Association Between Prescription Drug Monitoring Programs and Nonfatal and Fatal Drug Overdoses: A Systematic Review: Annals of Internal Medicine: Vol 168, No 11

Background: Prescription drug monitoring programs (PDMPs) are a key component of the president's Prescription Drug Abuse Prevention Plan to prevent opioid overdoses in the United States. Purpose: To examine whether PDMP implementation is associated with changes in nonfatal and fatal overdoses; identify features of programs differentially associated with those outcomes; and investigate any potential unintended consequences of the programs. Data Sources: Eligible publications from MEDLINE, Current Contents Connect (Clarivate Analytics), Science Citation Index (Clarivate Analytics), Social Sciences Citation Index (Clarivate Analytics), and ProQuest Dissertations indexed through 27 December 2017 and additional studies from reference lists. Study Selection: Observational studies (published in English) from U.S. states that examined an association between PDMP implementation and nonfatal or fatal overdoses. Data Extraction: 2 investigators independently extracted data from and rated the risk of bias (ROB) of studies by using established criteria. Consensus determinations involving all investigators were used to grade strength of evidence for each intervention. Data Synthesis: Of 2661 records, 17 articles met the inclusion criteria. These articles examined PDMP implementation only (n = 8), program features only (n = 2), PDMP implementation and program features (n = 5), PDMP implementation with mandated provider review combined with pain clinic laws (n = 1), and PDMP robustness (n = 1). Evidence from 3 studies was insufficient to draw conclusions regarding an association between PDMP implementation and nonfatal overdoses. Low-strength evidence from 10 studies suggested a reduction in fatal overdoses with PDMP implementation. Program features associated with a decrease in overdose deaths included mandatory provider review, provider authorization to access PDMP data, frequency of reports, and monitoring of nonscheduled drugs. Three of 6 studies found an increase in heroin overdoses after PDMP implementation. Limitation: Few studies, high ROB, and heterogeneous analytic methods and outcome measurement. Conclusion: Evidence that PDMP implementation either increases or decreases nonfatal or fatal overdoses is largely insufficient, as is evidence regarding positive associations between specific administrative features and successful programs. Some evidence showed unintended consequences. Research is needed to identify a set of “best practices” and complementary initiatives to address these consequences. Primary Funding Source: National Institute on Drug Abuse and Bureau of Justice Assistance.

Percutaneous Closure Versus Medical Treatment in Stroke Patients With Patent Foramen Ovale: A Systematic Review and Meta-analysis: Annals of Internal Medicine: Vol 168, No 5

Background: New evidence emerged recently regarding the percutaneous closure of patent foramen ovale (PFO) to prevent recurrent stroke in patients with cryptogenic stroke. Purpose: To compare risks for recurrent cerebrovascular events in adults with PFO and cryptogenic stroke who underwent PFO closure versus those who received medical therapy alone. Data Sources: PubMed, Scopus, and Google Scholar from 1 December 2004 through 14 September 2017; references of eligible studies; relevant scientific session abstracts; and cardiology Web sites. Study Selection: Randomized controlled trials, published in English, that compared PFO closure using a currently available device with medical treatment alone and that reported, at minimum, the rates of stroke or transient ischemic attack (TIA) or of new-onset atrial fibrillation (AF) or atrial flutter (AFL). Data Extraction: 2 investigators independently extracted study data and assessed study quality. Data Synthesis: 4 of 5 trials comparing PFO closure with medical therapy used commercially available devices. These 4 trials, involving 2531 patients, found that PFO closure reduced the risk for the main outcome of stroke or TIA (risk difference [RD], −0.029 [95% CI, −0.050 to −0.007]) and increased the risk for new-onset AF or AFL (RD, 0.033 [CI, 0.012 to 0.054]). The beneficial effect of PFO closure was associated with larger interatrial shunts (P = 0.034). Limitation: Trials were not double-blind, and inclusion criteria were heterogeneous. Conclusion: Compared with medical treatment, PFO closure prevents recurrent stroke and TIA but increases the incidence of AF or AFL in PFO carriers with cryptogenic stroke. Primary Funding Source: Italian Ministry of Education, University and Research (MIUR). (PROSPERO: CRD42017074686)

Electric Cars and Electromagnetic Interference With Cardiac Implantable Electronic Devices: A Cross-sectional Evaluation

Scrutiny-Dependent Cancer and Self-fulfilling Risk Factors

U.S. Food and Drug Administration Precertification Pilot Program for Digital Health Software: Weighing the Benefits and Risks

