METHODS: Methadone-maintained therapy (MMT) users from three centers in Malaysia had their exhaled carbon monoxide (eCO) levels recorded via the piCO+ and iCOTM Smokerlyzers®, their nicotine dependence assessed with the Malay version of the Fagerström Test for Nicotine Dependence (FTND-M), and daily tobacco intake measured via the Opiate Treatment Index (OTI) Tobacco Q-score. Pearson partial correlations were used to compare the eCO results of both devices, as well as the corresponding FTND-M scores.
RESULTS: Among the 146 participants (mean age 47.9 years, 92.5% male, and 73.3% Malay ethnic group) most (55.5%) were moderate smokers (6-19 cigarettes/day). Mean eCO categories were significantly correlated between both devices (r=0.861, p<0.001), and the first and second readings were significantly correlated for each device (r=0.94 for the piCO+ Smokerlyzer®, p<0.001; r=0.91 for the iCOTM Smokerlyzer®, p<0.001). Exhaled CO correlated positively with FTND-M scores for both devices. The post hoc analysis revealed a significantly lower iCOTM Smokerlyzer® reading of 0.82 (95% CI: 0.69-0.94, p<0.001) compared to that of the piCO+ Smokerlyzer®, and a significant intercept of -0.34 (95% CI: -0.61 - -0.07, p=0.016) on linear regression analysis, suggesting that there may be a calibration error in one or more of the iCOTM Smokerlyzer® devices.
CONCLUSIONS: The iCOTM Smokerlyzer® readings are highly reproducible compared to those of the piCO+ Smokerlyzer®, but calibration guidelines are required for the mobile-phone-based device. Further research is required to assess interchangeability.
METHODS: A cross-sectional survey was conducted among medical students aged 18 years old and above in 7 countries; Egypt, Romania, Malaysia, and Yemen, Iraq, India, and Nigeria. We used social media platforms between September 27 and November 4, 2022. An anonymous online survey using the 5C scale was conducted using snowball and convenience Sampling methods to assess the 5 psychological antecedents of vaccination (i.e., confidence, constraints, complacency, and calculation, as well as collective responsibility).
RESULTS: A total of 2780 participants were recruited. Participants' median age was 22 years and 52.1% of them were males. The 5C psychological antecedents of vaccination were as follows: 55% were confident about vaccination, 10% were complacent, 12% experienced constraints, and 41% calculated the risk and benefit. Lastly, 32% were willing to be vaccinated for the prevention of infection transmission to others. The Country was a significant predictor of confidence, complacency, having constraints, and calculation domains (P < 0.001). Having any idea about the mpox vaccine was linked to 1.6 times higher odds of being more confident [OR = 1.58 (95% CI, 1.26-1.98), P < 0.001] Additionally, living in a rural area significantly increased complacency [OR = 1.42 (95% CI, 1.05-1.95), P = 0.024] as well as having anyone die from mpox [OR = 3.3 (95% CI, 1.64-6.68), P < 0.001]. Education level was associated with increased calculation [OR = 2.74 (95% CI, 1.62-4.64), P < 0.001]. Moreover, being single and having no chronic diseases significantly increased the calculation domain [OR = 1.40 (95% CI, 1.06-1.98), P = 0.02] and [OR = 1.54 (95% CI, 1.10-2.16), P = 0.012] respectively. Predictors of collective responsibility were age 31-45 years [OR = 2.89 (95% CI, 1.29-6.48), P = 0.01], being single [OR = 2.76 (95% CI, 1.94 -3.92), P < 0.001], being a graduate [OR = 1.59 (95% CI (1.32-1.92), P < 0.001], having no chronic disease [OR = 2.14 (95% CI, 1.56-2.93), P < 0.001], and not knowing anyone who died from mpox [OR = 2.54 (95% CI, 1.39-4.64), P < 0.001), as well as living in a middle-income country [OR = 0.623, (95% CI, 0.51-0.73), P < 0.001].
CONCLUSIONS: This study underscores the multifaceted nature of psychological antecedents of vaccination, emphasizing the impact of socio-demographic factors, geographic location, and awareness, as well as previous experiences on individual attitudes and collective responsibility towards vaccination.
OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.
METHODS: We used three single nucleotide polymorphisms (SNPs) (rs8176746, rs505922, and rs8176704) to determine ABO genotype in 2,774 aggressive prostate cancer cases and 4,443 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). Unconditional logistic regression was used to calculate age and study-adjusted odds ratios and 95% confidence intervals for the association between blood type, genotype, and risk of aggressive prostate cancer (Gleason score ≥8 or locally advanced/metastatic disease (stage T3/T4/N1/M1).
RESULTS: We found no association between ABO blood type and risk of aggressive prostate cancer (Type A: OR = 0.97, 95%CI = 0.87-1.08; Type B: OR = 0.92, 95%CI =n0.77-1.09; Type AB: OR = 1.25, 95%CI = 0.98-1.59, compared to Type O, respectively). Similarly, there was no association between "dose" of A or B alleles and aggressive prostate cancer risk.
CONCLUSIONS: ABO blood type was not associated with risk of aggressive prostate cancer.