UNASSIGNED: blood centres are often faced with the problem of donor lapsing resulting in loss of donors from the already strained donor pool. In Zimbabwe, 70% of the donated blood comes from younger donors aged 40 years and below, who at the same time, have high attrition rates. This study seeks to apply the concept of survival analysis in analysing blood donor lapsing rates.
UNASSIGNED: in analysing the donor lapsing and retention rates, data on 450 first-time blood donors at the National Blood Service Zimbabwe, in Harare´s blood bank for the period 2014 to 2017 was extracted from the donors´ database. The Cox proportional hazards (Cox PH) and Kaplan-Meier methods were applied in the analysis. Donor demographic characteristics suspected of having effect on donor lapsing and retention were identified and analysed.
UNASSIGNED: the study findings show that 56.9% of the donors had lapsed by the end of the four-year study period. Results from the multiple Cox PH model indicate that donor age had a significant effect on blood donor retention time (p = 0.000918 < 0.05). The hazard ratio (HR) = 0.615 with 95% CI: (0.461; 0.820) shows that the relatively older donors had a lower hazard (38.5% lower) of lapsing compared to the hazard for younger donors. The effect of gender, blood donor group and donation time interval on donor retention and attrition were not statistically significant. Male donors had HR = 1.03; 95% CI (0.537; 1.99) with (p = 0.922 > 0.05) and donors with a 4-month interval between donations had HR = 1.31; 95% CI (0.667; 2.59) with (p = 0.430 > 0.05).
UNASSIGNED: the study confirmed the problem of donor attrition faced by blood centres. The age of the donor had a significant effect on the retention time of blood donors before lapsing. The older the blood donor, the lower the risk of lapsing. The Zimbabwe National Blood Service (NBSZ) Blood Centre authorities should have a critical mass of individuals above 40 years as potential blood donors because of their reliability in blood donation according to the study findings.

UNASSIGNED: The prevalence of hypertension and uncontrolled hypertension may differ by age and sex.
UNASSIGNED: We included participants in the Atherosclerosis Risk in Communities study at seven study visits over 33 years (visit 1: 15 636 participants; mean age, 54 years; 55% women), estimating sex differences in prevalence of hypertension (systolic blood pressure ≥130 mm Hg; diastolic blood pressure ≥80 mm Hg; or self-reported antihypertension medication use) and uncontrolled hypertension (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg) using unadjusted and comorbidity-adjusted models.
UNASSIGNED: The prevalence of hypertension increased from 40% (ages, 43-46 years) to 93% (ages, 91-94 years). Within hypertensive individuals, the prevalence of uncontrolled hypertension was higher in men (33%) than women (23%) at ages 43 to 46 years but became higher in women than men starting at ages 61 to 64, with 56% of women and 40% men having uncontrolled hypertension at ages 91 to 94. This sex difference was not explained by differences in coronary heart disease, diabetes, body mass index, estimated glomerular filtration rate, number of antihypertension medications, classes of medications, or adherence to medications. In both sexes, uncontrolled hypertension was associated with a higher risk for chronic kidney disease progression (hazard ratio, 1.5 [1.2-1.9]; P=4.5×10-4), heart failure (hazard ratio, 1.6 [1.4-2.0]; P=8.1×10-7), stroke (hazard ratio, 2.1 [1.6-2.8]; P=1.8×10-8), and mortality (hazard ratio, 1.5 [1.3-1.6]; P=6.2×10-19).
UNASSIGNED: Sex differences in the prevalence of hypertension and uncontrolled hypertension vary by age, with the latter having implications for health throughout the life course.

OBJECTIVE: The objective of this study is to evaluate the relationship of psoriasis and neovascular Age-related Macular Degeneration (AMD) in diabetic mellitus (DM) population.
METHODS: Nationwide, population-based, retrospective cohort study.
METHODS: Records of patients who had been diagnosed with type 2 diabetes mellitus over 40 years of age from January 2009 to December 2012 were analyzed. The incidence of neovascular AMD was observed from the index year to December 2018 in all subjects. We compared the incidence rate of neovascular AMD among the psoriasis group and control group. Covariates include age, sex, BMI, income level, smoking status, drinking status, regular exercise habits, hypertension, dyslipidemia, end-stage renal disease, diabetic retinopathy, glucose level, the prescription of more than three oral hypoglycemic agents, and a history of diabetes mellitus exceeding five years.
RESULTS: Of 2,245,358 type 2 DM patients, 20,853 patients were classified in the psoriasis group, and the other 2,224,505 individuals in the control group. A total of 105 neovascular AMD cases occurred in the psoriasis group and 7,459 cases in the control group. According to multivariable Cox proportional hazard models, individuals with psoriasis had a significantly higher risk for neovascular AMD compared to controls (HR=1.329, 95% confidence interval: 1.096-1.612) after adjustments for covariates.
CONCLUSIONS: This study demonstrated that psoriasis was an independent risk factor for developing neovascular AMD in DM patients. Therefore, physicians should be alert to the development of neovascular AMD in DM patients who also have psoriasis.