In 2017, the U.S. Food and Drug Administration (FDA) announced a new program for software classified as a medical device. The Digital Health Software Precertification (Pre-Cert) Program is designed to expedite regulatory review for companies that demonstrate quality and organizational excellence in software development. Although Pre-Cert is intended to promote the worthy goals of access and innovation in digital health, many questions have been raised. In particular, Pre-Cert may reduce incentives for developers to study the safety and effectiveness of their software products before patients start to rely on them. Although postmarket surveillance can mitigate risks of these products, the FDA does not have as much authority after a product's widespread use to enforce data collection deadlines. Pre-Cert may also create confusion for patients and physicians, who may believe that marketed products were subject to rigorous study.

Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening

Background: Lung cancer screening guidelines recommend using individualized risk models to refer ever-smokers for screening. However, different models select different screening populations. The performance of each model in selecting ever-smokers for screening is unknown. Objective: To compare the U.S. screening populations selected by 9 lung cancer risk models (the Bach model; the Spitz model; the Liverpool Lung Project [LLP] model; the LLP Incidence Risk Model [LLPi]; the Hoggart model; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 [PLCOM2012]; the Pittsburgh Predictor; the Lung Cancer Risk Assessment Tool [LCRAT]; and the Lung Cancer Death Risk Assessment Tool [LCDRAT]) and to examine their predictive performance in 2 cohorts. Design: Population-based prospective studies. Setting: United States. Participants: Models selected U.S. screening populations by using data from the National Health Interview Survey from 2010 to 2012. Model performance was evaluated using data from 337 388 ever-smokers in the National Institutes of Health–AARP Diet and Health Study and 72 338 ever-smokers in the CPS-II (Cancer Prevention Study II) Nutrition Survey cohort. Measurements: Model calibration (ratio of model-predicted to observed cases [expected–observed ratio]) and discrimination (area under the curve [AUC]). Results: At a 5-year risk threshold of 2.0%, the models chose U.S. screening populations ranging from 7.6 million to 26 million ever-smokers. These disagreements occurred because, in both validation cohorts, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) were well-calibrated (expected–observed ratio range, 0.92 to 1.12) and had higher AUCs (range, 0.75 to 0.79) than 5 models that generally overestimated risk (expected–observed ratio range, 0.83 to 3.69) and had lower AUCs (range, 0.62 to 0.75). The 4 best-performing models also had the highest sensitivity at a fixed specificity (and vice versa) and similar discrimination at a fixed risk threshold. These models showed better agreement on size of the screening population (7.6 million to 10.9 million) and achieved consensus on 73% of persons chosen. Limitation: No consensus on risk thresholds for screening. Conclusion: The 9 lung cancer risk models chose widely differing U.S. screening populations. However, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) most accurately predicted risk and performed best in selecting ever-smokers for screening. Primary Funding Source: Intramural Research Program of the National Institutes of Health/National Cancer Institute.

Why Internists Might Want Single-Payer Health Care

Identifying Patients for Whom Lung Cancer Screening Is Preference-Sensitive: A Microsimulation Study: Annals of Internal Medicine: Vol 169, No 1

Background: Many health systems are exploring how to implement low-dose computed tomography (LDCT) screening programs that are effective and patient-centered. Objective: To examine factors that influence when LDCT screening is preference-sensitive. Design: State-transition microsimulation model. Data Sources: Two large randomized trials, published decision analyses, and the SEER (Surveillance, Epidemiology, and End Results) cancer registry. Target Population: U.S.-representative sample of simulated patients meeting current U.S. Preventive Services Task Force criteria for screening eligibility. Time Horizon: Lifetime. Perspective: Individual. Intervention: LDCT screening annually for 3 years. Outcome Measures: Lifetime quality-adjusted life-year gains and reduction in lung cancer mortality. To examine the effect of preferences on net benefit, disutilities (the “degree of dislike”) quantifying the burden of screening and follow-up were varied across a likely range. The effect of varying the rate of false-positive screening results and overdiagnosis associated with screening was also examined. Results of Base-Case Analysis: Moderate differences in preferences about the downsides of LDCT screening influenced whether screening was appropriate for eligible persons with annual lung cancer risk less than 0.3% or life expectancy less than 10.5 years. For higher-risk eligible persons with longer life expectancy (roughly 50% of the study population), the benefits of LDCT screening overcame even highly negative views about screening and its downsides. Results of Sensitivity Analysis: Rates of false-positive findings and overdiagnosed lung cancer were not highly influential. Limitation: The quantitative thresholds that were identified may vary depending on the structure of the microsimulation model. Conclusion: Identifying circumstances in which LDCT screening is more versus less preference-sensitive may help clinicians personalize their screening discussions, tailoring to both preferences and clinical benefit. Primary Funding Source: None.

