Explore the vast range of titles available.

Evidence-based medicine is the application of scientific evidence to clinical practice. This article discusses the difficulties of applying global evidence (\"average effects\" measured as population means) to local problems (individual patients or groups who might depart from the population average). It argues that the benefit or harm of most treatments in clinical trials can be misleading and fail to reveal the potentially complex mixture of substantial benefits for some, little benefit for many, and harm for a few. Heterogeneity of treatment effects reflects patient diversity in risk of disease, responsiveness to treatment, vulnerability to adverse effects, and utility for different outcomes. Recognizing these factors, researchers can design studies that better characterize who will benefit from medical treatments, and clinicians and policymakers can make better use of the results.

This exploratory trial was conducted to test the effects of an alpha7 nicotinic receptor partial agonist, TC-5619, on cognitive dysfunction and negative symptoms in subjects with schizophrenia. In the United States and India, 185 outpatients (18-60 years; male 69%; 46% tobacco users) with schizophrenia treated with quetiapine or risperidone monotherapy were randomized to 12 weeks of placebo (n=91) or TC-5619 (n=94; orally once daily 1 mg day 1 to week 4, 5 mg week 4 to 8, and 25 mg week 8 to 12). The primary efficacy outcome measure was the Groton Maze Learning Task (GMLT; executive function) of the CogState Schizophrenia Battery (CSB). Secondary outcome measures included: CSB composite score; Scale for Assessment of Negative Symptoms (SANS); Clinical Global Impression-Global Improvement (CGI-I); CGI-severity (CGI-S); and Subject Global Impression-Cognition. GMLT statistically favored TC-5619 (P=0.036) in this exploratory trial. SANS also statistically favored TC-5619 (P=0.030). No other secondary outcome measure demonstrated a drug effect in the total population; there was a statistically significant drug effect on working memory in tobacco users. The results were typically stronger in favor of TC-5619 in tobacco users and occasionally better in the United States than in India. TC-5619 was generally well tolerated with no clinically noteworthy safety findings. These results support the potential benefits of TC-5619 and alpha7 nicotinic receptor partial agonists for cognitive dysfunction and negative symptoms in schizophrenia.

Public health researchers are addressing new research questions (e.g., effects of environmental tobacco smoke, Hurricane Katrina) for which the randomized controlled trial (RCT) may not be a feasible option. Drawing on the potential outcomes framework (Rubin Causal Model) and Campbellian perspectives, we consider alternative research designs that permit relatively strong causal inferences. In randomized encouragement designs, participants are randomly invited to participate in one of the treatment conditions, but are allowed to decide whether to receive treatment. In quantitative assignment designs, treatment is assigned on the basis of a quantitative measure (e.g., need, merit, risk). In observational studies, treatment assignment is unknown and presumed to be nonrandom. Major threats to the validity of each design and statistical strategies for mitigating those threats are presented.

Objectives. We explore how misclassification in disease status can distort the exposure–disease association in a study with dichotomous disease and exposure status. Methods. We define the difference in population odds ratios between populations with and without disease misclassification as population-level bias and derive the bias as a function of sensitivity and specificity for observed disease status. The magnitude and direction of bias can be elucidated through analytic derivations, as illustrated with numerical examples. Results. Patterns of bias exist not only for nondifferential misclassification but also for some differential misclassification scenarios. We have provided conditions defined in terms of sensitivity and specificity that correspond to each pattern of bias. Conclusions. Caution is needed in interpreting results when misclassification is present. Our findings can be used to assess the effects of disease misclassification in a population when sensitivity and specificity are known or can be estimated.

Background The COVID-19 pandemic spurred publication of a rapid proliferation of studies on potential therapeutic agents. While important for the advancement of clinical care, pressure to collect, analyze, and report data in an expedited manner could potentially increase the rate of important errors, some of which would be captured in published errata. We hypothesized that COVID-19 therapeutic studies published in the early years of the pandemic would be associated with a high rate of published errata and that, within these errata, there would be a high prevalence of serious errors. Methods We performed a review of published errata associated with empirical studies of COVID-19 treatments. Errata were identified via a MEDLINE and Embase search spanning January 2020 through September 2022. Errors located within each published erratum were characterized by location within publication, error type, and error seriousness. Results Of 47 studies on COVID-19 treatments with published errata, 18 met inclusion criteria. Median time from publication of the original article to publication of the associated erratum was 76 days (range, 12–511 days). A majority of errata addressed issues with author attribution or conflict of interest disclosures (39.5%) or numerical results (25.6%). Only one erratum contained a serious error: a typographical error which could have misled readers into believing that the treatment in question had serious adverse effects when in fact it did not. Conclusions Despite accelerated publication times, we found among studies of COVID-19 treatments the majority of errata (17/18) reported minor errors that did not lead to misinterpretation of the study results. Retractions, an indicator of scientific misdirection even more concerning than errata, were beyond the scope of this review.

Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation research. However, combining sampling strategies may be more appropriate to the aims of implementation research and more consistent with recent developments in quantitative methods. This paper reviews the principles and practice of purposeful sampling in implementation research, summarizes types and categories of purposeful sampling strategies and provides a set of recommendations for use of single strategy or multistage strategy designs, particularly for state implementation research.

