Project description:The COVID-19 pandemic due to the novel coronavirus SARS CoV-2 has inspired remarkable breakthroughs in the development of vaccines against the virus and the launch of several phase 3 vaccine trials in Summer 2020 to evaluate vaccine efficacy (VE). Trials of vaccine candidates using mRNA delivery systems developed by Pfizer-BioNTech and Moderna have shown substantial VEs of 94-95%, leading the US Food and Drug Administration to issue Emergency Use Authorizations and subsequent widespread administration of the vaccines. As the trials continue, a key issue is the possibility that VE may wane over time. Ethical considerations dictate that trial participants be unblinded and those randomized to placebo be offered study vaccine, leading to trial protocol amendments specifying unblinding strategies. Crossover of placebo subjects to vaccine complicates inference on waning of VE. We focus on the particular features of the Moderna trial and propose a statistical framework based on a potential outcomes formulation within which we develop methods for inference on potential waning of VE over time and estimation of VE at any postvaccination time. The framework clarifies assumptions made regarding individual- and population-level phenomena and acknowledges the possibility that subjects who are more or less likely to become infected may be crossed over to vaccine differentially over time. The principles of the framework can be adapted straightforwardly to other trials.
Project description:PURPOSE:Greater clinical validity and economic feasibility are driving the more widespread use of multiplex genetic technologies in routine clinical care, especially for applications in pharmacogenomics. Empirical data on the numbers and types of incidental findings generated through such testing are needed to develop policies and practices related to their clinical use. Of particular importance are disparities in findings relevant to different ancestry groups. METHODS:The Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment Resource, or PREDICT, is an institutional program to implement prospective clinical genotyping of 34 pharmacogenomic-related genes to guide drug selection and dosing. We curated 5,566 journal articles to quantify and characterize the incidental, non-pharmacogenomic genotype-phenotype associations that could be generated through this clinical genotyping project. RESULTS:We identified 372 putative incidental genotype-phenotype associations that might be revealed in patients undergoing clinical genotyping for pharmacogenomic purposes. Of these, 287 associations were supported by at least one study demonstrating an odds ratio ?2.0 or ?0.5. Numbers of potentially relevant findings varied widely by ancestry group. CONCLUSION:Rigorous clinical policies for the clinical management of incidental findings are needed because the sheer number of significant findings could prove overwhelming to health-care institutions, providers, and patients.
Project description:ObjectivesThis study compared ways of describing treatment effects. The objective was to better explain to clinicians and patients what they might expect from a given treatment, not only in terms of relative and absolute risk reduction, but also in projections of long-term survival.BackgroundThe restricted mean survival time (RMST) can be used to estimate of long-term survival, providing a complementary approach to more conventional metrics (e.g., absolute and relative risk), which may suggest greater benefits of therapy in high-risk patients compared with low-risk patients.MethodsRelative and absolute risk, as well as the RMST, were calculated in heart failure with reduced ejection fraction (HFrEF) trials.ResultsAs examples, in the RALES trial (more severe HFrEF), the treatment effect metrics for spironolactone versus placebo on heart failure hospitalization and/or cardiovascular death were a hazard ratio (HR) of 0.67 (95% confidence interval [CI]: 0.5 to 0.77), number needed to treat = 9 (7 to 14), and age extension of event-free survival +1.1 years (-0.1 to + 2.3 years). The corresponding metrics for EMPHASIS-HF (eplerenone vs. placebo in less severe HFrEF) were 0.64 (0.54 to 0.75), 14 (1 to 22), and +2.9 (1.2 to 4.5). In patients in PARADIGM-HF aged younger than 65 years, the metrics for sacubitril/valsartan versus enalapril were 0.77 (95% CI: 0.68 to 0.88), 23 (15 to 44), and +1.7 (0.6 to 2.8) years; for those aged 65 years or older, the metrics were 0.83 (95% CI: 0.73 to 0.94), 29 (17 to 83), and +0.9 (0.2 to 1.6) years, which provided evidence of a greater potential life extension in younger patients. Similar observations were found for lower risk patients.ConclusionsRMST event-free (and overall) survival estimates provided a complementary means of evaluating the effect of therapy in relation to age and risk. They also provided a clinically useful metric that should be routinely reported and used to explain the potential long-term benefits of a given treatment, especially to younger and less symptomatic patients.
Project description:Lung cancer is the commonest cancer worldwide. Mortality and incidence rates are traditionally used to assess cancer burden and as public health indicators. However, these metrics are difficult to interpret at an individual level. Providing the lifetime and 10-year risks of cancer could improve risk communication. Our aim was to estimate current lifetime and 10-year risks of lung cancer by smoking status and changes in these risks between 1995 and 2013 in a Swiss population. We used all lung cancer cases recorded between 1995 and 2013 by two population-based cancer registries in the contiguous cantons of Vaud and Valais, in Western Switzerland. We estimated sex-specific lifetime risk and 10-year risk of lung cancer using the current probability method, accounting for competing risk of death. Estimates were also provided by smoking status. Between 1995 and 2013, 9623 cases of lung cancer were recorded. During this period, the lifetime risk decreased in men from 7.1% to 6.7% and increased in women from 2.5% to 4.1%. In both sexes, the 10-year risk of lung cancer increased with age until the age of 60-70 and decreased thereafter. Difference in the cumulative risk between current, former, and never smokers were very large and reported in user-friendly charts to ease risk communication. These lifetime and 10-year risk estimates could be used systematically as public health indicators. Regularly updating risk estimations are necessary for conditions like lung cancer whose incidence has changed substantially.