Many clinical trials assess time-to-event endpoints. To describe the difference between groups in terms of time to event, we often employ hazard ratios. However, the hazard ratio is only informative in the case of proportional hazards (PHs) over time. There exist many other effect measures that do not require PHs. One of them is the average hazard ratio (AHR). Its core idea is to utilize a time-dependent weighting function that accounts for time variation. Though propagated in methodological research papers, the AHR is rarely used in practice. To facilitate its application, we unfold approaches for sample size calculation of an AHR test. We assess the reliability of the sample size calculation by extensive simulation studies covering various survival and censoring distributions with proportional as well as nonproportional hazards (N-PHs). The findings suggest that a simulation-based sample size calculation approach can be useful for designing clinical trials with N-PHs. Using the AHR can result in increased statistical power to detect differences between groups with more efficient sample sizes.

暂无摘要。

Epidemiologic studies frequently use risk ratios to quantify associations between exposures and binary outcomes. When the data are physically stored at multiple data partners, it can be challenging to perform individual-level analysis if data cannot be pooled centrally due to privacy constraints. Existing methods either require multiple file transfers between each data partner and an analysis center (e.g., distributed regression) or only provide approximate estimation of the risk ratio (e.g., meta-analysis). Here we develop a practical method that requires a single transfer of eight summary-level quantities from each data partner. Our approach leverages an existing risk-set method and software originally developed for Cox regression. Sharing only summary-level information, the proposed method provides risk ratio estimates and confidence intervals identical to those that would be provided - if individual-level data were pooled - by the modified Poisson regression. We justify the method theoretically, confirm its performance using simulated data, and implement it in a distributed analysis of COVID-19 data from the U.S. Food and Drug Administration\'s Sentinel System.

Long-term exposure to ambient PM2.5 is known associated with cardiovascular and respiratory health effects. However, the heterogeneous concentrationresponse function (CRF) between PM2.5 exposure across different concentration range and cardiopulmonary disease and diabetes mellitus (DM) incidence, and their implications on attributable years lived with disability (YLD) and regulation policy has not been well-studied. In this retrospective longitudinal cohort study, disease-free participants (approximately 170,000 individuals, aged ≥ 30 years) from the MJ Health Database were followed up (2007-2017) regarding incidents of coronary heart disease (CHD), ischemic stroke, chronic obstructive pulmonary disease (COPD), lower respiratory tract infections (LRIs), and DM. We used a time-dependent nonlinear weight-transformation Cox regression model for the CRF with an address-matched 3-year mean PM2.5 exposure estimate. Town/district-specific PM2.5-attributable YLD were calculated by multiplying the disease incidence rate, population attributable fraction, disability weight, and sex-age group specific subpopulation for each disease separately. The estimated CRFs for cardiopulmonary diseases were heterogeneously with the hazard ratios (HRs) increased rapidly for CHD and ischemic stroke at PM2.5 concentration lower than 10 μg/m3, whereas the HRs for DM (LRIs) increased with PM2.5 higher than 15 (20) μg/m3. Women had higher HRs for ischemic stroke and DM but not CHD. Relative to the lowest observed PM2.5 concentration of 6 μg/m3 of the study population, the PM2.5 level with an extra risk of 0.1 % (comparable to the disease incidence) for CHD, ischemic stroke, DM, and LRIs were 8.59, 11.85, 22.09, and 24.23 μg/m3, respectively. The associated attributable YLD decreased by 51.4 % with LRIs reduced most (83.6 %), followed by DM (63.7 %) as a result of PM2.5 concentration reduction from 26.10 to 16.82 μg/m3 during 2011-2019 in Taiwan. The proportion of YLD due to CHD and ischemic stroke remained dominant (56.4 %-69.9 %). The cost-benefit analysis for the tradeoff between avoidable YLD and mitigation cost suggested an optimal PM2.5 exposure level at 12 μg/m3. CRFs for cardiopulmonary diseases, attributable YLD, and regulation level, may vary depending on the national/regional background and spatial distribution of PM2.5 concentrations, as well as demographic characteristics.

