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Abstract Rationale Since their approval, there has been no real-world or randomized trial evidence evaluating the effect of the antifibrotic medications pirfenidone and nintedanib on clinically important outcomes such as mortality and hospitalizations. Objectives To evaluate the clinical effectiveness of the antifibrotic medications pirfenidone and nintedanib in patients with idiopathic pulmonary fibrosis. Methods Using a large U.S. insurance database, we identified 8,098 patients with idiopathic pulmonary fibrosis between October 1, 2014 and March 1, 2018. A one-to-one propensity score–matched cohort was created to compare patients treated with antifibrotic medications (n = 1,255) with those not on treatment (n = 1,255). The primary outcome was all-cause mortality. The secondary outcome was acute hospitalizations. Subgroup analyses were performed to evaluate mortality differences by drug. Measurements and Main Results The use of antifibrotic medications was associated with a decreased risk of all-cause mortality (hazard ratio [HR], 0.77; 95% confidence interval [CI], 0.62–0.98; P value = 0.034). However, this association was present only through the first 2 years of treatment. There was also a decrease in acute hospitalizations in the treated cohort (HR, 0.70; 95% CI, 0.61–0.80; P value <0.001). There was no significant difference in all-cause mortality between patients receiving pirfenidone and those on nintedanib (HR, 1.14; 95% CI, 0.79–1.65; P = 0.471). Conclusions Among patients with idiopathic pulmonary fibrosis, antifibrotic agents may be associated with a lower risk of all-cause mortality and hospitalization compared with no treatment. Future research should test the hypothesis that these treatments reduce early, but not long-term, mortality as demonstrated in our study.

Background. The value of rapid, panel-based molecular diagnostics for positive blood culture bottles (BCBs) has not been rigorously assessed. We performed a prospective randomized controlled trial evaluating outcomes associated with rapid multiplex PCR (rmPCR) detection of bacteria, fungi, and resistance genes directly from positive BCBs. Methods. A total of 617 patients with positive BCBs underwent stratified randomization into 3 arms: standard BCB processing (control, n = 207), rmPCR reported with templated comments (rmPCR, n = 198), or rmPCR reported with templated comments and real-time audit and feedback of antimicrobial orders by an antimicrobial stewardship team (rmPCR/AS, n = 212). The primary outcome was antimicrobial therapy duration. Secondary outcomes were time to antimicrobial de-escalation or escalation, length of stay (LOS), mortality, and cost. Results. Time from BCB Gram stain to microorganism identification was shorter in the intervention group (1.3 hours) vs control (22.3 hours) (P < .001). Compared to the control group, both intervention groups had decreased broad-spectrum piperacillin-tazobactam (control 56 hours, rmPCR 44 hours, rmPCR/AS 45 hours; P = .01) and increased narrow-spectrum β-lactam (control 42 hours, rmPCR 71 hours, rmPCR/AS 85 hours; P = .04) use, and less treatment of contaminants (control 25%, rmPCR 11%, rmPCR/AS 8%; P = .015). Time from Gram stain to appropriate antimicrobial de-escalation or escalation was shortest in the rmPCR/AS group (de-escalation: rmPCR/AS 21 hours, control 34 hours, rmPCR 38 hours, P < .001; escalation: rmPCR/AS 5 hours, control 24 hours, rmPCR 6 hours, P = .04). Groups did not differ in mortality, LOS, or cost. Conclusions. rmPCR reported with templated comments reduced treatment of contaminants and use of broad-spectrum antimicrobials. Addition of antimicrobial stewardship enhanced antimicrobial de-escalation. Clinical Trials Registration. NCT01898208.