Project description:False positive results in screening tests have potentially severe psychological, medical, and financial consequences for the recipient. However, there have been few efforts to quantify how the risk of a false positive accumulates over time. We seek to fill this gap by estimating the probability that an individual who adheres to the U.S. Preventive Services Task Force (USPSTF) screening guidelines will receive at least one false positive in a lifetime. To do so, we assembled a data set of 116 studies cited by the USPSTF that report the number of true positives, false negatives, true negatives, and false positives for the primary screening procedure for one of five cancers or six sexually transmitted diseases. We use these data to estimate the probability that an individual in one of 14 demographic subpopulations will receive at least one false positive for one of these eleven diseases in a lifetime. We specify a suitable statistical model to account for the hierarchical structure of the data, and we use the parametric bootstrap to quantify the uncertainty surrounding our estimates. The estimated probability of receiving at least one false positive in a lifetime is 85.5% (±0.9%) and 38.9% (±3.6%) for baseline groups of women and men, respectively. It is higher for subpopulations recommended to screen more frequently than the baseline, including more vulnerable groups such as pregnant women and men who have sex with men. Since screening technology is imperfect, false positives remain inevitable. The high lifetime risk of a false positive reveals the importance of educating patients about this phenomenon.
Project description:In ocular, neurologic, and cardiovascular diseases, macular segmentation data from spectral-domain optical coherence tomography (SD-OCT) provide morphologic, and OCT-angiography (OCTA) results give microvascular information about the macula. Age was shown to influence both methods' measurements. To further characterize this association, macular SD-OCT and OCTA changes were investigated in a population of juvenile, adult, and older individuals. Macular segment thickness and superficial (SCP) and deep plexus (DCP) vascular density (VD) of 157 healthy individuals aged 10-79 years were analyzed retrospectively. One-way analysis of variance (ANOVA) was used to compare age groups. The association between macular segmentation and OCTA parameters and between these and age was evaluated using linear regression. ANOVA and linear regression analysis showed a thickness decrease in the whole macular and in the ganglion cell and inner plexiform layers with age. While the foveal avascular zone area remained constant between age groups, VD of the SCP and DCP also decreased with age. In multiple linear regression, SCP and DCP VD were associated with inner macular segment thickness in an age-independent way. To conclude, the age-related microvascular and morphological changes in the macula described in this study can contribute to improving the understanding of macular aging processes and better interpreting OCT(A) results in healthy individuals and patients suffering from various retinal diseases.
Project description:BACKGROUND:Within cancer care, dynamic evaluations of the loss in expectation of life provides useful information to patients as well as physicians. The loss of lifetime function yields the conditional loss in expectation of life given survival up to a specific time point. Due to the inevitable censoring in time-to-event data, loss of lifetime estimation requires extrapolation of both the patient and general population survival function. In this context, the accuracy of different extrapolation approaches has not previously been evaluated. METHODS:The loss of lifetime function was computed by decomposing the all-cause survival function using the relative and general population survival function. To allow extrapolation, the relative survival function was fitted using existing parametric relative survival models. In addition, we introduced a novel mixture cure model suitable for extrapolation. The accuracy of the estimated loss of lifetime function using various extrapolation approaches was assessed in a simulation study and by data from the Danish Cancer Registry where complete follow-up was available. In addition, we illustrated the proposed methodology by analyzing recent data from the Danish Lymphoma Registry. RESULTS:No uniformly superior extrapolation method was found, but flexible parametric mixture cure models and flexible parametric relative survival models seemed to be suitable in various scenarios. CONCLUSION:Using extrapolation to estimate the loss of lifetime function requires careful consideration of the relative survival function outside the available follow-up period. We propose extensive sensitivity analyses when estimating the loss of lifetime function.
Project description:IntroductionOver the last decade, hypertension (HPT) is among the leading causes of death and morbidity in Ghana. In recent past, most health policy research in Ghana and Africa focussed on communicable diseases. In recent times, Ghana and other developing nations have shifted their attention to non-communicable diseases because most of these countries are going through an epidemiologic transition where there is a surge in the prevalence of HPT. This paper was therefore set out to estimate the cost of treating HPT in Ghana from the patients' and health system's perspectives.MethodWe used a cost of illness framework to simulate the cost of HPT management in Ghana taking into account 4 of the common target organ complications with the most mortality implication. A decision analytic model (DAM) was developed in Microsoft® Excel to simulate the progression of HPT patients and the Markov model was employed in simulating the lifetime cost of illness.ResultsThe results show that by 10 years from diagnosis, the probability of death from any of the 4 complications (ie, stroke, myocardial infarction, heart failure, and chronic kidney disease) is roughly 41.03%. By 20 years (or 243 months) from diagnosis, the probability of death is estimated to be 69.61%. However, by the 30th anniversary, the probability of death among the cohort is 82.3%. Also, the lifetime discounted cost of treating HPT is about GHS 869 106 which could range between GHS 570 239 and GHS 1.202 million if wide uncertainty is taken into account. This is equivalent to USD 119 056 (range: USD 78 115-164 723).ConclusionBy highlighting the lifetime cost of treating HPT in Ghana, policies can be formulated regarding the cost of treating HPT by the non-communicable disease unit and National Health Insurance Authority (NHIA) of the Ministry of Health.