Clinical Trials最新文献

BackgroundIn randomized controlled trials (RCTs), unplanned design modifications due to unexpected circumstances are seldom reported. Naively lumping data from pre- and post-design changes to estimate the size of the treatment effect, as planned in the original study, can introduce systematic bias and limit interpretability of the trial findings. There has been limited discussion on how to estimate the treatment effect when an RCT undergoes major design changes during the trial. Using our recently completed RCT, which underwent multiple design changes, as an example, we examined the statistical implications of design changes on the treatment effect estimates.MethodsOur example RCT aimed to test an advance care planning intervention targeting dementia patients and their surrogate decision-makers compared to usual care. The original trial underwent two major mid-trial design changes resulting in three smaller studies. The changes included altering the number of study arms and adding new recruitment sites, thus perturbing the initial statistical assumptions. We used a simulation study to mimic these design modifications in our RCT, generate independent patient-level data and evaluate naïve lumping of data, a two-stage fixed-effect and random-effect meta-analysis model to obtain an average effect size estimate from all studies. Standardized mean-difference and odds-ratio estimates at post-intervention were used as effect sizes for continuous and binary outcomes, respectively. The performance of the estimates from different methods were compared by studying their statistical properties (e.g. bias, mean squared error, and coverage probability of 95% confidence intervals).ResultsWhen between-design heterogeneity is negligible, the fixed- and random-effect meta-analysis models yielded accurate and precise effect-size estimates for both continuous and binary data. As between-design heterogeneity increased, the estimates from random meta-analysis methods indicated less bias and higher coverage probability compared to the naïve and fixed-effect methods, however the mean squared error was higher indicating greater uncertainty arising from a small number of studies. The between-study heterogeneity parameter was not precisely estimable due to fewer studies. With increasing sample sizes within each study, the effect-size estimates showed improved precision and statistical power.ConclusionsWhen a trial undergoes unplanned major design changes, the statistical approach to estimate the treatment effect needs to be determined carefully. Naïve lumping of data across designs is not appropriate even when the overall goal of the trial remains unchanged. Understanding the implications of the different aspects of design changes and accounting for them in the analysis of the data are essential for internal validity and reporting of the trial findings. Importantly, investigators must disclose the design changes clearly in their study reports.

A growing literature has explored the ethical obligations and current practices related to sharing aggregate results with research participants. However, no prior work has examined these issues in the context of pragmatic clinical trials. Several characteristics of pragmatic clinical trials may complicate both the ethics and the logistics of sharing aggregate results. Among these characteristics include that pragmatic clinical trials may affect the rights, welfare, and interests of not only patient-subjects but also clinicians, meaning that results may be owed to a broader range of groups than typically considered in other research contexts. In addition, some pragmatic clinical trials are conducted under a waiver of informed consent, meaning sharing results may alert participants that they were enrolled without their consent. This article explores the ethical dimensions that can inform decision-making about sharing aggregate results from pragmatic clinical trials, and provides recommendations for that sharing. A central insight is that healthcare institutions-as key partners for the conduct of pragmatic clinical trials-must also be key partners in decision-making about sharing aggregate pragmatic clinical trial results. We conclude with insights for future research.

Monitoring the conduct of phase III randomized controlled trials is driven by ethical reasons to protect the study integrity and the safety of trial participants. We propose a group sequential, pragmatic approach for monitoring the accumulating efficacy information in randomized controlled trials. The "Population Health Research Institute boundary" is simple to implement and sensible, as it considers the reduction in uncertainty with increasing information as the study progresses. It is also pragmatic, since it takes into consideration the typical monitoring behavior of monitoring committees of large multicenter trials and is relatively easily implemented. It not only controls the overall Lan-DeMets type I error probability (alpha) spent, but performs better than other group sequential boundaries for the total nominal study alpha. We illustrate the use of our monitoring approach in the early termination of two past completed trials.

Background/aims: Clinical trials provide an opportunity to identify new treatments and can offer patients access to treatments otherwise unavailable. However, approximately 10% of paediatric clinical trials discontinue before the trial has completed. If this premature termination is because the trial treatment(s) being investigated are identified to be ineffective or unsafe, it results in the abrupt discontinuation of the investigational medicinal product for participants. For some participants, there may not be other treatment options to pursue at the trial-end. Trials prematurely terminating can be a distressing experience for all involved and currently there is little published evidence about the guidance provided to healthcare professionals in the event of premature trial termination. The study protocol is the source of guidance for healthcare professionals delivering clinical research, detailing how to conduct all aspects of the trial. The aim was to quantify the proportion of clinical trial protocols that included premature trial termination and subsequently those that provided instructions related to participant management and care. In addition, to analyse the context in which premature termination was included and the detail of any instructions for participant management and care.

