No abstract

IMPORTANCE Postmarket safety events of novel pharmaceuticals and biologics occur when new safety risks are identified after initial regulatory approval of these therapeutics. These safety events can change how novel therapeutics are used in clinical practice and inform patient and clinician decision making.OBJECTIVES To characterize the frequency of postmarket safety events among novel therapeutics approved by the US Food and Drug Administration (FDA), and to examine whether any novel therapeutic characteristics known at the time of FDA approval were associated with increased risk. EXPOSURES Novel therapeutic characteristics known at the time of FDA approval, including drug class, therapeutic area, priority review, accelerated approval, orphan status, near-regulatory deadline approval, and regulatory review time. MAIN OUTCOMES AND MEASURESA composite of (1) withdrawals due to safety concerns, (2) FDA issuance of incremental boxed warnings added in the postmarket period, and (3) FDA issuance of safety communications.RESULTS From 2001 through 2010, the FDA approved 222 novel therapeutics (183 pharmaceuticals and 39 biologics). There were 123 new postmarket safety events (3 withdrawals, 61 boxed warnings, and 59 safety communications) during a median follow-up period of 11.7 years (interquartile range [IQR], 8.7-13.8 years), affecting 71 (32.0%) of the novel therapeutics. The median time from approval to first postmarket safety event was 4.2 years (IQR, 2.5-6.0 years), and the proportion of novel therapeutics affected by a postmarket safety event at 10 years was 30.8% (95% CI, 25.1%-37.5%). In multivariable analysis, postmarket safety events were statistically significantly more frequent among biologics (incidence rate ratio [IRR] = 1.93; 95% CI, 1.06-3.52; P = .03), therapeutics indicated for the treatment of psychiatric disease (IRR = 3.78; 95% CI, 1.77-8.06; P < .001), those receiving accelerated approval (IRR = 2.20; 95% CI, 1.15-4.21; P = .02), and those with near-regulatory deadline approval (IRR = 1.90; 95% CI, 1.19-3.05; P = .008); events were statistically significantly less frequent among those with regulatory review times less than 200 days (IRR = 0.46; 95% CI, 0.24-0.87; P = .02).CONCLUSIONS AND RELEVANCE Among 222 novel therapeutics approved by the FDA from 2001 through 2010, 32% were affected by a postmarket safety event. Biologics, psychiatric therapeutics, and accelerated and near-regulatory deadline approval were statistically significantly associated with higher rates of events, highlighting the need for continuous monitoring of the safety of novel therapeutics throughout their life cycle.

Background The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning (ML) techniques that address higher dimensional, non-linear relationships among variables would enhance prediction. We sought to compare the effectiveness of several ML algorithms for predicting readmissions. Methods and Results Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of Random Forests (RF), Boosting, RF combined hierarchically with Support Vector Machines (SVM) or Logistic Regression (LR) and Poisson Regression against traditional LR to predict 30-day and 180-day all-cause and heart fauilre-only readmissions. We randomly selected 50% of patients for a derivation set and the remaining patients comprised a validation set, repeated 100 times. We compared c-statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing ML model, RF, provided a 17.8% improvement over LR (mean c-statistics 0.628 and 0.533, respectively). For readmissions due to heart failure, Boosting improved the c-statistic by 24.9% over LR (mean c-statistic 0.678 and 0.543, respectively). For 30-day all cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with RF (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Conclusions ML methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates.

BACKGROUND The upcoming reauthorization of the Prescription Drug User Fee Act focuses on improving the review process for new drug applications at the Food and Drug Administration (FDA). METHODS Using publicly available information from the FDA, the European Medicines Agency (EMA), and Health Canada, we compared the time for completion of the first review and the total review time for all applications involving novel therapeutic agents approved by the three regulatory agencies from 2001 through 2010 and determined the geographic area in which each novel therapeutic agent was first approved for use. RESULTS There were 510 applications for novel therapeutic agents approved from 2001 through 2010 — 225 by the FDA, 186 by the EMA, and 99 by Health Canada; among the applications, there were 289 unique agents. The median length of time for completion of the first review was 303 days (interquartile range, 185 to 372) for applications approved by the FDA, 366 days (interquartile range, 310 to 445) for those approved by the EMA, and 352 days (interquartile range, 255 to 420) for those approved by Health Canada (P<0.001 for the comparison across the three agencies). The median total review time was also shorter at the FDA than at the EMA or Health Canada (P = 0.002). Among the 289 unique novel therapeutic agents, 190 were approved in both the United States and Europe (either by the EMA or through the mutual recognition process), of which 121 (63.7%) were first approved in the United States; similarly, 154 were approved in both the United States and Canada, of which 132 (85.7%) were first approved in the United States. CONCLUSIONS For novel therapeutic agents approved between 2001 and 2010, the FDA reviewed applications involving novel therapeutics more quickly, on average, than did the EMA or Health Canada, and the vast majority of these new therapeutic agents were first approved for use in the United States. (Funded by the Pew Charitable Trusts.)

In a period of dynamic change in health care technology, delivery, and behaviors, tracking trends in health and health care can provide a perspective on what is being achieved.OBJECTIVE To comprehensively describe national trends in mortality, hospitalizations, and expenditures in the Medicare fee-for-service population between 1999 and 2013. DESIGN, SETTING, AND PARTICIPANTS Serial cross-sectional analysis of Medicare beneficiaries aged 65 years or older between 1999 and 2013 using Medicare denominator and inpatient files. MAIN OUTCOMES AND MEASURESFor all Medicare beneficiaries, trends in all-cause mortality; for fee-for-service beneficiaries, trends in all-cause hospitalization and hospitalizationassociated outcomes and expenditures. Geographic variation, stratified by key demographic groups, and changes in the intensity of care for fee-for-service beneficiaries in the last 1, 3, and 6 months of life were also assessed. RESULTSThe sample consisted of 68 374 904 unique Medicare beneficiaries (fee-for-service and Medicare Advantage). All-cause mortality for all Medicare beneficiaries declined from 5.30% in 1999 to 4.45% in 2013 (difference, 0.85 percentage points; 95% CI, 0.83-0.87).