To design a functional, patient-centered model of patient complexity with practical applicability to analytic design and clinical practice. Existing literature on patient complexity has mainly identified its components descriptively and in isolation, lacking clarity as to their combined functions in disrupting care or to how complexity changes over time. The authors developed a cumulative complexity model, which integrates existing literature and emphasizes how clinical and social factors accumulate and interact to complicate patient care. A narrative literature review is used to explicate the model. The model emphasizes a core, patient-level mechanism whereby complicating factors impact care and outcomes: the balance between patient workload of demands and patient capacity to address demands. Workload encompasses the demands on the patient's time and energy, including demands of treatment, self-care, and life in general. Capacity concerns ability to handle work (e.g., functional morbidity, financial/social resources, literacy). Workload-capacity imbalances comprise the mechanism driving patient complexity. Treatment and illness burdens serve as feedback loops, linking negative outcomes to further imbalances, such that complexity may accumulate over time. With its components largely supported by existing literature, the model has implications for analytic design, clinical epidemiology, and clinical practice.

Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown. Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates. We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01), improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively), had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001). Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer). There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07); medication adherence at 6 months was no different across arms. Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results. clinical trials.gov NCT00949611.

Although randomized clinical trials are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence to evaluate the efficacy and safety of medical interventions is gaining interest. Whether observational data can be used to address the same clinical questions being answered by traditional clinical trials is still unclear. To identify the number of clinical trials published in high-impact journals in 2017 that could be feasibly replicated using observational data from insurance claims and/or electronic health records (EHRs). In this cross-sectional analysis, PubMed was searched to identify all US-based clinical trials, regardless of randomization, published between January 1, 2017, and December 31, 2017, in the top 7 highest-impact general medical journals of 2017. Trials were excluded if they did not involve human participants, did not use end points that represented clinical outcomes among patients, were not characterized as clinical trials, and had no recruitment sites in the United States. The primary outcomes were the number and percentage of trials for which the intervention, indication, trial inclusion and exclusion criteria, and primary end points could be ascertained from insurance claims and/or EHR data. Of the 220 US-based trials analyzed, 33 (15.0%) could be replicated using observational data because their intervention, indication, inclusion and exclusion criteria, and primary end points could be routinely ascertained from insurance claims and/or EHR data. Of the 220 trials, 86 (39.1%) had an intervention that could be ascertained from insurance claims and/or EHR data. Among the 86 trials, 62 (72.1%) had an indication that could be ascertained. Forty-five (72.6%) of 62 trials had at least 80% of inclusion and exclusion criteria data that could be ascertained. Of these 45 studies, 33 (73.3%) had at least 1 primary end point that could be ascertained. This study found that only 15% of the US-based clinical trials published in high-impact journals in 2017 could be feasibly replicated through analysis of administrative claims or EHR data. This finding suggests the potential for real-world evidence to complement clinical trials, both by examining the concordance between randomized experiments and observational studies and by comparing the generalizability of the trial population with the real-world population of interest.

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.

The use of medical imaging procedures has been increasing, and this study estimated the exposure of U.S. patients to low-dose ionizing radiation from these procedures. The exposure was substantial, largely because of radiation from computed tomography and nuclear imaging. The highest average effective dose was attributable to myocardial perfusion imaging, and most imaging occurred in outpatient settings. These data indicate that the use of imaging can result in high radiation doses. This study estimated the exposure of U.S. patients to low-dose ionizing radiation from medical imaging procedures. The exposure was substantial, largely because of radiation from computed tomography and nuclear imaging. Experimental and epidemiologic evidence has linked exposure to low-dose, ionizing radiation with the development of solid cancers and leukemia. 1 As a result, persons at risk for repeated radiation exposure, such as workers in health care and the nuclear industry, are typically monitored and restricted to effective doses of 100 mSv every 5 years (i.e., 20 mSv per year), with a maximum of 50 mSv allowed in any given year. 2 , 3 In contrast, radiation exposure in patients who undergo medical imaging procedures is not typically monitored, and patient data on longitudinal radiation exposure from these procedures are scant, even though in . . .

