. A total of 13 475 selected participants were used for data analysis. The interested independent and the outcome variable were DCa and HPV infection status (HPV infection; HPV subtype). Sociodemographic, dietary, laboratory, questionnaire, and physical examination data were covariates. Weighted binary logistic regression and generalized additive model (GAM) were used for the investigation of both linear and non-linear relationships between DCa and HPV infection status. RESULTS Weighted multivariable binary logistic regression indicated DCa was not associated with HPV infection and subtype (OR: 0.93; 95% CI: 0.82-1.05 for HPV infection; OR: 1.09; 95% CI: 0.93-1.28 for HPV subtype). For HPV infection, a non-linear correlation was detected, whose inflection points were 9.78 of log2 DCa. The OR values and the confidence intervals on both sides of inflection point were 0.83 (95% CI: 0.70-0.98) and 1.18 (95% CI: 0.91-1.52), respectively. CONCLUSIONS At the range of 3.32-9.78 of log2 calcium intake, DCa intake was negatively correlated with HPV infection. After this interval, DCa intake was not associated with the risk of HPV infection.


Subject(s)
Calcium, Dietary/pharmacology , Papillomavirus Infections/diagnosis , Adult , Diet , Female , Humans , Logistic Models , Middle Aged , Nutrition Surveys/statistics & numerical data , Papillomaviridae/pathogenicity , Papillomavirus Infections/prevention & control , Prevalence , Risk Factors , Surveys and Questionnaires , United States
2.
Oncotarget ; 7(49): 81870-81879, 2016 Dec 06.
Article in English | MEDLINE | ID: mdl-27835909

ABSTRACT

Allopurinol is widely used for hyperuricemia and gouty arthritis, but is associated with cutaneous adverse drug reactions (CADRs). Recently, HLA-B*58:01 allele was identified as a strong genetic marker for allopurinol-induced CADRs in Han Chinese. However, the magnitude of association and diagnosis value of HLA-B*58:01 in allopurinol-induced CADRs remain inconclusive. To investigate this inconsistency, we conducted a meta-analysis of 21 pharmacogenetic studies, including 551 patients with allopurinol-induced CADRs, and 2,370 allopurinol-tolerant controls as well as 9,592 healthy volunteers. The summary OR for allopurinol-induced CADRs among HLA-B*58:01 carriers was 82.77 (95% CI: 41.63 - 164.58, P < 10-5) and 100.87 (95% CI: 63.91 - 159.21, P < 10-5) in matched and population based studies, respectively. Significant results were also observed when stratified by outcomes and ethnicity. Furthermore, the summary estimates for quantitative analysis of HLA-B*58:01 allele carriers in allopurinol-induced CADRs screening were as follows: sensitivity, 0.93 (95% CI: 0.85 - 0.97); specificity, 0.89 (95% CI: 0.87 - 0.91); positive likelihood ratio, 8.24 (95% CI: 6.92 - 9.81); negative likelihood ratio, 0.084 (95% CI: 0.039 - 0.179); and diagnostic odds ratio, 98.59 (95% CI: 43.31 - 224.41). The AUSROC was 0.92 (95% CI: 0.89-0.94), indicating the high diagnostic performance. Our results indicated that allopurinol-SCAR is strongly associated with HLA-B*58:01, and HLA-B*58:01 is a highly specific and effective genetic marker for the detection allopurinol-induced CADRs, especially for Asian descents.


Subject(s)
Allopurinol/adverse effects , Drug Eruptions/genetics , Gout Suppressants/adverse effects , HLA-B Antigens/genetics , Pharmacogenomic Variants , Asian People/genetics , Drug Eruptions/diagnosis , Drug Eruptions/ethnology , Drug Eruptions/immunology , Genetic Predisposition to Disease , HLA-B Antigens/immunology , Humans , Odds Ratio , Pharmacogenetics , Pharmacogenomic Testing , Risk Assessment , Risk Factors
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