Background Heart failure presents a growing clinical and economic burden in the USA. Robust cost data on the burden of illness are critical to inform economic evaluations of new therapeutic interventions. Objectives This systematic literature review of heart failure-related costs in the USA aimed to assess the quality of the published evidence and provide a narrative synthesis of current data. Methods Four electronic databases (MEDLINE, EMBASE, EconLit, and the Centre for Reviews and Dissemination York Database, including the NHS Economic Evaluation Database and Health Technology Assessment Database) were searched for journal articles published between January 2014 and March 2020. The review, registered with PROSPERO (CRD42019134201), was restricted to cost-of-illness studies in adults with heart failure events in the USA. Results Eighty-seven studies were included, 41 of which allowed a comparison of cost estimates across studies. The annual median total medical costs for heart failure care were estimated at $24,383 per patient, with heart failure-specific hospitalizations driving costs (median $15,879 per patient). Analyses of subgroups revealed that heart failure-related costs are highly sensitive to individual patient characteristics (such as the presence of comorbidities and age) with large variations even within a subgroup. Additionally, differences in study design and a lack of standardized reporting limited the ability to compare cost estimates. The finding that costs are higher for patients with heart failure with reduced ejection fraction compared with patients with preserved ejection fraction highlights the need for differentiating among different heart failure types. Conclusions The review underpins the conclusion drawn in earlier reviews, namely that hospitalization costs are the key driver of heart failure-related costs. Analyses of subgroups provide a clearer understanding of sources of heterogeneity in cost data. While current cost estimates provide useful indications of economic burden, understanding the nuances of the data is critical to support its application. Electronic supplementary material The online version of this article (10.1007/s40273-020-00952-0) contains supplementary material, which is available to authorized users.

Studies of the effects of exposures after cancer diagnosis on cancer recurrence and survival can provide important information to the growing group of cancer survivors. Observational studies that address this issue generally fall into one of two categories: 1) those using health plan automated data that contain "continuous" information on exposures, such as studies that use pharmacy records; and 2) survey or interview studies that collect information directly from patients once or periodically postdiagnosis. Reverse causation, confounding, selection bias, and information bias are common in observational studies of cancer outcomes in relation to exposures after cancer diagnosis. We describe these biases, focusing on sources of bias specific to these types of studies, and we discuss approaches for reducing them. Attention to known challenges in epidemiologic research is critical for the validity of studies of postdiagnosis exposures and cancer outcomes.

Background Breast cancer tends to occur in an older age group of women also burdened with comorbidities such as cardiovascular disease (CVD). Numerous medications used to manage CVD (e.g., statins and antihypertensives) are hypothesized to alter breast cancer risk, but there are few studies on breast cancer outcomes. The COMBO (COmmonly used Medications and Breast Cancer Outcomes) cohort was developed to study how medications and co-morbidities influence breast cancer prognosis. Methods Cohort study among adult women, diagnosed with incident early stage breast cancer, and enrolled in an integrated health plan. Data sources included health plan administrative databases, Surveillance, Epidemiology, and End Results tumor registry, and medical records. Statins, angiotensin converting enzyme inhibitors (ACEI), beta blockers (BB), calcium blockers, and diuretics were the exposures of interest. The outcome was second breast cancer events (SBCE) defined as recurrence or second primary breast cancer. We used multivariable Cox proportional hazards models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for SBCE and components of SBCE. Results 4,216 women were followed for a median of 6.3 years, and 13.2% experienced a SBCE (first of: n=415 recurrences and n=143 second primary breast cancers). Compared to non-users, we observed an increased risk of second primary breast cancer with ACEI use (HR=1.66; 95% CI, 1.06–2.58) and an increased risk of recurrence with BB use (HR=1.29; 95% CI, 1.01–1.64). There was suggestion of a reduced risk of SBCE with statin use (HR=0.82; 95% CI, 0.62–1.08) and second primary breast cancer with BB use (HR=0.77; 95% CI, 0.50–1.19). No differences in outcomes were observed by duration of medication use. Conclusions The majority of CVD medications evaluated in this study appear safe with respect to SBCE, but ACEI and BB use warrant further evaluation. The study presented is one example of the questions that can be addressed using the COMBO cohort.