Evaluating the Supporting Evidence of Medical Cannabis Claims Made on Clinic Websites: Cross-Sectional Study.

BACKGROUND: Since the legalization of medical cannabis in Canada in 2013, prescription of cannabis for medical purposes has become commonplace and a multibillion dollar industry has formed. Much of the media coverage surrounding medical cannabis has been positive in nature, leading to Canadians potentially underestimating the adverse effects of medical cannabis use. In recent years, there has been a large increase in clinic websites advertising the use of medical cannabis for health indications. However, little is known about the quality of the evidence used by these clinic websites to describe the effectiveness of cannabis used for medical purposes. OBJECTIVE: We aimed to identify the indications for medical cannabis reported by cannabis clinics in Ontario, Canada, and the evidence these clinics cited to support cannabis prescription. METHODS: We conducted a cross-sectional web search to identify all cannabis clinic websites within Ontario, Canada, that had physician involvement and identified their primary purpose as cannabis prescription. Two reviewers independently searched these websites to identify all medical indications for which cannabis was promoted and reviewed and critically appraised all studies cited using the Oxford Centre for Evidence-Based Medicine Levels of Evidence rubric. RESULTS: A total of 29 clinics were identified, promoting cannabis for 20 different medical indications including migraines, insomnia, and fibromyalgia. There were 235 unique studies cited on these websites to support the effectiveness of cannabis for these indications. A high proportion (36/235, 15.3%) of the studies were identified to be at the lowest level of evidence (level 5). Only 4 clinic websites included any mention of harms associated with cannabis. CONCLUSIONS: Cannabis clinic websites generally promote cannabis use as medically effective but cite low-quality evidence to support these claims and rarely discuss harms. The recommendation of cannabis as a general therapeutic for many indications unsupported by high-quality evidence is potentially misleading for medical practitioners and patients. This disparity should be carefully evaluated in context of the specific medical indication and an individualized patient risk assessment. Our work illustrates the need to increase the quality of research performed on the medical effects of cannabis.

Socioeconomic and immigration status and COVID-19 testing in Toronto, Ontario: retrospective cross-sectional study.

BACKGROUND: Preliminary evidence suggests that individuals living in lower income neighbourhoods are at higher risk of COVID-19 infection. The relationship between sociodemographic characteristics and COVID-19 risk warrants further study. METHODS: We explored the association between COVID-19 test positivity and patients' socio-demographic variables, using neighborhood sociodemographic data collected retrospectively from two COVID-19 Assessment Centres in Toronto, ON. RESULTS: Eighty-three thousand four hundred forty three COVID-19 tests completed between April 5-September 30, 2020, were analyzed. Individuals living in neighbourhoods with the lowest income or highest concentration of immigrants were 3.4 (95% CI: 2.7 to 4.9) and 2.5 (95% CI: 1.8 to 3.7) times more likely to test positive for COVID-19 than those in highest income or lowest immigrant neighbourhoods, respectively. Testing was higher among individuals from higher income neighbourhoods, at lowest COVID-19 risk, compared with those from low-income neighbourhoods. CONCLUSIONS: Targeted efforts are needed to improve testing availability in high-risk regions. These same strategies may also ensure equitable COVID-19 vaccine delivery.

Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials.

OBJECTIVE: To report the improvements achieved with clinical decision support systems and examine the heterogeneity from pooling effects across diverse clinical settings and intervention targets. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline up to August 2019. ELIGIBILITY CRITERIA FOR SELECTING STUDIES AND METHODS: Randomised or quasi-randomised controlled trials reporting absolute improvements in the percentage of patients receiving care recommended by clinical decision support systems. Multilevel meta-analysis accounted for within study clustering. Meta-regression was used to assess the degree to which the features of clinical decision support systems and study characteristics reduced heterogeneity in effect sizes. Where reported, clinical endpoints were also captured. RESULTS: In 108 studies (94 randomised, 14 quasi-randomised), reporting 122 trials that provided analysable data from 1 203 053 patients and 10 790 providers, clinical decision support systems increased the proportion of patients receiving desired care by 5.8% (95% confidence interval 4.0% to 7.6%). This pooled effect exhibited substantial heterogeneity (I2=76%), with the top quartile of reported improvements ranging from 10% to 62%. In 30 trials reporting clinical endpoints, clinical decision support systems increased the proportion of patients achieving guideline based targets (eg, blood pressure or lipid control) by a median of 0.3% (interquartile range -0.7% to 1.9%). Two study characteristics (low baseline adherence and paediatric settings) were associated with significantly larger effects. Inclusion of these covariates in the multivariable meta-regression, however, did not reduce heterogeneity. CONCLUSIONS: Most interventions with clinical decision support systems appear to achieve small to moderate improvements in targeted processes of care, a finding confirmed by the small changes in clinical endpoints found in studies that reported them. A minority of studies achieved substantial increases in the delivery of recommended care, but predictors of these more meaningful improvements remain undefined.

Janus Kinase Mutations in Mice Lacking PU.1 and Spi-B Drive B Cell Leukemia through Reactive Oxygen Species-Induced DNA Damage.

Precursor B cell acute lymphoblastic leukemia (B-ALL) is caused by genetic lesions in developing B cells that function as drivers for the accumulation of additional mutations in an evolutionary selection process. We investigated secondary drivers of leukemogenesis in a mouse model of B-ALL driven by PU.1/Spi-B deletion (Mb1-CreΔPB). Whole-exome-sequencing analysis revealed recurrent mutations in Jak3 (encoding Janus kinase 3), Jak1, and Ikzf3 (encoding Aiolos). Mutations with a high variant-allele frequency (VAF) were dominated by C→T transition mutations that were compatible with activation-induced cytidine deaminase, whereas the majority of mutations, with a low VAF, were dominated by C→A transversions associated with 8-oxoguanine DNA damage caused by reactive oxygen species (ROS). The Janus kinase (JAK) inhibitor ruxolitinib delayed leukemia onset, reduced ROS and ROS-induced gene expression signatures, and altered ROS-induced mutational signatures. These results reveal that JAK mutations can alter the course of leukemia clonal evolution through ROS-induced DNA damage.

