Statistical issues arising in the Women's Health Initiative

The aged female rhesus macaque as a translational model for human menopause and hormone therapy

Progress in understanding the causes of physiological and behavioral changes in post-menopausal women is hampered by the paucity of animal models that accurately recapitulate these age-associated changes. Here we evaluate the translational potential of female rhesus macaques (Macaca mulatta). Like women, these long-lived diurnal primates show marked neuroendocrine changes during aging, as well as perturbed sleep-wake cycles and cognitive decline. Furthermore, the brains of old rhesus macaques show some of the same pathological hallmarks of Alzheimer's disease as do humans, including amyloidosis and tauopathology. Importantly, unlike humans, rhesus macaques can be maintained under tightly controlled environmental conditions, such as photoperiod, temperature and diet, and tissues can be collected with zero postmortem interval; this makes them especially suitable for studies aimed at elucidating underlying molecular mechanisms. Recent findings from female macaques are helping to elucidate how sex-steroids influence gene expression within the brain and contribute to the maintenance of cognitive function and amelioration of age-associated pathologies. Taken together, these findings emphasize the translational value of female rhesus macaques as a model for elucidating causal mechanisms that underlie normative and pathological changes in post-menopausal women. They also provide a pragmatic platform upon which to develop safe and effective therapies.

Menopausal Hormone Therapy and Ovarian and Endometrial Cancers: Long-Term Follow-Up of the Women's Health Initiative Randomized Trials

PURPOSE

Menopausal hormone therapy's influence on ovarian and endometrial cancers remains unsettled. Therefore, we assessed the long-term influence of conjugated equine estrogen (CEE) plus medroxyprogesterone acetate (MPA) and CEE-alone on ovarian and endometrial cancer incidence and mortality in the Women's Health Initiative randomized, placebo-controlled clinical trials.

MATERIALS AND METHODS

Postmenopausal women, age 50-79 years, were entered on two randomized clinical trials evaluating different menopausal hormone therapy regimens. In 16,608 women with a uterus, 8,506 were randomly assigned to once daily 0.625 mg of CEE plus 2.5 mg once daily of MPA and 8,102 placebo. In 10,739 women with previous hysterectomy, 5,310 were randomly assigned to once daily 0.625 mg of CEE-alone and 5,429 placebo. Intervention was stopped for cause before planned 8.5-year intervention after 5.6 years (CEE plus MPA) and after 7.2 years (CEE-alone). Outcomes include incidence and mortality from ovarian and endometrial cancers and deaths after these cancers.

RESULTS

After 20-year follow-up, CEE-alone, versus placebo, significantly increased ovarian cancer incidence (35 cases [0.041%] v 17 [0.020%]; hazard ratio [HR], 2.04 [95% CI, 1.14 to 3.65]; P = .014) and ovarian cancer mortality (P = .006). By contrast, CEE plus MPA, versus placebo, did not increase ovarian cancer incidence (75 cases [0.051%] v 63 [0.045%]; HR, 1.14 [95% CI, 0.82 to 1.59]; P = .44) or ovarian cancer mortality but did significantly lower endometrial cancer incidence (106 cases [0.073%] v 140 [0.10%]; HR, 0.72 [95% CI, 0.56 to 0.92]; P = .01).

CONCLUSION

In randomized clinical trials, CEE-alone increased ovarian cancer incidence and ovarian cancer mortality, while CEE plus MPA did not. By contrast, CEE plus MPA significantly reduced endometrial cancer incidence.

Time-varying living arrangements and suicide death in the general population sample: 14-year causal survival analysis via pooled logistic regression

AIMS

While past research suggested that living arrangements are associated with suicide death, no study has examined the impact of sustained living arrangements and the change in living arrangements. Also, previous survival analysis studies only reported a single hazard ratio (HR), whereas the actual HR may change over time. We aimed to address these limitations using causal inference approaches.

METHODS

Multi-point data from a general Japanese population sample were used. Participants reported their living arrangements twice within a 5-year time interval. After that, suicide death, non-suicide death and all-cause mortality were evaluated over 14 years. We used inverse probability weighted pooled logistic regression and cumulative incidence curve, evaluating the association of time-varying living arrangements with suicide death. We also studied non-suicide death and all-cause mortality to contextualize the association. Missing data for covariates were handled using random forest imputation.

RESULTS

A total of 86,749 participants were analysed, with a mean age (standard deviation) of 51.7 (7.90) at baseline. Of these, 306 died by suicide during the 14-year follow-up. Persistently living alone was associated with an increased risk of suicide death (risk difference [RD]: 1.1%, 95% confidence interval [CI]: 0.3-2.5%; risk ratio [RR]: 4.00, 95% CI: 1.83-7.41), non-suicide death (RD: 7.8%, 95% CI: 5.2-10.5%; RR: 1.56, 95% CI: 1.38-1.74) and all-cause mortality (RD: 8.7%, 95% CI: 6.2-11.3%; RR: 1.60, 95% CI: 1.42-1.79) at the end of the follow-up. The cumulative incidence curve showed that these associations were consistent throughout the follow-up. Across all types of mortality, the increased risk was smaller for those who started to live with someone and those who transitioned to living alone. The results remained robust in sensitivity analyses.

CONCLUSIONS

Individuals who persistently live alone have an increased risk of suicide death as well as non-suicide death and all-cause mortality, whereas this impact is weaker for those who change their living arrangements.

Handling time-varying treatments in observational studies: A scoping review and recommendations

OBJECTIVE

Time-varying treatments are common in observational studies. However, when assessing treatment effects, the methodological framework has not been systematically established for handling time-varying treatments. This study aimed to examine the current methods for dealing with time-varying treatments in observational studies and developed practical recommendations.

METHODS

We searched PubMed from 2000 to 2021 for methodological articles about time-varying treatments, and qualitatively summarized the current methods for handling time-varying treatments. Subsequently, we developed practical recommendations through interactive internal group discussions and consensus by a panel of external experts.

RESULTS

Of the 36 eligible reports (22 methodological reviews, 10 original studies, 2 tutorials and 2 commentaries), most examined statistical methods for time-varying treatments, and only a few discussed the overarching methodological process. Generally, there were three methodological components to handle time-varying treatments. These included the specification of treatment which may be categorized as three scenarios (i.e., time-independent treatment, static treatment regime, or dynamic treatment regime); definition of treatment status which could involve three approaches (i.e., intention-to-treat, per-protocol, or as-treated approach); and selection of analytic methods. Based on the review results, a methodological workflow and a set of practical recommendations were proposed through two consensus meetings.

CONCLUSIONS

There is no consensus process for assessing treatment effects in observational studies with time-varying treatments. Previous efforts were dedicated to developing statistical methods. Our study proposed a stepwise workflow with practical recommendations to assist the practice.

