Canada’s First Celebrity Drug Trial: R v. Hatfield, 1985

Since the 1960s, celebrity drug trials have usually involved actors or musicians. The first drug prosecution of a Canadian “celebrity” took place in 1985 after the Royal Canadian Mounted Police (RCMP) found a small amount of marijuana in the luggage of New Brunswick Premier Richard Hatfield at the airport in Fredericton. He was charged with simple possession and, aided by a team of lawyers, pleaded not guilty. Although Hatfield was the most successful premier in the province’s history, he was facing challenges over the economy and language policy, and a finding of guilt would have devastated both his political career and the fortunes of his party. This article examines the Hatfield drug prosecution, which was followed by revelations of drug use with university students in 1981, as a chapter in Canadian legal and political history. It involved not only a privileged defendant, but also the independence of judges, the role of the RCMP, the relationship between the courts and the media, federal-provincial relations and an internal RCMP probe. Hatfield, the political celebrity, won his 1985 court battle but, with his lifestyle impugned, lost in the court of public opinion. In 1987, his party was crushed by the landslide victory of Frank McKenna’s Liberals.

Using historical data to facilitate clinical prevention trials in Alzheimer disease? An analysis of longitudinal MCI (mild cognitive impairment) data sets

Background The Placebo Group Simulation Approach (PGSA) aims at partially replacing randomized placebo-controlled trials (RPCTs), making use of data from historical control groups in order to decrease the needed number of study participants exposed to lengthy placebo treatment. PGSA algorithms to create virtual control groups were originally derived from mild cognitive impairment (MCI) data of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. To produce more generalizable algorithms, we aimed to compile five different MCI databases in a heuristic manner to create a “standard control algorithm” for use in future clinical trials. Methods We compared data from two North American cohort studies (n=395 and 4328, respectively), one company-sponsored international clinical drug trial (n=831) and two convenience patient samples, one from Germany (n=726), and one from Switzerland (n=1558). Results Despite differences between the five MCI samples regarding inclusion and exclusion criteria, their baseline demographic and cognitive performance data varied less than expected. However, the five samples differed markedly with regard to their subsequent cognitive performance and clinical development: (1) MCI patients from the drug trial did not deteriorate on verbal fluency over 3 years, whereas patients in the other samples did; (2) relatively few patients from the drug trial progressed from MCI to dementia (about 10% after 4 years), in contrast to the other four samples with progression rates over 30%. Conclusion Conventional MCI criteria were insufficient to allow for the creation of well-defined and internationally comparable samples of MCI patients. More recently published criteria for MCI or “MCI due to AD” are unlikely to remedy this situation. The Alzheimer scientific community needs to agree on a standard set of neuropsychological tests including appropriate selection criteria to make MCI a scientifically more useful concept. Patient data from different sources would then be comparable, and the scientific merits of algorithm-based study designs such as the PGSA could be properly assessed.

Comparison of weekly and daily recall of pain as an endpoint in a randomized phase 3 trial of cabozantinib for metastatic castration-resistant prostate cancer

Introduction Scant evidence reveals whether the use of weekly versus daily pain ratings leads to meaningful differences when measuring pain as a clinical trial outcome. We compared the ability of weekly ratings and descriptors of daily ratings to evaluate pain as an endpoint in a randomized phase 3 drug trial. Methods Participants ( n = 119) with metastatic castration-resistant prostate cancer were randomized to treatment arms and rated their pain on the average and at its worst during a baseline week and at weeks 3, 6, and 12 of study treatment. For each reporting period, participants rated their pain daily for 7 days. On day 7, participants rated their pain over the prior 7 days. We estimated mean differences and intraclass correlation coefficients of the weekly ratings and the mean and the maximum daily ratings. We compared the ability of the weekly ratings and the daily rating descriptors to detect change in pain and evaluated the agreement of the weekly rating and the mean daily rating of pain at its worst to detect treatment response. Results For both pain constructs, the weekly rating was consistently higher than the mean daily rating and lower than the maximum daily rating yet was moderately to highly correlated with both daily rating descriptors (intraclass correlation coefficient range = 0.55–0.94). The weekly rating and the daily rating descriptors consistently detected change in pain for the study sample and participant subgroups. Substantial agreement existed between the weekly rating and the mean daily rating of pain at its worst when used with trial protocol opioid criteria to detect treatment response (Cohen’s κ = 0.71). Conclusion Use of daily over weekly ratings delivered no added benefit in evaluating pain in this clinical trial. This study is the first to compare weekly and daily recall to measure pain as an endpoint in a randomized phase 3 drug trial, and the pattern of differences in ratings that we observed is consistent with other recent evaluations of weekly and daily symptom reporting.

Using Historical Data to Facilitate Clinical Prevention Trials in Alzheimer Disease?

BackgroundThe Placebo Group Simulation Approach (PGSA) aims at partially replacing Randomized Placebo-Controlled Trials (RPCTs) using data from historical control groups in order to decrease the needed number of study participants exposed to lengthy placebo treatment. PGSA algorithms were originally derived from Mild Cognitive Impairment (MCI) data of the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. To produce more generalizable algorithms, we aimed to compile five different MCI databases in an heuristic manner to create a ‘standard control algorithm’ for use in future clinical trials.MethodsWe compared data from two North American cohort studies (n= 395 and 4,328, respectively) one international clinical drug trial (n= 831) and two convenience patient samples, one from Germany (n=726), and one from Switzerland (n=1,558).ResultsDespite differences between the five MCI samples regarding inclusion and exclusion criteria, their baseline demographic and cognitive performance data varied less than expected. However, the five samples differed markedly with regard to their subsequent cognitive performance and clinical development: (1) MCI patients from the drug trial did not deteriorate on verbal fluency over 3 years, whereas patients in the other samples did; (2) relatively few patients from the drug trial progressed from MCI to dementia (about 10% after 4 years), in contrast to the other four samples with progression rates over 30 percent.ConclusionConventional MCI criteria were insufficient to allow for the creation of well-defined and internationally comparable samples of MCI patients. More recently published MCI criteria are unlikely to remedy this situation. The Alzheimer scientific community needs to agree on a standard set of neuropsychological tests including appropriate selection criteria to make MCI a scientifically more useful concept. Patient data from different sources would then be comparable and the scientific merits of algorithm-based study designs such as the PGSA could be properly assessed.

Increasing the reproducibility of fluid biomarker studies in neurodegenerative studies

Biomarkers have revolutionized scientific research on neurodegenerative diseases, in particular Alzheimer’s disease, transformed drug trial design, and are also increasingly improving patient management in clinical practice. A few key cerebrospinal fluid biomarkers have been robustly associated with neurodegenerative diseases. Several novel biomarkers are very promising, especially blood-based markers. However, many biomarker findings have had low reproducibility despite initial promising results. In this perspective, we identify possible sources for low reproducibility of studies on fluid biomarkers for neurodegenerative diseases, with a focus on Alzheimer’s disease. We suggest guidelines for researchers and journal editors, with the aim to improve reproducibility of findings.