Methods: The ClinicalTrials.gov database was searched by a single reviewer for UK interventional drug trials enrolling children with an available study protocol. Protocols were searched to assess if the risk of premature trial termination was identified, the context for premature termination being included, if information was provided to support the management and care of participants should this situation occur and the detail of those instructions. Data were summarised descriptively.

Results: Of 245 clinical trial protocols, 235 (95.9%) identified the possibility of premature trial termination, the majority within the context of the sponsor asserting their right to terminate the trial (82.7%, 115/235) and providing reasons why the trial could be stopped (65.5%, 91/235). Forty-two percent (98/235) provided guidance for participant management and care, most commonly to contact/inform the participant (45.9%, 45/98). Directions varied in the quantity and level of detail.

Conclusions: This review of UK clinical trial protocol highlights that information surrounding premature termination is lacking, with only 42% providing guidance on the care of trial participants. While this ensures regulatory compliance, it fails to consider the challenge for healthcare professionals in managing participants on-going care or the duty of care owed to participants. Further research is required to understand if additional documents are being used in practice, and if these meet the needs of healthcare professionals in supporting research participants and families during premature trial termination

Background: Over the course of a clinical trial, irregularities may arise in the data. Trialists implement human-intensive, expensive central statistical monitoring procedures to identify and correct these irregularities before the results of the trial are analyzed and disseminated. Machine learning algorithms have shown promise for identifying center-level irregularities in multi-center clinical trials with minimal human intervention. We aimed to characterize the form-level data irregularities in several historical clinical trials and evaluate the ability of a machine learning-based outlier detection algorithm to identify them.

Methods: Data irregularities previously identified by humans in historical clinical trials were ascertained by comparing preliminary snapshots of the trial databases to the final, locked databases. We measured the ability of a machine learning based outlier detection algorithm to identify form-level irregularities using concordance (area under the receiver operator characteristic), positive predictive value (precision), and sensitivity (recall).

Results: We examined preliminary snapshots of seven historical clinical trials which randomized a total of 77,001 participants. We extracted a total of 1,267,484 completed entries from 358 case report forms containing irregularities from all snapshots across all trials, containing a total of 24,850 form-wide irregularities (median per-form form-level irregularity rate: 1.81%). Our proposed machine learning algorithm detects form-level irregularities with a median concordance of 0.74 (interquartile range = 0.57-0.89), slightly exceeding the performance of a previously proposed machine learning approach with a median area under the receiver operator characteristic of 0.73 (interquartile range = 0.54-0.88).

Conclusion: Data irregularities in historical clinical trials were ascertained by comparing preliminary snapshots of the trial database to the final database. These irregularities can be categorized according to their scope. Irregularities can be successfully detected by a machine learning algorithm as early or earlier than a human can, without human intervention. Such an approach may complement existing techniques for central statistical monitoring in large multi-center randomized controlled trials and possibly improve the efficiency of costly data verification processes.

Background/aims: The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE^®) was developed to capture symptomatic adverse events from the patient perspective. We aim to describe statistical properties of PRO-CTCAE items and summary scores and to provide evidence for recommendations regarding PRO-CTCAE administration and reporting.

Methods: Using data from the PRO-CTCAE validation study (NCT02158637), prevalence, means, and standard deviations of PRO-CTCAE items, composite scores, and mean and maximum scores across attributes (frequency, severity, and/or interference) of symptomatic adverse events were calculated. For each adverse event, correlations and agreement between attributes, correlations between attributes and composite scores, and correlations between composite, mean, and maximum scores were estimated.

Results: PRO-CTCAE items were completed by 899 patients with various cancer types. Most patients reported experiencing one or more adverse events, with the most prevalent being fatigue (87.7%), sad/unhappy feelings (66.0%), anxiety (63.6%), pain (63.2%), insomnia (61.8%), and dry mouth (60.0%). Attributes were moderately to strongly correlated within an adverse event (r = 0.53 to 0.77, all p < 0.001) but not fully concordant (κ_weighted = 0.26 to 0.60, all p < 0.001), with interference demonstrating lowest mean scores and prevalence among attributes of the same adverse event. Attributes were moderately to strongly correlated with composite scores (r = 0.67 to 0.97, all p < 0.001). Composite scores were moderately to strongly correlated with mean and maximum scores for the same adverse event (r = 0.69 to 0.94, all p < 0.001). Correlations between composite scores of different adverse events varied widely (r = 0.04 to 0.68) but were moderate to strong for conceptually related adverse events.