Statistical and Scientific Considerations Concerning the Interpretation, Replicability, and Transportability of Research Findings

To advance scientific understanding of disease processes and related intervention effects, study results should be free from bias and replicable. More broadly, investigators seek results that are transportable, that is, applicable to a perceived study population as well as in other environments and populations. We review fundamental statistical issues that arise in the analysis of observational data from disease cohorts and other sources and discuss how these issues affect the transportability and replicability of research results. Much of the literature focuses on estimating average exposure or intervention effects at the population level, but we argue for more nuanced analyses of conditional effects that reflect the complexity of disease processes.

Novel Use of Patient-Specific Covariates From Oncology Studies in the Era of Biomedical Data Science: A Review of Latest Methodologies

In this article, we review different applications of how to incorporate individual patient variables into clinical research within oncology. These methodologies range from the more traditional use of baseline covariates from randomized clinical trials, as well as observational studies, to using covariates to generalize the results of randomized clinical trials to other populations. Individual patient variables also allow for the consideration of heterogeneity in treatment effects and individualized treatment rules. We primarily consider two treatment groups and mostly focus on time-to-event outcomes where such methodologies have been well established and widely applied. We also discuss more conceptually newer statistical research that has not been widely applied in clinical oncology, but is likely to make an impact in future oncology research. With the increasing amount of biomedical data available for analysis, it is inevitable that more methods are developed to make best use of information, to advance oncology research.

Home Versus Facility Dialysis and Mortality in Australia and New Zealand

RATIONALE & OBJECTIVE

Mortality is an important outcome for all dialysis stakeholders. We examined associations between dialysis modality and mortality in the modern era.

STUDY DESIGN

Observational study comparing dialysis inception cohorts 1998-2002, 2003-2007, 2008-2012, and 2013-2017.

SETTING & PARTICIPANTS

Australia and New Zealand (ANZ) dialysis population.

EXPOSURE

The primary exposure was dialysis modality: facility hemodialysis (HD), continuous ambulatory peritoneal dialysis (CAPD), automated PD (APD), or home HD.

OUTCOME

The main outcome was death.

ANALYTICAL METHODS

Cause-specific proportional hazards models with shared frailty and subdistribution proportional hazards (Fine and Gray) models, adjusting for available confounding covariates.

RESULTS

In 52,097 patients, the overall death rate improved from ~15 deaths per 100 patient-years in 1998-2002 to ~11 in 2013-2017, with the largest cause-specific contribution from decreased infectious death. Relative to facility HD, mortality with CAPD and APD has improved over the years, with adjusted hazard ratios in 2013-2017 of 0.88 (95% CI, 0.78-0.99) and 0.91 (95% CI, 0.82-1.00), respectively. Increasingly, patients with lower clinical risk have been adopting APD, and to a lesser extent CAPD. Relative to facility HD, mortality with home HD was lower throughout the entire period of observation, despite increasing adoption by older patients and those with more comorbidities. All effects were generally insensitive to the modeling approach (initial vs time-varying modality, cause-specific versus subdistribution regression), different follow-up time intervals (5 year vs 7 year vs 10 year). There was no effect modification by diabetes, comorbidity, or sex.

LIMITATIONS

Potential for residual confounding, limited generalizability.

CONCLUSIONS

The survival of patients on PD in 2013-2017 appears greater than the survival for patients on facility HD in ANZ. Additional research is needed to assess whether changing clinical risk profiles over time, varied dialysis prescription, and morbidity from dialysis access contribute to these findings.

Association of Menopausal Hormone Therapy With Breast Cancer Incidence and Mortality During Long-term Follow-up of the Women's Health Initiative Randomized Clinical Trials

IMPORTANCE

The influence of menopausal hormone therapy on breast cancer remains unsettled with discordant findings from observational studies and randomized clinical trials.

OBJECTIVE

To assess the association of prior randomized use of estrogen plus progestin or prior randomized use of estrogen alone with breast cancer incidence and mortality in the Women's Health Initiative clinical trials.

DESIGN, SETTING, AND PARTICIPANTS

Long-term follow-up of 2 placebo-controlled randomized clinical trials that involved 27 347 postmenopausal women aged 50 through 79 years with no prior breast cancer and negative baseline screening mammogram. Women were enrolled at 40 US centers from 1993 to 1998 with follow-up through December 31, 2017.

INTERVENTIONS

In the trial involving 16 608 women with a uterus, 8506 were randomized to receive 0.625 mg/d of conjugated equine estrogen (CEE) plus 2.5 mg/d of medroxyprogesterone acetate (MPA) and 8102, placebo. In the trial involving 10 739 women with prior hysterectomy, 5310 were randomized to receive 0.625 mg/d of CEE alone and 5429, placebo. The CEE-plus-MPA trial was stopped in 2002 after 5.6 years' median intervention duration, and the CEE-only trial was stopped in 2004 after 7.2 years' median intervention duration.

MAIN OUTCOMES AND MEASURES

The primary outcome was breast cancer incidence (protocol prespecified primary monitoring outcome for harm) and secondary outcomes were deaths from breast cancer and deaths after breast cancer.

RESULTS

Among 27 347 postmenopausal women who were randomized in both trials (baseline mean [SD] age, 63.4 years [7.2 years]), after more than 20 years of median cumulative follow-up, mortality information was available for more than 98%. CEE alone compared with placebo among 10 739 women with a prior hysterectomy was associated with statistically significantly lower breast cancer incidence with 238 cases (annualized rate, 0.30%) vs 296 cases (annualized rate, 0.37%; hazard ratio [HR], 0.78; 95% CI, 0.65-0.93; P = .005) and was associated with statistically significantly lower breast cancer mortality with 30 deaths (annualized mortality rate, 0.031%) vs 46 deaths (annualized mortality rate, 0.046%; HR, 0.60; 95% CI, 0.37-0.97; P = .04). In contrast, CEE plus MPA compared with placebo among 16 608 women with a uterus was associated with statistically significantly higher breast cancer incidence with 584 cases (annualized rate, 0.45%) vs 447 cases (annualized rate, 0.36%; HR, 1.28; 95% CI, 1.13-1.45; P < .001) and no significant difference in breast cancer mortality with 71 deaths (annualized mortality rate, 0.045%) vs 53 deaths (annualized mortality rate, 0.035%; HR, 1.35; 95% CI, 0.94-1.95; P= .11).

CONCLUSIONS AND RELEVANCE

In this long-term follow-up study of 2 randomized trials, prior randomized use of CEE alone, compared with placebo, among women who had a previous hysterectomy, was significantly associated with lower breast cancer incidence and lower breast cancer mortality, whereas prior randomized use of CEE plus MPA, compared with placebo, among women who had an intact uterus, was significantly associated with a higher breast cancer incidence but no significant difference in breast cancer mortality.

