F-18-Fluorodeoxyglucose Positron Emission Tomography Imaging-Assisted Management of Patients With Severe Left Ventricular Dysfunction and Suspected Coronary Disease A Randomized, Controlled Trial (PARR-2)

ObjectivesWe conducted a randomized trial to assess the effectiveness of F-18-fluorodeoxyglucose (FDG) positron emission tomography (PET)-assisted management in patients with severe ventricular dysfunction and suspected coronary disease.BackgroundSuch patients may benefit from revascularization, but have significant perioperative morbidity and mortality. F-18-fluorodeoxyglucose PET can detect viable myocardium that might recover after revascularization.MethodsIncluded were patients with severe left ventricular (LV) dysfunction and suspected coronary disease being considered for revascularization, heart failure, or transplantation work-ups or in whom PET was considered potentially useful. Patients were stratified according to recent angiography or not, then randomized to management assisted by FDG PET (n = 218) or standard care (n = 212). The primary outcome was the composite of cardiac death, myocardial infarction, or recurrent hospital stay for cardiac cause, within 1 year.ResultsAt 1 year, the cumulative proportion of patients who had experienced the composite event was 30% (PET arm) versus 36% (standard arm) (relative risk 0.82, 95% confidence interval [CI] 0.59 to 1.14; p = 0.16). The hazard ratio (HR) for the composite outcome, PET versus standard care, was 0.78 (95% CI 0.58 to 1.1; p = 0.15); for patients that adhered to PET recommendations for revascularization, revascularization work-up, or neither, HR = 0.62 (95% CI 0.42 to 0.93; p = 0.019); in those without recent angiography, for cardiac death, HR = 0.4 (95% CI 0.17 to 0.96; p = 0.035).ConclusionsThis study did not demonstrate a significant reduction in cardiac events in patients with LV dysfunction and suspected coronary disease for FDG PET-assisted management versus standard care. In those who adhered to PET recommendations and in patients without recent angiography, significant benefits were observed. The utility of FDG PET is best realized in this subpopulation and when adherence to recommendations can be achieved

Markov modeling of disease progression and mortality

Prognostic studies of progression and mortality in different diseases are essential to understand the role of particular prognostic factors and, thus, improve prognosis and ultimately help selecting appropriate interventions. Yet, such studies often face serious limitations of available data and/or of the existing statistical methods. One difficulty concerns separating the effects of putative prognostic factors on different clinical endpoints or “competing events” such as e.g. disease recurrence vs. recurrence-free death, or death due to disease vs. death due to other causes. This issue becomes even more challenging because data sources, such as cancer registries, often record only the date of death but not the cause of death. This can lead to bias in assessing the role of prognostic factors whose impact on the disease-specific mortality is quite different from their impact on all-cause mortality. It is important, therefore, to use methods that can deal accurately and efficiently with both (i) alternative pathways of disease progression, and (ii) unknown causes of death. The aforementioned challenges are addressed by 3 manuscripts. Previous empirical studies have suggested the potential advantages of using multi-state Markov models, over conventional time-to-event methods, to analyze competing risks and multi-state pathways of disease progression. In the 1st paper, I attempted to systematically assess, through a series of simulations, the performance of Markov models in this context and confirmed the accuracy of both point estimates of the regression coefficients and hypothesis tests. On the other hand, Relative Survival regression models have been developed, in the context of single-endpoint time-to-event analyses, to correct the regression coefficients for the unknown causes of death. Yet, no existing statistical model permits simultaneous combination of the advantages of both (i) Markov multi-state modeling, and (ii) Relative Survival. Therefore, in theLes études pronostiques sur l'évolution et la mortalité de certaines pathologies sont essentielles pour comprendre le rôle de certains facteurs pronostiques et ainsi, améliorer le pronostic et finalement aider dans le choix des interventions thérapeutiques appropriées. Jusqu'à présent, les études de ce type ont été souvent confrontées à d'importantes limitations dans les données et/ou les méthodes statistiques disponibles. Une des difficultés concerne la discrimination, pour un même facteur pronostique, de ses effets sur différents critères cliniques ou événements concurrents, comme la récidive de la maladie vs le décès sans récidive, ou le décès dû à la pathologie vs le décès dû à d'autres causes. Ce problème devient d'autant plus important que les sources de données, comme les registres, enregistrent souvent uniquement la date de décès mais pas la cause. Ceci peut conduire à des biais dans l'évaluation du rôle des facteurs pronostiques dont l'effet sur la mortalité spécifique dû à la pathologie est différent de celui sur la mortalité toutes causes confondues. Il est donc important d'utiliser des méthodes qui puissent prendre en compte correctement à la fois (i) les différentes évolutions possibles de la pathologie et (ii) l'absence de la connaissance de la cause de décès. Les problèmes méthodologiques mentionnés précédemment sont traités dans 3 articles. Les études empiriques précédentes ont suggéré des avantages potentiels à utiliser les modèles multi-états de Markov à la place des modèles de survie conventionnels dans l'analyse des risques compétitifs et des différentes phases possibles d'évolution d'une pathologie. Le premier article tente d'évaluer méthodiquement, à l'aide de simulations, les performances des modèles de Markov dans ce contexte et confirme l'exactitude à la fois de l'estimation des coefficients de la régression et des tests d'hypothèse. D'un autre coté, les mo