Conclusions: Results provide evidence for PRO-CTCAE administration and reporting recommendations that the full complement of attributes be administered for each adverse event, and that attributes as well as summary scores be reported.

There is growing interest in using embedded research methods, particularly pragmatic clinical trials, to address well-known evidentiary shortcomings afflicting the health care system. Reviews of pragmatic clinical trials published between 2014 and 2019 found that 8.8% were conducted with waivers of informed consent; furthermore, the number of trials where consent is not obtained is increasing with time. From a regulatory perspective, waivers of informed consent are permissible when certain conditions are met, including that the study involves no more than minimal risk, that it could not practicably be carried out without a waiver, and that waiving consent does not violate participants' rights and welfare. Nevertheless, when research is conducted with a waiver of consent, several ethical challenges arise. We must consider how to: address empirical evidence showing that patients and members of the public generally prefer prospective consent, demonstrate respect for persons using tools other than consent, promote public trust and investigator integrity, and ensure an adequate level of participant protections. In this article, we use examples drawn from real pragmatic clinical trials to argue that prospective consultation with representatives of the target study population can address, or at least mitigate, many of the ethical challenges posed by waivers of informed consent. We also consider what consultation might involve to illustrate its feasibility and address potential objections.

Background/aims: Including women of childbearing age in a clinical trial makes it necessary to consider two factors from a bioethical perspective: first, the lack of knowledge about the potential teratogenic effects of an investigational product, and also, the principle of justice not to exclude any population from the benefits of research. The most common way to address this issue is by requiring volunteers to use contraceptives before, during, and a few weeks after the clinical trial. This work presents all the strategies used to promote contraception use and prevent pregnancy during the Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease (API ADAD) Colombia clinical trial. Two characteristics of this trial make it of special interest for closely monitoring contraception use. One is that the trial lasted more than 7 years, and the other is that participants could be carriers of the E280A PSEN1 mutation, leading to a mild cognitive impairment as early as their late 30s.

Methods: An individual medical evaluation to select the contraception method that best fits the volunteer was carried out during the screening visit, remitting to the gynecologist when necessary. All non-surgical contraception methods were supplied by the sponsor. Staff were trained on contraception counseling, correctly dispensing contraceptive drugs to volunteers, and identifying, reporting, and following up on pregnancies. Two comprehensive educational campaigns on contraception use were performed, and the intervention included all volunteers. In addition, volunteers were asked on an annual survey to evaluate the dispensing procedure. Finally, the effectiveness of these strategies was retrospectively evaluated, comparing by extrapolation the number of pregnancies presented throughout the trial with the General Fertility Rate in Colombia.

Results: A total of 159 female volunteers were recruited. All strategies were implemented as planned, even during the COVID-19 contingency. Ten pregnancies occurred during the evaluation period (2015-2021). Two were planned; the rest were associated with a potential therapeutic failure or incorrect use of contraceptive methods for a contraceptive failure of 0.49% per year. Sixty percent of pregnancies led to an abortion, either miscarriage or therapeutic abortion. However, there was not enough data to associate the pregnancy outcome with the administration of the investigational product. Finally, we observed a lower fertility rate in women participating in the trial compared to the Colombian population.

Conclusion: The lower rates of contraceptive failure and the decrease in the incidence of pregnancies in women participating in the trial compared to the Colombian population across the 7 years of evaluation suggest that the strategies used in API ADAD Colombia were adequate and effective in addressing contraception use.

Background: Concerns about low accrual have long been a standard part of the discourse on cancer clinical trials, reaching even as far as the news media. Indeed, so many trials are closed before completing accrual that a cottage industry has recently developed creating statistical models to predict trial failure. We previously proposed four methodologic fixes for the current crisis in clinical trials: (1) dramatically reducing the number of eligibility criteria, (2) using data routinely collected in clinical practice for trial endpoints; then lowering barriers to accrual by (3) cluster randomization or (4) staged consent.

Methods: We report our practical experience of applying these fixes to randomized trials at Memorial Sloan Kettering Cancer Center.

Results: We have completed seven single-center randomized trials, with several more underway and accruing rapidly, with a total accrual approaching 10,000. Many of the trials have compared surgical interventions, an area where trials have traditionally been hard to complete. Only one of these trials was externally funded. While low costs were possible due to the existing research infrastructure at our institution, such infrastructure is common at major cancer centers.

Conclusions: Further research on innovative clinical trial designs is warranted, particularly in higher-stakes settings, and in trials of medical and radiotherapy interventions.