The benefit of early survival on PD versus HD—Why this is (still) very important

There are a number of misconceptions around the identified early survival benefit of peritoneal dialysis (PD) relative to hemodialysis (HD), including that such benefits “even out in the end” since the relative risk of death over time eventually encompasses 1.0 (or even an estimate that is unfavorable to PD); that the early benefit is, in fact, most likely due to unmeasured confounding; and such benefits are only due to the influence of central venous catheters and “crash starters” in the HD group. In fact, the early survival benefit results in a substantial gain of patient life years in PD cohorts relative to HD ones, even if it the benefit appears to “even out in the end,” is relatively insensitive to unmeasured confounding, and persists even when the effects of central venous catheters are accounted for. In this review, the calculations and arguments are made to support these tenets. Survival on dialysis is still one of the most important considerations for all stakeholders in the end-stage kidney disease community, including patients who rank it among their top priorities. Shared decision-making is a fundamental patient right and requires both balanced information and an iterative mechanism for a consensual decision based on shared understanding and purpose. A cornerstone of this process should be an explicit discussion of the early survival benefit of PD relative to HD.

Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis

Background

Clinical research and medical practice can be advanced through the prediction of an individual’s health state, trajectory, and responses to treatments. However, the majority of current clinical risk prediction models are based on regression approaches or machine learning algorithms that are static, rather than dynamic. To benefit from the increasing emergence of large, heterogeneous data sets, such as electronic health records (EHRs), novel tools to support improved clinical decision making through methods for individual-level risk prediction that can handle multiple variables, their interactions, and time-varying values are necessary.

Methods

We introduce a novel dynamic approach to clinical risk prediction for survival, longitudinal, and multivariate (SLAM) outcomes, called random forest for SLAM data analysis (RF-SLAM). RF-SLAM is a continuous-time, random forest method for survival analysis that combines the strengths of existing statistical and machine learning methods to produce individualized Bayes estimates of piecewise-constant hazard rates. We also present a method-agnostic approach for time-varying evaluation of model performance.

Results

We derive and illustrate the method by predicting sudden cardiac arrest (SCA) in the Left Ventricular Structural (LV) Predictors of Sudden Cardiac Death (SCD) Registry. We demonstrate superior performance relative to standard random forest methods for survival data. We illustrate the importance of the number of preceding heart failure hospitalizations as a time-dependent predictor in SCA risk assessment.

Conclusions

RF-SLAM is a novel statistical and machine learning method that improves risk prediction by incorporating time-varying information and accommodating a large number of predictors, their interactions, and missing values. RF-SLAM is designed to easily extend to simultaneous predictions of multiple, possibly competing, events and/or repeated measurements of discrete or continuous variables over time.Trial registration: LV Structural Predictors of SCD Registry (clinicaltrials.gov, NCT01076660), retrospectively registered 25 February 2010

Evaluating Community-Based Translational Interventions Using Historical Controls: Propensity Score vs. Disease Risk Score Approach

Many community-based translations of evidence-based interventions are designed as one-arm studies due to ethical and other considerations. Evaluating the impacts of such programs is challenging. Here, we examine the effectiveness of the lifestyle intervention implemented by the Special Diabetes Program for Indians Diabetes Prevention (SDPI-DP) demonstration project, a translational lifestyle intervention among American Indian and Alaska Native communities. Data from the landmark Diabetes Prevention Program placebo group was used as a historical control. We compared the use of propensity score (PS) and disease risk score (DRS) matching to adjust for potential confounder imbalance between groups. The unadjusted hazard ratio (HR) for diabetes risk was 0.35 for SDPI-DP lifestyle intervention vs. control. However, when relevant diabetes risk factors were considered, the adjusted HR estimates were attenuated toward 1, ranging from 0.56 (95% CI 0.44-0.71) to 0.69 (95% CI 0.56-0.96). The differences in estimated HRs using the PS and DRS approaches were relatively small but DRS matching resulted in more participants being matched and smaller standard errors of effect estimates. Carefully employed, publicly available randomized clinical trial data can be used as a historical control to evaluate the intervention effectiveness of one-arm community translational initiatives. It is critical to use a proper statistical method to balance the distributions of potential confounders between comparison groups in this kind of evaluations.

Dapagliflozin and cardiovascular mortality and disease outcomes in a population with type 2 diabetes similar to that of the DECLARE-TIMI 58 trial: A nationwide observational study

AIMS

To investigate cardiovascular (CV) safety and event rates for dapagliflozin versus other glucose-lowering drugs (GLDs) in a real-world type 2 diabetes population after applying the main inclusion criteria and outcomes from the DECLARE-TIMI 58 study.

METHODS

Patients with new initiation of dapagliflozin and/or other GLDs were identified in Swedish nationwide healthcare registries for the period 2013 to 2016. Patients were included if they met the main DECLARE-TIMI 58 inclusion criteria: age ≥40 years and established CV disease or presence of multiple-risk factors, e.g. men aged ≥55 years and women aged ≥60 years with hypertension or dyslipidaemia. Propensity scores for the likelihood of dapagliflozin initiation were calculated, then 1:3 matching was carried out. DECLARE-TIMI 58 outcomes were hospitalization for heart failure (HHF) or CV-specific mortality, and major adverse CV events (MACE; CV-specific mortality, myocardial infarction, or stroke). Cox survival models were used to estimate hazard ratios (HRs).

RESULTS

After matching, a total of 28 408 new-users of dapagliflozin and/or other GLDs were identified, forming the population for the present study (henceforth referred to as the DECLARE-like cohort. The mean age of this cohort was 66 years, and 34% had established CV disease. Dapagliflozin was associated with 21% lower risk of HHF or CV mortality versus other GLDs (HR 0.79, 95% confidence interval [CI] 0.69-0.92) and had no significant association with MACE (HR 0.90, 95% CI 0.79-1.03). HHF and CV mortality risks, separately, were lower at HR 0.79 (95% CI 0.67-0.93) and HR 0.75 (95% CI 0.57-0.97), respectively. Non-significant associations were seen for myocardial infarction and stroke: HR 0.91 (95% CI 0.74-1.11) and HR 1.06 (95% CI 0.87-1.30), respectively.

CONCLUSION

In a real-world population similar to those included in the DECLARE-TIMI 58 study, dapagliflozin was safe with regard to CV outcomes and resulted in lower event rates of HHF and CV mortality versus other GLDs.

Assessment of proportional hazard assumption in aggregate data: a systematic review on statistical methodology in clinical trials using time-to-event endpoint

Background

The evaluation of the proportional hazards (PH) assumption in survival analysis is an important issue when Hazard Ratio (HR) is chosen as summary measure. The aim is to assess the appropriateness of statistical methods based on the PH assumption in oncological trials.