Examining treatment targets and equity in bone-active medication use within secondary fracture prevention: a systematic review and meta-analysis

Purpose: This systematic review seeks to evaluate the proportion of fragility fracture patients screened in secondary fracture prevention programs who were indicated for pharmacological treatment, received prescriptions for bone-active medications, and initiated the prescribed medication. Additionally, the study aims to analyze equity in pharmacological treatment by examining equity-related variables including age, sex, gender, race, education, income, and geographic location.Methods: We conducted a systematic review to ascertain the proportion of fragility fracture patients indicated for treatment who received prescriptions and/or initiated bone-active medication through secondary fracture prevention programs. We also examined treatment indications reported in studies and eligibility criteria to confirm patients who were eligible for treatment. To compute the pooled proportions for medication prescription and initiation, we carried out a single group proportional meta-analysis. We also extracted the proportions of patients who received a prescription and/or began treatment based on age, sex, race, education, socioeconomic status, location, and chronic conditionsResults: This review included 122 studies covering 114 programs. The pooled prescription rate was 77%, and the estimated medication initiation rate was 71%. Subgroup analysis revealed no significant difference in treatment initiation between the Fracture Liaison Service and other programs. Across all studies, age, sex, and socioeconomic status were the only equity variables reported in relation to treatment outcomes.Conclusion: Our systematic review emphasizes the need for standardized reporting guidelines in post-fracture interventions. Moreover, considering equity stratifiers in the analysis of health outcomes will help address inequities and improve the overall quality and reach of secondary fracture prevention programs

Long-Term Outcomes in Adult Patients With Pulmonary Hypertension After Percutaneous Closure of Atrial Septal Defects

BACKGROUND Pulmonary hypertension (PH), recently redefined as mean pulmonary arterial pressure >20 mm Hg (PH$_{20}$), may be observed in patients with atrial septal defects (ASD). We aimed to determine the effect of preprocedural PH$_{20}$ status on outcomes among patients undergoing ASD closure. METHODS Study population was selected from a retrospective registry of adult patients who underwent percutaneous ASD closure from 1998 to 2016 from a single center and had right heart catheterizations during the procedure. The clinical registry was linked to administrative databases to capture short- and long-term outcomes. RESULTS We included a total of 632 ASD closure patients of whom 359 (56.8%) had PH$_{20}$. The mean follow-up length was 7.6±4.6 years. Patients with PH$_{20}$ were older (mean age 56.5 versus 43.1 years, P<0.001) and a higher prevalence of comorbidities including hypertension (54.3% versus 21.6%, P<0.001) and diabetes (18.1% versus 5.9%, P<0.001) than those without PH. In a Cox proportional hazards model after covariate adjustment, patients with PH had a significantly higher risk of developing major adverse cardiac and cerebrovascular events (heart failure, stroke, myocardial infarction, or cardiovascular mortality), with hazards ratio 2.45 (95% CI, 1.4-4.4). When applying the prior, mean pulmonary arterial pressure ≥25 mm Hg (PH$_{25}$) cutoff, a significantly higher hazard of developing major adverse cardiac and cerebrovascular events was observed in PH versus non-PH patients. CONCLUSIONS ASD patients with PH undergoing closure suffer from more comorbidities and worse long-term major adverse cardiac and cerebrovascular events outcomes, compared with patients without PH. The use of the new PH$_{20}$ definition potentially dilutes the effect of this serious condition on outcomes in this population

Associations of serum levels of sex hormones in follicular and luteal phases of the menstrual cycle with breast tissue characteristics in young women