Patient-clinician secure messaging is an important function in patient portals and enables patients and clinicians to communicate on a wide spectrum of issues in a timely manner. With its growing adoption and patient engagement, it is time to comprehensively study the secure messages and user behaviors in order to improve patient-centered care. The aim of this paper was to analyze the secure messages sent by patients and clinicians in a large multispecialty health system at Mayo Clinic, Rochester. We performed message-based, sender-based, and thread-based analyses of more than 5 million secure messages between 2010 and 2017. We summarized the message volumes, patient and clinician population sizes, message counts per patient or clinician, as well as the trends of message volumes and user counts over the years. In addition, we calculated the time distribution of clinician-sent messages to understand their workloads at different times of a day. We also analyzed the time delay in clinician responses to patient messages to assess their communication efficiency and the back-and-forth rounds to estimate the communication complexity. During 2010-2017, the patient portal at Mayo Clinic, Rochester experienced a significant growth in terms of the count of patient users and the total number of secure messages sent by patients and clinicians. Three clinician categories, namely \"physician-primary care,\" \"registered nurse-specialty,\" and \"physician-specialty,\" bore the majority of message volume increase. The patient portal also demonstrated growing trends in message counts per patient and clinician. The \"nurse practitioner or physician assistant-primary care\" and \"physician-primary care\" categories had the heaviest per-clinician workload each year. Most messages by the clinicians were sent from 7 AM to 5 PM during a day. Yet, between 5 PM and 7 PM, the physicians sent 7.0% (95,785/1,377,006) of their daily messages, and the nurse practitioner or physician assistant sent 5.4% (22,121/408,526) of their daily messages. The clinicians replied to 72.2% (1,272,069/1,761,739) patient messages within 1 day and 90.6% (1,595,702/1,761,739) within 3 days. In 95.1% (1,499,316/1,576,205) of the message threads, the patients communicated with their clinicians back and forth for no more than 4 rounds. Our study found steady increases in patient adoption of the secure messaging system and the average workload per clinician over 8 years. However, most clinicians responded timely to meet the patients' needs. Our study also revealed differential patient-clinician communication patterns across different practice roles and care settings. These findings suggest opportunities for care teams to optimize messaging tasks and to balance the workload for optimal efficiency.

In this study of the review time for new-drug applications for novel therapeutics approved in the United States, Canada, and Europe from 2001 through 2010, the FDA completed reviews more quickly than did the European Medicines Agency (EMA) and Health Canada. The Prescription Drug User Fee Act (PDUFA) of 1992 was enacted to augment the resources of the Food and Drug Administration (FDA) that are devoted to reviewing applications for drugs for humans and to ensuring drug efficacy and safety. 1 In exchange for meeting clear performance standards, the FDA is authorized by PDUFA to collect user fees for each new application to support the infrastructure needed for review, such as the hiring of additional staff. Although PDUFA has contributed to a substantial reduction in the review times for drug applications over the past two decades, 2 , 3 meeting these performance standards has . . .

ObjectiveTo identify the relationships between county-level area deprivation and patterns of both opioid prescriptions and drug-poisoning mortality.Design, setting and participantsFor this retrospective cross-sectional study, we used the IQVIA Xponent data to capture opioid prescriptions and Centres for Disease Control and Prevention National Vital Statistics System to assess drug-poisoning mortality. The Area Deprivation Index (ADI) is a composite measure of social determinants of health comprised of 17 US census indicators, spanning four socioeconomic domains. For all US counties with available opioid prescription (2712 counties) and drug-poisoning mortality (3133 counties) data between 2012 and 2017, we used negative binomial regression to examine the association between quintiles of county-level ADI and the rates of opioid prescriptions and drug-poisoning mortality adjusted for year, age, race and sex.Primary outcome measuresCounty-level opioid prescription fills and drug-poisoning mortality.ResultsBetween 2012 and 2017, overall rates of opioid prescriptions decreased from 96.6 to 72.2 per 100 people, while the rates of drug-poisoning mortality increased from 14.3 to 22.8 per 100 000 people. Opioid prescription and drug-poisoning mortality rates were consistently higher with greater levels of deprivation. The risk of filling an opioid prescription was 72% higher, and the risk of drug-poisoning mortality was 36% higher, for most deprived compared with the least deprived counties (both p<0.001).DiscussionCounties with greater area-level deprivation have higher rates of filled opioid prescriptions and drug-poisoning mortality. Although opioid prescription rates declined across all ADI quintiles, the rates of drug-poisoning mortality continued to rise proportionately in each ADI quintile. This underscores the need for individualised and targeted interventions that consider the deprivation of communities where people live.