Methods

We selected 58 randomised controlled trials comparing at least two pharmacological treatments with a time-to-event as primary endpoint in advanced non-small-cell lung cancer. Data from Kaplan–Meier curves were used to calculate the relative hazard at each time point and the Restricted Mean Survival Time (RMST). The PH assumption was assessed with a fixed-effect meta-regression.

Results

In 19% of the trials, there was evidence of non-PH. Comparison of treatments with different mechanisms of action was associated (P = 0.006) with violation of the PH assumption. In all the superiority trials where non-PH was detected, the conclusions using the RMST corresponded to that based on the Cox model, although the magnitude of the effect given by the HR was systematically greater than the one from the RMST ratio.

Conclusion

As drugs with new mechanisms of action are being increasingly employed, particular attention should be paid on the statistical methods used to compare different types of agents.

Changes in Overall Diet Quality in Relation to Survival in Postmenopausal Women with Breast Cancer: Results from the Women's Health Initiative

BACKGROUND

Lifestyle factors are important for cancer survival. However, empirical evidence regarding the effects of dietary changes on mortality in breast cancer survivors is sparse.

OBJECTIVE

The objective was to examine the associations of changes in overall diet quality, indicated by the Healthy Eating Index (HEI)-2010 score, with mortality in breast cancer survivors.

DESIGN

This was a prospective cohort study from September 1993 through September 30, 2015.

PARTICIPANTS/SETTING

This study included 2,295 postmenopausal women who were diagnosed with invasive breast cancer and completed a food frequency questionnaire both before and after the diagnosis of breast cancer in the Women's Health Initiative.

MAIN OUTCOME MEASURES

The HEI-2010 score (maximum score of 100) was calculated based on consumption of 12 dietary components. The outcomes were mortality from all causes, breast cancer, and causes other than breast cancer.

STATISTICAL ANALYSES PERFORMED

Multivariable Cox proportional hazards models were used to estimate adjusted hazard ratios of mortality from all causes, breast cancer, and other causes.

RESULTS

Over 12 years of follow-up, 763 deaths occurred. Compared with women with relatively stable diet quality (±14.9% change in HEI-2010 score), women who decreased diet quality (≥15% decrease in HEI-2010 score) had a higher risk of death from breast cancer (adjusted hazard ratio 1.66, 95% CI 1.09 to 2.52). Increased diet quality (≥15% increase in HEI-2010 score) was not significantly associated with lower risk of death. These associations persisted after additional adjustment for change in body mass index.

CONCLUSIONS

Among women with breast cancer, decreased diet quality after breast cancer diagnosis was associated with higher risk of death from breast cancer.

Lower Risk of Heart Failure and Death in Patients Initiated on Sodium-Glucose Cotransporter-2 Inhibitors Versus Other Glucose-Lowering Drugs: The CVD-REAL Study (Comparative Effectiveness of Cardiovascular Outcomes in New Users of Sodium-Glucose Cotransporter-2 Inhibitors)

BACKGROUND

Reduction in cardiovascular death and hospitalization for heart failure (HHF) was recently reported with the sodium-glucose cotransporter-2 inhibitor (SGLT-2i) empagliflozin in patients with type 2 diabetes mellitus who have atherosclerotic cardiovascular disease. We compared HHF and death in patients newly initiated on any SGLT-2i versus other glucose-lowering drugs in 6 countries to determine if these benefits are seen in real-world practice and across SGLT-2i class.

METHODS

Data were collected via medical claims, primary care/hospital records, and national registries from the United States, Norway, Denmark, Sweden, Germany, and the United Kingdom. Propensity score for SGLT-2i initiation was used to match treatment groups. Hazard ratios for HHF, death, and their combination were estimated by country and pooled to determine weighted effect size. Death data were not available for Germany.

RESULTS

After propensity matching, there were 309 056 patients newly initiated on either SGLT-2i or other glucose-lowering drugs (154 528 patients in each treatment group). Canagliflozin, dapagliflozin, and empagliflozin accounted for 53%, 42%, and 5% of the total exposure time in the SGLT-2i class, respectively. Baseline characteristics were balanced between the 2 groups. There were 961 HHF cases during 190 164 person-years follow-up (incidence rate, 0.51/100 person-years). Of 215 622 patients in the United States, Norway, Denmark, Sweden, and the United Kingdom, death occurred in 1334 (incidence rate, 0.87/100 person-years), and HHF or death in 1983 (incidence rate, 1.38/100 person-years). Use of SGLT-2i, versus other glucose-lowering drugs, was associated with lower rates of HHF (hazard ratio, 0.61; 95% confidence interval, 0.51-0.73; P<0.001); death (hazard ratio, 0.49; 95% confidence interval, 0.41-0.57; P<0.001); and HHF or death (hazard ratio, 0.54; 95% confidence interval, 0.48-0.60; P<0.001) with no significant heterogeneity by country.

CONCLUSIONS

In this large multinational study, treatment with SGLT-2i versus other glucose-lowering drugs was associated with a lower risk of HHF and death, suggesting that the benefits seen with empagliflozin in a randomized trial may be a class effect applicable to a broad population of patients with type 2 diabetes mellitus in real-world practice.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT02993614.

Extended versus Standard Pelvic Lymph Node Dissection in Radical Prostatectomy on Oncological and Functional Outcomes: A Systematic Review and Meta-Analysis

BACKGROUND

We evaluated the effect of the extent of pelvic lymph node dissection (PLND) on oncological and functional outcomes in patients with intermediate- to high-risk prostate cancer (PCa) by conducting a systematic review and meta-analysis.

METHODS

Two independent researchers performed a systematic review of radical prostatectomy (RP) with extended PLND (ePLND), and RP with standard (sPLND) or limited PLND (lPLND) in patients with PCa using the PubMed, EMBASE, and Cochrane Library databases and using the terms 'prostatectomy', 'lymph node excision', and 'prostatic neoplasm'. The primary outcome was biochemical-free survival, which was analyzed by extracting survival data from the published Kaplan-Meier (KM) curves. In addition, we obtained summarized survival curves by reconstructing the KM data. Secondary outcomes of the recovery of erection and continence were also analyzed.

RESULTS

Nine studies involving over 1554 patients were included, one of which was a randomized controlled trial. The pooled analysis showed a significant difference in biochemical recurrence between ePLND and sPLND (hazard ratio 0.71, 95% confidence interval 0.56-0.90, p = 0.005), with no significant between-study heterogeneity (I ² = 37%). From the summary survival curves, it can be observed that the curves for the two groups diverged more and more as a function of time. From the analyses of functional outcomes including only three studies, no statistically significant differences in the recovery of erectile function and continence were observed. No evidence of significant publication bias was found.