BACKGROUND: Drinking water at U.S. Marine Corps Base (MCB) Camp Lejeune, North Carolina was contaminated with trichloroethylene and other industrial solvents from 1953 to 1985.
METHODS: A cohort mortality study was conducted of Marines/Navy personnel who, between 1975 and 1985, began service and were stationed at Camp Lejeune (N = 159,128) or MCB Camp Pendleton, California (N = 168,406), and civilian workers employed at Camp Lejeune (N = 7,332) or Camp Pendleton (N = 6,677) between October 1972 and December 1985. Camp Pendleton\'s drinking water was not contaminated with industrial solvents. Mortality follow-up was between 1979 and 2018. Proportional hazards regression was used to calculate adjusted hazard ratios (aHRs) comparing mortality rates between Camp Lejeune and Camp Pendleton cohorts. The ratio of upper and lower 95% confidence interval (CI) limits, or CIR, was used to evaluate the precision of aHRs. The study focused on underlying causes of death with aHRs ≥ 1.20 and CIRs ≤ 3.
RESULTS: Deaths among Camp Lejeune and Camp Pendleton Marines/Navy personnel totaled 19,250 and 21,134, respectively. Deaths among Camp Lejeune and Camp Pendleton civilian workers totaled 3,055 and 3,280, respectively. Compared to Camp Pendleton Marines/Navy personnel, Camp Lejeune had aHRs ≥ 1.20 with CIRs ≤ 3 for cancers of the kidney (aHR = 1.21, 95% CI: 0.95, 1.54), esophagus (aHR = 1.24, 95% CI: 1.00, 1.54) and female breast (aHR = 1.20, 95% CI: 0.73, 1.98). Causes of death with aHRs ≥ 1.20 and CIR > 3, included Parkinson disease, myelodysplastic syndrome and cancers of the testes, cervix and ovary. Compared to Camp Pendleton civilian workers, Camp Lejeune had aHRs ≥ 1.20 with CIRs ≤ 3 for chronic kidney disease (aHR = 1.88, 95% CI: 1.13, 3.11) and Parkinson disease (aHR = 1.21, 95% CI: 0.72, 2.04). Female breast cancer had an aHR of 1.19 (95% CI: 0.76, 1.88), and aHRs ≥ 1.20 with CIRs > 3 were observed for kidney and pharyngeal cancers, melanoma, Hodgkin lymphoma, and chronic myeloid leukemia. Quantitative bias analyses indicated that confounding due to smoking and alcohol consumption would not appreciably impact the findings.
CONCLUSIONS: Marines/Navy personnel and civilian workers likely exposed to contaminated drinking water at Camp Lejeune had increased hazard ratios for several causes of death compared to Camp Pendleton.

Canada\'s decentralized healthcare system may lead to regional disparities in survival among Canadians diagnosed with central nervous system (CNS) tumours. We identified 50,670 patients diagnosed with a first-ever primary CNS tumour between 2008 and 2017 with follow-up until 31 December 2017. We selected the four highest incidence histologies and used proportional hazard regression to estimate hazard ratios (HRs) for five regions (British Columbia, Prairie Provinces, Ontario, Atlantic Provinces and the Territories), adjusting for sex, tumour behaviour and patient age. Ontario had the best survival profile for all histologies investigated. The Atlantic Provinces had the highest HR for glioblastoma (HR = 1.26, 95% CI: 1.18-1.35) and malignant glioma not otherwise specified (NOS) (Overall: HR = 1.87, 95% CI:1.43-2.43; Pediatric population: HR = 2.86, 95% CI: 1.28-6.39). For meningioma, the Territories had the highest HR (HR = 2.44, 95% CI: 1.09-5.45) followed by the Prairie Provinces (HR = 1.52, 95% CI: 1.38-1.67). For malignant unclassified tumours, the highest HRs were in British Columbia (HR = 1.45, 95% CI: 1.22-1.71) and the Atlantic Provinces (HR = 1.40, 95% CI: 1.13-1.74). There are regional differences in the survival of CNS patients at the population level for all four specific histological types of CNS tumours investigated. Factors contributing to these observed regional survival differences are unknown and warrant further investigation.

Breast cancer is the fifth-ranked cancer globally. Despite early diagnosis and advances in treatment, breast cancer mortality is increasing. This meta-analysis aims to examine all possible prognostic factors that improve/deteriorate breast cancer-specific survival. MEDLINE, PubMed, ScienceDirect, Ovid, and Google Scholar were systematically searched until September 16, 2023. The retrieved studies from 1995 to 2022 accumulated 1,386,663 cases from 30 countries. A total of 13 out of 22 prognostic factors were significantly associated with breast cancer-specific survival. A random-effects model provided a pooled estimate of the top five poorest prognostic factors, including Stage 4 (HR = 12.12; 95% CI: 5.70, 25.76), followed by Stage 3 (HR = 3.42, 95% CI: 2.51, 4.67), a comorbidity index ≥ 3 (HR = 3.29; 95% CI: 4.52, 7.35), the poor differentiation of cancer cell histology (HR = 2.43; 95% CI: 1.79, 3.30), and undifferentiated cancer cell histology (HR = 2.24; 95% CI: 1.66, 3.01). Other survival-reducing factors include positive nodes, age, race, HER2-receptor positivity, and overweight/obesity. The top five best prognostic factors include different types of mastectomies and breast-conserving therapies (HR = 0.56; 95% CI: 0.44, 0.70), medullary histology (HR = 0.62; 95% CI: 0.53, 0.72), higher education (HR = 0.72; 95% CI: 0.68, 0.77), and a positive estrogen receptor status (HR = 0.78; 95% CI: 0.65, 0.94). Heterogeneity was observed in most studies. Data from developing countries are still scarce.