Background: In previous work in young women aged 15-30 years we measured breast water and fat using MR and obtained blood for hormone assays on the same day in the follicular phase of the menstrual cycle. Only serum growth hormone levels and sex hormone binding globulin (SHBG) were significantly associated with percent breast water after adjustment for covariates. The sex hormones estradiol, progesterone and testosterone were not associated with percent water in the breast in the follicular phase of the menstrual cycle. In the present study we have examined the association of percent breast water with serum levels of sex hormones in both follicular and luteal phase of the menstrual cycle. Methods: In 315 healthy white Caucasian young women aged 15-30 with regular menstrual cycles who had not used oral contraceptives or other hormones in the previous 6 months, we used MR to determine percent breast water, and obtained blood samples for hormone assays within 10 days of the onset of the most recent menstrual cycle (follicular phase) of the cycle on the same day as the MR scan, and a second blood sample on days 19-24 of the cycle. Serum progesterone levels of > = 5 mmol/L in days 19-24 were used to define the 225 subjects with ovulatory menstrual cycles, whose data are the subject of the analyses shown here. Results: SHBG was positively associated with percent water in both follicular and luteal phases of the menstrual cycle. Total and free estradiol and total and free testosterone were not associated with percent water in the follicular phase, but in young women with ovulatory cycles, were all negatively associated with percent water in the luteal phase. Conclusions: Our results from young women aged 15-30 years add to the evidence that the extent of fibroglandular tissue in the breast that is reflected in both mammographic density and breast water is associated positively with higher serum levels of SHBG, but not with higher levels of sex hormones

Mammographic features associated with interval breast cancers in screening programs

Abstract Introduction Percent mammographic density (PMD) is associated with an increased risk of interval breast cancer in screening programs, as are younger age, pre-menopausal status, lower body mass index and hormone therapy. These factors are also associated with variations in PMD. We have examined whether these variables influence the relative frequency of interval and screen-detected breast cancer, independently or through their associations with PMD. We also examined the association of tumor size with PMD and dense and non-dense areas in screen-detected and interval breast cancers. Methods We used data from three case-control studies nested in screened populations. Interval breast cancer was defined as invasive breast cancer detected within 12 months of a negative mammogram. We used a computer-assisted method of measuring the dense and total areas of breast tissue in the first (baseline) mammogram taken at entry to screening programs and calculated the non-dense area and PMD. We compared these mammographic features, and other risk factors at baseline, in women with screen-detected (n?=?718) and interval breast cancer (n?=?125). Results In multi-variable analysis, the baseline characteristics of younger age, greater dense area and smaller non-dense mammographic area were significantly associated with interval breast cancer compared to screen-detected breast cancer. Compared to screen-detected breast cancers, interval cancers had a larger maximum tumor diameter within each mammographic measure. Conclusions Age and the dense and non-dense areas in the baseline mammogram were independently associated with interval breast cancers in screening programs. These results suggest that decreased detection of cancers caused by the area of dense tissue, and more rapid growth associated with a smaller non-dense area, may both contribute to risk of interval breast cancer. Tailoring screening to individual mammographic characteristics at baseline may reduce the number of interval cancers

Evidence that breast tissue stiffness is associated with risk of breast cancer.

BACKGROUND: Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. METHODS: Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. RESULTS: After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. CONCLUSION: An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement

Mammographic density and breast cancer: a comparison of related and unrelated controls in the Breast Cancer Family Registry

Abstract Introduction Percent mammographic density (PMD) is a strong and highly heritable risk factor for breast cancer. Studies of the role of PMD in familial breast cancer may require controls, such as the sisters of cases, selected from the same 'risk set' as the cases. The use of sister controls would allow control for factors that have been shown to influence risk of breast cancer such as race/ethnicity, socioeconomic status and a family history of breast cancer, but may introduce 'overmatching' and attenuate case-control differences in PMD. Methods To examine the potential effects of using sister controls rather than unrelated controls in a case-control study, we examined PMD in triplets, each comprised of a case with invasive breast cancer, an unaffected full sister control, and an unaffected unrelated control. Both controls were matched to cases on age at mammogram. Total breast area and dense area in the mammogram were measured in the unaffected breast of cases and a randomly selected breast in controls, and the non-dense area and PMD calculated from these measurements. Results The mean difference in PMD between cases and controls, and the standard deviation (SD) of the difference, were slightly less for sister controls (4.2% (SD = 20.0)) than for unrelated controls (4.9% (SD = 25.7)). We found statistically significant correlations in PMD between cases (n = 228) and sister controls (n = 228) (r = 0.39 (95% CI: 0.28, 0.50; P <0.0001)), but not between cases and unrelated controls (n = 228) (r = 0.04 (95% CI: -0.09, 0.17; P = 0.51)). After adjusting for other risk factors, square root transformed PMD was associated with an increased risk of breast cancer when comparing cases to sister controls (adjusted odds ratio (inter-quintile odds ratio (IQOR) = 2.19, 95% CI = 1.20, 4.00) or to unrelated controls (adjusted IQOR = 2.62, 95% CI = 1.62, 4.25). Conclusions The use of sister controls in case-control studies of PMD resulted in a modest attenuation of case-control differences and risk estimates, but showed a statistically significant association with risk and allowed control for race/ethnicity, socioeconomic status and family history