CONCLUSIONS

In patients with PCa, ePLND could be an oncological benefit; however, a functional compromise cannot be determined.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample

Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women's Health Initiative.

Cartilage-Repair Innovation at a Standstill: Methodologic and Regulatory Pathways to Breaking Free

Articular cartilage defects strongly predispose patients to developing early joint degeneration and osteoarthritis, but for more than 15 years, no new cartilage-repair technologies that we know of have been approved by the U.S. Food and Drug Administration. Many studies examining novel approaches to cartilage repair, including cell, tissue, or matrix-based techniques, have shown great promise, but completing randomized controlled trials (RCTs) to establish safety and efficacy has been challenging, providing a major barrier to bringing these innovations into clinical use. In this article, we review reasons that surgical innovations are not well-suited for testing through RCTs. We also discuss how analytical methods for reducing bias, such as propensity scoring, make prospective observational studies a potentially viable alternative for testing the safety and efficacy of cartilage-repair and other novel therapies, offering the real possibility of therapeutic innovation.

Comparison of Treatment Effects Measured by the Hazard Ratio and by the Ratio of Restricted Mean Survival Times in Oncology Randomized Controlled Trials

PURPOSE

We aimed to compare empirically the treatment effects measured by the hazard ratio (HR) and by the difference (and ratio) of restricted mean survival times (RMST) in oncology randomized trials.

METHODS

We selected oncology randomized controlled trials from five leading journals during the last 6 months of 2014. We reconstructed individual patient data for one time-to-event outcome from each trial, preferably the primary outcome. We reanalyzed each trial and compared the treatment effect estimated by the HR with that by the difference (and ratio) of RMST. We estimated an average ratio of the HR to the ratio of RMST; an average ratio less than one indicates more optimistic assessments with HRs.

RESULTS

We analyzed 54 randomized controlled trials totaling 33,212 patients. The selected outcome was overall survival in 21 (39%) trials. There was evidence of nonproportionality of hazards in 13 (24%) trials. The HR and RMST-based measures were in agreement regarding the statistical significance of the effect, except in one case. The median HR was 0.84 (Q1 to Q3 range, 0.67 to 0.97) and the median difference in RMST was 1.12 months (range, 0.22 to 2.75 months). The average ratio of the HR to the ratio of RMST was 1.11 (95% CI, 1.07 to 1.15), with substantial between-trial variability (I(2) = 86%). Results were consistent by outcome type (overall survival v other outcomes) and whether the proportional hazard assumption held or not.

CONCLUSION

On average, the HR provided significantly larger treatment effect estimates than the ratio of RMST. The HR may seem large when the absolute effect is small. RMST-based measures should be routinely reported in randomized trials with time-to-event outcomes.

A Reappraisal of Women's Health Initiative Estrogen-Alone Trial: Long-Term Outcomes in Women 50-59 Years of Age

The Women's Health Initiative (WHI) Estrogen-Alone Trial randomized postmenopausal women, 50 to 79 years of age, with prior hysterectomy, to conjugated equine estrogens (CEE) or placebo with a 5.9-year median duration of CEE use. In 2013, the WHI published outcomes for additional extended follow-up. Reported here for the first time is an analysis of the number needed to treat with CEE rather than placebo for younger women (50-59 years) to prevent an adverse long-term outcome. For every 76 women randomized to CEE at 50-59 years, one less myocardial infarction occurred during the 13-year cumulative long-term follow-up. For every 37 women randomized to CEE at 50-59 years, one less woman experienced a global index endpoint (including coronary heart disease, invasive breast cancer, stroke, pulmonary embolism, colorectal cancer, hip fracture, and death) during the 13-year follow-up. Younger women (50-59 years), compared to older women, had more favorable cumulative long-term outcomes for MI and global index. Though a subgroup analysis is not an adequate basis for making primary prevention guideline recommendations, the WHI Estrogen-Alone Trial outcomes strongly suggest that a similar course of estrogen initiated at 50-59 years in postmenopausal women with prior hysterectomy results in significant long-term health benefit.

Observational and clinical trial findings on the comparative effectiveness of diabetes drugs showed agreement

OBJECTIVES

This study compares an observational study of diabetes treatment effectiveness to randomized controlled trials to assess their convergent validity.

STUDY DESIGN AND SETTING

Multivariate models were developed using observational data to describe change in hemoglobin A1c (HbA1c; % unit) and weight (kilograms) after addition of a second-line oral diabetes drug to metformin monotherapy. Randomized trials of these scenarios were systematically identified. The models were used to simulate each trial, and simulated and actual results were compared by linear regression and meta-analysis.

RESULTS

Thirty-two randomized trials of second-line diabetes oral therapy were identified. For all outcomes and drugs studied, simulation and actual results correlated (P < 0.001). There were no statistically significant differences between meta-analyzed randomized and simulated results for effect on HbA1c. For effect on weight, results were qualitatively comparable, but for sulfonylureas, the simulated weight gain was nominally greater than seen in the randomized controlled trials.

CONCLUSION

An observational study of diabetes drug effectiveness showed convergent validity with randomized data. This supports cautious use of the observational research to draw conclusions about drug effectiveness in populations not studied in clinical trials. This approach may be useful in other situations where observational and randomized data need integration.

Changing concepts: Menopausal hormone therapy and breast cancer

Hormone therapy is still used by millions of women for menopausal symptoms. Concerns regarding hormone therapy and breast cancer were initially based on case reports and retrospective case-control studies. However, recent results from large prospective cohort studies and the Women's Health Initiative (WHI) randomized placebo-controlled hormone therapy trials have substantially changed concepts regarding how estrogen alone and estrogen plus progestin influence breast cancer. The preponderance of observational studies suggested that estrogen alone and estrogen plus progestin both increased the risk of breast cancer, with cancers commonly diagnosed at an early stage. However, substantially different results emerged from the WHI randomized hormone therapy trials. In the WHI trial evaluating estrogen plus progestin in postmenopausal women with an intact uterus, combined hormone therapy statistically significantly increased the risk of breast cancer and hindered breast cancer detection, leading to delayed diagnosis and a statistically significant increase in breast cancer mortality. By contrast, estrogen alone use by postmenopausal women with prior hysterectomy in the WHI trial did not substantially interfere with breast cancer detection and statistically significantly decreased the risk of breast cancer. Differential mammography usage patterns may explain differences between observational study and randomized trial results. In clinical practice, hormone therapy users have mammograms more frequently than nonusers, leading to more and earlier stage cancer detection. By contrast, in the WHI randomized trials, mammogram frequency was protocol mandated and balanced between comparison groups. Currently, the different effects of estrogen plus progestin vs estrogen alone on breast cancer are not completely understood.