Aspirin in Patients With Previous Percutaneous Coronary Intervention Undergoing Noncardiac Surgery

Background: Uncertainty remains about the effects of aspirin in patients with prior percutaneous coronary intervention (PCI) having noncardiac surgery. Objective: To evaluate benefits and harms of perioperative aspirin in patients with prior PCI. Design: Nonprespecified subgroup analysis of a multicenter factorial trial. Computerized Internet randomization was done between 2010 and 2013. Patients, clinicians, data collectors, and outcome adjudicators were blinded to treatment assignment. (ClinicalTrials.gov: NCT01082874) Setting: 135 centers in 23 countries. Patients: Adults aged 45 years or older who had or were at risk for atherosclerotic disease and were having noncardiac surgery. Exclusions were placement of a bare-metal stent within 6 weeks, placement of a drug-eluting stent within 1 year, or receipt of nonstudy aspirin within 72 hours before surgery. Intervention: Aspirin therapy (overall trial, n = 4998; subgroup, n = 234) or placebo (overall trial, n = 5012; subgroup, n = 236) initiated within 4 hours before surgery and continued throughout the perioperative period. Of the 470 subgroup patients, 99.9% completed follow-up. Measurements: The 30-day primary outcome was death or nonfatal myocardial infarction; bleeding was a secondary outcome. Results: In patients with prior PCI, aspirin reduced the risk for the primary outcome (absolute risk reduction, 5.5% [95% CI, 0.4% to 10.5%]; hazard ratio [HR], 0.50 [CI, 0.26 to 0.95]; P for interaction = 0.036) and for myocardial infarction (absolute risk reduction, 5.9% [CI, 1.0% to 10.8%]; HR, 0.44 [CI, 0.22 to 0.87]; P for interaction = 0.021). The effect on the composite of major and life-threatening bleeding in patients with prior PCI was uncertain (absolute risk increase, 1.3% [CI, −2.6% to 5.2%]). In the overall population, aspirin increased the risk for major bleeding (absolute risk increase, 0.8% [CI, 0.1% to 1.6%]; HR, 1.22 [CI, 1.01 to 1.48]; P for interaction = 0.50). Limitation: Nonprespecified subgroup analysis with small sample. Conclusion: Perioperative aspirin may be more likely to benefit rather than harm patients with prior PCI. Primary Funding Source: Canadian Institutes of Health Research.

Effect of a Digital Health Intervention on Receipt of Colorectal Cancer Screening in Vulnerable Patients: A Randomized Controlled Trial: Annals of Internal Medicine: Vol 168, No 8

Background: Screening for colorectal cancer (CRC) reduces mortality, yet more than one third of age-eligible Americans are unscreened. Objective: To examine the effect of a digital health intervention, Mobile Patient Technology for Health–CRC (mPATH-CRC), on rates of CRC screening. Design: Randomized clinical trial. (ClinicalTrials.gov: NCT02088333) Setting: 6 community-based primary care practices. Participants: 450 patients (223 in the mPATH-CRC group and 227 in usual care) scheduled for a primary care visit and due for routine CRC screening. Intervention: An iPad application that displays a CRC screening decision aid, lets patients order their own screening tests, and sends automated follow-up electronic messages to support patients. Measurements: The primary outcome was chart-verified completion of CRC screening within 24 weeks. Secondary outcomes were ability to state a screening preference, intention to receive screening, screening discussions, and orders for screening tests. All outcome assessors were blinded to randomization. Results: Baseline characteristics were similar between groups; 37% of participants had limited health literacy, and 53% had annual incomes less than $20 000. Screening was completed by 30% of mPATH-CRC participants and 15% of those receiving usual care (logistic regression odds ratio, 2.5 [95% CI, 1.6 to 4.0]). Compared with usual care, more mPATH-CRC participants could state a screening preference, planned to be screened within 6 months, discussed screening with their provider, and had a screening test ordered. Half of mPATH-CRC participants (53%; 118 of 223) “self-ordered” a test via the program. Limitation: Participants were English speakers in a single health care system. Conclusion: A digital health intervention that allows patients to self-order tests can increase CRC screening. Future research should identify methods for implementing similar interventions in clinical care. Primary Funding Source: National Cancer Institute.