Association of Low-Value Testing With Subsequent Health Care Use and Clinical Outcomes Among Low-risk Primary Care Outpatients Undergoing an Annual Health Examination.

Importance: The association of low-value testing with downstream care and clinical outcomes among primary care outpatients is unknown to date. Objective: To assess the association of low-value testing with subsequent care among low-risk primary care outpatients undergoing an annual health examination (AHE). Design, Setting, and Participants: This population-based retrospective cohort study used administrative health care claims from Ontario, Canada, for primary care outpatients undergoing an AHE between April 1, 2012, and March 31, 2016, to identify individuals who could be placed into one (or more) of the following 3 cohorts: adult patients (18 years or older) at low risk for cardiovascular and pulmonary disease, adult patients at low risk for cardiovascular disease, and female patients (aged 13-20 years or older than 69 years) at low risk for cervical cancer. The dates of analysis were June 3 to September 12, 2019. Exposures: Low-value screening tests were defined per cohort as (1) a chest radiograph within 7 days, (2) an electrocardiogram (ECG) within 30 days, or (3) a Papanicolaou test within 7 days after an AHE. Main Outcomes and Measures: Subsequent specialist visits, diagnostic tests, and procedures within 90 days after a low-value test (if the patient had a chest radiograph, ECG, or Papanicolaou test) or end of the exposure observation window (if not tested). Results: Included in the chest radiograph, ECG, and Papanicolaou test cohorts of propensity score-matched pairs were 43 532 patients (mean [SD] age, 47.5 [14.4] years; 38.5% female), 245 686 patients (mean [SD] age, 49.9 [13.7] years; 51.1% female), and 29 194 patients (mean [SD] age, 45.5 [27.1] years; 100% female), respectively. At 90 days, chest radiographs in low-risk patients were associated with an additional 0.87 (95% CI, 0.69-1.05) and 1.96 (95% CI, 1.71-2.22) patients having an outpatient pulmonology visit or an abdominal or thoracic computed tomography scan per 100 patients, respectively, and ECGs in low-risk patients were associated with an additional 1.92 (95% CI, 1.82-2.02), 5.49 (95% CI, 5.33-5.65), and 4.46 (95% CI, 4.31-4.61) patients having an outpatient cardiologist visit, a transthoracic echocardiogram, or a cardiac stress test per 100 patients, respectively. At 180 days, Papanicolaou testing in low-risk patients was associated with an additional 1.31 (95% CI, 0.84-1.78), 52.8 (95% CI, 51.9-53.6), and 0.84 (95% CI, 0.66-1.01) patients having an outpatient gynecology visit, a follow-up Papanicolaou test, or colposcopy per 100 patients, respectively. Conclusions and Relevance: Observed associations in this population-based cohort study suggest that testing in low-risk patients as part of an AHE increases the likelihood of subsequent specialist visits, diagnostic tests, and procedures.

Physician Characteristics Associated With Ordering 4 Low-Value Screening Tests in Primary Care.

Importance: Efforts to reduce low-value tests and treatments in primary care are often ineffective. These efforts typically target physicians broadly, most of whom order low-value care infrequently. Objectives: To measure physician-level use rates of 4 low-value screening tests in primary care to investigate the presence and characteristics of primary care physicians who frequently order low-value care. Design, Setting, and Participants: A retrospective cohort study was conducted using administrative health care claims collected between April 1, 2012, and March 31, 2016, in Ontario, Canada. This study measured use of 4 low-value screening tests-repeated dual-energy x-ray absorptiometry (DXA) scans, electrocardiograms (ECGs), Papanicolaou (Pap) tests, and chest radiographs (CXRs)-among low-risk outpatients rostered to a common cohort of primary care physicians. Exposures: Physician sex, years since medical school graduation, and primary care model. Main Outcomes and Measures: This study measured the number of tests to which a given physician ranked in the top quintile by ordering rate. The resulting cross-test score (range, 0-4) reflects a physician's propensity to order low-value care across screening tests. Physicians were then dichotomized into infrequent or isolated frequent users (score, 0 or 1, respectively) or generalized frequent users for 2 or more tests (score, ≥2). Results: The final sample consisted of 2394 primary care physicians (mean [SD] age, 51.3 [10.0] years; 50.2% female), who were predominantly Canadian medical school graduates (1701 [71.1%]), far removed from medical school graduation (median, 25.3 years; interquartile range, 17.3-32.3 years), and reimbursed via fee-for-service in a family health group (1130 [47.2%]). They ordered 302 509 low-value screening tests (74 167 DXA scans, 179 855 ECGs, 19 906 Pap tests, and 28 581 CXRs) after 3 428 557 ordering opportunities. Within the cohort, generalized frequent users represented 18.4% (441 of 2394) of physicians but ordered 39.2% (118 665 of 302 509) of all low-value screening tests. Physicians who were male (odds ratio, 1.29; 95% CI, 1.01-1.64), further removed from medical school graduation (odds ratio, 1.03; 95% CI, 1.02-1.04), or in an enhanced fee-for-service payment model (family health group) vs a capitated payment model (family health team) (odds ratio, 2.04; 95% CI, 1.42-2.94) had increased odds of being generalized frequent users. Conclusions and Relevance: This study identified a group of primary care physicians who frequently ordered low-value screening tests. Tailoring future interventions to these generalized frequent users might be an effective approach to reducing low-value care.