LifeGene--a large prospective population-based study of global relevance

Studying gene-environment interactions requires that the amount and quality of the lifestyle data is comparable to what is available for the corresponding genomic data. Sweden has several crucial prerequisites for comprehensive longitudinal biomedical research, such as the personal identity number, the universally available national health care system, continuously updated population and health registries and a scientifically motivated population. LifeGene builds on these strengths to bridge the gap between basic research and clinical applications with particular attention to populations, through a unique design in a research-friendly setting. LifeGene is designed both as a prospective cohort study and an infrastructure with repeated contacts of study participants approximately every 5 years. Index persons aged 18-45 years old will be recruited and invited to include their household members (partner and any children). A comprehensive questionnaire addressing cutting-edge research questions will be administered through the web with short follow-ups annually. Biosamples and physical measurements will also be collected at baseline, and re-administered every 5 years thereafter. Event-based sampling will be a key feature of LifeGene. The household-based design will give the opportunity to involve young couples prior to and during pregnancy, allowing for the first study of children born into cohort with complete pre-and perinatal data from both the mother and father. Questions and sampling schemes will be tailored to the participants' age and life events. The target of LifeGene is to enroll 500,000 Swedes and follow them longitudinally for at least 20 years.

Designs for linkage analysis and association studies of complex diseases

Genetic linkage analysis has been a traditional means for identifying regions of the genome with large genetic effects that contribute to a disease. Following linkage analysis, association studies are widely pursued to fine-tune regions with significant linkage signals. For complex diseases which often involve function of multi-genetic variants each with small or moderate effect, linkage analysis has little power compared to association studies. In this chapter, we give a brief review of design issues related to linkage analysis and association studies with human genetic data. We introduce methods commonly used for linkage and association studies and compared the relative merits of the family-based and population-based association studies. Compared to candidate gene studies, a genomewide blind searching of disease variant is proving to be a more powerful approach. We briefly review the commonly used two-stage designs in genome-wide association studies. As more and more biological evidences indicate the role of genomic imprinting in disease, identifying imprinted genes becomes critically important. Design and analysis in genetic mapping imprinted genes are introduced in this chapter. Recent efforts in integrating gene expression analysis and genetic mapping, termed expression quantitative trait loci (eQTLs) mapping or genetical genomics analysis, offer new prospect in elucidating the genetic architecture of gene expression. Designs in genetical genomics analysis are also covered in this chapter.

Improved logrank-type tests for survival data using adaptive weights

For testing for treatment effects with time-to-event data, the logrank test is the most popular choice and has some optimality properties under proportional hazards alternatives. It may also be combined with other tests when a range of nonproportional alternatives are entertained. We introduce some versatile tests that use adaptively weighted logrank statistics. The adaptive weights utilize the hazard ratio obtained by fitting the model of Yang and Prentice (2005, Biometrika 92, 1-17). Extensive numerical studies have been performed under proportional and nonproportional alternatives, with a wide range of hazard ratios patterns. These studies show that these new tests typically improve the tests they are designed to modify. In particular, the adaptively weighted logrank test maintains optimality at the proportional alternatives, while improving the power over a wide range of nonproportional alternatives. The new tests are illustrated in several real data examples.

Data analysis methods and the reliability of analytic epidemiologic research

Publications that compare randomized controlled trial and cohort study results on the effects of postmenopausal estrogen-plus-progestin therapy are reviewed. The 2 types of studies agree in identifying an early elevation in coronary heart disease risk, and a later developing elevation in breast cancer risk. Effects among women who begin hormone therapy within a few years after the menopause may be comparatively more favorable for coronary heart disease and less favorable for breast cancer. These analyses illustrate the potential of modern data analysis methods to enhance the reliability and interpretation of epidemiologic data.

Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease

BACKGROUND

The Women's Health Initiative randomized trial found greater coronary heart disease (CHD) risk in women assigned to estrogen/progestin therapy than in those assigned to placebo. Observational studies had previously suggested reduced CHD risk in hormone users.

METHODS

Using data from the observational Nurses' Health Study, we emulated the design and intention-to-treat (ITT) analysis of the randomized trial. The observational study was conceptualized as a sequence of "trials," in which eligible women were classified as initiators or noninitiators of estrogen/progestin therapy.

RESULTS

The ITT hazard ratios (HRs) (95% confidence intervals) of CHD for initiators versus noninitiators were 1.42 (0.92-2.20) for the first 2 years, and 0.96 (0.78-1.18) for the entire follow-up. The ITT HRs were 0.84 (0.61-1.14) in women within 10 years of menopause, and 1.12 (0.84-1.48) in the others (P value for interaction = 0.08). These ITT estimates are similar to those from the Women's Health Initiative. Because the ITT approach causes severe treatment misclassification, we also estimated adherence-adjusted effects by inverse probability weighting. The HRs were 1.61 (0.97-2.66) for the first 2 years, and 0.98 (0.66-1.49) for the entire follow-up. The HRs were 0.54 (0.19-1.51) in women within 10 years after menopause, and 1.20 (0.78-1.84) in others (P value for interaction = 0.01). We also present comparisons between these estimates and previously reported Nurses' Health Study estimates.

CONCLUSIONS

Our findings suggest that the discrepancies between the Women's Health Initiative and Nurses' Health Study ITT estimates could be largely explained by differences in the distribution of time since menopause and length of follow-up.

Underreporting of energy intake and associated factors in a Latino population at risk of developing type 2 diabetes

The objective of this study was to examine the extent of underreporting of total energy intake and associated factors in a low-income, low-literacy, predominantly Caribbean Latino community in Lawrence, MA. Two hundred fifteen Latinos participated in a diabetes prevention study, for which eligibility included a >or=30% risk of developing diabetes in 7.5 years. Dietary self-reported energy intake was assessed using three randomly selected days of 24-hour diet recalls. Basal metabolic rate (BMR) was estimated using the Mifflin-St Jeor equation. Underreporting was determined by computing a ratio of energy intake to BMR, with a ratio of 1.55 expected for sedentary populations. Linear regression analyses were used to identify factors associated with underreporting (energy intake:BMR ratio). The population was predominately women (77%), middle-aged (mean 52+/-11 years), obese (78% had a body mass index >or=30); low-literate (62% < high school education), unemployed (57% reported no job), married or living with partner (52%), and some had a family history of diabetes (37% had siblings with diabetes). Reported total daily energy intake was 1,540+/-599 kcal, whereas estimated BMR was 1,495.7+/-245.1 kcal/day. When multiplied by an activity factor (1.20 for sedentariness), expected energy intake was 1,794+/-294.0 per day, indicating underreporting by an average of 254 kcal/day. Mean energy intake:BMR was 1.03+/-0.37, and was lower for participants with higher body mass index, siblings with diabetes, sedentary lifestyle, and those who were unemployed. Energy intake underreporting is prevalent in this low-income, low-literacy Caribbean Latino population. Future studies are needed to develop dietary assessment measures that minimize underreporting in this population.

