This report aims to provide methodological guidance to help practitioners select the most appropriate weighting method based on propensity scores for their analysis out of many available options (eg, ...inverse probability treatment weights, standardised mortality ratio weights, fine stratification weights, overlap weights, and matching weights), and outlines recommendations for transparent reporting of studies using weighting based on the propensity scores.
Regulators consider randomized controlled trials (RCTs) as the gold standard for evaluating the safety and effectiveness of medications, but their costs, duration, and limited generalizability have ...caused some to look for alternatives. Real world evidence based on data collected outside of RCTs, such as registries and longitudinal healthcare databases, can sometimes substitute for RCTs, but concerns about validity have limited their impact. Greater reliance on such real world data (RWD) in regulatory decision making requires understanding why some studies fail while others succeed in producing results similar to RCTs. Key questions when considering whether RWD analyses can substitute for RCTs for regulatory decision making are WHEN one can study drug effects without randomization and HOW to implement a valid RWD analysis if one has decided to pursue that option. The WHEN is primarily driven by externalities not controlled by investigators, whereas the HOW is focused on avoiding known mistakes in RWD analyses.
The analysis of longitudinal healthcare data outside of highly controlled parallel‐group randomized trials, termed real‐world evidence (RWE), has received increasing attention in the medical ...literature. In this paper, we discuss the potential role of RWE in drug regulation with a focus on the analysis of healthcare databases. We present several cases in which RWE is already used and cases in which RWE could potentially support regulatory decision making. We summarize key issues that investigators and regulators should consider when designing or evaluating such studies, and we propose a structured process for implementing analyses that facilitates regulatory review. We evaluate the empirical evidence base supporting the validity, transparency, and reproducibility of RWE from analysis of healthcare databases and discuss the work that still needs to be done to ensure that such analyses can provide decision‐ready evidence on the effectiveness and safety of treatments.
•Tg mouse models of AD show social withdrawal and depressive-like behaviours with age.•Tg mouse models of AD show early sleep-wake disturbances and increased aggression.•Tg mouse models of AD show ...mixed results concerning generalized apathy or anxiety.•Tg mouse models of AD are an important tool to study biological mechanisms of BPSD.
Transgenic mouse models have been used extensively to model the cognitive impairments arising from Alzheimer’s disease (AD)-related pathology. However, less is known about the relationship between AD-related pathology and the behavioural and psychological symptoms of dementia (BPSD) commonly presented by patients. This review discusses the BPSD-like behaviours recapitulated by several mouse models of AD-related pathology, including the APP/PS1, Tg2576, 3xTg-AD, 5xFAD, and APP23 models. Current evidence suggests that social withdrawal and depressive-like behaviours increase with progressive neuropathology, and increased aggression and sleep-wake disturbances are present even at early stages; however, there is no clear evidence to support increased anxiety-like behaviours, agitation (hyperactivity), or general apathy. Overall, transgenic mouse models of AD-related pathology recapitulate some of the BPSD-like behaviours associated with AD, but these behaviours vary by model. This reflects the patient population, where AD patients typically exhibit one or more BPSD, but rarely all symptoms at once. As a result, we suggest that transgenic mouse models are an important tool to investigate the pathology underlying BPSD in human AD patients.
Many investigational drugs fail in late-stage clinical development. A better understanding of why investigational drugs fail can inform clinical practice, regulatory decisions, and future research.
...To assess factors associated with regulatory approval or reasons for failure of investigational therapeutics in phase 3 or pivotal trials and rates of publication of trial results.
Using public sources and commercial databases, we identified investigational therapeutics that entered pivotal trials between 1998 and 2008, with follow-up through 2015. Agents were classified by therapeutic area, orphan designation status, fast track designation, novelty of biological pathway, company size, and as a pharmacologic or biologic product.
For each product, we identified reasons for failure (efficacy, safety, commercial) and assessed the rates of publication of trial results. We used multivariable logistic regression models to evaluate factors associated with regulatory approval.
Among 640 novel therapeutics, 344 (54%) failed in clinical development, 230 (36%) were approved by the US Food and Drug Administration (FDA), and 66 (10%) were approved in other countries but not by the FDA. Most products failed due to inadequate efficacy (n = 195; 57%), while 59 (17%) failed because of safety concerns and 74 (22%) failed due to commercial reasons. The pivotal trial results were published in peer-reviewed journals for 138 of the 344 (40%) failed agents. Of 74 trials for agents that failed for commercial reasons, only 6 (8.1%) were published. In analyses adjusted for therapeutic area, agent type, firm size, orphan designation, fast-track status, trial year, and novelty of biological pathway, orphan-designated drugs were significantly more likely than nonorphan drugs to be approved (46% vs 34%; adjusted odds ratio aOR, 2.3; 95% CI, 1.4-3.7). Cancer drugs (27% vs 39%; aOR, 0.5; 95% CI, 0.3-0.9) and agents sponsored by small and medium-size companies (28% vs 42%; aOR, 0.4; 95% CI, 0.3-0.7) were significantly less likely to be approved.