ObjectivesOpioids and non-steroidal anti-inflammatory drugs (NSAIDs) are frequently prescribed for chronic musculoskeletal pain, despite limited evidence of effectiveness and well-documented adverse effects. We assessed the effects of participating in a structured, personalized self-experiment (“N-of-1 trial”) on analgesic prescribing in patients with chronic musculoskeletal pain.MethodsWe randomized 215 patients with chronic pain to participate in an N-of-1 trial facilitated by a mobile health app or to receive usual care. Medical records of participating patients were reviewed at enrollment and 6 months later to assess analgesic prescribing. We established thresholds of ≥ 50, ≥ 20, and > 0 morphine milligram equivalents (MMEs) per day to capture patients taking relatively high doses only, patients taking low-moderate as well as relatively high doses, and patients taking any dose of opioids, respectively.ResultsThere was no significant difference between the N-of-1 and control groups in the percentage of patients prescribed any opioids (relative odds ratio (ROR) = 1.05; 95% confidence interval [CI] = 0.61 to 1.80, p = 0.87). There was a clinically substantial but statistically not significant reduction of the percentage of patients receiving ≥ 20 MME (ROR = 0.58; 95% CI = 0.33 to 1.04, p = 0.07) and also in the percentage receiving ≥ 50 MME (ROR = 0.50; 95% CI = 0.19 to 1.34, p = 0.17). There was a significant reduction in the proportion of patients in the N-of-1 group prescribed NSAIDs compared with control (relative odds ratio = 0.53; 95% CI = 0.29 to 0.96, p = 0.04), with no concomitant increase in average pain intensity. There was no significant change in use of adjunctive medications (acetaminophen, gabapentenoids, or topicals).DiscussionThese exploratory results suggest that participation in N-of-1 trials may reduce long-term use of NSAIDs; there is also a weak signal for an effect on use of opioids. Additional research is needed to confirm these results and elucidate possible mechanisms.Trial RegistrationClinicalTrials.gov Identifier: NCT02116621.

The differential effects of so-called 'first- and second generation' antipsychotic medications, when given in the first episode, on the long-term outcome of schizophrenia remain to be elucidated. We compared the 9-year outcomes of individuals initially randomised to clozapine or chlorpromazine. One-hundred and sixty individuals with treatment-naive, first episode schizophrenia or schizophreniform disorder in a mental health centre in Beijing, China were randomised to clozapine or chlorpromazine treatment for up to 2 years,followed by up to an additional 7 years of naturalistic treatment. The primary outcome was remission status for individuals in each group. Individuals in both groups spent essentially equal amounts of time in each clinical state over the follow-up time period(remission, 78%; intermediate, 8%; relapse, 14%). There were no significant differences on other measures of illness severity. The clozapine group was more likely than the chlorpromazine group to remain on the medication to which they were originally assigned (26% v. 10%, P = 0.01). There were no significant differences between the two groups on other secondary efficacy outcomes. These findings support the comparability in effectiveness between antipsychotic medications but with slightly greater tolerability of clozapine in the treatment of first-episode psychosis.

Randomized controlled trials in depressed patients selected for elevated suicidal risk are rare. The resultant lack of data leaves uncertainty about treatment in this population. This study compared a serotonin reuptake inhibitor with a noradrenergic/dopaminergic antidepressant in major depression with elevated suicidal risk factors. We conducted a double-blind, randomized, clinical pilot trial of paroxetine ( N =36) or bupropion ( N =38) in DSM IV major depression with a suicide attempt history or current suicidal ideation. The effects during acute (8 weeks) and continuation treatment (up to 16 weeks) were measured. Main outcomes were suicidal behavior and ideation. The secondary outcome was modified 17-item Hamilton Depression Rating Scale score subtracting the suicide item (mHDRS-17). Treatment was not associated with time to a suicidal event and no treatment main effect or treatment × time interaction on suicidal ideation or mHDRS-17 was found. Exploratory model selection showed modest advantages for paroxetine on: (1) mHDRS-17 ( p =0.02); and (2) in a separate model adjusted for baseline depression, for suicidal ideation measured with the Beck Scale for Suicidal Ideation ( p =0.03), with benefit increasing with baseline severity. Depressed patients with greater baseline suicidal ideation treated with paroxetine compared with bupropion appeared to experience greater acute improvement in suicidal ideation, after adjusting for global depression. Given the lack of evidence-based pharmacotherapy guidelines for suicidal, depressed patients—an important public health population—this preliminary finding merits further study.

OBJECTIVE: To determine whether redefining primary care team roles would improve outcomes for patients beginning a new treatment episode for major depression. DESIGN: Following stratification, 6 of 12 practices were randomly assigned to the intervention condition. Intervention effectiveness was evaluated by patient reports of 6-month change in 100-point depression symptom and functional status scales. SETTING: Twelve community primary care practices across the country employing no onsite mental health professional. PATIENTS: Using two-stage screening, practices enrolled 479 depressed adult patients (73.4% of those eligible); 90.2% completed six-month follow-up. INTERVENTION: Two primary care physicians, one nurse, and one administrative staff member in each intervention practice received brief training to improve the detection and management of major depression. MAIN RESULTS: In patients beginning a new treatment episode, the intervention improved depression symptoms by 8.2 points (95% confidence interval [CI], 0.2 to 16.1; P=.04). Within this group, the intervention improved depression symptoms by 16.2 points (95% CI, 4.5 to 27.9; P=.007), physical role functioning by 14.1 points (95% CI, 1.1 to 29.2; P=.07), and satisfaction with care (P=.02) for patients who reported antidepressant medication was an acceptable treatment at baseline. Patients already in treatment at enrollment did not benefit from the intervention. CONCLUSIONS: In practices without onsite mental health professionals, brief interventions training primary care teams to assume redefined roles can significantly improve depression outcomes in patients beginning a new treatment episode. Such interventions should target patients who report that antidepressant medication is an acceptable treatment for their condition. More research is needed to determine how primary care teams can best sustain these redefined roles over time.[PUBLICATION ABSTRACT]