Monitoring and reporting of the Women's Health Initiative randomized hormone therapy trials

BACKGROUND

The Women's Health Initiative (WHI) randomized trial of estrogen plus progestin (E + P) was terminated early based on an assessment of harms exceeding benefits for disease prevention. The results contravened prevailing wisdom and a large body of literature regarding benefits of menopausal hormone therapy. The results and their interpretation have been the subject of considerable debate.

PURPOSE/METHODS

To describe the process of developing a trial monitoring plan, the key interim and final data, and to explain the choice of statistical methods used in trial monitoring and reporting.

RESULTS

A formalized monitoring plan was developed using statistical methods that acknowledged protocol-defined design and analysis plans, input of monitoring board members especially regarding the role of various study outcomes, and multiple comparisons. Major early departures from design assumptions concerning treatment effects indicated a need for additional flexibility in safety monitoring. When the trials were stopped early, questions arose as to how closely the statistical methods in published reports should correspond to those defined by protocol or used in monitoring.

METHODS

were selected to provide a simple and transparent summary of the primary results, with a cautious interpretation promoted by acknowledgement of multiple testing.

CONCLUSIONS

Developing a formal trial monitoring plan with a view towards influencing clinical practice is useful for creating consensus among DSMB members regarding the evidence that would justify stopping a trial and the framework to be used to address statistical complexities. Departures from design assumptions typically occur. These reinforce the role of the DSMB in exercising their judgment, and the judicious adaptation of these statistical guidelines in monitoring and reporting trials. In communicating the results in such circumstances, priority should be given to presenting as fair, accurate and transparent a view of the data and findings as current methods and technology allow.

Observational studies, clinical trials, and the women's health initiative

The complementary roles fulfilled by observational studies and randomized controlled trials in the population science research agenda is illustrated using results from the Women's Health Initiative (WHI). Comparative and joint analyses of clinical trial and observational study data can enhance observational study design and analysis choices, and can augment randomized trial implications. These concepts are described in the context of findings from the WHI randomized trials of postmenopausal hormone therapy and of a low-fat dietary pattern, especially in relation to coronary heart disease, stroke, and breast cancer. The role of biomarkers of exposure and outcome, including high-dimensional genomic and proteomic biomarkers, in the elucidation of disease associations, will also be discussed in these same contexts.

Vascular and metabolic effects of sex steroids: new insights into clinical trials

The early discontinuation of the Women's Health Initiative trials of daily conjugated estrogens and medroxyprogesterone and of conjugated estrogens only was hailed as the "death to the use of hormone replacement regimens" in menopause. The analyses showed risks outweighing benefits of hormone therapy when given broadly to postmenopausal women. The expanding basic science and clinical research on the specific actions of sex steroids at the genomic and nongenomic level, however, shed new insight into these results. This review focuses on the vascular and metabolic effects of sex steroids to illustrate new advances. Understanding the mechanisms of sex steroid receptor action in a tissue-specific manner, ligand-specific dose responses, and the effects of steroid hormones in normal compared to diseased tissues may explain some of the outcomes in the clinical trials. Further research will clarify the potential benefits and risks of hormone therapy after menopause, both in individual patients and in selected populations.

Multistage Sampling for Genetic Studies

In the past, to study Mendelian diseases, segregating families have been carefully ascertained for segregation analysis, followed by collecting extended multiplex families for linkage analysis. This would then be followed by association studies, using independent case-control samples and/or additional family data. Recently, for complex diseases, the initial sampling has been for a genome-wide linkage analysis, often using independent sib-pairs or nuclear families, to identify candidate regions for follow-up with association studies, again using case-control samples and/or additional family data. We now have the ability to conduct genome-wide association studies using 100,000-500,000 diallelic genetic markers. For such studies we focus especially on efficient two-stage association sampling designs, which can retain nearly optimal statistical power at about half the genotyping cost. Similarly, beginning an association study by genotyping pooled samples may also be a viable option if the cost of accurately pooling DNA samples outweighs genotyping costs. Finally, we note that the sampling of family data for linkage analysis is not a practice that should be automatically discontinued.

Early aggressive care and delayed recovery from whiplash: isolated finding or reproducible result?

OBJECTIVE

To test the reproducibility of the finding that early intensive care for whiplash injuries is associated with delayed recovery.

METHODS

We analyzed data from a cohort study of 1,693 Saskatchewan adults who sustained whiplash injuries between July 1, 1994 and December 31, 1994. We investigated 8 initial patterns of care that integrated type of provider (general practitioners, chiropractors, and specialists) and number of visits (low versus high utilization). Cox models were used to estimate the association between patterns of care and time to recovery while controlling for injury severity and other confounders.

RESULTS

Patients in the low-utilization general practitioner group and those in the general medical group had the fastest recovery even after controlling for important prognostic factors. Compared with the low-utilization general practitioner group, the 1-year rate of recovery in the high-utilization chiropractic group was 25% slower (adjusted hazard rate ratio [HRR] 0.75, 95% confidence interval [95% CI] 0.54-1.04), in the low-utilization general practitioner plus chiropractic group the rate was 26% slower (HRR 0.74, 95% CI 0.60-0.93), and in the high-utilization general practitioner plus chiropractic combined group the rate was 36% slower (HRR 0.64, 95% CI 0.50-0.83).

CONCLUSION

The observation that intensive health care utilization early after a whiplash injury is associated with slower recovery was reproduced in an independent cohort of patients. The results add to the body of evidence suggesting that early aggressive treatment of whiplash injuries does not promote faster recovery. In particular, the combination of chiropractic and general practitioner care significantly reduces the rate of recovery.

Traditional nonsteroidal anti-inflammatory drugs and postmenopausal hormone therapy: a drug-drug interaction?

BACKGROUND

Suppression of prostacyclin (PGI2) is implicated in the cardiovascular hazard from inhibitors of cyclooxygenase (COX)-2. Furthermore, estrogen confers atheroprotection via COX-2-dependent PGI2 in mice, raising the possibility that COX inhibitors may undermine the cardioprotection, suggested by observational studies, of endogenous or exogenous estrogens.