Roughly half of investigational drugs entering late-stage clinical development fail during or after pivotal clinical trials, primarily because of concerns about safety, efficacy, or both. Results for the majority of studies of investigational drugs that fail are not published in peer-reviewed journals.
Cardiovascular disease is a competing cause of death in patients with cancer with early-stage disease. This elevated cardiovascular disease risk is thought to derive from both the direct effects of ...cancer therapies and the accumulation of risk factors such as hypertension, weight gain, cigarette smoking, and loss of cardiorespiratory fitness. Effective and viable strategies are needed to mitigate cardiovascular disease risk in this population; a multimodal model such as cardiac rehabilitation may be a potential solution. This statement from the American Heart Association provides an overview of the existing knowledge and rationale for the use of cardiac rehabilitation to provide structured exercise and ancillary services to cancer patients and survivors. This document introduces the concept of cardio-oncology rehabilitation, which includes identification of patients with cancer at high risk for cardiac dysfunction and a description of the cardiac rehabilitation infrastructure needed to address the unique exposures and complications related to cancer care. In this statement, we also discuss the need for future research to fully implement a multimodal model of cardiac rehabilitation for patients with cancer and to determine whether reimbursement of these services is clinically warranted.
Background The incidence of opioid-related death in women has increased 5-fold over the past decade. For many women, their initial opioid exposure will occur in the setting of routine medical care. ...Approximately 1 in 3 deliveries in the United States is by cesarean, and opioids are commonly prescribed for postsurgical pain management. Objective The objective of this study was to determine the risk that opioid-naïve women prescribed opioids after cesarean delivery will subsequently become consistent prescription opioid users in the year following delivery and to identify predictors for this behavior. Study Design We identified women in a database of commercial insurance beneficiaries who underwent cesarean delivery and who were opioid naïve in the year prior to delivery. To identify persistent users of opioids, we used trajectory models, which group together patients with similar patterns of medication filling during follow-up, based on patterns of opioid dispensing in the year following cesarean delivery. We then constructed a multivariable logistic regression model to identify independent risk factors for membership in the persistent user group. Results A total of 285 of 80,127 (0.36%, 95% confidence interval, 0.32–0.40), opioid-naïve women became persistent opioid users (identified using trajectory models based on monthly patterns of opioid dispensing) following cesarean delivery. Demographics and baseline comorbidity predicted such use with moderate discrimination (c statistic = 0.73). Significant predictors included a history of cocaine abuse (risk, 7.41%; adjusted odds ratio, 6.11, 95% confidence interval, 1.03–36.31) and other illicit substance abuse (2.36%; adjusted odds ratio, 2.78, 95% confidence interval, 1.12–6.91), tobacco use (1.45%; adjusted odds ratio, 3.04, 95% confidence interval, 2.03–4.55), back pain (0.69%; adjusted odds ratio, 1.74, 95% confidence interval, 1.33–2.29), migraines (0.91%; adjusted odds ratio, 2.14, 95% confidence interval, 1.58–2.90), antidepressant use (1.34%; adjusted odds ratio, 3.19, 95% confidence interval, 2.41–4.23), and benzodiazepine use (1.99%; adjusted odds ratio, 3.72, 95% confidence interval, 2.64–5.26) in the year prior to the cesarean delivery. Conclusion A very small proportion of opioid-naïve women (approximately 1 in 300) become persistent prescription opioid users following cesarean delivery. Preexisting psychiatric comorbidity, certain pain conditions, and substance use/abuse conditions identifiable at the time of initial opioid prescribing were predictors of persistent use.
Randomized clinical trials (RCTs) are the gold standard in producing clinical evidence of efficacy and safety of medical interventions. More recently, a new paradigm is emerging—specifically within ...the context of preauthorization regulatory decision‐making—for some novel uses of real‐world evidence (RWE) from a variety of real‐world data (RWD) sources to answer certain clinical questions. Traditionally reserved for rare diseases and other special circumstances, external controls (eg, historical controls) are recognized as a possible type of control arm for single‐arm trials. However, creating and analyzing an external control arm using RWD can be challenging since design and analytics may not fully control for all systematic differences (biases). Nonetheless, certain biases can be attenuated using appropriate design and analytical approaches. The main objective of this paper is to improve the scientific rigor in the generation of external control arms using RWD. Here we (a) discuss the rationale and regulatory circumstances appropriate for external control arms, (b) define different types of external control arms, and (c) describe study design elements and approaches to mitigate certain biases in external control arms. This manuscript received endorsement from the International Society for Pharmacoepidemiology (ISPE).
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