Objective To characterize the prospective controlled clinical studies for all novel drugs that were initially approved by the Food and Drug Administration on the basis of limited evidence. Design Systematic review. Data sources Drugs@FDA database and PubMed. Study inclusion All prospective controlled clinical studies published after approval for all novel drugs initially approved by the FDA between 2005 and 2012 on the basis of a single pivotal trial, pivotal trials that used surrogate markers of disease as primary endpoints, or both. Results Between 2005 and 2012 the FDA approved 117 novel drugs for 123 indications on the basis of a single pivotal trial, pivotal trials that used surrogate markers of disease, or both (single surrogate trials). We identified 758 published controlled studies over a median of 5.5 years (interquartile range 3.4-8.2) after approval, most of which (554 of 758; 73.1%) were studies for indications approved on the basis of surrogate markers of disease. Most postapproval studies used active comparators—67 of 77 (87.0%) indications approved on the basis of single pivotal trials, 365 of 554 (65.9%) approvals based on surrogate marker trials, and 100 of 127 (78.7%) approvals based on single surrogate trials—and examined surrogate markers of efficacy as primary endpoints—51 of 77 (66.2%), 512 of 554 (92.4%), and 110 of 127 (86.6%), respectively. Overall, no postapproval studies were identified for 43 of the 123 (35.0%) approved indications. The median total number of postapproval studies identified was 1 (interquartile range 0-2) for indications approved on the basis of a single pivotal trial, 3 (1-8) for indications approved on the basis of pivotal trials that used surrogate markers of disease as primary endpoints, and 1 (0-2) for single surrogate trial approvals, and the median aggregate number of patients enrolled in postapproval studies was 90 (0-509), 533 (122-3633), and 38 (0-666), respectively. The proportion of approved indications with one or more randomized, controlled, double blind study using a clinical outcome for the primary endpoint that was published after approval and showed superior efficacy was 18.2% (6 of 33), 2.0% (1 of 49), and 4.9% (2 of 41), respectively. Conclusions The quantity and quality of postapproval clinical evidence varied substantially for novel drugs first approved by the FDA on the basis of limited evidence, with few controlled studies published after approval that confirmed efficacy using clinical outcomes for the original FDA approved indication.

IntroductionCollection of high-quality data from large populations is considered essential to generate knowledge that is critical to an era of precision medicine. Cardiovascular disease (CVD) is a leading cause of mortality in China and is a suitable focus of an initiative to discover factors that would improve our ability to assess and modify individual risk.Methods and analysisThe pilot phase of China PEACE (Patient-centered Evaluative Assessment of Cardiac Events) Million Persons Project is being conducted during 2014–2015 in four provinces across China to demonstrate the feasibility of a population-based assessment. It is designed to screen 0.4 million community-dwelling residents aged 40–75 years with measurements of blood pressure, height and weight, a lipid blood test, and a questionnaire on cardiovascular-related health status. Participants identified at high risk of CVD receive further health assessments, including ECG, ultrasound scan, blood and urine analysis, and a questionnaire on lifestyle and medical history. Collection of blood and urine samples is used to establish a biobank. High-risk subjects are also counselled with suggestions regarding potential lifestyle changes. In addition, high-risk subjects are followed-up either in a return clinic visit or by telephone interview, with measurement of blood pressure, weight, ECG, and a questionnaire on survival status, hospitalisations and lifestyle. The first 0.1 million participants screened were used to conduct a preliminary analysis, with information on baseline characteristics, health-related behaviours, anthropometric variables, medical history, and prevalence of high-risk subjects.Ethics and disseminationThe central ethics committee at the China National Center for Cardiovascular Disease (NCCD) approved the pilot. Written informed consent is obtained from all participants on entry into the project. Findings will be disseminated in future peer-reviewed papers and will inform strategies aimed at developing precise methods of assessing and modifying risk.Trial registration numberNCT02536456.

Background: Racial inequities for patients with heart failure (HF) have been widely documented. HF patients who receive cardiology care during a hospital admission have better outcomes. It is unknown whether there are differences in admission to a cardiology or general medicine service by race. This study examined the relationship between race and admission service, and its effect on 30-day readmission and mortality Methods: We performed a retrospective cohort study from September 2008 to November 2017 at a single large urban academic referral center of all patients self-referred to the emergency department and admitted to either the cardiology or general medicine service with a principal diagnosis of HF, who self-identified as white, black, or Latinx. We used multivariable generalized estimating equation models to assess the relationship between race and admission to the cardiology service. We used Cox regression to assess the association between race, admission service, and 30-day readmission and mortality. Results: Among 1967 unique patients (66.7% white, 23.6% black, and 9.7% Latinx), black and Latinx patients had lower rates of admission to the cardiology service than white patients (adjusted rate ratio, 0.91; 95% CI, 0.84–0.98, for black; adjusted rate ratio, 0.83; 95% CI, 0.72–0.97 for Latinx). Female sex and age >75 years were also independently associated with lower rates of admission to the cardiology service. Admission to the cardiology service was independently associated with decreased readmission within 30 days, independent of race. Conclusions: Black and Latinx patients were less likely to be admitted to cardiology for HF care. This inequity may, in part, drive racial inequities in HF outcomes.