METHODS AND FINDINGS

To identify an interaction between hormone therapy (HT) and COX inhibition, we measured a priori the association between concomitant nonsteroidal anti-inflammatory drugs (NSAIDs), excluding aspirin, in peri- and postmenopausal women on HT and the incidence of myocardial infarction (MI) in a population-based epidemiological study. The odds ratio (OR) of MI in 1,673 individuals and 7,005 controls was increased from 0.66 (95% confidence interval [CI] 0.50-0.88) when taking HT in the absence of traditional (t)NSAIDs to 1.50 (95% CI 0.85-2.64) when taking the combination of HT and tNSAIDs, resulting in a significant (p < 0.002) interaction. The OR when taking aspirin at doses of 150 mg/d or more was 1.41 (95% CI 0.47-4.22). However, a similar interaction was not observed with other commonly used drugs, including lower doses of aspirin, which target preferentially COX-1.

CONCLUSIONS

Whether estrogens confer cardioprotection remains controversial. Such a benefit was observed only in perimenopausal women in the only large randomized trial designed to address this issue. Should such a benefit exist, these results raise the possibility that COX inhibitors may undermine the cardioprotective effects of HT.

Sex steroid effects at target tissues: mechanisms of action

Our understanding of the mechanisms of sex hormone action has changed dramatically over the last 10 years. Estrogens, progestins, and androgens are the steroid hormones that modulate reproductive function. Recent data have shown that many other tissues are targets of sex hormones in addition to classical reproductive organs. This review outlines new advances in our understanding of the spectrum of steroid hormone ligands, newly recognized target tissues, structure-function relationships of steroid receptors, and, finally, their genomic and nongenomic actions. Sex-based specific effects are often related to the different steroid hormone mileu in men compared with women. Understanding the mechanisms of sex steroid action gives insight into the differences in normal physiology and disease states.

Adaptive two-stage analysis of genetic association in case-control designs

We study a two-stage analysis of genetic association for case-control studies. In the first stage, we compare Hardy-Weinberg disequilibrium coefficients between cases and controls and, in the second stage, we apply the Cochran- Armitage trend test. The two analyses are statistically independent when Hardy-Weinberg equilibrium holds in the population, so all the samples are used in both stages. The significance level in the first stage is adaptively determined based on its conditional power. Given the level in the first stage, the level for the second stage analysis is determined with the overall Type I error being asymptotically controlled. For finite sample sizes, a parametric bootstrap method is used to control the overall Type I error rate. This two-stage analysis is often more powerful than the Cochran-Armitage trend test alone for a large association study. The new approach is applied to SNPs from a real study.

Estimating causal effects from observational data with a model for multiple bias

Conventional analyses of observational data may be biased due to confounding, sampling and measurement, and may yield interval estimates that are much too narrow because they do not take into account uncertainty about unknown bias parameters, such as misclassification probabilities. We used a simple, multiple bias adjustment method to estimate the causal effect of social anxiety disorder (SAD) on subsequent depression. A Monte Carlo sensitivity analysis was applied to data from the Early Developmental Stages of Psychiatry (EDSP) study, and bias due to confounding, sampling and measurement was modelled. With conventional logistic regression analysis, the risk for depression was elevated in the presence of SAD only in the older cohort (age 17-24 years at baseline assessment); odds ratio (OR) = 3.06, 95% confidence interval (CI) 1.64-5.70, adjusted for sex and age. The bias-adjusted estimate was 2.01 with interval limits of 0.61 and 9.71. Thus, given the data and the bias model used, there was considerably more uncertainty about the real effect, but the probability that SAD increases the risk for subsequent depression (OR > 1) was 88.6% anyway. Multiple bias modelling, if properly used, reveals the necessity for a better understanding of bias, suggesting a need to conduct larger and more adequate validation studies on instruments that are used to diagnose mental disorders.

Statistical Issues in Genomic Cohort Studies

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

Cardiovascular risk and hormone replacement therapy

PURPOSE OF REVIEW

The purpose of this review is to summarize the studies in humans of the relationship between hormone replacement therapy and coronary heart disease and stroke.

RECENT FINDINGS

Randomized controlled trial evidence of the effect of hormone replacement therapy on coronary heart disease, stroke and atherosclerosis comes from nine individual secondary prevention randomized controlled trials, four individual primary prevention randomized controlled trials and a pooled analysis of 22 randomized controlled trials that had primary aims to examine noncardiovascular outcomes but which reported cardiovascular events by randomized groups. With the exception of one small primary prevention randomized controlled trial that found a weak protective effect of hormone replacement therapy on the progression of carotid artery intima media thickness, all other randomized controlled trials have found hormone replacement therapy either increases the risk of cardiovascular disease or has no effect.

SUMMARY

Randomized controlled trial evidence conducted in a variety of populations suggests that hormone replacement therapy is not protective against the risk of coronary heart disease, stroke or progression of atherosclerosis. The prevention of cardiovascular disease in women, as in men, should focus on implementing effective methods of reducing smoking, obesity, high blood pressure, dyslipidaemia and glucose intolerance.

Neuroendocrine changes in the aging reproductive axis of female rhesus macaques (Macaca mulatta)

Femalerhesus macaques show monthly menstrual cycles and eventually enter menopause at approximately 25 yr of age. To help identify early biomarkers of menopause in this nonhuman primate, we monitored reproductive hormones longitudinally from aged female macaques during the transitions from premenopause to perimenopause and postmenopause and found that, indeed, elevated plasma FSH was a better predictive factor of menopause onset than age. In a second experiment, we compared reproductive hormone profiles of young adult macaques (8-10 yr old) with those of regularly cycling old macaques (approximately 24 yr old). Indwelling vascular catheters were used for remote blood collection for at least 100 consecutive days, thereby covering three complete menstrual cycles in each macaque. Plasma levels of estradiol, progesterone, LH, FSH, follicular phase inhibin B, and anti-müllerian hormone (AMH) were determined during each menstrual cycle and were averaged for each animal; group mean differences were analyzed using one-way ANOVA. Old premenopausal macaques showed regular menstrual cycles that were qualitatively indistinguishable from those of young macaques; peak plasma levels of estradiol, progesterone, and LH were not significantly different. In marked contrast, peak plasma FSH concentrations were significantly higher, while inhibin B and AMH levels were generally lower, in the old premenopausal macaques compared with those in the young macaques. These data provide further evidence that rhesus macaques serve as an excellent model to study underlying mechanisms of human menopause. Furthermore, the data suggest that an age-related change in FSH, inhibin B, and AMH secretion may be the first endocrine manifestation of the transition into perimenopause, potentially having value in predicting the onset of the perimenopausal transition.

Current state of hormone replacement therapy: the case for using trimegestone

Estrogen deficiency has a negative impact on the quality of life of postmenopausal women and is associated with vasomotor symptoms, insomnia and emotional lability. Other manifestations of estrogen deficiency include dry skin, dry vagina and dyspareunia, in addition to bone loss. Estrogen replacement effectively reverses these changes. The only indication for the administration of a progestogen is to protect the postmenopausal uterus against the potential development of endometrial hyperplasia and carcinoma.